Big Data to Knowledge: Difference between revisions

Revision as of 17:44, 17 March 2015

Revision as of 17:45, 17 March 2015

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PI: Mark W. Craven

Grant Number: 1U54AI117924-01<ref>{{cite web |url= http://projectreporter.nih.gov/project_info_description.cfm?aid=8921373&icde=22003161 |title= University of Wisconsin – Madison BD2K Project Information - Center for Predictive Computational Phenotyping BD2K Project Information |work= projectreporter.nih.gov }}</ref>

The '''Center for Predictive Computational Phenotyping''' aims to accelerate the impact of predictive modeling on clinical practice. The Center will focus on issues related to computational phenotyping and will produce disease prediction models from machine learning and statistical methods; these models will integrate data from electronic health records, images, molecular profiles and other datasets to predict patient risks for breast cancer, heart attacks and severe blood clots.<ref>{{cite web |url= http://bd2k.nih.gov/FY14/COE/Craven.pdf |title= University of Wisconsin – Madison BD2K Abstract| work= bd2k.nih.gov }}</ref>

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PI: Scott L. Delp

Grant Number: 1U54EB020405-01<ref>{{cite web |url= http://projectreporter.nih.gov/project_info_description.cfm?aid=8905651&icde=22003200 |title= Stanford University BD2K Project Information - National Center for Mobility Data Integration to Insight (The Mobilize Center) BD2K Project Information |work= projectreporter.nih.gov }}</ref>

The '''Mobilize Center''' is poised to provide access to mobility data for over ten million people. The center will develop and disseminate a range of novel data science tools, including modeling and analysis methods to predict and improve the outcomes of surgeries in children with cerebral palsy and gait pathology; to identify new approaches to optimize mobility in individuals with osteoarthritis, running injuries, and other movement impairments; and to discover methods that motivate overweight and obese individuals to exercise more and in ways that promote joint health.<ref>{{cite web |url= http://mobilize.stanford.edu/ |title= The Mobilize BD2K Center of Excellence Homepage | work= mobilize.stanford.edu/ }}</ref><ref>{{cite web |url= http://bd2k.nih.gov/FY14/COE/Delp.pdf |title= Stanford University Mobilize Center BD2K Abstract| work= bd2k.nih.gov }}</ref>

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PIs: Jiawei Han, Saurabh Sinha, Jun Sorg, and Richard Weinshilboum

Grant Number: 1U54GM114838-01<ref>{{cite web |url= http://projectreporter.nih.gov/project_info_description.cfm?aid=8774407&icde=22110323 |title= The University of Illinois Urbana-Champaign BD2K Project Information - KnowEng, a Scalable Knowledge Engine for Large-Scale Genomic Data BD2K Project Information |work= projectreporter.nih.gov }}</ref>

The '''KnowEng Center''' will build a computational Knowledge Engine that uses data mining and machine learning techniques to obtain and combine gene function and gene interaction information from disparate genomic data sources. This integrated genomic environment will enable scientists and medical practitioners to add their own datasets to the engine and explore models generated from the incorporation of their data within the existing knowledge-base.<ref>{{cite web |url= http://bd2k.nih.gov/FY14/COE/Han.pdf |title= The University of Illinois Urbana-Champaign BD2K Abstract| work= bd2k.nih.gov }}</ref>

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PIs: David H. Haussler, David Patterson, and Laura Van’t Veer

Grant Number: 1-U54HG007990-01<ref>{{cite web |url= http://projectreporter.nih.gov/project_info_description.cfm?aid=8775080&icde=22748910&ddparam=&ddvalue=&ddsub=&cr=9&csb=default&cs=ASC |title= The University of California Santa Cruz BD2K Project Information - National Center for MobilityBig Data Integrationin toTranslational InsightGenomics (TheBD2K MobilizeProject Center)Information |work= projectreporter.nih.gov }}</ref>

The '''Center for Big Data in Translational Genomics''' is a multinational collaboration between academia and industry that will create data models and analysis tools to analyze massive datasets of genomic information. Such tools can be used for analysis of the genomes and the gene expression data from thousands of individuals to uncover the contribution of gene variants to disease, with an initial focus on cancer. This knowledge will be instrumental in the development of precision diagnostic and treatment methods.<ref>{{cite web |url= http://bd2k.nih.gov/FY14/COE/Haussler.pdf |title= The University of California Santa Cruz BD2K Abstract| work= bd2k.nih.gov }}</ref>