Generic placeholder image

Protein & Peptide Letters

Editor-in-Chief

ISSN (Print): 0929-8665
ISSN (Online): 1875-5305

Predicting the Classification of Transcription Factors by Incorporating their Binding Site Properties into a Novel Mode of Chou's Pseudo Amino Acid Composition

Author(s): Liang-Yun Ren, Yu-Sen Zhang and Ivan Gutman

Volume 19 , Issue 11 , 2012

Page: [1170 - 1176] Pages: 7

DOI: 10.2174/092986612803217088

Price: $65

Abstract

Transcription factors (TF) are proteins that control the first step of gene expression, the transcription of DNA into RNA sequences. The mechanism of transcriptional regulatory can be much better understood if the category of transcription factors is known. We developed a new method for predicting the classification of transcription factors by incorporating their binding site properties into a novel mode of Chou's pseudo amino acid composition. The properties include the length of TFBSs for a TF, a new_PWM value, the proportion of not conservative TFBSs, the proportion of nonucleosome of TFBSs, the proportion of conserved-nucleosome of TFBSs, and the GC content of TFBSs. We construct a vector with these properties to represent a TF. Then the vectors which stand for TFs were classified with SVMs. The high accuracy obtained shows that these properties are of great significance for a TF.

Keywords: Transcription factor, classification, nucleosome, TFBS, SVM


Rights & Permissions Print Export Cite as
© 2022 Bentham Science Publishers | Privacy Policy