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.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54HG004028-10
Application #
8737919
Study Section
Special Emphasis Panel (ZRG1-BST-K (52))
Program Officer
Bonazzi, Vivien
Project Start
2005-09-23
Project End
2015-07-31
Budget Start
2014-08-01
Budget End
2015-07-31
Support Year
10
Fiscal Year
2014
Total Cost
$3,409,670
Indirect Cost
$969,139
Name
Stanford University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
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van der Weyden, Louise; Arends, Mark J; Campbell, Andrew D et al. (2017) Genome-wide in vivo screen identifies novel host regulators of metastatic colonization. Nature 541:233-236
Kamdar, Maulik R; Musen, Mark A (2017) Mechanism-based Pharmacovigilance over the Life Sciences Linked Open Data Cloud. AMIA Annu Symp Proc 2017:1014-1023
Kamdar, Maulik R; Walk, Simon; Tudorache, Tania et al. (2017) BiOnIC: A Catalog of User Interactions with Biomedical Ontologies. Semant Web ISWC 10588:130-138
Martínez-Romero, Marcos; O'Connor, Martin J; Shankar, Ravi D et al. (2017) Fast and Accurate Metadata Authoring Using Ontology-Based Recommendations. AMIA Annu Symp Proc 2017:1272-1281
Martínez-Romero, Marcos; Jonquet, Clement; O'Connor, Martin J et al. (2017) NCBO Ontology Recommender 2.0: an enhanced approach for biomedical ontology recommendation. J Biomed Semantics 8:21
Kamdar, Maulik R; Musen, Mark A (2017) PhLeGrA: Graph Analytics in Pharmacology over the Web of Life Sciences Linked Open Data. Proc Int World Wide Web Conf 2017:321-329
van der Weyden, Louise; Karp, Natasha A; Swiatkowska, Agnieszka et al. (2017) Genome wide in vivo mouse screen data from studies to assess host regulation of metastatic colonisation. Sci Data 4:170129
Ochs, Christopher; Perl, Yehoshua; Geller, James et al. (2017) An empirical analysis of ontology reuse in BioPortal. J Biomed Inform 71:165-177
Nead, Kevin T; Gaskin, Greg; Chester, Cariad et al. (2016) Androgen Deprivation Therapy and Future Alzheimer's Disease Risk. J Clin Oncol 34:566-71

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