A Graph Theoretic Approach for the Feature Extraction of Transcription Factor Binding Sites

Autor:	Albert Y. Chi, Yinglei Song, Junfeng Qu
Rok vydání:	2015
Předmět:	Regulation of gene expression business.industry Computer science Feature extraction Promoter Statistical model Pattern recognition Computational biology DNA binding site Artificial intelligence Binding site business Transcription factor Gene
Zdroj:	Intelligent Computing Theories and Methodologies ISBN: 9783319221854 ICIC (2)
DOI:	10.1007/978-3-319-22186-1_44
Popis:	Recent work in molecular biology has revealed that transcription factors are biologically important in gene regulation. A transcription factor regulates the expression level of a gene by binding to the promoter region of the gene. A model that can accurately describe the binding sites of a transcription factor is thus crucial for understanding the biological mechanisms of gene regulation. In this paper, we develop a new feature extraction algorithm that can accurately obtain features of the binding sites of a transcription factor. The obtained features describe the pair-wise correlations of different positions in a binding site. Based on these features, pair-wise correlations can be integrated into a statistical model that describes the binding sites of a transcriptional factor. Our testing results show that, this approach is able to identify important features for transcription factor binding sites and statistical models based on these features can achieve prediction accuracy that is higher than or comparable with that of other feature extraction methods.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::03fae8eb28057f8bc7250efbb2c97c08 https://doi.org/10.1007/978-3-319-22186-1_44 Zobrazit plný text záznamu