title: Eukaryotic promoter recognition by binding sites for transcription factors.
abstract: A method for identification of eukaryotic promoters by localization of binding sites for transcription factors has been suggested. The binding sites for a range of transcription factors have been found to be distributed unevenly. Based on these distributions, we have constructed a weight matrix of binding site localization. On the basis of the weight matrix we have, in turn, designed an algorithm for promoter recognition. To increase the accuracy of the method, we have developed a routine that breaks any promoter sample into subsamples. The method to be reported on allows much better recognition accuracy than does the approach based on detection of the TATA box. In particular, the overprediction error is three times lower following our method. The program FunSiteP recognizes promoters from newly uncovered sequences and tentatively identifies the functional class the promoters must belong to. We have introduced the notion of 'regulatory potential' for the degree to which any region of the sequences is similar to the real eukaryotic promoter. By making use of the potential, we have revealed putative transcription start sites and extended regions of transcription regulation.
authors.affiliation: Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk, Russia.
authors.forename: Y V
authors.initials: YV
authors.lastname: Kondrakhin
authors.forename: A E
authors.initials: AE
authors.lastname: Kel
authors.forename: N A
authors.initials: NA
authors.lastname: Kolchanov
authors.forename: A G
authors.initials: AG
authors.lastname: Romashchenko
authors.forename: L
authors.initials: L
authors.lastname: Milanesi
mesh_terms: D000465:Algorithms; D000818:Animals; D001483:Base Sequence; D001665:Binding Sites / Q000235:genetics; D004247:DNA / Q000235:genetics / Q000378:metabolism; D016208:Databases, Factual; D005057:Eukaryotic Cells; D006801:Humans; D008969:Molecular Sequence Data; D011401:Promoter Regions, Genetic; D012984:Software; D016385:TATA Box / Q000235:genetics; D014157:Transcription Factors / Q000378:metabolism*
chemical_list: D014157:Transcription Factors; D004247:DNA