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).
Bioinformatics aims to solve biological problems by using techniques from mathematics, statistics, computer science, and machine learning. Recent years have observed the essential use of these techniques in this rapidly growing field. Examples of such applications include those to gene expression data analysis, gene-protein interactions, protein folding and structure prediction, genetic and molecular networks, sequence and structural motifs, genomics and proteomics, text mining in bioinformatics, and so on. Bioinformatics provides opportunities for developing novel machine learning techniques; and machine learning plays a key role in advancing bioinformatics. The workshop is devoted to computational challenges of important biological problems. The goal of this workshop is to bring together researchers in both machine learning and bioinformatics to discuss state-of-the-art machine learning algorithms and their applications to various tasks in bioinformatics.
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