The National Center for Integrative Biomedical Informatics (NCIBI) is one of eight National Centers for Biomedical Computing (NCBC) within the NIH Roadmap. The NCBC program is focused on building a universal computing infrastructure designed to speed progress in biomedical research. NCIBI was founded in September 2005 and is based at the University of Michigan as part of the Department of Computational Medicine and Bioinformatics (DCMB).

Led jointly by teams of computational and biomedical scientists, NCIBI:

Integrates vast amounts of diverse, multi-scale data and derived knowledge, including context-appropriate molecular biology information from emerging experimental data; gene, protein, and metabolite databases; and the published literature.

Collaborates to determine how these data sets can best be represented and developed into resources that will advance research and facilitate biomedical discoveries.

Creates relevant tools for analytically exploring the data to uncover and validate functional associations and possible causal and conditional relationships involved in mechanisms of complex physiological processes or diseases.

Develops an array of tutorials, seminars, documentation, and other training materials to assure both the usability and usefulness of NCIBI tools.

Disseminates discoveries and processes to biomedical communities worldwide through publications, presentations, national partnerships and collaborators, and e-networking initiatives such as an RSS feed and the NCIBI gateway.

News

The tranSMART Foundation Wins Awards at the BioIT World 2015 Conference!

NCIBI researchers among international team that identifies genetic variants that contribute to mental illness.

Dr. Gilbert S. Omenn discusses the emerging HUPO Human Proteome Project on Australian SkyNews.

New Tools and Services

The tranSMART Foundation Announces Version 1.1 of the tranSMART Open Source Data Sharing Platform for the Life Sciences Community

We are pleased to announce the official release of our new web-based tool, LRpath. This tool performs gene set enrichment testing, an approach used to identify key pathways and other biological concepts affected in high-throughput experiments. LRpath uses all analyzed genes and their significance levels to assess enrichment, and thus does not require a significance cut-off. It is powerful for experiments with either small or large sample size, and offers the ability to cluster and compare enrichment results from multiple experiments.

We are pleased to announce a release of Metscape 2.2. The most prominent changes include a more versatile workflow and enhanced visualization features.

Gene2MeSH and Metab2MeSH versions 3.0 have been released.

Announcing the MiMI 3.1 release. This update adds compatibility with Cytoscape versions 2.8 and 2.8.1, fixes links to external web services, and incorporates the ability to search for Genes by MeSH terms.

RECENT Publications

A High-Confidence Human Plasma Proteome Reference Set with Estimated Concentrations in PeptideAtlas. Farrah T, Deutsch EW, Omenn GS, Campbell DS, Sun Z, Bletz JA, Mallick P, Katz JE, Malmstrom J, Ossola R, Watts JD, Lin B, Zhang H, Moritz RL, Aebersold RH. (Mol Cell Proteomics 2011)

A role for coding functional variants in HNF4A in type 2 diabetes susceptibility. Jafar-Mohammadi B, Groves CJ, Gjesing AP, Herrera BM, Winckler W, Stringham HM, Morris AP, Lauritzen T, Doney AS, Morris AD, Weedon MN, Swift AJ, Kuusisto J, Laakso M, Altshuler D, Hattersley AT, Collins FS, Boehnke M, Hansen T, Pedersen O, Palmer CN, Frayling TM, DIAGRAM Consortium, Gloyn AL, McCarthy MI. (Diabetologia 2011)

Unified translation repression mechanism for microRNAs and upstream AUGs. Ajay SS, Athey BD, Lee I. (BMC Genomics 2010)