NCBO Wiki - User contributions [en]

Immunology Ontologies and Their Applications in Processing Clinical Data

2012-05-21T00:50:14Z

Agoldfain: Added more specifics to the OGMS working session

The National Center for Biomedical Ontology [http://bioontology.org (NCBO)] in collaboration with the Protein Ontology [http://pir.georgetown.edu/pro/ (PRO)] and the Infectious Disease Ontology [http://infectiousdiseaseontology.org/page/Main_Page (IDO)] will host a three-day dissemination workshop in Buffalo, NY on June 11-13, 2012.
:Day 1 will provide a survey of current ontology-based research in immunology and infectious disease with a view to future coordination among ontology developers and users in this field.
:Day 2 will be focused on flow cytometry, including the question of the Cell and Protein Ontologies and of the role of surface protein expression in cell type classification.
:Day 3 will include a session devoted to the use of ontologies to assist clinicians working with infectious disease data, followed by a session on the Ontology for General Medical Science.

'''Venue:
:Days 1 and 2, [http://www.universityinn.com/ Ramada Inn, UB North Campus, Buffalo]
:Day 3: [http://www.hwi.buffalo.edu/about_hwi/visitor/maps_directions.html, Hauptmann-Woodward Institute, Buffalo]

'''Goals'''

Provisional goals of the meeting are:

To identify and coordinate activities on-going in immunology ontology and related fields, with special attention to the use of ontologies to support clinical data analysis in flow cytometry and related fields.

'''Registration'''

This meeting is free for registered participants. Space is limited and those interested in participating should contact [mailto:phismith@buffalo.edu Barry Smith] as soon as possible.

----

'''
== Draft Schedule ==
'''

''Day 1: Monday, June 11, 2012''

09:00 Registration and Breakfast

'''An Overview of Ontologies to Support Research in Immunology and Infectious Disease'''

'''Morning: The Gene Ontology, Reactome, The Immunology Ontology, The Immune Epitope Ontology and the Allergy Ontology'''

09:30 Cathy Wu (University of Delaware) and Barry Smith (University at Buffalo)
'''Bio-Ontologies for Immunology Research: An Introduction
:::We will survey the goals of the meeting, and describe the relations between a number of interdependent ontologies being developed in the domain of immunology.

10:00 Alexander Diehl (University at Buffalo)
::The Gene Ontology and Immune System Processes

10:30 Break

11:00 Cliburn Chan (Duke University)
::Ontology for cellular immune networks
:::Will describe initial work on an ontology of cellular immune networks that is designed to capture the qualitative cytokine expression patterns and cellular phenotypes associated with specific immune activation networks (e.g. Th1 network). We will outline use of the ontology for immune assay integration and statistical enrichment analysis.

11:30 Anna Maria Masci (Duke University)
::The Immunology Ontology (with special focus on the liver)
:::An emerging scenario is uncovering immune response as a sophisticated biological process, which requires an intensive cross-talk between immunocytes, parenchymal and stromal cell types. These timely and anatomically restricted interactions regulate the outcome of immune response to damage induced by stress and pathogens. Due to its complexity and patho-physiological relevance, the liver represents an interesting prototype of context-dependent immune response. We will introduce the Liver Immunology Ontology (LIO), which has as primary goal the representation of the immune response induced in the context of the liver.

12:00 Peter d'Eustacho (New York University)
::Innate Immunity: Signaling via Toll-Like Receptors in Reactome
:::The innate immune responses mediated by Toll-like receptors (TLR) provide a first line of defense against microbial pathogens in many vertebrates. In Reactome we have integrated annotations of human TLR molecular functions with those of 6800 other human proteins involved in diverse biological processes to generate a resource suitable for data mining, pathway analysis, and other systems biology approaches. These annotations allow human TLR proteins, the complexes they form, and the functions they mediate to be classified and related to those of structurally similar TLR proteins from chicken, mouse, and other species.

12:30 Lunch
'''Lunchtime talk'''
:Atul Butte (Stanford): Discovery of a novel inflammatory receptor and related drug for type 2 diabetes from integration of publicly-available microarray data

14:00 Alexander C. Yu (University at Buffalo)
::The Allergy Ontology

14:30 Lindsay Cowell (University of Texas Southwestern Medical Center)
::An Introduction to the Infectious Disease Ontology
:::Update on IDO-Core; simplified definitions; new approach to MIREOTing; new terms/definitions/relations; a template for creating an IDO Extension

15:00 Break

15:30 Albert Goldfain (Blue Highway)
::Staph Aureus (Sa) IDO

16:00 Christos (Kitsos) Louis (IMBB-FORTH, Crete)
::IDO Mal (Malaria Ontology)

16:30 Yu Lin (University of Michigan)
::IDOBru (Brucellosis Ontology)
:::IDOBru is an extension ontology of IDO. We will focus on those aspects of Brucellosis represented in IDOBru as outlined in [http://www.jbiomedsem.com/content/2/1/9]. We will also discuss IDOBru's policy on use of IDs, and its treatment of Brucella-host interaction.

17:00 Oliver He (University of Michigan)
::Contributions of the Vaccine Ontology (VO) to Immunology Research and Public Health
:::Vaccinology is applied immunology. VO is a community-based biomedical ontology in the domain of vaccine and vaccination. We will introduce the top level of VO, and sketch applications of VO in elucidating fundamental protective immune mechanisms and improving public health.

----

''Day 2: Tuesday, June 12, 2012''

'''Ontologies and Flow Cytometry Informatics'''

:'''Background''' Increasingly, flow cytometry is being employed in clinical laboratories for the diagnosis, prognosis and monitoring of disease. The advent of highly multidimensional flow cytometry and automated gating algorithms for the analysis of flow cytometry data, coupled with the rise of personalized medicine, are poised to expand greatly the need for a reliable, structured framework for the representation of the types of cells present in human blood and tissues. We are currently enhancing the representation of hematopoietic and other cell types in the Cell Ontology (CL) to allow for the logical definition of cell types based on cellular attributes, and in doing so we rely on relations to terms of the Protein Ontology (PRO) as a key component of these definitions. The goal of today's session is explore how the use of clinical flow cytometry data can serve as a driver of ontology development in both the PRO and the CL by assessing current standard clinical assays and recent approaches based on automated gating of multidimensional flow cytometry.

:Examples of questions to be addressed include:
::Which protein isoforms and post-translationally modified forms identified by flow cytometry typing reagents need to be represented in the PRO to enable cell types defined in their terms to be represented in the CL?
::How can use of the PRO and CL ontologies will promote standardization in interpretation and integration of clinical flow cytometry data?

08:30 Breakfast

09:00 Alexander Diehl (Buffalo) and Lindsay Cowell (University of Texas Southwestern Medical Center)
'''9am-noon: Introduction to the Protein Ontology Flow Cytometry Driving Biological Project'''

:::Assessing representation requirements for Flow Cytometry in PRO, CL, IEDB, OBI, ImmPort, and Immune System Modeling.
::Development of a data store to collect extended cell type-protein relationships.
::Defining a tool wish-list for CL-linked flow cytometry analysis and CL-assisted marker selection for cell type analysis.

Presentations during the morning session will include:
Cathy Wu (Delaware), Darren Natale (Georgetown) and Alexander Diehl (Buffalo)
::The Protein Ontology and Cell Type Definitions

Alexander Diehl (Buffalo)
::Overview of Hematopoietic Cell Types in the Cell Ontology

12:30 Lunch

'''Afternoon: Automated gating of Flow Cytometry results and linking to the Cell Ontology. Flow cytometry typing of normal and malignant cell types'''

13:30 Cliburn Chan (Duke)
::Automated flow cytometry analysis in HIV studies
:::Will describe recent work on automated cell subset identification and alignment across multiple HIV-related data sets with statistical mixture models. What do we need in order to be able to use ontologies for automated annotation and labeling of cell subsets?

14:00 Nikesh Kotecha (Cytobank)
::Incorporating annotations into the analysis workflow - examples using Cytobank and NCBO's BioPortal

14:30 Alexander Diehl (Buffalo)
::An Ontological Treatment of Protein Marker Expression on Multiple Myeloma Subtypes
::Overview of Euroflow Leukemia Typing Panels

15:00 Break

15:30 Oliver He (University of Michigan)
::How Flow Cytometry can be used in Vaccine Research
:::To better understand fundamental protective immune mechanisms, flow cytometry has frequently been used to measure vaccine-induced innate immunity, and antigen-specific T-cell and B-cell responses. Biomedical ontologies (e.g., VO, OBI, and PRO) play important roles in data representation, integration, and automated reasoning in vaccine-related flow cytometry research.

16:00 Ryan Brinkman (Vancouver)
::1. Overview of the representation of flow cytometry assays in OBI
::2. Overview of [http://www.bioconductor.org/packages/release/bioc/html/flowMeans.html flowMeans] and [http://flowcap.flowsite.org/ flowCAP]
::3. Connecting results from automated FCM analysis systems with the Cell Ontology

----

''Day 3: Wednesday, June 13, 2012:9:00am-6:00pm''

'''The Role of Ontologies in Clinical Medicine'''

Note change of venue to: [http://www.hwi.buffalo.edu/about_hwi/visitor/maps_directions.html, Hauptmann-Woodward Institute, Buffalo]

9:00 Breakfast

Further discussion of Immunology Ontology including:

9:30 Bjoern Peters (La Jolla Institute for Allergy and Immunology)
::Representation of immunology experiments using OBI
::Representing epitope mapping experiments for the Immune Epitope Database (IEDB)
:::The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meaning to describe all aspects of how biomedical investigations are conducted. OBI builds on the Gene Ontology (GO) and related efforts that provide a formal and interoperable representation of biomedical knowledge. OBI adds the ability to describe how this knowledge was derived. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. The presentation will describe the state of OBI and several applications that are using it. Specific focus will be on epitope mapping and characterization experiments captured in the Immune Epitope Database (IEDB) which heavily utilizes OBI. The presentation will also point out gaps in coverage of immunological terms that are currently in OBI but poorly defined and outside the scope of OBI, and which deserve a better home.

10:30 Break

11:00 Alexander Diehl (Buffalo)
:Towards Auto-Immune Disease Ontology

'''noon-3pm SESSION OPEN TO THE PUBLIC: Practical Applications of Ontologies in Clinical Research''' (includes lunch)

:Albert Goldfain (Blue Highway / Syracuse)
::Creating Personalized Infectious Disease Ontologies

:Alan Ruttenberg (Buffalo)
::The Protein Ontology and the treatment of protein isoforms, mutations, and aggregates of relevance to Alzheimer's Disease

:Christos (Kitsos) Louis (IMBB-FORTH, Crete)
::Ontologies and Vector-Borne Diseases

:Werner Ceusters (Buffalo)
::Assessment instruments and biomedical reality: examples in the pain domain

'''3pm-6pm: Working Session on the Ontology for General Medical Science (OGMS)'''

:Moderator: Albert Goldfain (Blue Highway / Syracuse)
:Topics to be treated will include:
::Current status of OGMS and the OGMS Reference
::Linking diseases to their underlying disorders using basis relations
::Defining 'relapse' and 'remission' processes.
::Updates on the Vital Sign Ontology
::Recipes for OGMS-conformant extension ontologies
:''Close: 6:00pm''
----
'''Relevant ontology efforts'''

:GO-IP Gene Ontology -- Immunological Process (Alexander Diehl)
:CL Cell ontology immune branches (e.g. for dendritic cells)
:PRO Protein Ontology
:IO Immunology Ontology (Lindsay Cowell and Alexander Diehl)
:IEO Immune Epitope Ontology (Bjoern Peters)
:MHC Major Histocompatibility Complex Ontology (Bjoern Peters)
:OGMS Ontology for General Medical Science (Albert Goldfain)
:IDO Infectious Disease Ontology (Lindsay Cowell)
:Vaccine Ontology (Oliver He)
:AO Allergy Ontology (Alex C. Yu)
:ND Neurological Disease Ontology (Alexander Diehl)
----
'''

== Participants will include ==
'''

:Ryan Brinkman (University of British Columbia)
:Atul Butte (Stanford University)
:James S. Cavenaugh (University of Rochester Medical Center)
:Werner Ceusters (University at Buffalo)
:Cliburn Chan (Duke University)
:Quan Chen (NIH/NIAID)
:Melanie Courtot (BCCRC, Vancouver)
:Lindsay Cowell (University of Texas Southwestern Medical Center)
:Oliver Crespo (BD Biosciences, San Jose, CA)
:Paresh Dandona (Diabetes and Endocrinology Center of Western New York / University at Buffalo)
:Peter d'Eustachio (New York University)
:Alexander Diehl (University at Buffalo)
:Chester Fox (University at Buffalo)
:Lee Ann Garrett-Sinha (University at Buffalo)
:Albert Goldfain (University at Buffalo, Syracuse University and Blue Highway, Inc.)
:Oliver He (University of Michigan)
:Leonard Jacuzzo (University at Buffalo)
:Mark Jensen (University at Buffalo)
:Christos (Kitsos) Louis (IMBB-FORTH, Crete)
:Nikesh Kotecha (Cytobank)
:Yu Lin (University of Michigan)
:Wei Luo (University at Buffalo)
:Supriya Mahajan (University at Buffalo)
:Anna Maria Masci (Duke University)
:Darren Natale (Georgetown University)
:Dave Parrish (Digital Infuzion)
:Bjoern Peters (La Jolla Institute for Allergy and Immunology)
:Mark Ressler (University at Buffalo)
:Jessica L. Reynolds (University at Buffalo)
:Alan Ruttenberg (University at Buffalo)
:Stanley A. Schwartz (University at Buffalo)
:Prontip Saelee (University at Buffalo)
:Veronica Shamovsky (NYU School of Medicine)
:Barry Smith (University at Buffalo)
:Cathy Wu (University of Delaware, Georgetown University)
:Alex C. Yu (University at Buffalo)

IDO Workshop 2010

2010-12-09T19:32:37Z

Agoldfain: /* Schedule */

== Background ==

A two-day IDO workshop for invited participants will be held on December 8-9, 2010. Venue: Baltimore Airport Hilton. This meeting is being organized as part of the series of Dissemination Workshops organized under the auspices of the National Center for
Biomedical Ontology ([http://bioontology.org NCBO]).

The Infectious Disease Ontology (IDO) is a general terminology, taxonomy, and logical representation of entities relevant to all
infectious diseases. IDO is already being applied through disease-specific IDO extensions to the study of seven diseases,
including diseases of bacterial, viral, and eukaryotic origin.

Recently, the IDO has been adopted by the virus and bacterial Bioinformatics Resource Centers (BRCs) established by the NIAID to
serve integration of a broad array of -omics, epidemiological and clinical data.

For more information about IDO and its sub-domain extensions especially in the areas of HIV, influenza, Malaria, and Staphylococcus aureus bacteremia. See http://www.infectiousdiseaseontology.org.

This NCBO Workshop on the Infectious Disease Ontology is funded by the United States National Institutes of Health through the NIH Roadmap for Medical Research, Grant 1 U54 HG004028. Its content is solely the responsibility of the organizers and presenters and does not necessarily represent the official views of the National Human Genome Research Institute or the National Institutes of Health. Information on the National Centers for Biomedical Computing can be found at http://nihroadmap.nih.gov/bioinformatics.

== Goals of the Meeting ==

*The primary goal of this meeting is to explore the potential benefits of using the IDO Infectious Disease Ontology as a controlled vocabulary for promoting consistency in the ways infectious disease data are described. IDO provides both a vocabulary of terms and a set of precise definitions that have been thoroughly reviewed for biological accuracy and logical consistency.

*We will explore the benefits of the IDO controlled vocabulary, especially in advancing the work of the Bioinformatics Resource Centers, in areas such as:

::clinical data integration
::text and data mining
::genetic susceptibility to infectious disease
::disease surveillance
::plant infectious disease

*The meeting will also address relations between IDO and other parallel initiatives, including [http://tsb.mssm.edu/primeportal/ PRIME], [http://www.debugit.eu/ DebugIT], and the various IDO extension ontologies.

*To address these goals, speakers are asked to address the following points
**The goals of their project
:::biological questions for research projects
:::content and functions for computational resource projects
**The tasks for which terminologies are needed
**The terminologies currently being used
:::brief description of any terminologies developed specifically for the project
:::description of the ways in which current terminologies are inadequate for the project’s needs

==New Pre-Release Version of IDO==
Following the workshop, we will release a new version of IDO. This version has only minor differences from the version released in May 2010 with respect to terms, definitions, and hierarchy. The primary difference is in the addition of OWL DL restrictions for many terms. This new version of IDO will be presented at the workshop and can be accessed via the following PURLs:
*Full IDO http://purl.obolibrary.org/obo/ido/2010-12-02/ido.owl
*Obsolete classes omitted http://purl.obolibrary.org/obo/ido/2010-12-02/ido-main.owl
*Axioms omitted http://purl.obolibrary.org/obo/ido/2010-12-02/ido-base.owl
*Asserted hierarchy only http://purl.obolibrary.org/obo/ido/2010-12-02/ido-asserted.owl
*OBO version, no axioms http://purl.obolibrary.org/obo/ido/2010-12-02/ido.obo

As always, comments, criticisms, and term requests are welcome. Please submit them on the issue tracker (http://code.google.com/p/infectious-disease-ontology/), email the discussion list (http://groups.google.com/group/ido-discuss), or email them directly to Lindsay Cowell (lindsay DOT cowell AT utsouthwestern DOT edu).

== Schedule ==

'''Day 1: Wednesday, December 8'''

*9:00am Introduction: The current state of IDO and its role as a controlled vocabulary for infectious disease research (Session chair: Smith)
::Lindsay Cowell: Scope and Content of IDO // [http://ontology.buffalo.edu/10/IDO/Cowell.pdf Presentation]

*10:00am Session 1: Bioinformatics Resource Centers (Session chair: Scheuermann)
::Richard Scheuermann
:::BRCs Overview: Virus Pathogen Resource (ViPR) and Influenza Research Database (IRD) // [http://ontology.buffalo.edu/10/IDO/Scheuermann_BRC.pptx Presentation]
::Chris Stoeckert
:::EuPathDB - Eukaryotic Pathogen Database Resource // [http://ontology.buffalo.edu/10/IDO/Stoeckert_EuPathDB-IDO.pptx Presentation]

*11:30am Session 1 continued (Session chair: Sobral)
::Pantelis Topalis
:::VectorBase - Invertebrate Vectors of Human Pathogens // [http://ontology.buffalo.edu/10/IDO/VectorBase.pptx Presentation]
::Bruno Sobral
:::PATRIC - Pathosystems Resource Integration Center
:::PathogenPortal - Bioinformatics Resource Centers Portal

*2:00pm Session 2: Additional large data and information repositories relevant for infectious disease research (Session chair: Scheuermann)
::Richard Scheuermann
:::ImmPort - Immunology Database and Analysis Portal // [http://ontology.buffalo.edu/10/IDO/Scheuermann_ImmPort.ppt Presentation]
::Barry Smith
:::PRIME - Program for Research on Immune Modeling and Experimentation // [http://ontology.buffalo.edu/10/IDO/Smith_PRIME.pptx Presentation]

*3:00pm Session 3: General discussion of the Utility of IDO as a Controlled Vocabulary (Session chair: Smith)

*4:00pm Refreshment Break

*4:30pm Session 4: Decision Support Use Cases (Session chair: Fuentes)
::Saul Lozano-Fuentes - Dengue/vector control // [http://ontology.buffalo.edu/10/IDO/Saul/Lozano.ppt Presentation] [http://ontology.buffalo.edu/10/IDO/Saul/power%20of%20Runway-DDMS.wmv Runway Video]
::Daniel Schober - DeBugIT - Detecting and Eliminating Bacteria using Information Technology // [http://ontology.buffalo.edu/10/IDO/Schober_DCO.ppt Presentation]

*5:30pm End of Day 1

'''Day 2: Thursday, December 9'''

'''PLEASE NOTE: Wireless Internet Access is available at no charge in the lobby area and in NCBO/IDO guest rooms.'''

*8:30am Continental Breakfast

*9:00am Session 1: Data Integration Use Cases (Session chair: Goldfain)
::Alexander Diehl - Comprehensive Annotation System for Infectious Disease Data // [http://ontology.buffalo.edu/10/IDO/Diehl.ppt Presentation]
::Mélanie Courtot - PCIRN - Public Health Agency of Canada / Canadian Institutes of Health Research Influenza Research Network // [http://ontology.buffalo.edu/10/IDO/Courtot.pdf Presentation]
::Albert Goldfain - Linking Vital Signs Data to IDO Disease Models // [http://www.buffalo.edu/~ag33/VitalsIDOModels.ppt Presentation]
::Patricia Whetsel - NCBO Bioportal

*11:00am Refreshment Break

*11:30am Session 2: IDO Extensions (Session chair: Ruttenberg)
::Yu Lin - Brucellosis Ontology
::Burke Squires - Flu-IDO

*12:30pm Lunch Break

*2:00pm Session 2 continued
::Oliver He - VIOLIN - VO
::Alan Zheng - OntoBee
::Pankaj Jaswal - Plant IDO

*3:00pm Session 3: Next Steps Lindsay Cowell

*4:00pm Close of NCBO/IDO 2010 Workshop

'''Format'''

Presentations will be short introductions to group discussion. All sessions will emphasize group discussion over presentation.

== Venue ==

A block of guest rooms at a discounted rate has been arranged for those NCBO/IDO 2010 attendees requiring lodging at:

[http://www.hiltonbaltimorebwi.com Hilton Baltimore BWI Airport]
1739 West Nursery Road
Linthicum Heights, MD 21090

To make reservations by phone call 1-800-HILTONS (or the hotel 443-577-2411) and be sure to mention that you are part of Group Name:''' NCBO – IDO 2010''' / Group Code: '''NCBO'''.

To access our online reservation link, click [http://www.hilton.com/en/hi/groups/personalized/BWIAPHF-NCBO-20101207/index.jhtml?WT.mc_id=POG]

* The Hilton Baltimore BWI Airport offers complimentary shuttle service from/to BWI airport, and complimentary internet access in the lobby-area.

* NCBO–IDO 2010 attendees will also receive complimentary internet access in their guest room.

* To take advantage of the special rate and free internet access in your guest room, you must secure your room reservation '''no later than November 15, 2010'''.

Driving directions for local participants can be found here [http://www1.hilton.com/en_US/hi/hotel/BWIAPHF-Hilton-Baltimore-BWI-Airport-Maryland/directions.do]

== Participants ==

Mauricio B. Almeida (Universidade Federal de Minas Gerais, Brazil)

Sivaram Arabandi (Case Western Reserve University)

Mathias Brochhausen (Institute for Formal Ontology and Medical Information Science, Saarland University)

Mélanie Courtot (British Columbia Cancer Research Center, Vancouver)

Lindsay Cowell (University of Texas Southwestern Medical Center, Dallas)

Alexander Diehl (University at Buffalo)

Saul Lozano-Fuentes (Colorado State University)

Andrei Gabrielian (NIAID / NIH)

Albert Goldfain (University at Buffalo)

Yongqun "Oliver" He (University of Michigan Medical Center)

Pankaj Jaiswal (Plant Ontology / Oregon State University)

Jessica Kissinger (Center for Tropical & Emerging Global Diseases / University of Georgia)

Yu Lin (University of Michigan Medical Center)

Joanne Luciano (Predictive Medicine, Inc. and Rensselaer Polytechnic Institute (RPI))

Chunhong Mao (PATRIC, Virginia Bioinformatics Institute)

Alan Ruttenberg (Science Commons / University at Buffalo)

Richard Scheuermann (University of Texas Southwestern Medical Center at Dallas)

Daniel Schober (Universität Freiburg, Germany)

Barry Smith (NCBO / University at Buffalo)

Bruno Sobral (PATRIC, Virginia Bioinformatics Institute)

Burke Squires (University of Texas Southwestern Medical Center at Dallas)

Ram Sriram (National Institute of Science and Technology)

Christian Stoeckert (Penn Center for Bioinformatics / University of Pennsylvania)

Dan Sullivan (PATRIC, Virginia Bioinformatics Institute)

Pantelis Topalis (VectorBase / IMBB-FORTH, Crete)

Miguel H. Torres-Urquidy (CDC / OID / NCIRD)

Patricia Whetzel (NCBO, Stanford)

Robert Williams (Uniformed Services University)

Allen Xiang (University of Michigan Medical Center)

Jie Zheng (Penn Center for Bioinformatics / University of Pennsylvania)

IDO Workshop 2010

2010-12-05T21:42:29Z

Agoldfain: /* Schedule */

== Background ==

A two-day IDO workshop for invited participants will be held on December 8-9, 2010. Venue: Baltimore Airport Hilton. This meeting is being organized as part of the series of Dissemination Workshops organized under the auspices of the National Center for
Biomedical Ontology ([http://bioontology.org NCBO]).

The Infectious Disease Ontology (IDO) is a general terminology, taxonomy, and logical representation of entities relevant to all
infectious diseases. IDO is already being applied through disease-specific IDO extensions to the study of seven diseases,
including diseases of bacterial, viral, and eukaryotic origin.

Recently, the IDO has been adopted by the virus and bacterial Bioinformatics Resource Centers (BRCs) established by the NIAID to
serve integration of a broad array of -omics, epidemiological and clinical data.

For more information about IDO and its sub-domain extensions especially in the areas of HIV, influenza, Malaria, and Staphylococcus aureus bacteremia. See http://www.infectiousdiseaseontology.org.

This NCBO Workshop on the Infectious Disease Ontology is funded by the United States National Institutes of Health through the NIH Roadmap for Medical Research, Grant 1 U54 HG004028. Its content is solely the responsibility of the organizers and presenters and does not necessarily represent the official views of the National Human Genome Research Institute or the National Institutes of Health. Information on the National Centers for Biomedical Computing can be found at http://nihroadmap.nih.gov/bioinformatics.

== Goals of the Meeting ==

*The primary goal of this meeting is to explore the potential benefits of using the IDO Infectious Disease Ontology as a controlled vocabulary for promoting consistency in the ways infectious disease data are described. IDO provides both a vocabulary of terms and a set of precise definitions that have been thoroughly reviewed for biological accuracy and logical consistency.

*We will explore the benefits of the IDO controlled vocabulary, especially in advancing the work of the Bioinformatics Resource Centers, in areas such as:

::clinical data integration
::text and data mining
::genetic susceptibility to infectious disease
::disease surveillance
::plant infectious disease

*The meeting will also address relations between IDO and other parallel initiatives, including [http://tsb.mssm.edu/primeportal/ PRIME], [http://www.debugit.eu/ DebugIT], and the various IDO extension ontologies.

*To address these goals, speakers are asked to address the following points
**The goals of their project
:::biological questions for research projects
:::content and functions for computational resource projects
**The tasks for which terminologies are needed
**The terminologies currently being used
:::brief description of any terminologies developed specifically for the project
:::description of the ways in which current terminologies are inadequate for the project’s needs

==New Pre-Release Version of IDO==
Following the workshop, we will release a new version of IDO. This version has only minor differences from the version released in May 2010 with respect to terms, definitions, and hierarchy. The primary difference is in the addition of OWL DL restrictions for many terms. This new version of IDO will be presented at the workshop and can be accessed via the following PURLs:
*Full IDO http://purl.obolibrary.org/obo/ido/2010-12-02/ido.owl
*Obsolete classes omitted http://purl.obolibrary.org/obo/ido/2010-12-02/ido-main.owl
*Axioms omitted http://purl.obolibrary.org/obo/ido/2010-12-02/ido-base.owl
*Asserted hierarchy only http://purl.obolibrary.org/obo/ido/2010-12-02/ido-asserted.owl
*OBO version, no axioms http://purl.obolibrary.org/obo/ido/2010-12-02/ido.obo

As always, comments, criticisms, and term requests are welcome. Please submit them on the issue tracker (http://code.google.com/p/infectious-disease-ontology/), email the discussion list (http://groups.google.com/group/ido-discuss), or email them directly to Lindsay Cowell (lindsay DOT cowell AT utsouthwestern DOT edu).

== Schedule ==

'''Tuesday, December 7'''

*7:00-9:00pm Welcome Reception (Sponsored by the University of Texas Southwestern Medical Center at Dallas; Cash Bar)
:Private Room in BWI Hilton's Acqua Restaurant (1st floor, to the right of the front desk)

'''Day 1: Wednesday, December 8'''

'''PLEASE NOTE: Wireless Internet Access is available at no charge in the lobby area and in NCBO/IDO guest rooms.'''

*8:30am Registration & Continental Breakfast

*9:00am Introduction: The current state of IDO and its role as a controlled vocabulary for infectious disease research (Session chair: Smith)
::Lindsay Cowell: Scope and Content of IDO
::Barry Smith: How use of IDO creates information integration across multiple domains

*10:00am Session 1: Bioinformatics Resource Centers (Session chair: Scheuermann)
::Richard Scheuermann
:::BRCs Overview
:::ViPR - Virus Pathogen Resource
:::IRD - Influenza Research Database
::Chris Stoeckert
:::EuPathDB - Eukaryotic Pathogen Database Resource

*11:00am Refreshment Break

*11:30am Session 1 continued (Session chair: Sobral)
::Pantelis Topalis
:::VectorBase - Invertebrate Vectors of Human Pathogens
::Bruno Sobral
:::PATRIC - Pathosystems Resource Integration Center
:::PathogenPortal - Bioinformatics Resource Centers Portal

*12:30pm Lunch Break

*2:00pm Session 2: Additional large data and information repositories relevant for infectious disease research (Session chair: Scheuermann)
::Richard Scheuermann
:::ImmPort - Immunology Database and Analysis Portal
::Barry Smith
:::PRIME - Program for Research on Immune Modeling and Experimentation

*3:00pm Session 3: General discussion of the Utility of IDO as a Controlled Vocabulary (Session chair: Smith)

*4:00pm Refreshment Break

*4:30pm Session 4: Decision Support Use Cases (Session chair: Fuentes)
::Saul Lozano-Fuentes - Dengue/vector control
::Daniel Schober - DeBugIT - Detecting and Eliminating Bacteria using Information Technology

*5:30pm End of Day 1

*6:00pm Dinner (for interested participants; No-host/Dutch treat)
:Private Room in BWI Hilton's Acqua Restaurant (1st floor, to the right of the front desk)

'''Day 2: Thursday, December 9'''

'''PLEASE NOTE: Wireless Internet Access is available at no charge in the lobby area and in NCBO/IDO guest rooms.'''

*8:30am Continental Breakfast

*9:00am Session 1: Data Integration Use Cases (Session chair: Goldfain)
::Alexander Diehl - Comprehensive Annotation System for Infectious Disease Data
::Anna Maria Masci - CFAR - Centers for AIDS Research
::Mélanie Courtot - PCIRN - Public Health Agency of Canada / Canadian Institutes of Health Research Influenza Research Network
::Albert Goldfain - Linking Vital Signs Data to IDO Disease Models

*11:00am Refreshment Break

*11:30am Session 2: IDO Extensions (Session chair: Ruttenberg)
::Yu Lin - Brucellosis Ontology
::Burke Squires - Flu-IDO

*12:30pm Lunch Break

*2:00pm Session 2 continued
::Oliver He - VIOLIN - VO
::Pankaj Jaswal - Plant IDO

*3:00pm Session 3: Next Steps Lindsay Cowell

*4:00pm Close of NCBO/IDO 2010 Workshop

'''Format'''

Presentations will be short introductions to group discussion. All sessions will emphasize group discussion over presentation.

== Venue ==

A block of guest rooms at a discounted rate has been arranged for those NCBO/IDO 2010 attendees requiring lodging at:

[http://www.hiltonbaltimorebwi.com Hilton Baltimore BWI Airport]
1739 West Nursery Road
Linthicum Heights, MD 21090

To make reservations by phone call 1-800-HILTONS (or the hotel 443-577-2411) and be sure to mention that you are part of Group Name:''' NCBO – IDO 2010''' / Group Code: '''NCBO'''.

To access our online reservation link, click [http://www.hilton.com/en/hi/groups/personalized/BWIAPHF-NCBO-20101207/index.jhtml?WT.mc_id=POG]

* The Hilton Baltimore BWI Airport offers complimentary shuttle service from/to BWI airport, and complimentary internet access in the lobby-area.

* NCBO–IDO 2010 attendees will also receive complimentary internet access in their guest room.

* To take advantage of the special rate and free internet access in your guest room, you must secure your room reservation '''no later than November 15, 2010'''.

Driving directions for local participants can be found here [http://www1.hilton.com/en_US/hi/hotel/BWIAPHF-Hilton-Baltimore-BWI-Airport-Maryland/directions.do]

== Confirmed Participants ==

Mauricio B. Almeida (Universidade Federal de Minas Gerais, Brazil)

Sivaram Arabandi (Case Western Reserve University)

Mathias Brochhausen (Institute for Formal Ontology and Medical Information Science, Saarland University)

Mélanie Courtot (British Columbia Cancer Research Center, Vancouver)

Lindsay Cowell (University of Texas Southwestern Medical Center, Dallas)

Alexander Diehl (University at Buffalo)

Saul Lozano-Fuentes (Colorado State University)

Albert Goldfain (University at Buffalo)

Yongqun "Oliver" He (University of Michigan Medical Center)

Pankaj Jaiswal (Plant Ontology / Oregon State University)

Jessica Kissinger (Center for Tropical & Emerging Global Diseases / University of Georgia)

Yu Lin (University of Michigan Medical Center)

Joanne Luciano (Predictive Medicine, Inc. and Rensselaer Polytechnic Institute (RPI))

Chunhong Mao (PATRIC, Virginia Bioinformatics Institute)

Anna Maria Masci (Duke University Medical Center)

Alan Ruttenberg (Science Commons / University at Buffalo)

Richard Scheuermann (University of Texas Southwestern Medical Center at Dallas)

Daniel Schober (Universität Freiburg, Germany)

Barry Smith (NCBO / University at Buffalo)

Bruno Sobral (PATRIC, Virginia Bioinformatics Institute)

Burke Squires (University of Texas Southwestern Medical Center at Dallas)

Christian Stoeckert (Penn Center for Bioinformatics / University of Pennsylvania)

Dan Sullivan (PATRIC, Virginia Bioinformatics Institute)

Pantelis Topalis (VectorBase / IMBB-FORTH, Crete)

Miguel H. Torres-Urquidy (CDC / OID / NCIRD)

Patricia Whetzel (NCBO, Stanford)

Allen Xiang (University of Michigan Medical Center)

Jie Zheng (Penn Center for Bioinformatics / University of Pennsylvania)

IDO Workshop 2010

2010-11-30T17:55:01Z

Agoldfain: /* Schedule */

== Background ==

A two-day IDO workshop for invited participants will be held on December 8-9, 2010. Venue: Baltimore Airport Hilton. This meeting is being organized as part of the series of Dissemination Workshops organized under the auspices of the National Center for
Biomedical Ontology ([http://bioontology.org NCBO]).

The Infectious Disease Ontology (IDO) is a general terminology, taxonomy, and logical representation of entities relevant to all
infectious diseases. IDO is already being applied through disease-specific IDO extensions to the study of seven diseases,
including diseases of bacterial, viral, and eukaryotic origin.

Recently, the IDO has been adopted by the virus and bacterial Bioinformatics Resource Centers (BRCs) established by the NIAID to
serve integration of a broad array of -omics, epidemiological and clinical data.

For more information about IDO and its sub-domain extensions especially in the areas of HIV, influenza, Malaria, and Staphylococcus aureus bacteremia. See http://www.infectiousdiseaseontology.org.

This NCBO Workshop on the Infectious Disease Ontology is funded by the United States National Institutes of Health through the NIH Roadmap for Medical Research, Grant 1 U54 HG004028. Its content is solely the responsibility of the organizers and presenters and does not necessarily represent the official views of the National Human Genome Research Institute or the National Institutes of Health. Information on the National Centers for Biomedical Computing can be found at http://nihroadmap.nih.gov/bioinformatics.

== Goals of the Meeting ==

*The primary goal of this meeting is to explore the potential benefits of using the IDO Infectious Disease Ontology as a controlled vocabulary for promoting consistency in the ways infectious disease data are described. IDO provides both a vocabulary of terms and a set of precise definitions that have been thoroughly reviewed for biological accuracy and logical consistency.

*We will explore the benefits of the IDO controlled vocabulary, especially in advancing the work of the Bioinformatics Resource Centers, in areas such as:

::clinical data integration
::text and data mining
::genetic susceptibility to infectious disease
::disease surveillance
::plant infectious disease

*The meeting will also address relations between IDO and other parallel initiatives, including [http://tsb.mssm.edu/primeportal/ PRIME], [http://www.debugit.eu/ DebugIT], and the various IDO extension ontologies.

*To address these goals, speakers are asked to address the following points
**The goals of their project
:::biological questions for research projects
:::content and functions for computational resource projects
**The tasks for which terminologies are needed
**The terminologies currently being using
:::brief description of any terminologies developed specifically for the project
:::description of the ways in which current terminologies are inadequate for the project’s needs

== Schedule ==

'''Tuesday, December 7'''

*7:00-9:00pm Welcome Reception (Sponsored by the University of Texas Southwestern Medical Center at Dallas; Cash Bar)

'''Day 1: Wednesday, December 8'''

*8:30am Registration & Continental Breakfast

*9:00am Introduction: The current state of IDO and its role as a controlled vocabulary for infectious disease research (Session chair: Smith)
::Lindsay Cowell: Scope and Content of IDO
::Barry Smith: How use of IDO creates information integration across multiple domains

*10:00am Session 1: Bioinformatics Resource Centers (Session chair: Scheuermann)
::Richard Scheuermann
:::BRCs Overview
:::ViPR - Virus Pathogen Resource
:::IRD - Influenza Research Database
::Chris Stoeckert
:::EuPathDB - Eukaryotic Pathogen Database Resource

*11:00am Refreshment Break

*11:30am Session 1 continued (Session chair: Sobral)
::Pantelis Topalis
:::VectorBase - Invertebrate Vectors of Human Pathogens
::Bruno Sobral
:::PATRIC - Pathosystems Resource Integration Center
:::PathogenPortal - Bioinformatics Resource Centers Portal

*12:30pm Lunch Break

*2:00pm Session 2: Additional large data and information repositories relevant for infectious disease research (Session chair: Scheuermann)
::Richard Scheuermann
:::ImmPort - Immunology Database and Analysis Portal
::TBD
:::PRIME - Program for Research on Immune Modeling and Experimentation

*3:00pm Session 3: General discussion of the Utility of IDO as a Controlled Vocabulary (Session chair: Smith)

*4:00pm Refreshment Break

*4:30pm Session 4: Decision Support Use Cases (Session chair: Fuentes)
::Saul Lozano-Fuentes - Dengue/vector control
::Daniel Schober - DeBugIT - Detecting and Eliminating Bacteria using Information Technology

*5:30pm End of Day 1

*6:00pm Dinner (for interested participants; No-host/Dutch treat)

'''Day 2: Thursday, December 9'''

*8:30am Continental Breakfast

*9:00am Session 1: Data Integration Use Cases (Session chair: Goldfain)
::Alexander Diehl - Comprehensive Annotation System for Infectious Disease Data
::Anna Maria Masci - CFAR - Centers for AIDS Research
::Stanley Schwartz - UB HIV project
::Mélanie Courtot - PCIRN - Public Health Agency of Canada / Canadian Institutes of Health Research Influenza Research Network
::Albert Goldfain - Linking Vital Signs Data to a ''Staphylococcus aureus'' IDO Disease Model

*11:00am Refreshment Break

*11:30am Session 2: IDO Extensions (Session chair: Ruttenberg)
::Yu Lin - Brucellosis Ontology
::Burke Squires - Flu-IDO

*12:30pm Lunch Break

*2:00pm Session 2 continued
::Oliver He - VIOLIN - VO
::Pankaj Jaswal - Plant IDO

*3:00pm Session 3: Next Steps Lindsay Cowell

*4:00pm Close of NCBO/IDO 2010 Workshop

'''Format'''

Presentations will be short introductions to group discussion. All sessions will emphasize group discussion over presentation.

== Venue ==

A block of guest rooms at a discounted rate has been arranged for those NCBO/IDO 2010 attendees requiring lodging at:

[http://www.hiltonbaltimorebwi.com Hilton Baltimore BWI Airport]
1739 West Nursery Road
Linthicum Heights, MD 21090

To make reservations by phone call 1-800-HILTONS (or the hotel 443-577-2411) and be sure to mention that you are part of Group Name:''' NCBO – IDO 2010''' / Group Code: '''NCBO'''.

To access our online reservation link, click [http://www.hilton.com/en/hi/groups/personalized/BWIAPHF-NCBO-20101207/index.jhtml?WT.mc_id=POG]

* The Hilton Baltimore BWI Airport offers complimentary shuttle service from/to BWI airport, and complimentary internet access in the lobby-area.

* NCBO–IDO 2010 attendees will also receive complimentary internet access in their guest room.

* To take advantage of the special rate and free internet access in your guest room, you must secure your room reservation '''no later than November 15, 2010'''.

Driving directions for local participants can be found here [http://www1.hilton.com/en_US/hi/hotel/BWIAPHF-Hilton-Baltimore-BWI-Airport-Maryland/directions.do]

== Participants ==

Mauricio B. Almeida (Universidade Federal de Minas Gerais, Brazil)

Sivaram Arabandi (Case Western Reserve University)

Mathias Brochhausen (Institute for Formal Ontology and Medical Information Science, Saarland University)

Mélanie Courtot (British Columbia Cancer Research Center, Vancouver)

Lindsay Cowell (University of Texas Southwestern Medical Center, Dallas)

Alexander Diehl (Gene Ontology / The Jackson Laboratory)

Saul Lozano-Fuentes (Colorado State University)

Albert Goldfain (University at Buffalo)

Yongqun "Oliver" He (University of Michigan Medical Center)

Pankaj Jaiswal (Plant Ontology / Oregon State University)

Jessica Kissinger (Center for Tropical & Emerging Global Diseases / University of Georgia)

Yu Lin (University of Michigan Medical Center)

Joanne Luciano (Predictive Medicine, Inc. and Rensselaer Polytechnic Institute (RPI))

Chunhong Mao (PATRIC, Virginia Bioinformatics Institute)

Anna Maria Masci (Duke University Medical Center)

Alan Ruttenberg (Science Commons / University at Buffalo)

Richard Scheuermann (University of Texas Southwestern Medical Center at Dallas)

Daniel Schober (Universität Freiburg, Germany)

Maulik Shukla (PATRIC, Virginia Bioinformatics Institute)

Barry Smith (NCBO / University at Buffalo)

Bruno Sobral (PATRIC, Virginia Bioinformatics Institute)

Burke Squires (University of Texas Southwestern Medical Center at Dallas)

Christian Stoeckert (Penn Center for Bioinformatics / University of Pennsylvania)

Dan Sullivan (PATRIC, Virginia Bioinformatics Institute)

Pantelis Topalis (VectorBase / IMBB-FORTH, Crete)

Miguel H. Torres-Urquidy (CDC / OID/ NCIRD)

Patricia Whetzel (NCBO, Stanford)

Allen Xiang (University of Michigan Medical Center)

Jie Zheng (Penn Center for Bioinformatics / University of Pennsylvania)

IDO Workshop 2010

2010-11-30T17:47:46Z

Agoldfain: /* Schedule */

== Background ==

A two-day IDO workshop for invited participants will be held on December 8-9, 2010. Venue: Baltimore Airport Hilton. This meeting is being organized as part of the series of Dissemination Workshops organized under the auspices of the National Center for
Biomedical Ontology ([http://bioontology.org NCBO]).

The Infectious Disease Ontology (IDO) is a general terminology, taxonomy, and logical representation of entities relevant to all
infectious diseases. IDO is already being applied through disease-specific IDO extensions to the study of seven diseases,
including diseases of bacterial, viral, and eukaryotic origin.

Recently, the IDO has been adopted by the virus and bacterial Bioinformatics Resource Centers (BRCs) established by the NIAID to
serve integration of a broad array of -omics, epidemiological and clinical data.

For more information about IDO and its sub-domain extensions especially in the areas of HIV, influenza, Malaria, and Staphylococcus aureus bacteremia. See http://www.infectiousdiseaseontology.org.

This NCBO Workshop on the Infectious Disease Ontology is funded by the United States National Institutes of Health through the NIH Roadmap for Medical Research, Grant 1 U54 HG004028. Its content is solely the responsibility of the organizers and presenters and does not necessarily represent the official views of the National Human Genome Research Institute or the National Institutes of Health. Information on the National Centers for Biomedical Computing can be found at http://nihroadmap.nih.gov/bioinformatics.

== Goals of the Meeting ==

*The primary goal of this meeting is to explore the potential benefits of using the IDO Infectious Disease Ontology as a controlled vocabulary for promoting consistency in the ways infectious disease data are described. IDO provides both a vocabulary of terms and a set of precise definitions that have been thoroughly reviewed for biological accuracy and logical consistency.

*We will explore the benefits of the IDO controlled vocabulary, especially in advancing the work of the Bioinformatics Resource Centers, in areas such as:

::clinical data integration
::text and data mining
::genetic susceptibility to infectious disease
::disease surveillance
::plant infectious disease

*The meeting will also address relations between IDO and other parallel initiatives, including [http://tsb.mssm.edu/primeportal/ PRIME], [http://www.debugit.eu/ DebugIT], and the various IDO extension ontologies.

*To address these goals, speakers are asked to address the following points
**The goals of their project
:::biological questions for research projects
:::content and functions for computational resource projects
**The tasks for which terminologies are needed
**The terminologies currently being using
:::brief description of any terminologies developed specifically for the project
:::description of the ways in which current terminologies are inadequate for the project’s needs

== Schedule ==

'''Tuesday, December 7'''

*7:00-9:00pm Welcome Reception (Sponsored by the University of Texas Southwestern Medical Center at Dallas; Cash Bar)

'''Day 1: Wednesday, December 8'''

*8:30am Registration & Continental Breakfast

*9:00am Introduction: The current state of IDO and its role as a controlled vocabulary for infectious disease research (Session chair: Smith)
::Lindsay Cowell: Scope and Content of IDO
::Barry Smith: How use of IDO creates information integration across multiple domains

*10:00am Session 1: Bioinformatics Resource Centers (Session chair: Scheuermann)
::Richard Scheuermann
:::BRCs Overview
:::ViPR - Virus Pathogen Resource
:::IRD - Influenza Research Database
::Chris Stoeckert
:::EuPathDB - Eukaryotic Pathogen Database Resource

*11:00am Refreshment Break

*11:30am Session 1 continued (Session chair: Sobral)
::Pantelis Topalis
:::VectorBase - Invertebrate Vectors of Human Pathogens
::Bruno Sobral
:::PATRIC - Pathosystems Resource Integration Center
:::PathogenPortal - Bioinformatics Resource Centers Portal

*12:30pm Lunch Break

*2:00pm Session 2: Additional large data and information repositories relevant for infectious disease research (Session chair: Scheuermann)
::Richard Scheuermann
:::ImmPort - Immunology Database and Analysis Portal
::TBD
:::PRIME - Program for Research on Immune Modeling and Experimentation

*3:00pm Session 3: General discussion of the Utility of IDO as a Controlled Vocabulary (Session chair: Smith)

*4:00pm Refreshment Break

*4:30pm Session 4: Decision Support Use Cases (Session chair: Fuentes)
::Saul Lozano-Fuentes - Dengue/vector control
::Daniel Schober - DeBugIT - Detecting and Eliminating Bacteria using Information Technology

*5:30pm End of Day 1

*6:00pm Dinner (for interested participants; No-host/Dutch treat)

'''Day 2: Thursday, December 9'''

*8:30am Continental Breakfast

*9:00am Session 1: Data Integration Use Cases (Session chair: Goldfain)
::Alexander Diehl - Comprehensive Annotation System for Infectious Disease Data
::Anna Maria Masci - CFAR - Centers for AIDS Research
::Stanley Schwartz - UB HIV project
::Mélanie Courtot - PCIRN - Public Health Agency of Canada / Canadian Institutes of Health Research Influenza Research Network
::Albert Goldfain - Linking Vital Signs Device Data to a ''Staphylococcus aureus'' IDO Disease Model

*11:00am Refreshment Break

*11:30am Session 2: IDO Extensions (Session chair: Ruttenberg)
::Yu Lin - Brucellosis Ontology
::Burke Squires - Flu-IDO

*12:30pm Lunch Break

*2:00pm Session 2 continued
::Oliver He - VIOLIN - VO
::Pankaj Jaswal - Plant IDO

*3:00pm Session 3: Next Steps Lindsay Cowell

*4:00pm Close of NCBO/IDO 2010 Workshop

'''Format'''

Presentations will be short introductions to group discussion. All sessions will emphasize group discussion over presentation.

== Venue ==

A block of guest rooms at a discounted rate has been arranged for those NCBO/IDO 2010 attendees requiring lodging at:

[http://www.hiltonbaltimorebwi.com Hilton Baltimore BWI Airport]
1739 West Nursery Road
Linthicum Heights, MD 21090

To make reservations by phone call 1-800-HILTONS (or the hotel 443-577-2411) and be sure to mention that you are part of Group Name:''' NCBO – IDO 2010''' / Group Code: '''NCBO'''.

To access our online reservation link, click [http://www.hilton.com/en/hi/groups/personalized/BWIAPHF-NCBO-20101207/index.jhtml?WT.mc_id=POG]

* The Hilton Baltimore BWI Airport offers complimentary shuttle service from/to BWI airport, and complimentary internet access in the lobby-area.

* NCBO–IDO 2010 attendees will also receive complimentary internet access in their guest room.

* To take advantage of the special rate and free internet access in your guest room, you must secure your room reservation '''no later than November 15, 2010'''.

Driving directions for local participants can be found here [http://www1.hilton.com/en_US/hi/hotel/BWIAPHF-Hilton-Baltimore-BWI-Airport-Maryland/directions.do]

== Participants ==

Mauricio B. Almeida (Universidade Federal de Minas Gerais, Brazil)

Sivaram Arabandi (Case Western Reserve University)

Mathias Brochhausen (Institute for Formal Ontology and Medical Information Science, Saarland University)

Mélanie Courtot (British Columbia Cancer Research Center, Vancouver)

Lindsay Cowell (University of Texas Southwestern Medical Center, Dallas)

Alexander Diehl (Gene Ontology / The Jackson Laboratory)

Saul Lozano-Fuentes (Colorado State University)

Albert Goldfain (University at Buffalo)

Yongqun "Oliver" He (University of Michigan Medical Center)

Pankaj Jaiswal (Plant Ontology / Oregon State University)

Jessica Kissinger (Center for Tropical & Emerging Global Diseases / University of Georgia)

Yu Lin (University of Michigan Medical Center)

Joanne Luciano (Predictive Medicine, Inc. and Rensselaer Polytechnic Institute (RPI))

Chunhong Mao (PATRIC, Virginia Bioinformatics Institute)

Anna Maria Masci (Duke University Medical Center)

Alan Ruttenberg (Science Commons / University at Buffalo)

Richard Scheuermann (University of Texas Southwestern Medical Center at Dallas)

Daniel Schober (Universität Freiburg, Germany)

Maulik Shukla (PATRIC, Virginia Bioinformatics Institute)

Barry Smith (NCBO / University at Buffalo)

Bruno Sobral (PATRIC, Virginia Bioinformatics Institute)

Burke Squires (University of Texas Southwestern Medical Center at Dallas)

Christian Stoeckert (Penn Center for Bioinformatics / University of Pennsylvania)

Dan Sullivan (PATRIC, Virginia Bioinformatics Institute)

Pantelis Topalis (VectorBase / IMBB-FORTH, Crete)

Miguel H. Torres-Urquidy (CDC / OID/ NCIRD)

Patricia Whetzel (NCBO, Stanford)

Allen Xiang (University of Michigan Medical Center)

Jie Zheng (Penn Center for Bioinformatics / University of Pennsylvania)

IDO Workshop 2010

2010-11-30T17:45:27Z

Agoldfain: /* Schedule */ Modified Albert Goldfain's Talk Title

== Background ==

A two-day IDO workshop for invited participants will be held on December 8-9, 2010. Venue: Baltimore Airport Hilton. This meeting is being organized as part of the series of Dissemination Workshops organized under the auspices of the National Center for
Biomedical Ontology ([http://bioontology.org NCBO]).

The Infectious Disease Ontology (IDO) is a general terminology, taxonomy, and logical representation of entities relevant to all
infectious diseases. IDO is already being applied through disease-specific IDO extensions to the study of seven diseases,
including diseases of bacterial, viral, and eukaryotic origin.

Recently, the IDO has been adopted by the virus and bacterial Bioinformatics Resource Centers (BRCs) established by the NIAID to
serve integration of a broad array of -omics, epidemiological and clinical data.

For more information about IDO and its sub-domain extensions especially in the areas of HIV, influenza, Malaria, and Staphylococcus aureus bacteremia. See http://www.infectiousdiseaseontology.org.

This NCBO Workshop on the Infectious Disease Ontology is funded by the United States National Institutes of Health through the NIH Roadmap for Medical Research, Grant 1 U54 HG004028. Its content is solely the responsibility of the organizers and presenters and does not necessarily represent the official views of the National Human Genome Research Institute or the National Institutes of Health. Information on the National Centers for Biomedical Computing can be found at http://nihroadmap.nih.gov/bioinformatics.

== Goals of the Meeting ==

*The primary goal of this meeting is to explore the potential benefits of using the IDO Infectious Disease Ontology as a controlled vocabulary for promoting consistency in the ways infectious disease data are described. IDO provides both a vocabulary of terms and a set of precise definitions that have been thoroughly reviewed for biological accuracy and logical consistency.

*We will explore the benefits of the IDO controlled vocabulary, especially in advancing the work of the Bioinformatics Resource Centers, in areas such as:

::clinical data integration
::text and data mining
::genetic susceptibility to infectious disease
::disease surveillance
::plant infectious disease

*The meeting will also address relations between IDO and other parallel initiatives, including [http://tsb.mssm.edu/primeportal/ PRIME], [http://www.debugit.eu/ DebugIT], and the various IDO extension ontologies.

*To address these goals, speakers are asked to address the following points
**The goals of their project
:::biological questions for research projects
:::content and functions for computational resource projects
**The tasks for which terminologies are needed
**The terminologies currently being using
:::brief description of any terminologies developed specifically for the project
:::description of the ways in which current terminologies are inadequate for the project’s needs

== Schedule ==

'''Tuesday, December 7'''

*7:00-9:00pm Welcome Reception (Sponsored by the University of Texas Southwestern Medical Center at Dallas; Cash Bar)

'''Day 1: Wednesday, December 8'''

*8:30am Registration & Continental Breakfast

*9:00am Introduction: The current state of IDO and its role as a controlled vocabulary for infectious disease research (Session chair: Smith)
::Lindsay Cowell: Scope and Content of IDO
::Barry Smith: How use of IDO creates information integration across multiple domains

*10:00am Session 1: Bioinformatics Resource Centers (Session chair: Scheuermann)
::Richard Scheuermann
:::BRCs Overview
:::ViPR - Virus Pathogen Resource
:::IRD - Influenza Research Database
::Chris Stoeckert
:::EuPathDB - Eukaryotic Pathogen Database Resource

*11:00am Refreshment Break

*11:30am Session 1 continued (Session chair: Sobral)
::Pantelis Topalis
:::VectorBase - Invertebrate Vectors of Human Pathogens
::Bruno Sobral
:::PATRIC - Pathosystems Resource Integration Center
:::PathogenPortal - Bioinformatics Resource Centers Portal

*12:30pm Lunch Break

*2:00pm Session 2: Additional large data and information repositories relevant for infectious disease research (Session chair: Scheuermann)
::Richard Scheuermann
:::ImmPort - Immunology Database and Analysis Portal
::TBD
:::PRIME - Program for Research on Immune Modeling and Experimentation

*3:00pm Session 3: General discussion of the Utility of IDO as a Controlled Vocabulary (Session chair: Smith)

*4:00pm Refreshment Break

*4:30pm Session 4: Decision Support Use Cases (Session chair: Fuentes)
::Saul Lozano-Fuentes - Dengue/vector control
::Daniel Schober - DeBugIT - Detecting and Eliminating Bacteria using Information Technology

*5:30pm End of Day 1

*6:00pm Dinner (for interested participants; No-host/Dutch treat)

'''Day 2: Thursday, December 9'''

*8:30am Continental Breakfast

*9:00am Session 1: Data Integration Use Cases (Session chair: Goldfain)
::Alexander Diehl - Comprehensive Annotation System for Infectious Disease Data
::Anna Maria Masci - CFAR - Centers for AIDS Research
::Stanley Schwartz - UB HIV project
::Mélanie Courtot - PCIRN - Public Health Agency of Canada / Canadian Institutes of Health Research Influenza Research Network
::Albert Goldfain - The ''Staphylococcus aureus'' IDO Extension

*11:00am Refreshment Break

*11:30am Session 2: IDO Extensions (Session chair: Ruttenberg)
::Yu Lin - Brucellosis Ontology
::Burke Squires - Flu-IDO

*12:30pm Lunch Break

*2:00pm Session 2 continued
::Oliver He - VIOLIN - VO
::Pankaj Jaswal - Plant IDO

*3:00pm Session 3: Next Steps Lindsay Cowell

*4:00pm Close of NCBO/IDO 2010 Workshop

'''Format'''

Presentations will be short introductions to group discussion. All sessions will emphasize group discussion over presentation.

== Venue ==

A block of guest rooms at a discounted rate has been arranged for those NCBO/IDO 2010 attendees requiring lodging at:

[http://www.hiltonbaltimorebwi.com Hilton Baltimore BWI Airport]
1739 West Nursery Road
Linthicum Heights, MD 21090

To make reservations by phone call 1-800-HILTONS (or the hotel 443-577-2411) and be sure to mention that you are part of Group Name:''' NCBO – IDO 2010''' / Group Code: '''NCBO'''.

To access our online reservation link, click [http://www.hilton.com/en/hi/groups/personalized/BWIAPHF-NCBO-20101207/index.jhtml?WT.mc_id=POG]

* The Hilton Baltimore BWI Airport offers complimentary shuttle service from/to BWI airport, and complimentary internet access in the lobby-area.

* NCBO–IDO 2010 attendees will also receive complimentary internet access in their guest room.

* To take advantage of the special rate and free internet access in your guest room, you must secure your room reservation '''no later than November 15, 2010'''.

Driving directions for local participants can be found here [http://www1.hilton.com/en_US/hi/hotel/BWIAPHF-Hilton-Baltimore-BWI-Airport-Maryland/directions.do]

== Participants ==

Mauricio B. Almeida (Universidade Federal de Minas Gerais, Brazil)

Sivaram Arabandi (Case Western Reserve University)

Mathias Brochhausen (Institute for Formal Ontology and Medical Information Science, Saarland University)

Mélanie Courtot (British Columbia Cancer Research Center, Vancouver)

Lindsay Cowell (University of Texas Southwestern Medical Center, Dallas)

Alexander Diehl (Gene Ontology / The Jackson Laboratory)

Saul Lozano-Fuentes (Colorado State University)

Albert Goldfain (University at Buffalo)

Yongqun "Oliver" He (University of Michigan Medical Center)

Pankaj Jaiswal (Plant Ontology / Oregon State University)

Jessica Kissinger (Center for Tropical & Emerging Global Diseases / University of Georgia)

Yu Lin (University of Michigan Medical Center)

Joanne Luciano (Predictive Medicine, Inc. and Rensselaer Polytechnic Institute (RPI))

Chunhong Mao (PATRIC, Virginia Bioinformatics Institute)

Anna Maria Masci (Duke University Medical Center)

Alan Ruttenberg (Science Commons / University at Buffalo)

Richard Scheuermann (University of Texas Southwestern Medical Center at Dallas)

Daniel Schober (Universität Freiburg, Germany)

Maulik Shukla (PATRIC, Virginia Bioinformatics Institute)

Barry Smith (NCBO / University at Buffalo)

Bruno Sobral (PATRIC, Virginia Bioinformatics Institute)

Burke Squires (University of Texas Southwestern Medical Center at Dallas)

Christian Stoeckert (Penn Center for Bioinformatics / University of Pennsylvania)

Dan Sullivan (PATRIC, Virginia Bioinformatics Institute)

Pantelis Topalis (VectorBase / IMBB-FORTH, Crete)

Miguel H. Torres-Urquidy (CDC / OID/ NCIRD)

Patricia Whetzel (NCBO, Stanford)

Allen Xiang (University of Michigan Medical Center)

Jie Zheng (Penn Center for Bioinformatics / University of Pennsylvania)

Infectious Disease Ontology Workshop - Medinfo 2010

2010-09-17T13:21:40Z

Agoldfain:

== Medinfo 2010 Workshop ==
There will be an [http://www.infectiousdiseaseontology.org/Home.html IDO] workshop at the [http://www.medinfo2010.org/ 13th World Congress on Medical and Health Informatics (Medinfo 2010)] in Cape Town, South Africa on September 11, 2010 (17:00-18:30). A detailed program for Medinfo can be found [http://www.medinfo2010.org/docs/detailed_programme.pdf here].

Infectious diseases inflict a disproportionate burden on developing countries. A lack of adequate treatment and prevention resources has resulted in a higher prevalence of infectious disease among the world's poorest people. This underscores the need for approaches to informatics support which leverage limited resources as effectively and efficiently as possible. Increasingly, response to infectious disease requires the use of information from multiple, constantly changing data sources. Currently, such information is collected using discipline-specific methodologies and is stored in heterogeneous databases, electronic health records, paper charts, and clinical and public health data repositories. Infectious disease data thus often remains only locally accessible, and because it
is expressed in incompatible formats it does not allow for broad spectrum computational processing, querying, inference, or verification. Data silos hinder translational and comparative research. Aggregating data through use of a common data format and a common terminology (i.e., an ontology) allows a variety of secondary uses of data such as: rapid determination of pathogen type in infections or disease outbreaks, treatment decision support based on genetic characteristics of host and pathogen (e.g., drug resistance), and research to improve understanding of disease pathogenesis leading to development of new types of treatments. The Infectious Disease Ontology (IDO) addresses the problem of data silos by providing a consistent terminology, taxonomy, and logical representation of entities relevant to all infectious diseases. IDO is already being applied to the study of seven diseases, including diseases of bacterial, viral, and eukaryotic origin. The objectives of this workshop are to introduce IDO and the methodology for creating disease-specific IDO extensions, to present applications of the ontologies to the study of
Malaria, HIV, and Influenza, and to open up the IDO enterprise to a wider audience of medical informaticians.

==Workshop Description==
The workshop will consist of five presentations addressing the scope, design, evolution, and practical utility of IDO. Specifically, the first two will describe the principles of IDO and of the ontologies derived from it, and provide also a description of existing database efforts in the infectious disease domain. The remaining presentations will describe disease-specific ontologies developed from IDO and their application to specific data integration and processing tasks, including the planning of disease control measures, the integration of data from
studies in humans and studies in model organisms, the study of co-infection, disease surveillance, and the study of viral evolution.

==Presenters==
* [http://ontology.buffalo.edu/smith/ Barry Smith] (University at Buffalo)
* [http://org.buffalo.edu/goldfain/index.html Albert Goldfain] (Blue Highway LLC)
* [http://biostat.duke.edu/modules/dukefaculty/viewDetails.php?d=cowel001&t=1 Lindsay G. Cowell] (University of Texas Southwestern Medical Center)
* [http://www.anobase.org/~louis/ Christos Louis] (IMBB-FORTH and University of Crete)

==Talk Abstracts==

=== Infectious Disease Ontology: The Very Idea. ([http://www.buffalo.edu/~ag33/OBOFoundry-Medinfo-2010.ppt slides]) ''Speaker: Barry Smith'' ===
When computers are used in the storage and processing of data about infectious diseases and their causes, incidence, and treatment, there are obvious advantages to the use of a common controlled vocabulary or ‘ontology’. By making data comparable even when it derives from different sources, the ontology not only aids information-driven research directed towards elucidation of the disease mechanisms involved and the development of novel therapeutics, it also enhances our ability to use legacy disease data in rapid analysis of data pertaining to novel pathogens or mutations. This talk will describe the IDO strategy for creating a common ontology resource that can support these ends, and outline the work of the IDO Consortium, which is attempting to realize this strategy in a variety of disease domains by means of a general purpose core containing disease-neutral terms (such as ‘host’, ‘pathogen’, ‘virulence’) together with a number of extension vocabularies created by communities of researchers managing data pertaining to specific human, animal and plant infectious diseases, as well as by vaccine researchers. One advantage of this strategy is that, as each new group of infectious disease researchers confronts the need for a controlled vocabulary to represent the phenomena in its specific domain, it has a ready-made set of terms to begin this process in the application of which it can draw on the lessons learned by others while at the same time ensuring interoperability of their own data with the data collected in other disease domains.

=== Introduction to the IDO Core. ([http://www.buffalo.edu/~ag33/IDOCoreMedinfo.ppt slides])''Speaker: Albert Goldfain'' ===

Despite the recent surge of interest in biomedical ontology, there was until recently little ontology coverage of the infectious disease domain, resulting in both an urgent need for ontology development in this field and the opportunity for a coordinated, community-wide development effort producing broad interoperability across the disease-specific specialties and across the clinical care, public health, and biomedical research domains. To provide the foundation for such an effort, we have developed a general infectious disease ontology (IDO Core) designed to serve as a central ontology (hub) from which disease-specific extensions (spokes) can be built through a process of specialization. The IDO core was designed i) to provide ontology coverage of terms generally relevant to infectious disease research, ii) to ensure interoperability between the IDO extensions, and iii) to achieve these ends on the basis of a W3C standard logical formalism intended to ensure extensibility of the ontologies while preserving their utility for computational applications. Each extension can be developed and maintained by domain experts, allowing for rapid progress towards the needed set of ontologies, ensuring biological accuracy of the extensions, and increasing the likelihood of broad adoption by the infectious disease research community. IDO Core thus provides an invaluable ontology resource for infectious disease researchers, allowing cross-domain data integration and supporting the computation-intensive data processing and analysis tasks becoming the basis of biomedical research.

IDO Core is intended to represent information along three dimensions:

* biological scale (gene, cell, organ, organism, and population)
* discipline (clinical, immunological, microbiological, epidemiological)
* host, pathogen, and vector organisms (e.g., human, rat, pig, maize, HIV, influenza, mosquito).

IDO Core makes distinctions between infections, infectious diseases, infectious disease courses, the diagnosis of infectious disease, and the signs and symptoms of infectious diseases. The conflation of any of these entities can lead to incoherent reasoning, inconsistent models of specific diseases, and even medical errors in electronic health records.

As a case-study in the use of IDO across diseases, we will describe the IDO Core representation of protective resistance. The resistance of pathogens to certain drugs is a central obstacle to the treatment and management of infectious disease. More generally, resistance can be used to describe phenomena such as the immunity of an individual to specific diseases and the resistance of disorders to specific treatments.

=== Malaria Ontology (IDOMAL) ''Speaker: Christos Louis'' ===

Hundreds of millions of cases of vector-borne diseases occur annually, the vast majority of which affect populations in tropical regions of the world. Malaria, the most prominent among them, causes more than one million deaths each year, mostly among small children in these areas. For a number of reasons, including the development of resistance against both drugs and insecticides, the numbers of cases, and of deaths, has not decreased substantially, in spite of the progress achieved in medical sciences in recent decades. There is there-fore a need for new tools that will help alleviate this problem. These will include IT tools such as decision support systems (DSS), which, especially in the cases of emerging epidemics, will use data collections to help local authorities plan their disease control measures. This module will describe our work on the IDOMAL malaria ontology, an IDO extension ontology that is designed to advance work in this broad area and will be used to drive both databases and the DSSs that rely on them. IDOMAL will contain terms from all four corners of the malaria domain, which is to say: the biology of vectors and of disease, epidemiology, and clinical features. We have already recruited the participation of expert collaborators in order to ensure the broadest and most accurate coverage of the disease. Our plans for the future include the expansion of IDOMAL to cover other vector-borne diseases.

=== HIV Ontology (IDOHIV) ''Speaker: Lindsay G. Cowell'' ===

In 2007, 33 million people were living with Human Immunodeficiency Virus (HIV), including 2 million children. Annually, there are approximately 2 million deaths as a result of HIV, with the leading cause of death being co-infection with Myco-bacterium tuberculosis (Mtb), a problem that is increasing with the appearance of new, highly virulent, drug-resistant strains of Mtb. A number of factors suggest that real progress towards alleviating the global HIV burden will require development of the terminological and logical infrastructure for broad data interoperability, and in particular for data interoperability across multiple disease domains. These include the central role of secondary infections in the HIV disease course, the importance of model infections to the study of HIV pathogenesis and vaccine efficacy, and the increasing need to synchronize the collection of data from patients enrolled in observational studies and clinical trials being carried out throughout the world. IDO is designed to provide the basis for the needed common terminological and logical architecture. This talk will describe the HIV Ontology (IDOHIV) developed as an IDO extension and will sketch the application of IDOHIV to i) the integration of results from Simian Immunodeficiency Virus (SIV) and HIV studies, ii) the study of HIV co-infection with Mtb and Hepatitis C Virus (HCV), and iii) the creation of an interactive, comprehensive database for the Duke Center for Aids Research (CFAR).

==Intended Audience==
The workshop does not assume any prior knowledge of ontologies or the infectious disease domain, and is aimed at a broad audience, including:
* medical informaticians
* biologists
* health care providers
* epidemiologists and public health workers
* bioinformatics researchers
* biomedical researchers
* computer scientists

==Goals==
* To demonstrate the advantages of a common approach for annotating infectious disease data
* To show how the IDO terminology can be used as a teaching tool.
* To showcase the multidisciplinary nature of IDO.
* To enable interested attendees to begin using IDO for annotating their own datasets.
* To enable interested attendees to begin creating their own [http://www.infectiousdiseaseontology.org/IDO_Extensions.html IDO extensions].

Infectious Disease Ontology Workshop - Medinfo 2010

2010-09-17T13:20:30Z

Agoldfain: Added agoldfain's slides

== Medinfo 2010 Workshop ==
There will be an [http://www.infectiousdiseaseontology.org/Home.html IDO] workshop at the [http://www.medinfo2010.org/ 13th World Congress on Medical and Health Informatics (Medinfo 2010)] in Cape Town, South Africa on September 11, 2010 (17:00-18:30). A detailed program for Medinfo can be found [http://www.medinfo2010.org/docs/detailed_programme.pdf here].

Infectious diseases inflict a disproportionate burden on developing countries. A lack of adequate treatment and prevention resources has resulted in a higher prevalence of infectious disease among the world's poorest people. This underscores the need for approaches to informatics support which leverage limited resources as effectively and efficiently as possible. Increasingly, response to infectious disease requires the use of information from multiple, constantly changing data sources. Currently, such information is collected using discipline-specific methodologies and is stored in heterogeneous databases, electronic health records, paper charts, and clinical and public health data repositories. Infectious disease data thus often remains only locally accessible, and because it
is expressed in incompatible formats it does not allow for broad spectrum computational processing, querying, inference, or verification. Data silos hinder translational and comparative research. Aggregating data through use of a common data format and a common terminology (i.e., an ontology) allows a variety of secondary uses of data such as: rapid determination of pathogen type in infections or disease outbreaks, treatment decision support based on genetic characteristics of host and pathogen (e.g., drug resistance), and research to improve understanding of disease pathogenesis leading to development of new types of treatments. The Infectious Disease Ontology (IDO) addresses the problem of data silos by providing a consistent terminology, taxonomy, and logical representation of entities relevant to all infectious diseases. IDO is already being applied to the study of seven diseases, including diseases of bacterial, viral, and eukaryotic origin. The objectives of this workshop are to introduce IDO and the methodology for creating disease-specific IDO extensions, to present applications of the ontologies to the study of
Malaria, HIV, and Influenza, and to open up the IDO enterprise to a wider audience of medical informaticians.

==Workshop Description==
The workshop will consist of five presentations addressing the scope, design, evolution, and practical utility of IDO. Specifically, the first two will describe the principles of IDO and of the ontologies derived from it, and provide also a description of existing database efforts in the infectious disease domain. The remaining presentations will describe disease-specific ontologies developed from IDO and their application to specific data integration and processing tasks, including the planning of disease control measures, the integration of data from
studies in humans and studies in model organisms, the study of co-infection, disease surveillance, and the study of viral evolution.

==Presenters==
* [http://ontology.buffalo.edu/smith/ Barry Smith] (University at Buffalo)
* [http://org.buffalo.edu/goldfain/index.html Albert Goldfain] (Blue Highway LLC)
* [http://biostat.duke.edu/modules/dukefaculty/viewDetails.php?d=cowel001&t=1 Lindsay G. Cowell] (University of Texas Southwestern Medical Center)
* [http://www.anobase.org/~louis/ Christos Louis] (IMBB-FORTH and University of Crete)

==Talk Abstracts==

=== Infectious Disease Ontology: The Very Idea. ([http://www.buffalo.edu/~ag33/OBOFoundry-Medinfo-2010.ppt slides]) ''Speaker: Barry Smith'' ===
When computers are used in the storage and processing of data about infectious diseases and their causes, incidence, and treatment, there are obvious advantages to the use of a common controlled vocabulary or ‘ontology’. By making data comparable even when it derives from different sources, the ontology not only aids information-driven research directed towards elucidation of the disease mechanisms involved and the development of novel therapeutics, it also enhances our ability to use legacy disease data in rapid analysis of data pertaining to novel pathogens or mutations. This talk will describe the IDO strategy for creating a common ontology resource that can support these ends, and outline the work of the IDO Consortium, which is attempting to realize this strategy in a variety of disease domains by means of a general purpose core containing disease-neutral terms (such as ‘host’, ‘pathogen’, ‘virulence’) together with a number of extension vocabularies created by communities of researchers managing data pertaining to specific human, animal and plant infectious diseases, as well as by vaccine researchers. One advantage of this strategy is that, as each new group of infectious disease researchers confronts the need for a controlled vocabulary to represent the phenomena in its specific domain, it has a ready-made set of terms to begin this process in the application of which it can draw on the lessons learned by others while at the same time ensuring interoperability of their own data with the data collected in other disease domains.

=== Introduction to the IDO Core. ([www.buffalo.edu/~ag33/IDOCoreMedinfo.ppt slides]''Speaker: Albert Goldfain'' ===

Despite the recent surge of interest in biomedical ontology, there was until recently little ontology coverage of the infectious disease domain, resulting in both an urgent need for ontology development in this field and the opportunity for a coordinated, community-wide development effort producing broad interoperability across the disease-specific specialties and across the clinical care, public health, and biomedical research domains. To provide the foundation for such an effort, we have developed a general infectious disease ontology (IDO Core) designed to serve as a central ontology (hub) from which disease-specific extensions (spokes) can be built through a process of specialization. The IDO core was designed i) to provide ontology coverage of terms generally relevant to infectious disease research, ii) to ensure interoperability between the IDO extensions, and iii) to achieve these ends on the basis of a W3C standard logical formalism intended to ensure extensibility of the ontologies while preserving their utility for computational applications. Each extension can be developed and maintained by domain experts, allowing for rapid progress towards the needed set of ontologies, ensuring biological accuracy of the extensions, and increasing the likelihood of broad adoption by the infectious disease research community. IDO Core thus provides an invaluable ontology resource for infectious disease researchers, allowing cross-domain data integration and supporting the computation-intensive data processing and analysis tasks becoming the basis of biomedical research.

IDO Core is intended to represent information along three dimensions:

* biological scale (gene, cell, organ, organism, and population)
* discipline (clinical, immunological, microbiological, epidemiological)
* host, pathogen, and vector organisms (e.g., human, rat, pig, maize, HIV, influenza, mosquito).

IDO Core makes distinctions between infections, infectious diseases, infectious disease courses, the diagnosis of infectious disease, and the signs and symptoms of infectious diseases. The conflation of any of these entities can lead to incoherent reasoning, inconsistent models of specific diseases, and even medical errors in electronic health records.

As a case-study in the use of IDO across diseases, we will describe the IDO Core representation of protective resistance. The resistance of pathogens to certain drugs is a central obstacle to the treatment and management of infectious disease. More generally, resistance can be used to describe phenomena such as the immunity of an individual to specific diseases and the resistance of disorders to specific treatments.

=== Malaria Ontology (IDOMAL) ''Speaker: Christos Louis'' ===

Hundreds of millions of cases of vector-borne diseases occur annually, the vast majority of which affect populations in tropical regions of the world. Malaria, the most prominent among them, causes more than one million deaths each year, mostly among small children in these areas. For a number of reasons, including the development of resistance against both drugs and insecticides, the numbers of cases, and of deaths, has not decreased substantially, in spite of the progress achieved in medical sciences in recent decades. There is there-fore a need for new tools that will help alleviate this problem. These will include IT tools such as decision support systems (DSS), which, especially in the cases of emerging epidemics, will use data collections to help local authorities plan their disease control measures. This module will describe our work on the IDOMAL malaria ontology, an IDO extension ontology that is designed to advance work in this broad area and will be used to drive both databases and the DSSs that rely on them. IDOMAL will contain terms from all four corners of the malaria domain, which is to say: the biology of vectors and of disease, epidemiology, and clinical features. We have already recruited the participation of expert collaborators in order to ensure the broadest and most accurate coverage of the disease. Our plans for the future include the expansion of IDOMAL to cover other vector-borne diseases.

=== HIV Ontology (IDOHIV) ''Speaker: Lindsay G. Cowell'' ===

In 2007, 33 million people were living with Human Immunodeficiency Virus (HIV), including 2 million children. Annually, there are approximately 2 million deaths as a result of HIV, with the leading cause of death being co-infection with Myco-bacterium tuberculosis (Mtb), a problem that is increasing with the appearance of new, highly virulent, drug-resistant strains of Mtb. A number of factors suggest that real progress towards alleviating the global HIV burden will require development of the terminological and logical infrastructure for broad data interoperability, and in particular for data interoperability across multiple disease domains. These include the central role of secondary infections in the HIV disease course, the importance of model infections to the study of HIV pathogenesis and vaccine efficacy, and the increasing need to synchronize the collection of data from patients enrolled in observational studies and clinical trials being carried out throughout the world. IDO is designed to provide the basis for the needed common terminological and logical architecture. This talk will describe the HIV Ontology (IDOHIV) developed as an IDO extension and will sketch the application of IDOHIV to i) the integration of results from Simian Immunodeficiency Virus (SIV) and HIV studies, ii) the study of HIV co-infection with Mtb and Hepatitis C Virus (HCV), and iii) the creation of an interactive, comprehensive database for the Duke Center for Aids Research (CFAR).

==Intended Audience==
The workshop does not assume any prior knowledge of ontologies or the infectious disease domain, and is aimed at a broad audience, including:
* medical informaticians
* biologists
* health care providers
* epidemiologists and public health workers
* bioinformatics researchers
* biomedical researchers
* computer scientists

==Goals==
* To demonstrate the advantages of a common approach for annotating infectious disease data
* To show how the IDO terminology can be used as a teaching tool.
* To showcase the multidisciplinary nature of IDO.
* To enable interested attendees to begin using IDO for annotating their own datasets.
* To enable interested attendees to begin creating their own [http://www.infectiousdiseaseontology.org/IDO_Extensions.html IDO extensions].

Infectious Disease Ontology Workshop - Medinfo 2010

2010-09-12T14:06:20Z

Agoldfain: Added Barry Smith's slides

== Medinfo 2010 Workshop ==
There will be an [http://www.infectiousdiseaseontology.org/Home.html IDO] workshop at the [http://www.medinfo2010.org/ 13th World Congress on Medical and Health Informatics (Medinfo 2010)] in Cape Town, South Africa on September 11, 2010 (17:00-18:30). A detailed program for Medinfo can be found [http://www.medinfo2010.org/docs/detailed_programme.pdf here].

Infectious diseases inflict a disproportionate burden on developing countries. A lack of adequate treatment and prevention resources has resulted in a higher prevalence of infectious disease among the world's poorest people. This underscores the need for approaches to informatics support which leverage limited resources as effectively and efficiently as possible. Increasingly, response to infectious disease requires the use of information from multiple, constantly changing data sources. Currently, such information is collected using discipline-specific methodologies and is stored in heterogeneous databases, electronic health records, paper charts, and clinical and public health data repositories. Infectious disease data thus often remains only locally accessible, and because it
is expressed in incompatible formats it does not allow for broad spectrum computational processing, querying, inference, or verification. Data silos hinder translational and comparative research. Aggregating data through use of a common data format and a common terminology (i.e., an ontology) allows a variety of secondary uses of data such as: rapid determination of pathogen type in infections or disease outbreaks, treatment decision support based on genetic characteristics of host and pathogen (e.g., drug resistance), and research to improve understanding of disease pathogenesis leading to development of new types of treatments. The Infectious Disease Ontology (IDO) addresses the problem of data silos by providing a consistent terminology, taxonomy, and logical representation of entities relevant to all infectious diseases. IDO is already being applied to the study of seven diseases, including diseases of bacterial, viral, and eukaryotic origin. The objectives of this workshop are to introduce IDO and the methodology for creating disease-specific IDO extensions, to present applications of the ontologies to the study of
Malaria, HIV, and Influenza, and to open up the IDO enterprise to a wider audience of medical informaticians.

==Workshop Description==
The workshop will consist of five presentations addressing the scope, design, evolution, and practical utility of IDO. Specifically, the first two will describe the principles of IDO and of the ontologies derived from it, and provide also a description of existing database efforts in the infectious disease domain. The remaining presentations will describe disease-specific ontologies developed from IDO and their application to specific data integration and processing tasks, including the planning of disease control measures, the integration of data from
studies in humans and studies in model organisms, the study of co-infection, disease surveillance, and the study of viral evolution.

==Presenters==
* [http://ontology.buffalo.edu/smith/ Barry Smith] (University at Buffalo)
* [http://org.buffalo.edu/goldfain/index.html Albert Goldfain] (Blue Highway LLC)
* [http://biostat.duke.edu/modules/dukefaculty/viewDetails.php?d=cowel001&t=1 Lindsay G. Cowell] (University of Texas Southwestern Medical Center)
* [http://www.anobase.org/~louis/ Christos Louis] (IMBB-FORTH and University of Crete)

==Talk Abstracts==

=== Infectious Disease Ontology: The Very Idea. ([http://www.buffalo.edu/~ag33/OBOFoundry-Medinfo-2010.ppt slides]) ''Speaker: Barry Smith'' ===
When computers are used in the storage and processing of data about infectious diseases and their causes, incidence, and treatment, there are obvious advantages to the use of a common controlled vocabulary or ‘ontology’. By making data comparable even when it derives from different sources, the ontology not only aids information-driven research directed towards elucidation of the disease mechanisms involved and the development of novel therapeutics, it also enhances our ability to use legacy disease data in rapid analysis of data pertaining to novel pathogens or mutations. This talk will describe the IDO strategy for creating a common ontology resource that can support these ends, and outline the work of the IDO Consortium, which is attempting to realize this strategy in a variety of disease domains by means of a general purpose core containing disease-neutral terms (such as ‘host’, ‘pathogen’, ‘virulence’) together with a number of extension vocabularies created by communities of researchers managing data pertaining to specific human, animal and plant infectious diseases, as well as by vaccine researchers. One advantage of this strategy is that, as each new group of infectious disease researchers confronts the need for a controlled vocabulary to represent the phenomena in its specific domain, it has a ready-made set of terms to begin this process in the application of which it can draw on the lessons learned by others while at the same time ensuring interoperability of their own data with the data collected in other disease domains.

=== Introduction to the IDO Core. ''Speaker: Albert Goldfain'' ===

Despite the recent surge of interest in biomedical ontology, there was until recently little ontology coverage of the infectious disease domain, resulting in both an urgent need for ontology development in this field and the opportunity for a coordinated, community-wide development effort producing broad interoperability across the disease-specific specialties and across the clinical care, public health, and biomedical research domains. To provide the foundation for such an effort, we have developed a general infectious disease ontology (IDO Core) designed to serve as a central ontology (hub) from which disease-specific extensions (spokes) can be built through a process of specialization. The IDO core was designed i) to provide ontology coverage of terms generally relevant to infectious disease research, ii) to ensure interoperability between the IDO extensions, and iii) to achieve these ends on the basis of a W3C standard logical formalism intended to ensure extensibility of the ontologies while preserving their utility for computational applications. Each extension can be developed and maintained by domain experts, allowing for rapid progress towards the needed set of ontologies, ensuring biological accuracy of the extensions, and increasing the likelihood of broad adoption by the infectious disease research community. IDO Core thus provides an invaluable ontology resource for infectious disease researchers, allowing cross-domain data integration and supporting the computation-intensive data processing and analysis tasks becoming the basis of biomedical research.

IDO Core is intended to represent information along three dimensions:

* biological scale (gene, cell, organ, organism, and population)
* discipline (clinical, immunological, microbiological, epidemiological)
* host, pathogen, and vector organisms (e.g., human, rat, pig, maize, HIV, influenza, mosquito).

IDO Core makes distinctions between infections, infectious diseases, infectious disease courses, the diagnosis of infectious disease, and the signs and symptoms of infectious diseases. The conflation of any of these entities can lead to incoherent reasoning, inconsistent models of specific diseases, and even medical errors in electronic health records.

As a case-study in the use of IDO across diseases, we will describe the IDO Core representation of protective resistance. The resistance of pathogens to certain drugs is a central obstacle to the treatment and management of infectious disease. More generally, resistance can be used to describe phenomena such as the immunity of an individual to specific diseases and the resistance of disorders to specific treatments.

=== Malaria Ontology (IDOMAL) ''Speaker: Christos Louis'' ===

Hundreds of millions of cases of vector-borne diseases occur annually, the vast majority of which affect populations in tropical regions of the world. Malaria, the most prominent among them, causes more than one million deaths each year, mostly among small children in these areas. For a number of reasons, including the development of resistance against both drugs and insecticides, the numbers of cases, and of deaths, has not decreased substantially, in spite of the progress achieved in medical sciences in recent decades. There is there-fore a need for new tools that will help alleviate this problem. These will include IT tools such as decision support systems (DSS), which, especially in the cases of emerging epidemics, will use data collections to help local authorities plan their disease control measures. This module will describe our work on the IDOMAL malaria ontology, an IDO extension ontology that is designed to advance work in this broad area and will be used to drive both databases and the DSSs that rely on them. IDOMAL will contain terms from all four corners of the malaria domain, which is to say: the biology of vectors and of disease, epidemiology, and clinical features. We have already recruited the participation of expert collaborators in order to ensure the broadest and most accurate coverage of the disease. Our plans for the future include the expansion of IDOMAL to cover other vector-borne diseases.

=== HIV Ontology (IDOHIV) ''Speaker: Lindsay G. Cowell'' ===

In 2007, 33 million people were living with Human Immunodeficiency Virus (HIV), including 2 million children. Annually, there are approximately 2 million deaths as a result of HIV, with the leading cause of death being co-infection with Myco-bacterium tuberculosis (Mtb), a problem that is increasing with the appearance of new, highly virulent, drug-resistant strains of Mtb. A number of factors suggest that real progress towards alleviating the global HIV burden will require development of the terminological and logical infrastructure for broad data interoperability, and in particular for data interoperability across multiple disease domains. These include the central role of secondary infections in the HIV disease course, the importance of model infections to the study of HIV pathogenesis and vaccine efficacy, and the increasing need to synchronize the collection of data from patients enrolled in observational studies and clinical trials being carried out throughout the world. IDO is designed to provide the basis for the needed common terminological and logical architecture. This talk will describe the HIV Ontology (IDOHIV) developed as an IDO extension and will sketch the application of IDOHIV to i) the integration of results from Simian Immunodeficiency Virus (SIV) and HIV studies, ii) the study of HIV co-infection with Mtb and Hepatitis C Virus (HCV), and iii) the creation of an interactive, comprehensive database for the Duke Center for Aids Research (CFAR).

==Intended Audience==
The workshop does not assume any prior knowledge of ontologies or the infectious disease domain, and is aimed at a broad audience, including:
* medical informaticians
* biologists
* health care providers
* epidemiologists and public health workers
* bioinformatics researchers
* biomedical researchers
* computer scientists

==Goals==
* To demonstrate the advantages of a common approach for annotating infectious disease data
* To show how the IDO terminology can be used as a teaching tool.
* To showcase the multidisciplinary nature of IDO.
* To enable interested attendees to begin using IDO for annotating their own datasets.
* To enable interested attendees to begin creating their own [http://www.infectiousdiseaseontology.org/IDO_Extensions.html IDO extensions].

Infectious Disease Ontology Workshop - Medinfo 2010

2010-08-09T17:22:04Z

Agoldfain:

== Medinfo 2010 Workshop ==
There will be an [http://www.infectiousdiseaseontology.org/Home.html IDO] workshop at the [http://www.medinfo2010.org/ 13th World Congress on Medical and Health Informatics (Medinfo 2010)] in Cape Town, South Africa on September 11, 2010 (17:00-18:30). A detailed program for Medinfo can be found [http://www.medinfo2010.org/docs/detailed_programme.pdf here].

Infectious diseases inflict a disproportionate burden on developing countries. A lack of adequate treatment and prevention resources has resulted in a higher prevalence of infectious disease among the world's poorest people. This underscores the need for approaches to informatics support which leverage limited resources as effectively and efficiently as possible. Increasingly, response to infectious disease requires the use of information from multiple, constantly changing data sources. Currently, such information is collected using discipline-specific methodologies and is stored in heterogeneous databases, electronic health records, paper charts, and clinical and public health data repositories. Infectious disease data thus often remains only locally accessible, and because it
is expressed in incompatible formats it does not allow for broad spectrum computational processing, querying, inference, or verification. Data silos hinder translational and comparative research. Aggregating data through use of a common data format and a common terminology (i.e., an ontology) allows a variety of secondary uses of data such as: rapid determination of pathogen type in infections or disease outbreaks, treatment decision support based on genetic characteristics of host and pathogen (e.g., drug resistance), and research to improve understanding of disease pathogenesis leading to development of new types of treatments. The Infectious Disease Ontology (IDO) addresses the problem of data silos by providing a consistent terminology, taxonomy, and logical representation of entities relevant to all infectious diseases. IDO is already being applied to the study of seven diseases, including diseases of bacterial, viral, and eukaryotic origin. The objectives of this workshop are to introduce IDO and the methodology for creating disease-specific IDO extensions, to present applications of the ontologies to the study of
Malaria, HIV, and Influenza, and to open up the IDO enterprise to a wider audience of medical informaticians.

==Workshop Description==
The workshop will consist of five presentations addressing the scope, design, evolution, and practical utility of IDO. Specifically, the first two will describe the principles of IDO and of the ontologies derived from it, and provide also a description of existing database efforts in the infectious disease domain. The remaining presentations will describe disease-specific ontologies developed from IDO and their application to specific data integration and processing tasks, including the planning of disease control measures, the integration of data from
studies in humans and studies in model organisms, the study of co-infection, disease surveillance, and the study of viral evolution.

==Presenters==
* [http://ontology.buffalo.edu/smith/ Barry Smith] (University at Buffalo)
* [http://org.buffalo.edu/goldfain/index.html Albert Goldfain] (Blue Highway LLC)
* [http://biostat.duke.edu/modules/dukefaculty/viewDetails.php?d=cowel001&t=1 Lindsay G. Cowell] (Duke University Medical Center)
* [http://www.anobase.org/~louis/ Christos Louis] (IMBB-FORTH and University of Crete)
* [http://www.utsouthwestern.edu/findfac/research/0,2357,16416,00.html Richard H. Scheuermann] (University of Texas Southwestern Medical Center)

==Talk Abstracts==

=== Infectious Disease Ontology: The Very Idea. ''Speaker: Barry Smith'' ===
When computers are used in the storage and processing of data about infectious diseases and their causes, incidence, and treatment, there are obvious advantages to the use of a common controlled vocabulary or ‘ontology’. By making data comparable even when it derives from different sources, the ontology not only aids information-driven research directed towards elucidation of the disease mechanisms involved and the development of novel therapeutics, it also enhances our ability to use legacy disease data in rapid analysis of data pertaining to novel pathogens or mutations. This talk will describe the IDO strategy for creating a common ontology resource that can support these ends, and outline the work of the IDO Consortium, which is attempting to realize this strategy in a variety of disease domains by means of a general purpose core containing disease-neutral terms (such as ‘host’, ‘pathogen’, ‘virulence’) together with a number of extension vocabularies created by communities of researchers managing data pertaining to specific human, animal and plant infectious diseases, as well as by vaccine researchers. One advantage of this strategy is that, as each new group of infectious disease researchers confronts the need for a controlled vocabulary to represent the phenomena in its specific domain, it has a ready-made set of terms to begin this process in the application of which it can draw on the lessons learned by others while at the same time ensuring interoperability of their own data with the data collected in other disease domains.

=== Introduction to the IDO Core. ''Speaker: Albert Goldfain'' ===

Despite the recent surge of interest in biomedical ontology, there was until recently little ontology coverage of the infectious disease domain, resulting in both an urgent need for ontology development in this field and the opportunity for a coordinated, community-wide development effort producing broad interoperability across the disease-specific specialties and across the clinical care, public health, and biomedical research domains. To provide the foundation for such an effort, we have developed a general infectious disease ontology (IDO Core) designed to serve as a central ontology (hub) from which disease-specific extensions (spokes) can be built through a process of specialization. The IDO core was designed i) to provide ontology coverage of terms generally relevant to infectious disease research, ii) to ensure interoperability between the IDO extensions, and iii) to achieve these ends on the basis of a W3C standard logical formalism intended to ensure extensibility of the ontologies while preserving their utility for computational applications. Each extension can be developed and maintained by domain experts, allowing for rapid progress towards the needed set of ontologies, ensuring biological accuracy of the extensions, and increasing the likelihood of broad adoption by the infectious disease research community. IDO Core thus provides an invaluable ontology resource for infectious disease researchers, allowing cross-domain data integration and supporting the computation-intensive data processing and analysis tasks becoming the basis of biomedical research.

IDO Core is intended to represent information along three dimensions:

* biological scale (gene, cell, organ, organism, and population)
* discipline (clinical, immunological, microbiological, epidemiological)
* host, pathogen, and vector organisms (e.g., human, rat, pig, maize, HIV, influenza, mosquito).

IDO Core makes distinctions between infections, infectious diseases, infectious disease courses, the diagnosis of infectious disease, and the signs and symptoms of infectious diseases. The conflation of any of these entities can lead to incoherent reasoning, inconsistent models of specific diseases, and even medical errors in electronic health records.

As a case-study in the use of IDO across diseases, we will describe the IDO Core representation of protective resistance. The resistance of pathogens to certain drugs is a central obstacle to the treatment and management of infectious disease. More generally, resistance can be used to describe phenomena such as the immunity of an individual to specific diseases and the resistance of disorders to specific treatments.

=== Malaria Ontology (IDOMAL) ''Speaker: Christos Louis'' ===

Hundreds of millions of cases of vector-borne diseases occur annually, the vast majority of which affect populations in tropical regions of the world. Malaria, the most prominent among them, causes more than one million deaths each year, mostly among small children in these areas. For a number of reasons, including the development of resistance against both drugs and insecticides, the numbers of cases, and of deaths, has not decreased substantially, in spite of the progress achieved in medical sciences in recent decades. There is there-fore a need for new tools that will help alleviate this problem. These will include IT tools such as decision support systems (DSS), which, especially in the cases of emerging epidemics, will use data collections to help local authorities plan their disease control measures. This module will describe our work on the IDOMAL malaria ontology, an IDO extension ontology that is designed to advance work in this broad area and will be used to drive both databases and the DSSs that rely on them. IDOMAL will contain terms from all four corners of the malaria domain, which is to say: the biology of vectors and of disease, epidemiology, and clinical features. We have already recruited the participation of expert collaborators in order to ensure the broadest and most accurate coverage of the disease. Our plans for the future include the expansion of IDOMAL to cover other vector-borne diseases.

=== HIV Ontology (IDOHIV) ''Speaker: Lindsay G. Cowell'' ===

In 2007, 33 million people were living with Human Immunodeficiency Virus (HIV), including 2 million children. Annually, there are approximately 2 million deaths as a result of HIV, with the leading cause of death being co-infection with Myco-bacterium tuberculosis (Mtb), a problem that is increasing with the appearance of new, highly virulent, drug-resistant strains of Mtb. A number of factors suggest that real progress towards alleviating the global HIV burden will require development of the terminological and logical infrastructure for broad data interoperability, and in particular for data interoperability across multiple disease domains. These include the central role of secondary infections in the HIV disease course, the importance of model infections to the study of HIV pathogenesis and vaccine efficacy, and the increasing need to synchronize the collection of data from patients enrolled in observational studies and clinical trials being carried out throughout the world. IDO is designed to provide the basis for the needed common terminological and logical architecture. This talk will describe the HIV Ontology (IDOHIV) developed as an IDO extension and will sketch the application of IDOHIV to i) the integration of results from Simian Immunodeficiency Virus (SIV) and HIV studies, ii) the study of HIV co-infection with Mtb and Hepatitis C Virus (HCV), and iii) the creation of an interactive, comprehensive database for the Duke Center for Aids Research (CFAR).

=== Influenza Ontology (IDOFLU) ''Speaker: Richard H. Scheuermann'' ===

With the recent outbreak of the pandemic H1N1 influenza strain in April of 2009, the public health impact of a potential-ly virulent influenza pandemic has once again become apparent. Many research and surveillance projects and bioinformatics resources have been established to develop novel diagnostics, therapeutics and vaccines in order to rapidly respond to a potential outbreak. The Influenza Research Database (IRD; www.fludb.org) is a public database and analysis resource focused on the support of influenza genome sequence and surveillance data to support these research activities. In order to make these data maximally interoperable with other databases, IRD incorporates data standards components that contribute to effective knowledge representation, including minimum information standards and ontologies that cover the domain of influenza research and surveillance. In this regard, we have developed the Influenza Infectious Disease Ontology (IDOFLU) based on the high-level framework provided by the Infectious Disease Ontology (IDO) following best practices in ontology development as promulgated by the Open Biomedical Ontology (OBO) Foundry. In this talk we will focus on a description of an ontological representation of influenza surveillance activities and experiments to assess viral evolution during virus passage through different hosts to illustrate the assembly of a domain-focused application ontology from reference ontology sources and its integration with minimum data standards developed in collaboration with the influenza research community.

==Intended Audience==
The workshop does not assume any prior knowledge of ontologies or the infectious disease domain, and is aimed at a broad audience, including:
* medical informaticians
* biologists
* health care providers
* epidemiologists and public health workers
* bioinformatics researchers
* biomedical researchers
* computer scientists

==Goals==
* To demonstrate the advantages of a common approach for annotating infectious disease data
* To show how the IDO terminology can be used as a teaching tool.
* To showcase the multidisciplinary nature of IDO.
* To enable interested attendees to begin using IDO for annotating their own datasets.
* To enable interested attendees to begin creating their own [http://www.infectiousdiseaseontology.org/IDO_Extensions.html IDO extensions].

Infectious Disease Ontology Workshop - Medinfo 2010

2010-08-09T17:04:51Z

Agoldfain: minor formatting fixes

== Medinfo 2010 Workshop ==
There will be an [http://www.infectiousdiseaseontology.org/Home.html IDO] workshop at the [http://www.medinfo2010.org/ 13th World Congress on Medical and Health Informatics (Medinfo 2010)] in Cape Town, South Africa on September 12, 2010.

Infectious diseases inflict a disproportionate burden on developing countries. A lack of adequate treatment and prevention resources has resulted in a higher prevalence of infectious disease among the world's poorest people. This underscores the need for approaches to informatics support which leverage limited resources as effectively and efficiently as possible. Increasingly, response to infectious disease requires the use of information from multiple, constantly changing data sources. Currently, such information is collected using discipline-specific methodologies and is stored in heterogeneous databases, electronic health records, paper charts, and clinical and public health data repositories. Infectious disease data thus often remains only locally accessible, and because it
is expressed in incompatible formats it does not allow for broad spectrum computational processing, querying, inference, or verification. Data silos hinder translational and comparative research. Aggregating data through use of a common data format and a common terminology (i.e., an ontology) allows a variety of secondary uses of data such as: rapid determination of pathogen type in infections or disease outbreaks, treatment decision support based on genetic characteristics of host and pathogen (e.g., drug resistance), and research to improve understanding of disease pathogenesis leading to development of new types of treatments. The Infectious Disease Ontology (IDO) addresses the problem of data silos by providing a consistent terminology, taxonomy, and logical representation of entities relevant to all infectious diseases. IDO is already being applied to the study of seven diseases, including diseases of bacterial, viral, and eukaryotic origin. The objectives of this workshop are to introduce IDO and the methodology for creating disease-specific IDO extensions, to present applications of the ontologies to the study of
Malaria, HIV, and Influenza, and to open up the IDO enterprise to a wider audience of medical informaticians.

==Workshop Description==
The workshop will consist of five presentations addressing the scope, design, evolution, and practical utility of IDO. Specifically, the first two will describe the principles of IDO and of the ontologies derived from it, and provide also a description of existing database efforts in the infectious disease domain. The remaining presentations will describe disease-specific ontologies developed from IDO and their application to specific data integration and processing tasks, including the planning of disease control measures, the integration of data from
studies in humans and studies in model organisms, the study of co-infection, disease surveillance, and the study of viral evolution.

==Presenters==
* [http://ontology.buffalo.edu/smith/ Barry Smith] (University at Buffalo)
* [http://org.buffalo.edu/goldfain/index.html Albert Goldfain] (Blue Highway LLC)
* [http://biostat.duke.edu/modules/dukefaculty/viewDetails.php?d=cowel001&t=1 Lindsay G. Cowell] (Duke University Medical Center)
* [http://www.anobase.org/~louis/ Christos Louis] (IMBB-FORTH and University of Crete)
* [http://www.utsouthwestern.edu/findfac/research/0,2357,16416,00.html Richard H. Scheuermann] (University of Texas Southwestern Medical Center)

==Talk Abstracts==

=== Infectious Disease Ontology: The Very Idea. ''Speaker: Barry Smith'' ===
When computers are used in the storage and processing of data about infectious diseases and their causes, incidence, and treatment, there are obvious advantages to the use of a common controlled vocabulary or ‘ontology’. By making data comparable even when it derives from different sources, the ontology not only aids information-driven research directed towards elucidation of the disease mechanisms involved and the development of novel therapeutics, it also enhances our ability to use legacy disease data in rapid analysis of data pertaining to novel pathogens or mutations. This talk will describe the IDO strategy for creating a common ontology resource that can support these ends, and outline the work of the IDO Consortium, which is attempting to realize this strategy in a variety of disease domains by means of a general purpose core containing disease-neutral terms (such as ‘host’, ‘pathogen’, ‘virulence’) together with a number of extension vocabularies created by communities of researchers managing data pertaining to specific human, animal and plant infectious diseases, as well as by vaccine researchers. One advantage of this strategy is that, as each new group of infectious disease researchers confronts the need for a controlled vocabulary to represent the phenomena in its specific domain, it has a ready-made set of terms to begin this process in the application of which it can draw on the lessons learned by others while at the same time ensuring interoperability of their own data with the data collected in other disease domains.

=== Introduction to the IDO Core. ''Speaker: Albert Goldfain'' ===

Despite the recent surge of interest in biomedical ontology, there was until recently little ontology coverage of the infectious disease domain, resulting in both an urgent need for ontology development in this field and the opportunity for a coordinated, community-wide development effort producing broad interoperability across the disease-specific specialties and across the clinical care, public health, and biomedical research domains. To provide the foundation for such an effort, we have developed a general infectious disease ontology (IDO Core) designed to serve as a central ontology (hub) from which disease-specific extensions (spokes) can be built through a process of specialization. The IDO core was designed i) to provide ontology coverage of terms generally relevant to infectious disease research, ii) to ensure interoperability between the IDO extensions, and iii) to achieve these ends on the basis of a W3C standard logical formalism intended to ensure extensibility of the ontologies while preserving their utility for computational applications. Each extension can be developed and maintained by domain experts, allowing for rapid progress towards the needed set of ontologies, ensuring biological accuracy of the extensions, and increasing the likelihood of broad adoption by the infectious disease research community. IDO Core thus provides an invaluable ontology resource for infectious disease researchers, allowing cross-domain data integration and supporting the computation-intensive data processing and analysis tasks becoming the basis of biomedical research.

IDO Core is intended to represent information along three dimensions:

* biological scale (gene, cell, organ, organism, and population)
* discipline (clinical, immunological, microbiological, epidemiological)
* host, pathogen, and vector organisms (e.g., human, rat, pig, maize, HIV, influenza, mosquito).

IDO Core makes distinctions between infections, infectious diseases, infectious disease courses, the diagnosis of infectious disease, and the signs and symptoms of infectious diseases. The conflation of any of these entities can lead to incoherent reasoning, inconsistent models of specific diseases, and even medical errors in electronic health records.

As a case-study in the use of IDO across diseases, we will describe the IDO Core representation of protective resistance. The resistance of pathogens to certain drugs is a central obstacle to the treatment and management of infectious disease. More generally, resistance can be used to describe phenomena such as the immunity of an individual to specific diseases and the resistance of disorders to specific treatments.

=== Malaria Ontology (IDOMAL) ''Speaker: Christos Louis'' ===

Hundreds of millions of cases of vector-borne diseases occur annually, the vast majority of which affect populations in tropical regions of the world. Malaria, the most prominent among them, causes more than one million deaths each year, mostly among small children in these areas. For a number of reasons, including the development of resistance against both drugs and insecticides, the numbers of cases, and of deaths, has not decreased substantially, in spite of the progress achieved in medical sciences in recent decades. There is there-fore a need for new tools that will help alleviate this problem. These will include IT tools such as decision support systems (DSS), which, especially in the cases of emerging epidemics, will use data collections to help local authorities plan their disease control measures. This module will describe our work on the IDOMAL malaria ontology, an IDO extension ontology that is designed to advance work in this broad area and will be used to drive both databases and the DSSs that rely on them. IDOMAL will contain terms from all four corners of the malaria domain, which is to say: the biology of vectors and of disease, epidemiology, and clinical features. We have already recruited the participation of expert collaborators in order to ensure the broadest and most accurate coverage of the disease. Our plans for the future include the expansion of IDOMAL to cover other vector-borne diseases.

=== HIV Ontology (IDOHIV) ''Speaker: Lindsay G. Cowell'' ===

In 2007, 33 million people were living with Human Immunodeficiency Virus (HIV), including 2 million children. Annually, there are approximately 2 million deaths as a result of HIV, with the leading cause of death being co-infection with Myco-bacterium tuberculosis (Mtb), a problem that is increasing with the appearance of new, highly virulent, drug-resistant strains of Mtb. A number of factors suggest that real progress towards alleviating the global HIV burden will require development of the terminological and logical infrastructure for broad data interoperability, and in particular for data interoperability across multiple disease domains. These include the central role of secondary infections in the HIV disease course, the importance of model infections to the study of HIV pathogenesis and vaccine efficacy, and the increasing need to synchronize the collection of data from patients enrolled in observational studies and clinical trials being carried out throughout the world. IDO is designed to provide the basis for the needed common terminological and logical architecture. This talk will describe the HIV Ontology (IDOHIV) developed as an IDO extension and will sketch the application of IDOHIV to i) the integration of results from Simian Immunodeficiency Virus (SIV) and HIV studies, ii) the study of HIV co-infection with Mtb and Hepatitis C Virus (HCV), and iii) the creation of an interactive, comprehensive database for the Duke Center for Aids Research (CFAR).

=== Influenza Ontology (IDOFLU) ''Speaker: Richard H. Scheuermann'' ===

With the recent outbreak of the pandemic H1N1 influenza strain in April of 2009, the public health impact of a potential-ly virulent influenza pandemic has once again become apparent. Many research and surveillance projects and bioinformatics resources have been established to develop novel diagnostics, therapeutics and vaccines in order to rapidly respond to a potential outbreak. The Influenza Research Database (IRD; www.fludb.org) is a public database and analysis resource focused on the support of influenza genome sequence and surveillance data to support these research activities. In order to make these data maximally interoperable with other databases, IRD incorporates data standards components that contribute to effective knowledge representation, including minimum information standards and ontologies that cover the domain of influenza research and surveillance. In this regard, we have developed the Influenza Infectious Disease Ontology (IDOFLU) based on the high-level framework provided by the Infectious Disease Ontology (IDO) following best practices in ontology development as promulgated by the Open Biomedical Ontology (OBO) Foundry. In this talk we will focus on a description of an ontological representation of influenza surveillance activities and experiments to assess viral evolution during virus passage through different hosts to illustrate the assembly of a domain-focused application ontology from reference ontology sources and its integration with minimum data standards developed in collaboration with the influenza research community.

==Intended Audience==
The workshop does not assume any prior knowledge of ontologies or the infectious disease domain, and is aimed at a broad audience, including:
* medical informaticians
* biologists
* health care providers
* epidemiologists and public health workers
* bioinformatics researchers
* biomedical researchers
* computer scientists

==Goals==
* To demonstrate the advantages of a common approach for annotating infectious disease data
* To show how the IDO terminology can be used as a teaching tool.
* To showcase the multidisciplinary nature of IDO.
* To enable interested attendees to begin using IDO for annotating their own datasets.
* To enable interested attendees to begin creating their own [http://www.infectiousdiseaseontology.org/IDO_Extensions.html IDO extensions].

Infectious Disease Ontology Workshop - Medinfo 2010

2010-05-05T22:35:19Z

Agoldfain: Added Talk Abstracts

== Medinfo 2010 Workshop ==
There will be an [http://www.infectiousdiseaseontology.org/Home.html IDO] workshop at the [http://www.medinfo2010.org/ 13th World Congress on Medical and Health Informatics (Medinfo 2010)] in Cape Town, South Africa on September 12, 2010.

Infectious diseases inflict a disproportionate burden on developing countries. A lack of adequate treatment and prevention resources has resulted in a higher prevalence of infectious disease among the world's poorest people. This underscores the need for approaches to informatics support which leverage limited resources as effectively and efficiently as possible. Increasingly, response to infectious disease requires the use of information from multiple, constantly changing data sources. Currently, such information is collected using discipline-specific methodologies and is stored in heterogeneous databases, electronic health records, paper charts, and clinical and public health data repositories. Infectious disease data thus often remains only locally accessible, and because it
is expressed in incompatible formats it does not allow for broad spectrum computational processing, querying, inference, or verification. Data silos hinder translational and comparative research. Aggregating data through use of a common data format and a common terminology (i.e., an ontology) allows a variety of secondary uses of data such as: rapid determination of pathogen type in infections or disease outbreaks, treatment decision support based on genetic characteristics of host and pathogen (e.g., drug resistance), and research to improve understanding of disease pathogenesis leading to development of new types of treatments. The Infectious Disease Ontology (IDO) addresses the problem of data silos by providing a consistent terminology, taxonomy, and logical representation of entities relevant to all infectious diseases. IDO is already being applied to the study of seven diseases, including diseases of bacterial, viral, and eukaryotic origin. The objectives of this workshop are to introduce IDO and the methodology for creating disease-specific IDO extensions, to present applications of the ontologies to the study of
Malaria, HIV, and Influenza, and to open up the IDO enterprise to a wider audience of medical informaticians.

==Workshop Description==
The workshop will consist of five presentations addressing the scope, design, evolution, and practical utility of IDO. Specifically, the first two will describe the principles of IDO and of the ontologies derived from it, and provide also a description of existing database efforts in the infectious disease domain. The remaining presentations will describe disease-specific ontologies developed from IDO and their application to specific data integration and processing tasks, including the planning of disease control measures, the integration of data from
studies in humans and studies in model organisms, the study of co-infection, disease surveillance, and the study of viral evolution.

==Presenters==
* [http://ontology.buffalo.edu/smith/ Barry Smith] (University at Buffalo)
* [http://org.buffalo.edu/goldfain/index.html Albert Goldfain] (Blue Highway LLC)
* [http://biostat.duke.edu/modules/dukefaculty/viewDetails.php?d=cowel001&t=1 Lindsay G. Cowell] (Duke University Medical Center)
* [http://www.anobase.org/~louis/ Christos Louis] (IMBB-FORTH and University of Crete)
* [http://www.utsouthwestern.edu/findfac/research/0,2357,16416,00.html Richard H. Scheuermann] (University of Texas Southwestern Medical Center)

==Talk Abstracts==

=== Infectious Disease Ontology: The Very Idea. ''Speaker: Barry Smith'' ===
When computers are used in the storage and processing of data about infectious diseases and their causes, incidence, and treatment, there are obvious advantages to the use of a common controlled vocabulary or ‘ontology’. By making data comparable even when it derives from different sources, the ontology not only aids information-driven research directed towards elucidation of the disease mechanisms involved and the development of novel therapeutics, it also enhances our ability to use legacy disease data in rapid analysis of data pertaining to novel pathogens or mutations. This talk will describe the IDO strategy for creating a common ontology resource that can support these ends, and outline the work of the IDO Consortium, which is attempting to realize this strategy in a variety of disease domains by means of a general purpose core containing disease-neutral terms (such as ‘host’, ‘pathogen’, ‘virulence’) together with a number of extension vocabularies created by communities of researchers managing data pertaining to specific human, animal and plant infectious diseases, as well as by vaccine researchers. One advantage of this strategy is that, as each new group of infectious disease researchers confronts the need for a controlled vocabulary to represent the phenomena in its specific domain, it has a ready-made set of terms to begin this process in the application of which it can draw on the lessons learned by others while at the same time ensuring interoperability of their own data with the data collected in other disease domains.

=== Introduction to the IDO Core. ''Speaker: Albert Goldfain'' ===

Despite the recent surge of interest in biomedical ontology, there was until recently little ontology coverage of the infec-tious disease domain, resulting in both an urgent need for on-tology development in this field and the opportunity for a coordinated, community-wide development effort producing broad interoperability across the disease-specific specialties and across the clinical care, public health, and biomedical research domains. To provide the foundation for such an ef-fort, we have developed a general infectious disease ontology (IDO Core) designed to serve as a central ontology (hub) from which disease-specific extensions (spokes) can be built through a process of specialization. The IDO core was de-signed i) to provide ontology coverage of terms generally rele-vant to infectious disease research, ii) to ensure interoperabili-ty between the IDO extensions, and iii) to achieve these ends on the basis of a W3C standard logical formalism intended to ensure extensibility of the ontologies while preserving their utility for computational applications. Each extension can be developed and maintained by domain experts, allowing for rapid progress towards the needed set of ontologies, ensuring biological accuracy of the extensions, and increasing the like-lihood of broad adoption by the infectious disease research community. IDO Core thus provides an invaluable ontology resource for infectious disease researchers, allowing cross-domain data integration and supporting the computation-intensive data processing and analysis tasks becoming the basis of biomedical research.

IDO Core is intended to represent information along three dimensions:

* biological scale (gene, cell, organ, organism, and population)
* discipline (clinical, immunological, microbiological, epidemiological)
* host, pathogen, and vector organisms (e.g., human, rat, pig, maize, HIV, influenza, mosquito).

IDO Core makes distinctions between infections, infectious diseases, infectious disease courses, the diagnosis of infectious disease, and the signs and symptoms of infectious diseases. The conflation of any of these entities can lead to incoherent reasoning, inconsistent models of specific diseases, and even medical errors in electronic health records.

As a case-study in the use of IDO across diseases, we will describe the IDO Core representation of protective resistance. The resistance of pathogens to certain drugs is a central ob-stacle to the treatment and management of infectious disease. More generally, resistance can be used to describe phenomena such as the immunity of an individual to specific diseases and the resistance of disorders to specific treatments.

=== Malaria Ontology (IDOMAL) ''Speaker: Christos Louis'' ===

Hundreds of millions of cases of vector-borne diseases occur annually, the vast majority of which affect populations in tropical regions of the world. Malaria, the most prominent among them, causes more than one million deaths each year, mostly among small children in these areas. For a number of reasons, including the development of resistance against both drugs and insecticides, the numbers of cases, and of deaths, has not decreased substantially, in spite of the progress achieved in medical sciences in recent decades. There is there-fore a need for new tools that will help alleviate this problem. These will include IT tools such as decision support systems (DSS), which, especially in the cases of emerging epidemics, will use data collections to help local authorities plan their disease control measures. This module will describe our work on the IDOMAL malaria ontology, an IDO extension ontolo-gy that is designed to advance work in this broad area and will be used to drive both databases and the DSSs that rely on them. IDOMAL will contain terms from all four corners of the malaria domain, which is to say: the biology of vectors and of disease, epidemiology, and clinical features. We have already recruited the participation of expert collaborators in order to ensure the broadest and most accurate coverage of the disease. Our plans for the future include the expansion of IDOMAL to cover other vector-borne diseases.

=== HIV Ontology (IDOHIV) ''Speaker: Lindsay G. Cowell'' ===

In 2007, 33 million people were living with Human Immuno-deficiency Virus (HIV), including 2 million children. Annually, there are approximately 2 million deaths as a result of HIV, with the leading cause of death being co-infection with Myco-bacterium tuberculosis (Mtb), a problem that is increasing with the appearance of new, highly virulent, drug-resistant strains of Mtb. A number of factors suggest that real progress towards alleviating the global HIV burden will require devel-opment of the terminological and logical infrastructure for broad data interoperability, and in particular for data interoperability across multiple disease domains. These include the central role of secondary infections in the HIV disease course, the importance of model infections to the study of HIV pathogenesis and vaccine efficacy, and the increasing need to synchronize the collection of data from patients enrolled in observational studies and clinical trials being carried out throughout the world. IDO is designed to provide the basis for the needed common terminological and logical architecture. This talk will describe the HIV Ontology (IDOHIV) developed as an IDO extension and will sketch the application of IDOHIV to i) the integration of results from Simian Immunodeficiency Virus (SIV) and HIV studies, ii) the study of HIV co-infection with Mtb and Hepatitis C Virus (HCV), and iii) the creation of an interactive, comprehensive database for the Duke Center for Aids Research (CFAR).

=== Influenza Ontology (IDOFLU) ''Speaker: Richard H. Scheuermann'' ===

With the recent outbreak of the pandemic H1N1 influenza strain in April of 2009, the public health impact of a potential-ly virulent influenza pandemic has once again become appar-ent. Many research and surveillance projects and bioinformatics resources have been established to develop novel diagnostics, therapeutics and vaccines in order to rapidly respond to a potential outbreak. The Influenza Research Database (IRD; www.fludb.org) is a public database and analysis resource focused on the support of influenza genome sequence and surveillance data to support these research activities. In order to make these data maximally interoperable with other databases, IRD incorporates data standards components that contribute to effective knowledge representation, including minimum information standards and ontologies that cover the domain of influenza research and surveillance. In this regard, we have developed the Influenza Infectious Disease Ontology (IDOFLU) based on the high-level framework provided by the Infectious Disease Ontology (IDO) following best practices in ontology development as promulgated by the Open Biomedical Ontology (OBO) Foundry. In this talk we will focus on a description of an ontological representation of influenza surveillance activities and experiments to assess viral evolution during virus passage through different hosts to illustrate the assembly of a domain-focused application ontology from reference ontology sources and its integration with minimum data standards developed in collaboration with the influenza research community.

==Intended Audience==
The workshop does not assume any prior knowledge of ontologies or the infectious disease domain, and is aimed at a broad audience, including:
* medical informaticians
* biologists
* health care providers
* epidemiologists and public health workers
* bioinformatics researchers
* biomedical researchers
* computer scientists

==Goals==
* To demonstrate the advantages of a common approach for annotating infectious disease data
* To show how the IDO terminology can be used as a teaching tool.
* To showcase the multidisciplinary nature of IDO.
* To enable interested attendees to begin using IDO for annotating their own datasets.
* To enable interested attendees to begin creating their own [http://www.infectiousdiseaseontology.org/IDO_Extensions.html IDO extensions].

Infectious Disease Ontology Workshop - Medinfo 2010

2010-05-05T20:57:37Z

Agoldfain:

Infectious Disease Ontology Workshop - Medinfo 2010

2010-05-05T20:55:41Z

Agoldfain:

Infectious Disease Ontology Workshop - Medinfo 2010

2010-05-05T20:51:24Z

Agoldfain:

Infectious Disease Ontology Workshop - Medinfo 2010

2010-05-05T20:45:44Z

Agoldfain:

Infectious Disease Ontology Workshop - Medinfo 2010

2010-05-05T20:40:18Z

Agoldfain:

== Medinfo 2010 Workshop ==
There will be an IDO workshop at the [http://www.medinfo2010.org/ 13th World Congress on Medical and Health Informatics (Medinfo 2010)] in Cape Town, South Africa (Sept 12-Sept 15).

Infectious diseases inflict a disproportionate burden on developing countries. A lack of adequate treatment and prevention resources has resulted in a higher prevalence of infectious disease among the world's poorest people. This underscores the need for approaches to informatics support which leverage limited resources as effectively and efficiently as possible. Increasingly, response to infectious disease requires the use of information from multiple, constantly changing data sources. Currently, such information is collected using discipline-specific methodologies and is stored in heterogeneous databases, electronic health records, paper charts, and clinical and public health data repositories. Infectious disease data thus often remains only locally accessible, and because it
is expressed in incompatible formats it does not allow for broad spectrum computational processing, querying, inference, or verification. Data silos hinder translational and comparative research. Aggregating data through use of a common data format and a common terminology (i.e., an ontology) allows a variety of secondary uses of data such as: rapid determination of pathogen type in infections or disease outbreaks, treatment decision support based on genetic characteristics of host and pathogen (e.g., drug resistance), and research to improve understanding of disease pathogenesis leading to development of new types of treatments. The Infectious Disease Ontology (IDO) addresses the problem of data silos by providing a consistent terminology, taxonomy, and logical representation of entities relevant to all infectious diseases. IDO is already being applied to the study of seven diseases, including diseases of bacterial, viral, and eukaryotic origin. The objectives of this workshop are to introduce IDO and the methodology for creating disease-specific IDO extensions, to present applications of the ontologies to the study of
Malaria, HIV, and Influenza, and to open up the IDO enterprise to a wider audience of medical informaticians.

==Workshop Description==
The workshop will consist of five presentations addressing the scope, design, evolution, and practical utility of IDO. Specifically, the first two will describe the principles of IDO and of the ontologies derived from it, and provide also a description of existing database efforts in the infectious disease domain. The remaining presentations will describe disease-specific ontologies developed from IDO and their application to specific data integration and processing tasks, including the planning of disease control measures, the integration of data from
studies in humans and studies in model organisms, the study of co-infection, disease surveillance, and the study of viral evolution.

==Expected Presenters==
* Barry Smith (University at Buffalo)
* Albert Goldfain (Blue Highway LLC)
* Lindsay G. Cowell (Duke University Medical Center)
* Christos Louis (IMBB-FORTH and University of Crete)
* Richard H. Scheuermann (University of Texas Southwestern Medical Center)

Infectious Disease Ontology

2010-05-05T20:31:36Z

Agoldfain: Added link to IDO MedInfo 2010 Workshop

== Please Visit the Main IDO Website ==

The main IDO website is http://www.infectiousdiseaseontology.org.

== Email List ==

Please subscribe to the Infectious Disease Ontology email list. Anyone can subscribe, and anyone can email the list. We plan to use the email list to discuss the addition of new terms and proposed changes to the current ontology. To subscribe, visit https://lists.duke.edu/sympa/. To email the list, write to ido@duke.edu.

== Medinfo 2010 Workshop ==
There will be an IDO workshop at the [http://www.medinfo2010.org/ 13th World Congress on Medical and Health Informatics (Medinfo 2010)]. A separate wiki for this workshop can be found here: [[Infectious Disease Ontology Workshop - Medinfo 2010]]

== Beginnings of an Infectious Disease Ontology ==

At the recent Infectious Disease Ontology Workshop (see below), we began preliminary work on a draft infectious disease ontology. OBO edit and Protege OWL versions of the ontology are available for download. Please send comments and suggestions to ido@duke.edu.
* http://www.duke.edu/~lgcowell/IDO_Workshop_Files/IDO.9.19.07.owl
* http://www.duke.edu/~lgcowell/IDO_Workshop_Files/IDO.9.19.07.pprj
* http://www.duke.edu/~lgcowell/IDO_Workshop_Files/IDO_10.08.07.obo

Accessible data to test the ontology, existing ontologies of related interest can be found here: [[Toolbox]]

Most current version of the ontology can be found [http://infectiousdiseaseontology.org here].

== Infectious Disease Ontology Meeting in Buffalo (September 16 - 17, 2008)==

Details available [http://www.bioontology.org/wiki/index.php/Infectious_Disease_Ontology_2008 here].

== Past Meetings ==

'''Infectious Disease Ontology Kick-off Workshop (September 19 - 20, 2007) and Meeting (September 21, 2007)'''

The Infectious Disease Ontology Workshop and Meeting (see link below under "Past Meetings") were intended to serve as both a training workshop for participants and a forum through which to establish a community for development, maintenance, and use of the Infectious Disease Ontology (IDO). The workshop and meeting were supported by the [http://www.bwfund.org Burroughs Wellcome Fund].

Training Workshop: September 19-20, 2007
* [http://meetings.cshl.edu/courses/c-ontol07.shtml Training Workshop on Infectious Disease Ontology]

Public Meeting: September 21, 2007
* [http://meetings.cshl.edu/courses/m-ontol07.html Infectious Disease: A Challenge for Biomedical Informatics]

''Report''

*http://www.duke.edu/~lgcowell/IDO_Workshop_Files/Infectious_Disease_Ontology_Meeting_Report.doc

''Slides''

September 19, 2007
* Morning Session 1 (Cowell): http://www.duke.edu/~lgcowell/IDO_Workshop_Files/Introduction_to_the_Human_Immune_System.ppt
* Morning Session 2 (Cowell): http://www.duke.edu/~lgcowell/IDO_Workshop_Files/Introduction_to_Microbial_Pathogenesis.ppt
* Afternoon and Evening Sessions (Smith): http://ontology.buffalo.edu/bio/IDO/

September 21, 2007
*Topics in Infectious Disease Research
**Stefan Kaufmann: [http://www.duke.edu/~lgcowell/IDO_Workshop_Files/Kaufmann_Infectious_Disease_Ontology_Meeting.ppt Global Threats Need Global Research Efforts: The Example of Tuberculosis]
**Ronald Veazey: Utility of Nonhuman Primates for Examining Transmission and Pathogenesis of HIV Infection
*Ontologies and their Application to Infectious Disease
**Steve Gordon: Surgical Endocarditis: Bringing Ontology into the Operating Room
**Michael Ashburner: [http://www.duke.edu/~lgcowell/IDO_Workshop_Files/Ashburner_Infectious_Disease_Ontology_Meeting.ppt Ontologies for Biomedicine: The GO Experience]
**Lynn Schriml: The GEMINA Information Resource
*Ontology and the Future of Infectious Disease Research (Panel Session)
**Cowell: http://www.duke.edu/~lgcowell/IDO_Workshop_Files/Cowell_Infectious_Disease_Ontology_Panel.ppt
**Scheuermann: http://www.duke.edu/~lgcowell/IDO_Workshop_Files/Scheuermann_Infectious_Disease_Ontology_Panel.ppt
**Stein: http://www.duke.edu/~lgcowell/IDO_Workshop_Files/Stein_Infectious_Disease_Ontology_Panel.ppt

''Software Downloads''
* Download the OBO-Edit ontology editor: http://oboedit.org/
* Download the Protege OWL ontology editor: http://protege.stanford.edu/download/download.html
* Protege OWL contains a very useful tutorial, you can access it by opening Protege OWL and looking under "Help"
* Download Pellet (a reasoner for OWL): http://pellet.owldl.com/
* The Protege developers have created a short, helpful guide to installing Pellet and making sure that Pellet is running in conjunction with Protege OWL: http://protege.stanford.edu/shortcourse/protege/200703/prepare.html

'''Workshop on the Ontology of Diseases, November 6-7, 2006'''

* [http://bioontology.org/wiki/index.php/Workshop_on_Ontology_of_Diseases Workshop on Ontology of Diseases]. Links to presentations at this meeting:
** Kent Spackman: SNOMED CT [http://ontology.buffalo.edu/medo/DiseaseOntology/2006/spackman.ppt Slides]
** Barry Smith: What a Disease Ontology is for [http://ontology.buffalo.edu/medo/DiseaseOntology/2006/Smith.ppt Slides] [http://ontology.buffalo.edu/medo/DiseaseOntology/2006/Smith.WMA Audio]
**Neil Williams: The Ontology of Powers, Dispositions and Tendencies [http://ontology.buffalo.edu/medo/DiseaseOntology/2006/Williams.ppt Slides]
** Louis J. Goldberg: Networks and the Ontology of Disease [http://ontology.buffalo.edu/medo/DiseaseOntology/2006/Goldberg.ppt Slides] [http://ontology.buffalo.edu/medo/DiseaseOntology/2006/Goldberg.WMA Audio]
** Werner Ceusters: The Ontology of Diagnosis: [http://www.org.buffalo.edu/RTU/papers/WhatIsaDiagnosis.ppt Slides] [http://ontology.buffalo.edu/medo/DiseaseOntology/2006/Ceusters.WMA Audio]
** Chris Mungall: DO and the OBO Foundry [http://ontology.buffalo.edu/medo/DiseaseOntology/2006/mungall.ppt Slides] [http://ontology.buffalo.edu/medo/DiseaseOntology/2006/Mungall.WMA Audio]

== Links ==

* [http://obofoundry.org The OBO Foundry]
* [http://diseaseontology.sourceforge.net/ The Disease Ontology]
* [ftp://ftp.tigr.org/pub/data/gemina/gemina_disease_02-21-07.obo.gz TIGR's Gemina Project Infectious Disease Ontology]
* [ftp://ftp.tigr.org/pub/data/gemina/ TIGR's Gemina Project Infectious Disease Ontology Data]
* [http://gemina.tigr.org Gemina Query Tool]
* [http://www.comp.leeds.ac.uk/qsr/pub/kr89.pdf Mereotopology of Phagocytosis and Exocytosis]
* [http://www.comp.leeds.ac.uk/qsr/pub/AAAI92.ps Qualitative Simulation of Phagocytosis]
* [http://www.phidias.us/phinfo Integrated pathogen-host interaction data in PHIDIAS]
* [http://www.violinet.org VIOLIN: University of Michigan Vaccine Database]
* [http://www.biotec.tu-dresden.de/sealife Sealife]

== Recommended Background Reading ==
* For a comprehensive introduction to ontology in general and the Basic Formal Ontology specifically, see http://www.ifomis.uni-saarland.de/projects/bfo/manual/
* Streaming video introduction to ontology by Barry Smith: http://ontology.buffalo.edu/smith/Ontology_Course.html
* For an explanation of the necessity of logic-based relations for automatic reasoning over ontologies, see [[Image:Relations_in_anatomical_ontologies_sa.pdf‎]]
* For an introduction to the Relations Ontology and a description of the formulation of logic-based relations for OBO foundry ontologies, see [[Image:Relations_in_Biomedical_Ontologies.pdf‎]]
* For corrections on Relation Ontology, especially the derives_from relation, see http://www.ifomis.uni-saarland.de/Home/DerivationBookVersion1-2.pdf
* For a description of the Foundational Model of Anatomy and the basic principles of ontology development, see http://sigpubs.biostr.washington.edu/archive/00000135/01/jbi-fma.pdf
* For a description of the representation of immunological processes in the Gene Ontology Biological Process Ontology, see http://bioinformatics.oxfordjournals.org/cgi/reprint/23/7/913
* For a discussion of common errors in OWL, see http://www.co-ode.org/resources/papers/CommonErrorsInOWL.pdf
* For an introduction to microbial pathogenisis, see http://www.duke.edu/~lgcowell/IDO_Workshop_Files/Pathogenicity_of_Micro-Organisms.pdf

Infectious Disease Ontology Workshop - Medinfo 2010

2010-05-05T20:24:24Z

Agoldfain: New page: Infectious diseases inflict a disproportionate burden on developing countries. A lack of adequate treatment and prevention resources has resulted in a higher prevalence of infectious disea...

Infectious diseases inflict a disproportionate burden on developing countries. A lack of adequate treatment and prevention resources has resulted in a higher prevalence of infectious disease among the world's poorest people. This underscores the need for approaches to informatics support which leverage limited resources as effectively and efficiently as possible. Increasingly, response to infectious disease requires the use of information from multiple, constantly changing data sources. Currently, such information is collected using discipline-specific methodologies and is stored in heterogeneous databases, electronic health records, paper charts, and clinical and public health data repositories. Infectious disease data thus often remains only locally accessible, and because it
is expressed in incompatible formats it does not allow for broad spectrum computational processing, querying, inference, or verification. Data silos hinder translational and comparative research. Aggregating data through use of a common data format and a common terminology (i.e., an ontology) allows a variety of secondary uses of data such as: rapid determination of pathogen type in infections or disease outbreaks, treatment decision support based on genetic characteristics of host and pathogen (e.g., drug resistance), and research to improve understanding of disease pathogenesis leading to development of new types of treatments. The Infectious Disease Ontology (IDO) addresses the problem of data silos by providing a consistent terminology, taxonomy, and logical representation of entities relevant to all infectious diseases. IDO is already being applied to the study of seven diseases, including diseases of bacterial, viral, and eukaryotic origin. The objectives of this workshop are to introduce IDO and the methodology for creating disease-specific IDO extensions, to present applications of the ontologies to the study of
Malaria, HIV, and Influenza, and to open up the IDO enterprise to a wider audience of medical informaticians.