The Biocomputing Research Lab

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Information Management for Drug Discovery


The state of the art in modern drug discovery involves investigating a large number of drug-like molecules using medium or high-throughput assays, often being conducted against multiple targets. Managing the information generated in such processes requires the ability to deal with complex, multifarious data as well as the development of new user-data interaction paradigms that help glean patterns hidden in the multitude of data by emphasizing exploration and information assimilation.
FreeFlowDB is a drug discovery information database system that is geared towards storing both structural as well as high-throughput assay information generated as part of a typical drug discovery process. FreeFlowDB supports powerful structural querying facilities that subsume within a common algorithmic framework exact structural matching, sub-structure querying, and in-exact matching. Furthermore, the system supports unified visualization-query facilities that allow interacting with assay as well as structure-activity information. This allows efficacious and intuitive query-analysis of large amounts of data for knowledge discovery.
Our research is being conducted in collaboration with the DeRisi Lab at UCSF and QB3 (California Institute for Quantitative Biosciences). This research is partially supported by the National Science Foundation grant IIS-0644418.


  1. T. Chan, P. Malik and R. Singh, "An Interactive Visualization-Based Approach for High Throughput Screening Information Management in Drug Discovery", IEEE International Conference on Engineering in Medicine and Biology Society (EMBC), 2006, pp. 5794-5797. [PDF]
  2. R. Singh, E. Velasquez, P. Vijayant and E. R. Yera, "FreeFlowDB: Storage, Querying and Interacting with Structure-Activity Information for High-Throughput Drug Discovery", IEEE International Symposium on Computer-Based Medical Systems (CBMS), 2006, pp. 75-80. [PDF]
  3. P. Malik, T. Chan, J. Vandergriff, J. Weisman, J. DeRisi and R. Singh, "Information Management And Interaction In High-Throughput Screening for Drug Discovery", Database Modeling in Biology: Practices and Challenges, Z. Ma, J. Y. Chen, eds. Book Chapter, To Appear, Springer Sciences+Business Media, Inc., New York, USA, 2006.
  4. R. Singh "An Overview of Computational Knowledge Discovery and Pattern Analysis Problems in Contemporary Drug Discovery and Design", DIMACS Summer School Tutorial on New Frontiers in Data Mining, Rutgers University, Piscataway, NJ, August 2001. Available online.
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