Dissertation > Biological Sciences > Biochemistry > Protein

Comparison of the structural model and its application in the prediction of transcription factor binding sites in the protein-DNA

Author ChenLing
Tutor WangFei
School Fudan University
Course Computer Software and Theory
Keywords Bioinformatics Data Mining Prediction of transcription factor binding sites Structural model of the protein-DNA
Type Master's thesis
Year 2010
Downloads 47
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Prediction of transcription factor binding sites is one of the hot issues of bioinformatics , its aim is to discover a crucial impact on gene upstream regulatory region of the gene expression regulatory elements . Transcription factor binding sites as a transcriptional regulatory elements , with regulatory functions in the genomic DNA sequence fragments , identify and predict it will help to explain the regulation of gene expression law . With the recognition and prediction of transcription factor binding sites in the sequence alignment the depth algorithm research and the development of computer technology , computer platform is increasingly becoming - important means of supporting research . The accurate and rapid prediction algorithm helps biologists understand the target gene of the transcription factor binding sites for further study of the regulation of gene transcription , and provide valuable reference information for biological experiments . At present , in the field has developed many transcription factor binding site prediction algorithms and software the famous MEME, AlignACE well BioProspector . This paper proposed a structural model based on the protein-DNA transcription factor binding sites prediction algorithm , the algorithm overcomes two inadequacies of the existing classic sequence prediction algorithm , namely : ① recognition accuracy is limited by priori knowledge ; ② lack of theoretical models of biological significance . Algorithm as the basis of three - dimensional spatial coordinates of the molecule of the protein-DNA complexes in the PDB database file , to create the corresponding chemical thermokinetic position weight matrix structure prediction method of identifying the target transcription factor binding sites , and outputs the corresponding The binding site sequence collection. Test and analysis of transcription factor binding sites database Jaspar experimental results and compared with the existing classic structure model prediction algorithms , it shows that the proposed algorithm is effective and feasible . Structure model prediction algorithms proposed by position weight matrix description of transcription factors in a variety of structural features recognition specificity of binding sites for transcription factor - nucleic acid interaction studies provide important clues structural analysis and quantitative tools . This algorithm as a prediction of transcription factor binding sites in computer-aided tools for biologists who want to molecular structural features of protein-DNA interaction studies have important reference .

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