Our lab develops and applies computational approaches for data mining, analysis and knowledge extraction from biomedical data. We are particularly active in the fields of structural bioinformatics, computational genomics and systems biology.

Our lab recently developed a number of novel methods for analysis and prediction of protein interactions, including those for membrane proteins, and for model quality assessment. We are also pursuing development of improved data mining methods that combine docking simulations, chemical similarity and toxicogenomics to predict activity of environmental factors and other small molecules.

We apply the methods we develop in the context of collaborative projects, and develop bioinformatics tools for functional and structural annotation of proteins and their complexes. Several of these tools, including SABLE, SPPIDER and POLYVIEW-3D, are available to the community as web servers and are being widely used by researchers from many countries.