title: BSS-HMM3s: an improved HMM method for identifying transcription factor binding sites.
abstract: Today, an important problem in molecular biology is the study of gene expression mechanism. The first step in determining differential gene expression is the binding of sequence specific transcription factors to regulatory regions of the genes. An important aspect to understand how a given transcription factor functions is to know the entire gamut of binding sites and potential target genes that the factor may regulate. In this paper, we presented an improved prediction method based on hidden Markov model (HMM) called BSS-HMM(3)s (binding site search based on third-order HMMs) for transcription factor binding sites. The results show that the predicted sensitivity and specificity of BSS-HMM(3)s increased 11.95 and 12.97%, respectively, compared with Match.
authors.affiliation: College of Sciences, Shanghai University, Department of Mathematics, 99 Shangda Road, Shanghai 200444, People's Republic of China.
authors.forename: Dong
authors.initials: D
authors.lastname: Xu
authors.forename: Hai Jun
authors.initials: HJ
authors.lastname: Liu
authors.forename: Yi Fei
authors.initials: YF
authors.lastname: Wang
mesh_terms: D000818:Animals; D001483:Base Sequence; D001665:Binding Sites / Q000235:genetics; D004247:DNA / Q000235:genetics / Q000378:metabolism; D030541:Databases, Genetic; D015870:Gene Expression; D006801:Humans; D008390:Markov Chains; D008957:Models, Genetic; D012985:Software Design; D014157:Transcription Factors / Q000378:metabolism*
chemical_list: D014157:Transcription Factors; D004247:DNA