Computational Biology


Richard Bonneau   Bud Mishra   Dennis Shasha   Tamar Schlick


Computational Biology deals with computational problems arising from biological systems. This is an active area of research at the Computer Science Department.

Richard Bonneau's research focusses is centered on two main areas: 1) developing computational and mathematical solutions to problems arising from functional genomeics or high throughput biological datasets and 2) deriving functional information from structure predictions and further development and implementation of Rosetta.

Bud Mishra's research in computational biology focuses on computational genomics. He has developed optical mapping technology, a successful approach to physical genome mapping. He aims to develop efficient practical algorithmic tools for genome mapping and sequencing, based on a high level programming language designed for this purpose.

Dennis Shasha is involved in three projects related to computational biology: the discovery of transcription factor networks, functional genomics and pattern matching. The first project aims to study natural analog circuits, consisting of special type of proteins (transcription factors) that regulate production of other proteins. Functional genomics aims to identify similar genes in different species, which requires very fast algorithms for sequence comparison. Approximate pattern matching is essential for finding correlations in biological data, as they are often obtained from experiments without perfect repeatability. The goal of Prof. Shasha's research is to produce algorithms and data structures that allow rapid approximate search across a variety of structural databases.

The work in Professor Schlick's group focuses on determining the structural and dynamical properties of macromolecules by computer simulation. Computational techniques are critically needed to link the static structural information on proteins and nucleic acids obtained by X-ray crystallography and nuclear magnetic resonance with the wide range of biological activity and reactivity in the realistic environment of the cell. In this goal, reliable numerical tools and simulation protocols are critical. Needed are a variety of models for spatial and temporal resolution of complex molecular systems, from the quantum-mechanical to molecular mechanics treatments. The rapidly advancing technology of faster computers, larger memories, and parallel-processing environments also offers new opportunities for theoretical advances and hence the impact of the field of structural biology/biophysics as a whole.

Research Interests

Richard Bonneau De novo structure prediction using Rosetta, structure-function relationship, regulatory network inference, biological pathway reconstruction, biclustering of large functional genomics datasets, data integration and visualization.
Bud Mishra Computational biology, including algorithms for identifying DNA associated with cancers, and computational aspects of the optical mapping approach to the Human Genome project. Computational game theory. Robotics. Computational algebra.
Dennis Shasha Biological computing, information exploration for difficult data, data mining for biology and finance.
Tamar Schlick Mathematical biology, molecular modeling, molecular dynamics, numerical methods, DNA and protein structure.

Related Projects

Bioinformatics Group   Computational Math and Chemistry

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