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Enhancing Motif Refinement by Incorporating Comparative Genomics Data

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Book cover Bioinformatics Research and Applications (ISBRA 2007)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 4463))

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Abstract

Transcription factor binding sites (TFBS) are often located in the upstream regions of genes and transcription factors (TFs) cause transcription regulation by binding at these locations. Predicting these binding sites is a difficult problem, and traditional methods have a high degree of false positives in their predictions. Comparative genomics data can help to improve motif predictions. In this paper, a new strategy is presented, which refines motif by taking the comparative genomics data into account. Tested with the help of both simulation data and biological data, we show that our method makes improved predictions. We also propose a new metric to score a motif profile. This score is biologically motivated and helps the algorithm in its predictions.

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Authors and Affiliations

  1. Bioinformatics Research Group (BioRG), School of Computing and Information Sciences, Florida International University, Miami, Florida, 33199, USA

    Erliang Zeng & Giri Narasimhan

Authors
  1. Erliang Zeng
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  2. Giri Narasimhan
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Ion Măndoiu Alexander Zelikovsky

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© 2007 Springer-Verlag Berlin Heidelberg

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Zeng, E., Narasimhan, G. (2007). Enhancing Motif Refinement by Incorporating Comparative Genomics Data. In: Măndoiu, I., Zelikovsky, A. (eds) Bioinformatics Research and Applications. ISBRA 2007. Lecture Notes in Computer Science(), vol 4463. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72031-7_30

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  • DOI: https://doi.org/10.1007/978-3-540-72031-7_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72030-0

  • Online ISBN: 978-3-540-72031-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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