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Biomed Res Int. 2015;2015:757530. doi: 10.1155/2015/757530. Epub 2015 Sep 3.

Understanding Transcription Factor Regulation by Integrating Gene Expression and DNase I Hypersensitive Sites.

Author information

1
School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China ; Instrument Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China.
2
School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China.
3
Instrument Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China ; School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China.
4
Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA ; Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN 46202, USA.

Abstract

Transcription factors are proteins that bind to DNA sequences to regulate gene transcription. The transcription factor binding sites are short DNA sequences (5-20 bp long) specifically bound by one or more transcription factors. The identification of transcription factor binding sites and prediction of their function continue to be challenging problems in computational biology. In this study, by integrating the DNase I hypersensitive sites with known position weight matrices in the TRANSFAC database, the transcription factor binding sites in gene regulatory region are identified. Based on the global gene expression patterns in cervical cancer HeLaS3 cell and HelaS3-ifnα4h cell (interferon treatment on HeLaS3 cell for 4 hours), we present a model-based computational approach to predict a set of transcription factors that potentially cause such differential gene expression. Significantly, 6 out 10 predicted functional factors, including IRF, IRF-2, IRF-9, IRF-1 and IRF-3, ICSBP, belong to interferon regulatory factor family and upregulate the gene expression levels responding to the interferon treatment. Another factor, ISGF-3, is also a transcriptional activator induced by interferon alpha. Using the different transcription factor binding sites selected criteria, the prediction result of our model is consistent. Our model demonstrated the potential to computationally identify the functional transcription factors in gene regulation.

PMID:
26425553
PMCID:
PMC4573618
DOI:
10.1155/2015/757530
[Indexed for MEDLINE]
Free PMC Article

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