I am interested in modeling, at the atomic level, physical processes underlying biological mechanisms. These include protein structure prediction and macromolecular docking. Nuclear hormone receptors represent a biological system that is of particular interest to me, as these transcription factors are naturally regulated by small molecule hormones that display physico-chemical properties very similar to drugs; as a result, nuclear receptors are attractive for pharmacological research driven towards therapeutic applications.

I also like to design computational tools that can derive valuable information from public genomics databases, by integrating heterogeneous data types. For instance, mapping genetic polymorphisms information extracted from ESTs and SNPs databases onto experimental or predicted protein 3D structures can produce knowledge driven hypotheses regarding the functional mechanism of genes that experimentalists can further test. Another example of orthogonal data integration that can synergistically improve the predictive power of computational genomics applications is the interfacing of expression data extracted from public sage libraries or micro-array repositories with the systematic mapping of genomic regulatory elements.