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The Research on the Discovery of Transcription Factor Binding Sites Based on Genetic Algorithm

Author: TianLuFang
Tutor: LiuWenYuan
School: Yanshan University
Course: Applied Computer Technology
Keywords: Transcription factor binding sites Gibbs sampling algorithm Position weight matrix Genetic Algorithms TRANSFAC DBTSS
CLC: Q75
Type: Master's thesis
Year: 2011
Downloads: 40
Quote: 0
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Abstract


Regulation of gene expression is to understand the biological genetic mechanisms crack organisms mystery key . Transcriptional gene expression crucial step for identification and annotation of transcription factor binding sites , and will no doubt be the key step is to study the transcriptional regulation of the law and then construct the expression and regulation of network . With the rapid development of biotechnology and computer technology , the use of computational methods to identify transcription factor binding sites has become a powerful auxiliary tool of traditional experimental methods . Accurate identification of transcription factor binding sites , provide more accurate data for people to study the biological mechanism to promote the study of biological experiments . Existing algorithms can generally be divided into two categories , based on the consensus sequences and position weight matrix . However , these algorithms are often easy to fall into local optimum , not easy to get the global optimal solution . In this paper, two transcription factor binding sites based on genetic algorithm recognition algorithm . Improved genetic algorithm to identify transcription factor binding sites , the algorithm expect to get the global optimal solution ; another genetic algorithm and the Gibbs sampling algorithm is a combination of transcription factor binding sites recognition algorithm , this algorithm uses location the weight matrix model , suitable for many types of biological data . ( 1) The algorithm improved genetic algorithm to identify transcription factor binding sites to re- define a fitness function , the function that contains the number of sites \scoring value, the algorithm is mainly in the sequence containing multiple transcription factor binding sites . ( 2 ) the genetic algorithm and the Gibbs sampling algorithm combined transcription factor binding sites recognition algorithm The algorithm by Gibbs sampling algorithm to generate position weight matrix , and then by the iteration of the genetic algorithm eventually generate a convergent position weight matrix . The main purpose of this algorithm is to design a recognition algorithm suitable for a variety of types of biological data . Experimental verification and analysis of the proposed method . Compare the experimental results with existing identification methods and the TRANSFAC DBTSS database marking information to verify the correctness and validity of the method .

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