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  The BaMM web server for de-novo motif discovery and regulatory sequence analysis.

Kiesel, A., Roth, C., Ge, W., Weß, M., Meier, M., & Söding, J. (2018). The BaMM web server for de-novo motif discovery and regulatory sequence analysis. Nucleic Acids Research, 46(W1), W215-W220. doi:10.1093/nar/gky431.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0001-6956-9 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-7612-4
Genre: Journal Article

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Kiesel, A.1, Author              
Roth, C.1, Author              
Ge, W.1, Author              
Weß, M.1, Author              
Meier, M.1, Author              
Söding, J.1, Author              
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1Research Group of Computational Biology, MPI for Biophysical Chemistry, Max Planck Society, ou_1933286              

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 Abstract: The BaMM web server offers four tools: (i) de-novo discovery of enriched motifs in a set of nucleotide sequences, (ii) scanning a set of nucleotide sequences with motifs to find motif occurrences, (iii) searching with an input motif for similar motifs in our BaMM database with motifs for >1000 transcription factors, trained from the GTRD ChIP-seq database and (iv) browsing and keyword searching the motif database. In contrast to most other servers, we represent sequence motifs not by position weight matrices (PWMs) but by Bayesian Markov Models (BaMMs) of order 4, which we showed previously to perform substantially better in ROC analyses than PWMs or first order models. To address the inadequacy of P- and E-values as measures of motif quality, we introduce the AvRec score, the average recall over the TP-to-FP ratio between 1 and 100. The BaMM server is freely accessible without registration at https://bammmotif.mpibpc.mpg.de.

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Language(s): eng - English
 Dates: 2018-05-282018-07-02
 Publication Status: Published in print
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 Rev. Method: Peer
 Identifiers: DOI: 10.1093/nar/gky431
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Title: Nucleic Acids Research
Source Genre: Journal
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Pages: - Volume / Issue: 46 (W1) Sequence Number: - Start / End Page: W215 - W220 Identifier: -