A central challenge for systems biology is to transform the data deluge characteristic of the post- genomic world, into the kind of knowledge that will lead to advances in biomedical science and clinical medicine. The transformation requires computer systems that will enable organizing, mining, analyzing and displaying the data in a manner that both informs and drives new hypotheses. VisANT (a visualization, mining system) and Predictome (an integrated database component) form an online graphical workspace and interface for principled integration, mining, discovery, and analysis of molecular networks. The system currently includes, or seamlessly accesses, data sets based on some 70 laboratory and computational methods, and more than 100 species. It has a distinguished and active advisory Board, more than 1000 registered users, is accessed by more than 1100 independent sites per month and has been cited approximately 300 times in the scientific literature. We propose substantially expanding the range of VisANT by including metabolic, chemical reaction, drug and disease related data. Equally importantly, a central goal of VisANT has been integration, and we will substantially extend its integrative capabilities, enabling the identification of disease related pathways, of similarities in mechanisms between phenotypically distinct diseases, and the identification of potential lead compounds for therapy. At the same time we propose substantial expansion of our outreach activities, and movement toward a true many-to many communication and discovery system.

National Institute of Health (NIH)
Research Project (R01)
Project #
Application #
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Ravichandran, Veerasamy
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Boston University
Biomed Engr/Col Engr/Engr Sta
United States
Zip Code
Harcombe, William R; Riehl, William J; Dukovski, Ilija et al. (2014) Metabolic resource allocation in individual microbes determines ecosystem interactions and spatial dynamics. Cell Rep 7:1104-15
Liu, Yang; Hu, Zhenjun (2014) Identification of collaborative driver pathways in breast cancer. BMC Genomics 15:605
Hu, Zhenjun (2014) Using VisANT to Analyze Networks. Curr Protoc Bioinformatics 8:8.8.1-8.8.39
Tian, Feng; Wang, Yajie; Seiler, Michael et al. (2014) Functional characterization of breast cancer using pathway profiles. BMC Med Genomics 7:45
Hu, Zhenjun (2013) Analysis strategy of protein-protein interaction networks. Methods Mol Biol 939:141-81
Hu, Zhenjun; Chang, Yi-Chien; Wang, Yan et al. (2013) VisANT 4.0: Integrative network platform to connect genes, drugs, diseases and therapies. Nucleic Acids Res 41:W225-31
Shigemizu, Daichi; Hu, Zhenjun; Hung, Jui-Hung et al. (2012) Using functional signatures to identify repositioned drugs for breast, myelogenous leukemia and prostate cancer. PLoS Comput Biol 8:e1002347
Huang, Chia-Ling; Lamb, John; Chindelevitch, Leonid et al. (2012) Correlation set analysis: detecting active regulators in disease populations using prior causal knowledge. BMC Bioinformatics 13:46