American Statistical Association
New York City
Metropolitan Area Chapter

Mailman School of Public Health
Columbia University
Department of Biostatistics Colloquium



DATA MINING OF SEQUENCE-DEPENDENT FEATURES
OF DNA AND KNOWLEDGE-BASED MONTE CARLO SIMULATION OF DNA CHAINS

by

Guohui Zheng
BioMaPS Institute for Quantitative Biology
Rutgers University


Abstract

Nucleic acid bases (A, T, G, C) contain structural and energetic signatures that contribute to the unique features of genetic sequences. Some of the most interesting features of double-helical DNA occur at the mesoscopic level, which is at chain lengths of a few hundred base pairs. For example, DNA loops of this size bring proteins bound at separate, widely spaced sites on the double helix into close contact, influencing not only the three dimensional organization of the genome but also the activity of proteins that control, shuffle, and express the genetic message. Some regularly repeating sequences of a few hundred base pairs exhibit strong natural curvature, adopting circular and super helical shapes. Such folding is an important facet of biological processes that involve long-range recognition and/or interactions. Indeed, naturally curved DNA can mimic the biological activity of proteins that bend DNA. In the purpose of understanding the mechanisms of aforementioned biological processes, this talk introduces: 1) our data mining, including an analysis of the spatial arrangements of neighboring DNA base pairs, covering mathematical approaches developed to quantify the orientation and displacement of the base pairs as well as structural trends and sequence-dependent features revealed in the database of high-resolution protein-DNA crystal structures; 2) Monte-Carlo simulation, which rests upon a novel set of knowledge -based potentials of dimeric deformability, a matrix treatment of global chain configuration, and Gibbs sampling of DNA configuration space.


Date: Tuesday, July 24, 2007
Time: 1:30 - 2:30 P.M.
Location: Mailman School of Public Health
Department of Biostatistics
722 West 168th Street
Biostatistics Conference Room (Room 627)
New York, New York

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