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).
The biological community is being inundated with a large amount of data and understanding this data is lagging behind the process of acquiring it. It is believed nature has left vital clues hidden in this data and there is a need for techniques and methodologies to work effectively in detecting these. Biological information processing exploits these regularities to gain understanding of the underlying model or phenomenon. For example, in its simplest form regularity could be repetition of functional or structural domains in a protein sequences or co-expression of genes in microarrays. When the data is in terms of networks, either representing protein-protein interactions or metabolic pathways, topological motifs tell a tale that will be fundamental in understanding the working of a biological system. The workshop aims to contribute significantly to the research effort by bringing together researchers from the many different groups engaged in biological projects having the study of regularities in the data as an underlying theme.
List of Keynote Speakers: