title: A novel computational method to predict transcription factor DNA binding preference.
abstract: Transcription factor binds to sequence specific sites in regulatory region to control nearby gene's expression. It is termed as the major regulator of transcription. However, identifying DNA binding preference of transcription factors systematically is still a challenge. By using the nearest neighbor algorithm, a novel computational approach was developed to predict transcription factor DNA binding preference based on the gene ontology [M. Ashburner, C.A. Ball, J.A. Blake, D. Botstein, H. Butler, J.M. Cherry, A.P. Davis, K. Dolinski, S.S. Dwight, J.T. Eppig, M.A. Harris, D.P. Hill, L. Issel-Tarver, A. Kasarskis, S. Lewis, J.C. Matese, J.E. Richardson, M. Ringwald, G.M. Rubin, G. Sherlock, Gene Ontology: tool for the unification of biology, Nat. Genet. 25 (2000) 25-29.] and 0/1 encoding system of nucleotide. The overall success rate of Jackknife cross-validation test for our predictor reaches 76.6%, which indicates the DNA binding preference is closely correlated with its biological functions and computational method developed in this contribution could be a powerful tool to investigate transcription factor DNA binding preference, especially for those novel transcription factors with little prior knowledge on its DNA binding preference.
authors.affiliation: Bioinformatics Center, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China.
authors.forename: Ziliang
authors.initials: Z
authors.lastname: Qian
authors.forename: Yu-Dong
authors.initials: YD
authors.lastname: Cai
authors.forename: Yixue
authors.initials: Y
authors.lastname: Li
mesh_terms: D000465:Algorithms; D019295:Computational Biology; D004247:DNA / Q000378:metabolism*; D008957:Models, Genetic; D011485:Protein Binding / Q000235:genetics; D014157:Transcription Factors / Q000378:metabolism*
chemical_list: D014157:Transcription Factors; D004247:DNA