Computational Biology


Richard Bonneau   Tamar Schlick   Dennis E. Shasha   Bud Mishra   Mehryar Mohri  

Computational Biology uses mathematical, statistical and algorithmic techniques to solve problems arising in biological research. The faculty working in this area collaborate with biologists and applied mathematicians on a broad range of problems in genomics, proteomics, molecular modeling, systems biology. The CS Department, along with a number of other departments and schools (Biology, Chemistry, Mathematics, Neuroscience, Sackler Institute of Biomedical Sciences, Mt. Sinai School of Medicine) participates in the interdisciplinary Computational Biology Program.

Richard Bonenau's lab develops and implements methods for modeling biological global regulatory circuits that are general and can be applied to many systems. He is one of the leaders in the development and deployment of "Rosetta", a state of the art protein folding program. The primary current research directions include distilling functional information from genome-wide de novo predictions, grouping genes into functionally related and co-regulated clusters, and learning the structure of biological circuits from data.

Tamar Schlick's group works 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, sophisticated models, reliable numerical tools and simulation protocols are critical; the group's research includes all of these aspects of computational molecular modeling.

Dennis Shasha's research interests are focused on three areas: algorithmic and visualization support for computational biology, time series analysis, and tree and graph pattern matching. In computational biology, Dennis Shasha works on tools and algorithms for plant genomics and proteomics research. Time series analysis is needed in many areas ranging from physics to finance to music. Dennis Shasha and collaborators are working on efficient algorithms for performing online windowed correlation analysis on very large time series datasets (thousands or even millions of numbers). Graph pattern matching problems also arise in many areas from XML querying to chemistry; Denis Shasha's group developed a number of algorithms and software tools for various graph matching problems. Dennis Shasha also works on several themes in databases: privacy-protection (when the server cannot be trusted as in out-sourcing cases), database tuning, and testing.

Bud Mishra has worked in many areas of Computer Science. His current focus is on applications of computer science and mathematical ideas to biological sciences. 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. He leads a number of projects in bioinformatics, primarily in genomics and systems biology, including a novel technology aimed at making fast and cheap sequencing of the human genome broadly accessible, a cancer genome atlas, algebraic model checking for systems biology, large-scale models of pandemic flu and smallpox and many others.

Mehryar Mohri's primary research areas are machine learning, theory and algorithms, text and speech processing, and computational biology. This includes in particular the study of the theoretical aspects of machine learning, the design of general and accurate learning algorithms, and their applications to large-scale learning problems such as those found in bioinformatics and language processing.

Participating Faculty from other Departments

Charles Peskin   Michael Shelley   Gloria Coruzzi   Kenneth Birnbaum


Related Web Pages

Bioinformatics group   Bonneau Lab   Computational Biology/Chemistry/Biomathemics lab   Computational Biology Program   Center for Functional Genomics  

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