Immunology Ontology: Difference between revisions

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== Schedule ==
== Schedule ==


'''8:30-10:00am Lecture'''


1. Introduction to biological ontology
== '''Morning Lecture''' ==
:what is an ontology, how is it different from a controlled vocabulary, a computerized lexicon, and a data dictionary?


2. Overview of ontologies with content relevant to immunology


:The Protein Ontology ([http://pir.georgetown.edu/pro/ PRO])
8:30am Introduction to biomedical ontology building (Barry Smith, [http://ncor.buffalo.edu/2013/Immunology/BS.ppt Slides])
:The Gene Ontology ([http://www.geneontology.org/ GO])
 
:The Cell Ontology ([http://www.obofoundry.org/cgi-bin/detail.cgi?id=cell CL])
:Identification of participant areas of interest in preparation for the afternoon practical session
:The Immune Epitope Ontology ([http://70.167.3.46/iedb/ ONTIE])
:Overview of biomedical ontology
::What is an ontology for?
::How ontologies can support data-driven research
::Glories and miseries of the Semantic Web
:How to build an ontology
::How to select appropriate starting points
::Mistakes to avoid
:::Reinventing the wheel
:::Confusing words with things
:Examples
::The [http://www.obofoundry.org/ OBO (Open Biological and Biomedical Ontologies) Foundry]
::The Ontology for Biomedical Investigations ([http://obi-ontology.org/page/Main_Page OBI])
 
9:15am Overview of ontologies with content relevant to immunology (Lindsay Cowell, [http://ncor.buffalo.edu/2013/Immunology/LC.pdf Slides])
 
:Use of ontology portals and search engines
::The Cell Ontology ([http://www.obofoundry.org/cgi-bin/detail.cgi?id=cell CL]) [http://bioportal.bioontology.org/ontologies/1006 Bioportal]
::The Protein Ontology ([http://pir.georgetown.edu/pro/ PRO]) [http://bioportal.bioontology.org/ontologies/50185/?p=terms&conceptid=PR%3A000000001 Bioportal]
:The Gene Ontology ([http://www.geneontology.org/ GO]) [http://www.geneontology.org/minutes/20060331_Additional-Material/posters/immunology-poster_adiehl.pdf Poster]
::Relation to MeSH and similar resources
:How are ontologies used?
::in defining data standards (example: [https://immport.niaid.nih.gov/immportWeb/home/home.do?loginType=full ImmPort])  
::to support data analysis (example: GO enrichment of microarray data)
::to support text mining and NLP, document retrieval
:::example: [http://www.gopubmed.org/web/gopubmed/ GOPubMed]
 
:The Infectious Disease Ontology ([http://infectiousdiseaseontology.org/page/Main_Page IDO])
:The Infectious Disease Ontology ([http://infectiousdiseaseontology.org/page/Main_Page IDO])
::Staph Aureus Ontology and Other IDO Extension Ontologies
::Staph Aureus Ontology and Other IDO Extension Ontologies
:The Vaccine Ontology ([http://www.violinet.org/vaccineontology/ VO])
:The Vaccine Ontology ([http://www.violinet.org/vaccineontology/ VO]) [http://ncor.buffalo.edu/2013/Immunology/VO.ppt Slides]
:The Ontology for Biomedical Investigations ([http://obi-ontology.org/page/Main_Page OBI])


[http://ncorwiki.buffalo.edu/index.php/Immunology_Ontologies Overview]
9:45am Formats and tools
 
:Brief remarks on formats: XML, RDF, OWL and OBO
::[http://www.geneontology.org/GO.format.shtml GO File Format Guide]
:Brief remarks on tools
::[http://protege.stanford.edu/ Protégé Ontology Editor]
::[http://ontofox.hegroup.org/ Ontofox] [http://ncor.buffalo.edu/2013/Immunology/Ontofox.pptx Slides]
::SPARQL
 
== '''Afternoon Practical Session: Building Small Ontologies in the Immunological Domain''' ==
 
1:00pm Establish target areas of interest (drawing on the work initiated in the 8:30am session above). Participants will suggest possible target areas, expanding this list in light of their own areas of interest and expertise.  
 
:Adaptive immunity
:Immune tolerance
:Inflammation
:Adaptive immunity
:Innate immunity
:Mucosal immunity
:Transplantation immunology /MHC
:Tumor microenvironment / Cancer
:Virology
 
(These are all areas for which a suitable single ontology does not already exist. Some of the items are taken from the DAIT list [http://www.niaid.nih.gov/about/organization/dait/Pages/default.aspx here].)
 
1:10 Participants will be divided into corresponding breakout groups. The task of each group will be to create a workplan for building an ontology (or ontologies) for their selected area. The workplan will consist minimally of
 
: i. a list of main terms in their selected area -- to create this list participants can use the terminological resources they use in their own work or any other source
 
Two samples:
:[http://ncor.buffalo.edu/2013/Immunology/allergy-example.docx allergy and allergic disease]
:[http://ncor.buffalo.edu/2013/Immunology/HIPC-Example/ soluble proteins (including cytokines and chemokines) relevant to the work of HIPC]]
 
: ii. a list of the main ontologies they would harvest as starting points; in identifying these ontologies participants should experiment with two or more of the ontology portals listed below
 
Each group should select a reporter, who will present the results of the group's work, and a recorder, who will take notes of the discussions and have control of the powerpoint slides documenting the results of these discussions.
 
2:20 Presentation of results: Each group is required to produce at least 4 slides
summarizing the results of their work.


3. How are ontologies used?
:Slide 1: Title and author list
:for data annotation à la GO and GMODs
:Slide 2: Quick comparison of the experience of using the 4 ontology browsers listed above; optional report on experience using MeSH
:in defining data standards (example: [https://immport.niaid.nih.gov/immportWeb/home/home.do?loginType=full ImmPort])
:Slide 3: List of the principal ontologies selected to be used as sources / starting points for development of the needed ontology
:to support data analysis (example: GO enrichment of microarray data)
:Slide 4: List of the main terms in the ontology (if possible with some rudimentary BFO organization)
:to support text mining and NLP, document retrieval
::example: [http://www.gopubmed.org/web/gopubmed/ GOPubMed]
:to integrate heterogeneous data / heterogeneous research communities (example: the [http://www.obofoundry.org/ OBO (Open Biological and Biomedical Ontologies) Foundry])


'''1:00-3:00pm: Practical Session'''
[http://ncor.buffalo.edu/2013/Immunology/Slides Slides]


Hands-on example of building a small ontology in the immunological domain
2.50 Summation


==Background Resources (will be reviewed in class)==
==Background Resources (will be reviewed in class)==
'''Immunological Ontologies'''
[http://ncorwiki.buffalo.edu/index.php/Immunology_Ontologies Overview]


'''Portals'''
'''Portals'''
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5. [http://www.nlm.nih.gov/mesh/MBrowser.html MeSH]
5. [http://www.nlm.nih.gov/mesh/MBrowser.html MeSH]


'''Software'''
[http://protege.stanford.edu/ Protege Ontology Editor]
[http://ontofox.hegroup.org/ Ontofox]


'''Literature'''
'''Literature'''

Latest revision as of 16:19, 13 June 2013

What:

Summer School for Quantitative Systems Immunology: Lecture and practical session on Immunology Ontology

When: Tuesday June 11

Where: Rafik B. Hariri Institute for Computing and Computational Science and Engineering, Boston University, Boston, MA on June 10-14, 2013.

Who: Lindsay Cowell and Barry Smith

Schedule

Morning Lecture

8:30am Introduction to biomedical ontology building (Barry Smith, Slides)

Identification of participant areas of interest in preparation for the afternoon practical session
Overview of biomedical ontology
What is an ontology for?
How ontologies can support data-driven research
Glories and miseries of the Semantic Web
How to build an ontology
How to select appropriate starting points
Mistakes to avoid
Reinventing the wheel
Confusing words with things
Examples
The OBO (Open Biological and Biomedical Ontologies) Foundry
The Ontology for Biomedical Investigations (OBI)

9:15am Overview of ontologies with content relevant to immunology (Lindsay Cowell, Slides)

Use of ontology portals and search engines
The Cell Ontology (CL) Bioportal
The Protein Ontology (PRO) Bioportal
The Gene Ontology (GO) Poster
Relation to MeSH and similar resources
How are ontologies used?
in defining data standards (example: ImmPort)
to support data analysis (example: GO enrichment of microarray data)
to support text mining and NLP, document retrieval
example: GOPubMed
The Infectious Disease Ontology (IDO)
Staph Aureus Ontology and Other IDO Extension Ontologies
The Vaccine Ontology (VO) Slides

9:45am Formats and tools

Brief remarks on formats: XML, RDF, OWL and OBO
GO File Format Guide
Brief remarks on tools
Protégé Ontology Editor
Ontofox Slides
SPARQL

Afternoon Practical Session: Building Small Ontologies in the Immunological Domain

1:00pm Establish target areas of interest (drawing on the work initiated in the 8:30am session above). Participants will suggest possible target areas, expanding this list in light of their own areas of interest and expertise.

Adaptive immunity
Immune tolerance
Inflammation
Adaptive immunity
Innate immunity
Mucosal immunity
Transplantation immunology /MHC
Tumor microenvironment / Cancer
Virology

(These are all areas for which a suitable single ontology does not already exist. Some of the items are taken from the DAIT list here.)

1:10 Participants will be divided into corresponding breakout groups. The task of each group will be to create a workplan for building an ontology (or ontologies) for their selected area. The workplan will consist minimally of

i. a list of main terms in their selected area -- to create this list participants can use the terminological resources they use in their own work or any other source

Two samples:

allergy and allergic disease
soluble proteins (including cytokines and chemokines) relevant to the work of HIPC]
ii. a list of the main ontologies they would harvest as starting points; in identifying these ontologies participants should experiment with two or more of the ontology portals listed below

Each group should select a reporter, who will present the results of the group's work, and a recorder, who will take notes of the discussions and have control of the powerpoint slides documenting the results of these discussions.

2:20 Presentation of results: Each group is required to produce at least 4 slides summarizing the results of their work.

Slide 1: Title and author list
Slide 2: Quick comparison of the experience of using the 4 ontology browsers listed above; optional report on experience using MeSH
Slide 3: List of the principal ontologies selected to be used as sources / starting points for development of the needed ontology
Slide 4: List of the main terms in the ontology (if possible with some rudimentary BFO organization)

Slides

2.50 Summation

Background Resources (will be reviewed in class)

Immunological Ontologies

Overview

Portals

1. The Open Biological and Biomedical Ontologies

2. Bioportal

3. Ontobee

4. EBI Ontology Lookup Service

5. MeSH


Literature

Diehl AD, Augustine AD, Blake JA, Cowell LG, et al. Hematopoietic cell types: prototype for a revised cell ontology. J Biomed Inform. 2011; 44(1).

Meehan TF, Masci AM, Abdulla A, Cowell LG, et al. Logical development of the cell ontology. BMC Bioinformatics. 2011; 12.

Aravind Subramanian, et al. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles, PNAS, 102 (43), 15545–15550.