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  KIRMES: Kernel-based Identification of Regulatory Modules in Euchromatic Sequences

Schultheiss, S., Busch, W., Lohmann, J., Kohlbacher, O., & Rätsch, G. (2008). KIRMES: Kernel-based Identification of Regulatory Modules in Euchromatic Sequences. In A. Beyer, & M. Schroeder (Eds.), German Conference on Bioinformatics: GCB 2008 (pp. 158-167). Bonn, Germany: Gesellschaft für Informatik.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0010-86F7-0 Version Permalink: https://hdl.handle.net/21.11116/0000-0010-86F8-F
Genre: Conference Paper

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https://dl.gi.de/items/b3dbb879-0e0f-4561-bf59-202d98b8d3d5 (Publisher version)
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 Creators:
Schultheiss, SJ1, Author                 
Busch, W1, Author                 
Lohmann, JU1, Author                 
Kohlbacher, O, Author                 
Rätsch, G, Author                 
Affiliations:
1Department Molecular Biology, Max Planck Institute for Developmental Biology, Max Planck Society, ou_3375790              

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 Abstract: Motivation: Understanding transcriptional regulation is one of the main challenges in computational biology. An important problem is the identification of transcription factor binding sites in promoter regions of potential transcription factor target genes. It is typically approached by position weight matrix-based motif identification algorithms using Gibbs sampling or heuristics for extending seed oligos. Such algorithms succeed in identifying single, relatively well conserved binding sites, but tend to fail when it comes to the identification of combinations of several degenerate binding sites as those often found in cis-regulatory modules.
Results: We propose a new algorithm that combines the benefits of existing motif finding with the ones of Support Vector Machines (SVMs) to find degenerate motifs in order to improve the modeling of regulatory modules. In experiments on microarray data from Arabidopsis thaliana we were able to show that the newly developed strat- egy significantly improves the recognition of transcription factor targets. Availability: The PYTHON source code (open source–licensed under GPL), the data for the experiments and a web-service are available at http://www.fml.mpg. de/raetsch/projects/kirmes.

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 Dates: 2008-09
 Publication Status: Issued
 Pages: -
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Title: German Conference on Bioinformatics 2008 (GCB 2008)
Place of Event: Dresden, Germany
Start-/End Date: 2008-09-09 - 2008-09-12

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Title: German Conference on Bioinformatics: GCB 2008
Source Genre: Proceedings
 Creator(s):
Beyer, A, Editor
Schroeder, M, Editor
Affiliations:
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Publ. Info: Bonn, Germany : Gesellschaft für Informatik
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 158 - 167 Identifier: ISBN: 978-3-88579-226-0

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Title: Gesellschaft für Informatik: GI-Edition / Proceedings
Source Genre: Series
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Pages: - Volume / Issue: 115 Sequence Number: - Start / End Page: - Identifier: -