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

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Intelligent Computing Theories and Methodologies (ICIC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9226))

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Abstract

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.

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Author information

Authors and Affiliations

  1. School of Electronics and Information Science, Jiangsu University of Science and Technology, Zhenjiang, 212003, Jiangsu, China

    Yinglei Song

  2. Department of Mathematics and Computer Science, University of Maryland Eastern Shore, Princess Anne, MD, 21853, USA

    Albert Y. Chi

  3. Department of Computer Science and Information Technology, Clayton State University, Morrow, GA, 30260, USA

    Junfeng Qu

Authors
  1. Yinglei Song
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  2. Albert Y. Chi
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  3. Junfeng Qu
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Corresponding author

Correspondence to Yinglei Song .

Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. University of Ulsan, Ulsan, Korea (Republic of)

    Kang-Hyun Jo

  3. Liverpool John Moores University, Liverpool, United Kingdom

    Abir Hussain

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Song, Y., Chi, A.Y., Qu, J. (2015). A Graph Theoretic Approach for the Feature Extraction of Transcription Factor Binding Sites. In: Huang, DS., Jo, KH., Hussain, A. (eds) Intelligent Computing Theories and Methodologies. ICIC 2015. Lecture Notes in Computer Science(), vol 9226. Springer, Cham. https://doi.org/10.1007/978-3-319-22186-1_44

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  • DOI: https://doi.org/10.1007/978-3-319-22186-1_44

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22185-4

  • Online ISBN: 978-3-319-22186-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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