We propose to continue the National Center for Biomedical Ontology (NCBO), which develops tools and methods for assimilating, archiving, accessing, and applying machine-processable representations of biomedical domain objects, processes, and relations to assist in the management, integration, visualization, analysis, and interpretation of the huge, distributed data sets that are now the hallmark of biomedical research and clinical care. Our center is truly national in scope, with participation of leading scientific groups at Stanford, Mayo Clinic, University at Buffalo, and the University of Victoria. Our objectives are defined by the following six Cores: (1) the development of enhanced computational methods for management of ontologies and controlled terminologies using current Web standards;integration of ontology authoring, publishing, and peer review;creation of a comprehensive ontology-based index of publicly available data resources;development of new analytic methods to summarize and profile biomedical data;(2) the promotion of Driving Biological Projects that can stimulate our research by suggesting new requirements and offering new test beds for deployment-initially involving the Cardiovascular Research Grid, the Rat Genome Database, the caNanoLab nanoparticle database, and the i2b2 National Center for Biomedical Computing, and later engaging the WHO's development of lCD-11, studies performed by ArrayExpress, and projects that will be selected via open requests for applications;(3) the maintenance of a computational infrastructure to support our research, development, and dissemination activities;provision of user support to the growing number of researchers and clinicians who use our technologies;(4) the training of the next generation of scientists in biomedical ontology;(5) a comprehensive set of dissemination activities, that include workshops, tutorials. Web-based seminars, and a major international conference;and (6) outstanding project administration conducted by a dedicated and talented management team. The NCBO will accelerate the transition of biomedicine into the world of e-science, facilitate the creation of a National Health Information Infrastructure, and extend a network of collaboration through its interactions with other NCBCs, with other research consortia, and with the biomedical community at large.

Public Health Relevance

The NCBO supports a burgeoning user community that is using ontologies to enhance biomedical research and to improve patient care. It supports bench scientists, clinician researchers, and workers in informatics in data annnotation, data integration, information retrieval, natural-language processing, electronic patient record systems, and decision-support systems. It is a primary source of semantic-technology infrastructure and expertise for biomedical research and the development of advanced clinical information svstems.

National Institute of Health (NIH)
National Human Genome Research Institute (NHGRI)
Specialized Center--Cooperative Agreements (U54)
Project #
Application #
Study Section
Special Emphasis Panel (ZRG1-BST-K (52))
Program Officer
Bonazzi, Vivien
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Stanford University
Internal Medicine/Medicine
Schools of Medicine
United States
Zip Code
Zykovich, Artem; Hubbard, Alan; Flynn, James M et al. (2014) Genome-wide DNA methylation changes with age in disease-free human skeletal muscle. Aging Cell 13:360-6
Ghebremariam, Yohannes T; Lee, Jerry C; LePendu, Paea et al. (2014) Response to letters regarding article, "unexpected effect of proton pump inhibitors: elevation of the cardiovascular risk factor asymmetric dimethylarginine". Circulation 129:e428
Wu, Stephen T; Juhn, Young J; Sohn, Sunghwan et al. (2014) Patient-level temporal aggregation for text-based asthma status ascertainment. J Am Med Inform Assoc 21:876-84
Walls, Ramona L; Deck, John; Guralnick, Robert et al. (2014) Semantics in support of biodiversity knowledge discovery: an introduction to the biological collections ontology and related ontologies. PLoS One 9:e89606
Lopez-Garcia, Pablo; Lependu, Paea; Musen, Mark et al. (2014) Cross-domain targeted ontology subsets for annotation: the case of SNOMED CORE and RxNorm. J Biomed Inform 47:105-11
Mort, Matthew; Sterne-Weiler, Timothy; Li, Biao et al. (2014) MutPred Splice: machine learning-based prediction of exonic variants that disrupt splicing. Genome Biol 15:R19
Wass, Mark N; Mooney, Sean D; Linial, Michal et al. (2014) The automated function prediction SIG looks back at 2013 and prepares for 2014. Bioinformatics 30:2091-2
Harpaz, Rave; Callahan, Alison; Tamang, Suzanne et al. (2014) Text mining for adverse drug events: the promise, challenges, and state of the art. Drug Saf 37:777-90
Jung, Kenneth; LePendu, Paea; Chen, William S et al. (2014) Automated detection of off-label drug use. PLoS One 9:e89324
Huang, Sandy H; LePendu, Paea; Iyer, Srinivasan V et al. (2014) Toward personalizing treatment for depression: predicting diagnosis and severity. J Am Med Inform Assoc 21:1069-75

Showing the most recent 10 out of 85 publications