Our research focus is on developing novel data mining and machine learning algorithms to accelerate knowledge discovery in life science and engineering fields. We are interested in analyzing a variety of biological data, particularly, high-throughput data including gene expression profiles, protein sequences and structures, protein-protein interactions, chemical structures, biological pathways and disease phenotypes. The applications of our work could be found in Immunology, Neurology, and Drug design.

We are currently working on many aspects of Bioinformatics, Systems Biology, and Computational Cancer Biology. Specifically, our research covers:

Bioinformatics:

  • analyzing and annotating protein functions
  • recognizing fold of protein sequences, especially pathological genes
  • identifying protein interface residue
  • understanding gene regulation mechanism
  • analyzing microarray data

Systems Biology:

  • elucidating protein interaction networks and protein-ligand interactions
  • understanding genetic regulatory networks
  • identifying modular structures in biological pathways

Cancer Biology:

  • identifying biomarkers from gene expression profiles
  • cancer diagnosis and classification using mass-spectrometry data
  • hits identification through drug virtual screening
  • analyzing cancer pathways
  • understanding the connection between static/dynamic biomolecule interactions and diseases