RESUMO
While high throughput screening (HTS) techniques are capable of generating large amounts of biologically significant data, assimilating and mining this information can be extremely complex and potentially crucial information patterns can easily be lost in the mounds of data. The predominantly life-science oriented scientific training of the researchers in this area furthermore, precludes their using complex querying or data-mining algorithms. Keeping in account these challenges, our goal in this paper is to provide a highly intuitive environment for storing and interacting with large amounts of HTS assay data. The principal modes of user-data interactions supported in the proposed paradigm are interaction and visualization rich. Moreover, they span the heterogeneous data modalities common to drug discovery, including but not limited to chemical structures, high-throughput assay formats, graphical information, and alpha-numeric data types. Case studies and experiments demonstrate the efficacy of the proposed approach in terms of its ease of use as well as its capability to discern complex information patterns in the data.
