Immunology Ontologies

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Background

This page has been created to support the ontology work of the Immunology Database and Analysis Portal (ImmPort) portal within the framework of the Bioinformatics Integration Support Contract (BISC), which is funded by the NIH’s National Institute of Allergy and Infectious Diseases (NIAID). ImmPort is designed to enable scientists to easily access and exchange interoperable complex data sets to accelerate scientific discovery. It provides advanced information technology support in the production, analysis, archiving, and exchange of scientific data for the diverse community of life science researchers supported by NIAID.

The huge plasticity of the immune response, the strong dependence upon the context in which it occurs and on physiological and pathological conditions, and the wide range of responses elicited, make immunology an especially challenging domain for data integration.

The ontologies documented below are designed to enhance the degree to which immunology research results can be expressed in a consistent fashion across communities and disciplines, thus advancing not only the analysis and integration of data but also its discoverability by scientists who were not involved in its creation. In this way, they will contribute to the realization of the goals of ImmPort to accelerate a more collaborative and coordinated research environment and create an integrated database. that broadens the usefulness of scientific data and advances hypothesis-driven and hypothesis-generating research, as well as the development of optimal methods for data collection, storage, exchange and interoperability.

The team of University at Buffalo ontologists with primary responsibility for this work includes:

  • Barry Smith, Professor of Philosophy, Neurology and Computer Science and Director of the National Center for Ontological Research.
  • Alexander Diehl, UB Department of Neurology
  • Alan Ruttenberg, UB Department of Oral Biology.

For further background see: http://www.buffalo.edu/news/releases/2009/01/9857.html

Ontologies

Recommended

Chemical Entities of Biological Interest (CHEBI) (Paper)

The Protein Ontology (PRO) Immunology Content in the Protein Ontology (Paper)

The Gene Ontology (GO)

Gene Ontology Immunology Branch

The Cell Ontology (CL)

Paper on FlowCL

The Immune Epitope Ontology (ONTIE) (paper)

Infectious Disease Ontology (IDO)

ImmPort Antibody Ontology

Vaccine Ontology

Ontology of Vaccine Adverse Events (Paper)

Ontology for Biomedical Investigations (OBI) (Paper)

Ontology for General Medical Science (OGMS)

VDJ Server Video


Under development

Allergy Ontology

Immunology Ontology

Ontology Consortia

OBO (Open Biological and Biomedical Ontologies) Foundry

Clinical Trial Ontology / CDISC

Ravi Shankar, Clinical Trial Ontology, March 13, 2014

CDISC Phuse paper on LabTests, 2010

Clinical Trial Ontology Meeting, 2007

CDISC Guru

Portals

Immunology Database and Analysis (ImmPort) Portal

NCBO Bioportal (ontology repository)

Ontobee (ontology visualization portal)

HIPC: Human Immunology Project Consortium

Program for Research on Immune Modeling and Experimentation PRIME

Immune Epitope Database and Analysis Resource

International ImMunoGeneTics Information System

ImmPort Antibody Registry

Alex Diehl, The ImmPort Antibody Registry and Ontology

Cytokines

Barry Smith, The OBO Foundry approach to ontologies and standards with special reference to cytokines

Laboratory Information Systems

Open Source

LabKey
OpenClinica
caLIMS (from NCI)
Labmatica
Bika

Proprietary

LabWare
Medidata
Perkin Elmer
Ruro
StarLIMS
LabWare LIMS (Waters)

Sample process focused:

BioFortis
Sampleminded

LIS vs. LIMS

Publications

Maecker, H., McCoy, J.P. & Nussenblatt, R. Standardizing immunophenotyping for the human immunology project. Nature reviews Immunology 12, 191-200 (2012).

Smith B, Ashburner M, Rosse C, Bard J, Bug W, Ceusters W, Goldberg LJ, Eilbeck K, Ireland A, Mungall CJ; OBI Consortium, Leontis N, Rocca-Serra P, Ruttenberg A, Sansone SA, Scheuermann RH, Shah N, Whetzel PL, Lewis S. , The OBO Foundry: Coordinated Evolution of Ontologies to Support Biomedical Data Integration, Nature Biotechnology, 25 (11), November 2007, 1251-1255.

Cowell LG, Smith B, Infectious Disease Ontology, in Vitali Sintchenko, Infectious Disease Informatics, New York: Springer, December 2009, 373-395.

Masci AM, Arighi CN, Diehl AD, Lieberman AE, Mungall C, Scheuermann RH, Smith B, Cowell LG, An improved ontological representation of dendritic cells as a paradigm for all cell types, BMC Bioinformatics, February 2009, 10:70.

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.

Goldfain A, Smith B, Cowell LG, Towards an Ontological Representation of Resistance: The Case of MRSA, Journal of Biomedical Informatics, 2011 (Feb.), 44:1, 35-41.

Scheuermann RH, Ceusters W, Smith B, Toward an Ontological Treatment of Disease and Diagnosis, Proceedings of the 2009 AMIA Summit on Translational Bioinformatics, 2009, 116-120.

Goldfain A, Smith B, Cowell LG, Dispositions and the Infectious Disease Ontology, in Antony Galton and Riichiro Mizoguchi (eds.), Formal Ontology in Information Systems. Proceedings of the Sixth International Conference (FOIS 2010), Amsterdam: IOS Press, 2010, 400-413.

Goldfain A, Smith B, Cowell LG, Constructing a Lattice of Infectious Disease Ontologies from a Staphylococcus aureus Isolate Repository”, Proceeedings of the Third International Conference on Biomedical Ontology, Graz, July 23-25, 2012 (CEUR, vol. 897).

Cox AP, Jensen M, Duncan W, Weinstock-Guttman B, Szigeti K, Ruttenberg A, Smith B, Diehl AD, Ontologies for the Study of Neurological Disease, Towards an Ontology of Mental Functioning (ICBO Workshop), Third International Conference on Biomedical Ontology, Graz, July 22, 2012.

Yu AC, Smith B, Schwartz S, [http://ontology.buffalo.edu/medo/ACAAI-2012.pdf Formal and Computable Representations of Allergic Diseases in the Electronic Health Record: An Approach Based on the Ontology of General Medical Science, 2012 Annual Meeting of the American College of Allergy, Asthma & Immunology (ACAAI), November 8-13, 2012, Anaheim, California (Poster).

Events

June 11-13, 2012

Immunology Ontologies and Their Applications in Processing Clinical Data

April 8, 2013

1st ImmPort Ontology Group Web Conference:
4:00pm Lindsay Cowell (UT Southwestern): The VDJ Server
5:00pm General discussion of CL and CyTOF

April 22, 2013

2nd ImmPort Ontology Group Web Conference
4:00pm Nikolay Samusik (Stanford): Charting the reference map of the immune system using CyTOF data

April 29, 2013

3rd Immport Ontology Group Web Conference
4:00pm Yannick Pouliot (Stanford): Peak Probability Contrasts (PPC)

June 11, 2013

Lecture and practical session on Immunology Ontology
Summer School for Quantitative Systems Immunology, Boston, MA.

June 24, 2013

4th Immport Ontology Group Web Conference

August 1, 2013

How to make ImmPort data fit for secondary use, Barry Smith
Immport Science Group

September 4-5, 2013

ImmPort Ontology Conference, Stanford University.

October 3, 2013 Ontology Update: Antibodies, Proteins Cells, Alexender Diehl

ImmPort Science Group

Oct 9-10, 2013

Training and Strategy Workshop for ImmPort Data Submitters, Rho Federal Systems Division, Chapel Hill, NC, October 9-10

January 21, 2014

Clinical Trial Data Wants to be Free
Presentation by Barry Smith, University at Buffalo Clinical and Research Ethics Seminar

February 27, 2014

Enhancing the Quality of ImmPort Data, Immport Science Group

March 13, 2014

5th ImmPort Ontology Group Web Conference
Presentation by Ravi Shankar on the Clinical Trial Ontology

March 18, 2014

Discussion with Labkey

March 20, 2014

Gene Expression and Cell Identity, Alexender Diehl
ImmPort Science Group

April 3, 2014

Ontology and the Future of Laboratory Information, David Parrish (sampleminded.com)
Buffalo CTRC

Powerpoint Presentations

Barry Smith, Strategies to Enhance Discoverability of Clinical Trial Data