This special focus is jointly sponsored by the Center for Discrete Mathematics and Theoretical Computer Science (DIMACS), the Biological, Mathematical, and Physical Sciences Interfaces Institute for Quantitative Biology (BioMaPS), and the Rutgers Center for Molecular Biophysics and Biophysical Chemistry (MB Center).
Biological processes in cells are based on specific molecular recognitions, which triggers cascade of biological responses. The physical basis of complex network interaction is the three-dimensional structure of proteins and their functional regions. Understanding how information encoded in these biomolecules is recognized and processed by the interacting partners is a fundamental problem of biology.
In this workship we discuss the development of algorithms for discovery of spatial patterns important for recognition, for uncovering deep evolutionary relationship of proteins, for predicting binding partners, and for simulating the protein-protein and protein-DNA recognition process. Specific topics of interests include protein-ligand and protein-protein binding site prediction, functional prediction of proteins with known structures but unknown functions, protein-protein interactions and docking, prediction of immune epitope, design of peptide modulators of protein-protein interactons, protein substructure matching, and evolution of structural biopattern. We hope further development in these areas will likely to formulate new research problems and motivate new algorithms in combinatorics, optimization, discrete mathematics, mathematical programming, and additional areas.