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  On the power of profiles for transcription factor binding site detection

Rahmann, S., Müller, T., & Vingron, M. (2003). On the power of profiles for transcription factor binding site detection. Statistical Applications in Genetics and Molecular Biology, 2(1), article 7-article 7.

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 Creators:
Rahmann, Sven1, Author              
Müller, Tobias, Author
Vingron, Martin2, Author              
Affiliations:
1Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433547              
2Gene 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: Transcription factor binding site (TFBS); Profile; Position specific score matrix (PSSM); Position-weight matrix (PWM); Log-odds score; Exact test; Significance; Power; TRANSFAC
 Abstract: Transcription factor binding site (TFBS) detection plays an important role in computational biology, with applications in gene finding and gene regulation. The sites are often modeled by gapless profiles, also known as position-weight matrices. Past research has focused on the significance of profile scores (the ability to avoid false positives), but this alone is not enough: The profile must also possess the power to detect the true positive signals. Several completed genomes are now available, and the search for TFBSs is moving to a large scale; so discriminating signal from noise becomes even more challenging. Since TFBS profiles are usually estimated from only a few experimentally confirmed instances, careful regularization is an important issue. We present a novel method that is well suited for this situation. We further develop measures that help in judging profile quality, based on both sensitivity and selectivity of a profile. It is shown that these quality measures can be efficiently computed, and we propose statistically well-founded methods to choose score thresholds. Our findings are applied to the TRANSFAC database of transcription factor binding sites. The results are disturbing: If we insist on a significance level of 5% in sequences of length 500, only 19% of the profiles detect a true signal instance with 95% success probability under varying background sequence compositions.

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Language(s): eng - English
 Dates: 2003
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: eDoc: 175931
 Degree: -

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Title: Statistical Applications in Genetics and Molecular Biology
Source Genre: Journal
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Pages: - Volume / Issue: 2 (1) Sequence Number: - Start / End Page: article 7 - article 7 Identifier: ISSN: 1544-6115