PgmNr D1528:
Model organism analysis using InterMine.

Authors:
Rachel Lyne 1,2 ; Karen Christie 5 ; Paul Davis 4 ; Jeff De Pons 7 ; Todd Harris 4 ; Kalpana Karra 3 ; Sheldon McKay 4 ; Howie Motenko 5 ; Paulo Nuin 4 ; Leyla Ruzicka 6 ; Julie Sullivan 1,2 ; Jennifer Smith 7 ; Sierra Taylor Moxon 6 ; Edith Wong 3 ; Mike Cherry 3 ; Joel Richardson 5 ; Mary Shimoyama 7 ; Lincoln Stein 4 ; Gos Micklem 1,2 ; Monte Westerfield 6,8

Institutes
1) Cambridge Systems Biology Centre, University of Cambridge, Cambridge, UK; 2) Department of Genetics, University of Cambridge, Cambridge, UK; 3) Department of Genetics, Stanford University, Stanford, CA; 4) Ontario Institute for Cancer Research, Toronto, ON, Canada; 5) The Jackson Laboratory, Bar Harbor, ME; 6) ZFIN, University of Oregon, Eugene, OR; 7) Human and Molecular Genetics Center, Medical College of Wisconsin, Milwaukee, WI; 8) Institute of Neuroscience, University of Oregon, Eugene, OR.

Keyword: webtools and databases
Abstract:

Ultimately the aim of studies in model organisms is to further understanding of human biology and disease and eventually facilitate the translation of research into clinical practice. The InterMOD consortium provides a framework for accessing model organism data through the InterMine data integration system (http://intermine.org). InterMine-based databases have been developed for budding yeast (http://yeastmine.yeastgenome.org), rat (http://www.ratmine.org), zebrafish (http://zebrafishmine.org), nematode (http://im-dev.wormbase.org/tools/wormmine), mouse (http://mousemine.org) and fruitfly (http://flymine.org) (known as the MOD-InterMine databases) together with a complementary InterMine database containing human data (http://humanmine.org). The result is a unified interface for data access, search and exploration, through which data from different model organism can be related to each other and to human data through orthology, and likewise model organism data can become more accessible to medical researchers.

The web interface includes a useful identifier resolution system, sophisticated query options and interactive results tables that enable powerful exploration of data, including summaries, filtering, browsing and support for lists. Graphical analysis tools provide a rich environment for data investigation including statistical enrichment of sets of genes or other biological entities.

The powerful, scriptable web service API includes client libraries in multiple widely used languages, including Python, Perl, Ruby, Java and JavaScript, allowing programmatic access to data and facilitating creation of bioinformatic workflows.

Building on this framework, and as part of the NIH BD2K program, we are creating tools that will interrelate human genes and their MOD orthologs, allowing users to examine similarities and differences across the range of model organisms, and therefore increasing the ease with which biomedical researchers can exploit MOD data. A pilot Gene Ontology Analysis tool will be presented.  Please come by for a demonstration to the poster/exhibition hall, to booth 403..