Immunology Ontology: Difference between revisions

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


1. Introduction to biological ontology
1. Introduction to biomedical ontology building
:What is an ontology, how is it different from a controlled vocabulary, a computerized lexicon, and a data dictionary?
: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
::Mistakes to avoid
:Example
::The Ontology for Biomedical Investigations ([http://obi-ontology.org/page/Main_Page OBI])


2. Overview of ontologies with content relevant to immunology
2. Overview of ontologies with content relevant to immunology
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::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]) [http://ncor.buffalo.edu/2013/Immunology/VO.ppt Slides]
: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]
[http://ncorwiki.buffalo.edu/index.php/Immunology_Ontologies Overview]
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Hands-on example of building a small ontology in the immunological domain
Hands-on example of building a small ontology in the immunological domain
[[Rules]]


==Background Resources (will be reviewed in class)==
==Background Resources (will be reviewed in class)==

Revision as of 18:32, 9 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

8:30-10:00am Lecture

1. Introduction to biomedical ontology building

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
Mistakes to avoid
Example
The Ontology for Biomedical Investigations (OBI)

2. Overview of ontologies with content relevant to immunology

The Protein Ontology (PRO)
The Gene Ontology (GO)
The Cell Ontology (CL)
The Immune Epitope Ontology (ONTIE)
The Infectious Disease Ontology (IDO)
Staph Aureus Ontology and Other IDO Extension Ontologies
The Vaccine Ontology (VO) Slides

Overview

3. 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

4. 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
to integrate heterogeneous data / heterogeneous research communities (example: the OBO (Open Biological and Biomedical Ontologies) Foundry)

1:00-3:00pm: Practical Session

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

Background Resources (will be reviewed in class)

Examples

[HIPC example http://ncor.buffalo.edu/2013/Immunology/HIPC-Example/]

[Allergy example http://ncor.buffalo.edu/2013/Immunology/allergy-example.docx]

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.