Activities of the BD2K Centers Consortium will be focused on gathering resources and achieving goals of the Initiative in ways that could not be accomplished effectively by individual Centers. The Consortium will assemble experts who are able to lead the fields represented under the heading of biomedical Big Data and advance the goals of the initiative in a coordinated way, and it will draw in institutions with the resources to provide the necessary support. We have identified several goals that we view as particularly important and that will be addressed more effectively by the Consortium than by individual Centers. These goals include 1) forming a close-knit, collaborative intellectual community focused on the challenges of the BD2K Initiative with an emphasis on interdisciplinary communication and collaboration;2) developing and implementing data standards, coordinating between those standards, and developing data management and analysis tools;3) anticipating emerging challenges related to Big Data that are not fully characterized in the current vision for the BD2K Initiative and initial development of strategies that address those challenges;and 4) exploring legal, ethical, and privacy concerns related to biomedical Big Data research. The KnowEnG Center at the University of Illinois is fully committed to participate actively in pursuing these objectives, and proposes to implement the following activities: 1) organizing workshops on topics proposed by Consortium members but of interest to all members, and building communities around the themes of the workshops that can extend beyond the Consortium;2) participating in Consortium-wide standards working groups aiming to improve interoperability between tools and methods developed in individual Centers, and in close cooperation with existing standards groups;3) organizing small conferences, on the model of the Gordon Conferences and with priority given to young investigators, focusing on the identification of emerging challenges in biomedical Big Data, with associated hackathons to address current challenges;4) organizing Consortium-wide colloquia to address legal, ethical and privacy/security issues associated with the analysis of biomedical Big Data

Public Health Relevance

The Centers of Excellence for Biomedical Big Data Computing funded by NIH will need to work together to address the challenges associated with the rapid increase in the availability of these data. The KnowEnG center at Illinois and Mayo will contribute its combined expertise in computational science and the management of clinical data to help define standards, explore future directions in the field, address privacy and security issues, and build a community of expertise in this area.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
1U54GM114838-01
Application #
8907589
Study Section
Special Emphasis Panel (ZRG1-BST-R (52))
Program Officer
Lyster, Peter
Project Start
Project End
Budget Start
2014-07-01
Budget End
2015-06-30
Support Year
1
Fiscal Year
2014
Total Cost
$72,133
Indirect Cost
$26,652
Name
University of Illinois Urbana-Champaign
Department
Type
DUNS #
041544081
City
Champaign
State
IL
Country
United States
Zip Code
61820
Cairns, Junmei; Ung, Choong Yong; da Rocha, Edroaldo Lummertz et al. (2016) A network-based phenotype mapping approach to identify genes that modulate drug response phenotypes. Sci Rep 6:37003
Hanson, C; Cairns, J; Wang, L et al. (2016) Computational discovery of transcription factors associated with drug response. Pharmacogenomics J 16:573-582
Wang, Sheng; Qu, Meng; Peng, Jian (2016) PROSNET: INTEGRATING HOMOLOGY WITH MOLECULAR NETWORKS FOR PROTEIN FUNCTION PREDICTION. Pac Symp Biocomput 22:27-38
Cohen, Nadia R; Ross, Christian A; Jain, Saloni et al. (2016) A role for the bacterial GATC methylome in antibiotic stress survival. Nat Genet 48:581-6
Bendre, Mangesh; Sun, Bofan; Zhang, Ding et al. (2015) DataSpread: Unifying Databases and Spreadsheets. Proceedings VLDB Endowment 8:2000-2003
Tao, Fangbo; Zhao, Bo; Fuxman, Ariel et al. (2015) Leveraging Pattern Semantics for Extracting Entities in Enterprises. Proc Int World Wide Web Conf 2015:1078-1088
Kordjamshidi, Parisa; Roth, Dan; Moens, Marie-Francine (2015) Structured learning for spatial information extraction from biomedical text: bacteria biotopes. BMC Bioinformatics 16:129
Ren, Xiang; El-Kishky, Ahmed; Wang, Chi et al. (2015) Automatic Entity Recognition and Typing from Massive Text Corpora: A Phrase and Network Mining Approach. KDD 2015:2319-2320
Stephens, Zachary D; Lee, Skylar Y; Faghri, Faraz et al. (2015) Big Data: Astronomical or Genomical? PLoS Biol 13:e1002195
Kuck, Jonathan; Zhuang, Honglei; Yan, Xifeng et al. (2015) Query-Based Outlier Detection in Heterogeneous Information Networks. Adv Database Technol 2015:325-336

Showing the most recent 10 out of 33 publications