The primary goal of the proposed Center of Excellence is to build a powerful and scalable Knowledge Engine for Genomics, KnowEnG. KnowEnG will transform the way biomedical researchers analyze their genome-wide data by integrating multiple analytical methods derived from the most advanced data mining and machine learning research to use the full breadth of existing knowledge about the relationships between genes as background, and providing an intuitive and professionally designed user interface. In order to achieve these goals, the project includes the following components: (1) gathering and integrating existing knowledgebases documenting connections between genes and their functions into a single Knowledge Network; (2) developing computational methods for analyzing genome-wide user datasets in the context of this pre-existing knowledge; (3) implementing these methods into scalable software components that can be deployed in a public or private cloud; (4) designing and implementing a Web-based user interface, based on the HUBZero toolkit, that enables the interactive analysis of user-supplied datasets in a graphics-driven and intuitive fashion; (5) thoroughly testing the functionality and usefulness of the KnowEnG environment in three large scale projects in the clinical sciences (pharmacogenomics of breast cancer), behavioral sciences (identification of gene regulatory modules underlying behavioral patterns) and drug discovery (genome-based prediction of the capacity of microorganisms to synthesize novel biologically active compounds). The KnowEng environment will be deployed in a cloud infrastructure and fully available to the community, as will be the software developed by the Center. The proposed Center is a collaboration between the University of Illinois (UIUC), a recognized world leader in computational science and engineering, and the Mayo Clinic, one of the leading clinical care and research organizations in the worid, and will be based at the UIUC Institute for Genomic Biology, which has state-of-the-art facilities and a nationally recognized program of multidisciplinary team-based genomic research.

Public Health Relevance

Physicians and biologists are now routinely producing very large, genome-wide datasets. These data need to be analyzed in the context of an even larger corpus of publically available data, in a manner that is approachable to non-specialist doctors and scientists. The proposed Center will leverage the latest computational techniques used to mine corporate or Internet data to enable the intuitive analysis and exploration of biomedical Big Data.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54GM114838-03
Application #
9096856
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Gregurick, Susan
Project Start
2014-09-29
Project End
2018-04-30
Budget Start
2016-05-01
Budget End
2017-04-30
Support Year
3
Fiscal Year
2016
Total Cost
Indirect Cost
Name
University of Illinois Urbana-Champaign
Department
Genetics
Type
Organized Research Units
DUNS #
041544081
City
Champaign
State
IL
Country
United States
Zip Code
61820
Adami, Guy R; Tangney, Christy C; Tang, Jessica L et al. (2018) Effects of green tea on miRNA and microbiome of oral epithelium. Sci Rep 8:5873
Xiao, Jinfeng; Blatti, Charles; Sinha, Saurabh (2018) SigMat: a classification scheme for gene signature matching. Bioinformatics 34:i547-i554
Saul, Michael C; Blatti, Charles; Yang, Wei et al. (2018) Cross-species systems analysis of evolutionary toolkits of neurogenomic response to social challenge. Genes Brain Behav :e12502
Hanson, Casey; Cairns, Junmei; Wang, Liewei et al. (2018) Principled multi-omic analysis reveals gene regulatory mechanisms of phenotype variation. Genome Res 28:1207-1216
Wang, Sheng; Ma, Jianzhu; Zhang, Wei et al. (2018) Typing tumors using pathways selected by somatic evolution. Nat Commun 9:4159
Wang, Liewei; Ingle, James; Weinshilboum, Richard (2018) Pharmacogenomic Discovery to Function and Mechanism: Breast Cancer as a Case Study. Clin Pharmacol Ther 103:243-252
Liem, David A; Murali, Sanjana; Sigdel, Dibakar et al. (2018) Phrase mining of textual data to analyze extracellular matrix protein patterns across cardiovascular disease. Am J Physiol Heart Circ Physiol 315:H910-H924
Singh, Sonal; Wang, Zhiying; Shahin, Mohamed H et al. (2018) Targeted sequencing identifies a missense variant in the BEST3 gene associated with antihypertensive response to hydrochlorothiazide. Pharmacogenet Genomics 28:251-255
Huang, Edward W; Wang, Sheng; Zhai, ChengXiang (2018) VisAGE: Integrating external knowledge into electronic medical record visualization. Pac Symp Biocomput 23:578-589
Zhang, Yi; Manjunath, Mohith; Zhang, Shilu et al. (2018) Integrative Genomic Analysis Predicts Causative Cis-Regulatory Mechanisms of the Breast Cancer-Associated Genetic Variant rs4415084. Cancer Res 78:1579-1591

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