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  DNA Motif Match Statistics Without Poisson Approximation

Kopp, W., & Vingron, M. (2019). DNA Motif Match Statistics Without Poisson Approximation. Journal of Computational Biology, 26(8), 846-865. doi:10.1089/cmb.2018.0144.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0005-9201-4 Version Permalink: http://hdl.handle.net/21.11116/0000-0005-9202-3
Genre: Journal Article

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Kopp_2019.pdf (Publisher version), 373KB
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© 2019 Mary Ann Liebert, Inc., publishers
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 Creators:
Kopp, W.1, Author
Vingron, Martin1, Author              
Affiliations:
1Gene regulation (Martin Vingron), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479639              

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Free keywords: Markov model dynamic programming motif enrichment
 Abstract: Transcription factors (TFs) play a crucial role in gene regulation by binding to specific regulatory sequences. The sequence motifs recognized by a TF can be described in terms of position frequency matrices. Searching for motif matches with a given position frequency matrix is achieved by employing a predefined score cutoff and subsequently counting the number of matches above this cutoff. In this article, we approximate the distribution of the number of motif matches based on a novel dynamic programming approach, which accounts for higher order sequence background (e.g., as is characteristic for CpG islands) and overlapping motif matches on both DNA strands. A comparison with our previously published compound Poisson approximation and a binomial approximation demonstrates that in particular for relaxed score thresholds, the dynamic programming approach yields more accurate results.

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Language(s): eng - English
 Dates: 2019-04-172019-08-12
 Publication Status: Published in print
 Pages: -
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 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1089/cmb.2018.0144
ISSN: 1557-8666 (Electronic)1066-5277 (Print)
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Title: Journal of Computational Biology
Source Genre: Journal
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Publ. Info: New York, NY : Mary Ann Liebert
Pages: - Volume / Issue: 26 (8) Sequence Number: - Start / End Page: 846 - 865 Identifier: ISSN: 1066-5277
CoNE: https://pure.mpg.de/cone/journals/resource/954925275499