Theoretical Molecular Biology and Computational Algorithms

Theoretical analysis and modeling is becoming increasingly important in computational biology and bioinformatics. Yale has a multitude of activities in statistical genomics, molecular evolution, computational development, cell simulations, and molecular dynamics. In particular, many research problems involve abstract modeling and questions. Example questions include: What are the functional modules of an integrated genome? Can we understand molecular processes as a form of computation? Both theoretical and practical biological problems generate unique algorithmic and computational problems including: alignments, motif searching, combinatorial optimization, machine learning, and high-performance computing. For example, even simple processing of the extremely large-scale data generated by state-of-the-art genomics facilities requires considerable software and hardware development. Yale has experts in algorithmic research, statistics, and advanced computing.

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