Improved detection of DNA motifs using a self-organized clustering of familial binding profiles
Open Access
- 1 June 2005
- journal article
- research article
- Published by Oxford University Press (OUP) in Bioinformatics
- Vol. 21 (Suppl 1) , i283-i291
Abstract
Motivation: One of the limiting factors in deciphering transcriptional regulatory networks is the effectiveness of motif-finding software. An emerging avenue for improving motif-finding accuracy aims to incorporate generalized binding constraints of related transcription factors (TFs), named familial binding profiles (FBPs), as priors in motif identification methods. A motif-finder can thus be ‘biased’ towards finding motifs from a particular TF family. However, current motif-finders allow only a single FBP to be used as a prior in a given motif-finding run. In addition, current FBP construction methods are based on manual clustering of position specific scoring matrices (PSSMs) according to the known structural properties of the TF proteins. Manual clustering assumes that the binding preferences of structurally similar TFs will also be similar. This assumption is not true, at least not for some TF families. Automatic PSSM clustering methods are thus required for augmenting the usefulness of FBPs. Results: A novel method is developed for automatic clustering of PSSM models. The resulting FBPs are incorporated into the SOMBRERO motif-finder, significantly improving its performance when finding motifs related to those that have been incorporated. SOMBRERO is thus the only existing de novo motif-finder that can incorporate knowledge of all known PSSMs in a given motif-finding run. Availability: The methods outlined will be incorporated into the next release of SOMBRERO, which is available from http://bioinf.nuigalway.ie/sombrero Contact:shaun.mahony@nuigalway.ie.Keywords
This publication has 28 references indexed in Scilit:
- MotifPrototyper: A Bayesian profile model for motif familiesProceedings of the National Academy of Sciences, 2004
- Constrained Binding Site Diversity within Families of Transcription Factors Enhances Pattern Discovery BioinformaticsJournal of Molecular Biology, 2004
- JASPAR: an open-access database for eukaryotic transcription factor binding profilesNucleic Acids Research, 2004
- Combining phylogenetic data with co-regulated genes to identify regulatory motifsBioinformatics, 2003
- How to make large self-organizing maps for nonvectorial dataNeural Networks, 2002
- Identifying target sites for cooperatively binding factorsBioinformatics, 2001
- Building a dictionary for genomes: Identification of presumptive regulatory sites by statistical analysisProceedings of the National Academy of Sciences, 2000
- Combinatorial pattern discovery in biological sequences: The TEIRESIAS algorithm.Bioinformatics, 1998
- Searching databases of conserved sequence regions by aligning protein multiple-alignments [published erratum appears in Nucleic Acids Res 1996 Nov 1;24(21):4372]Nucleic Acids Research, 1996
- Identification of common molecular subsequencesJournal of Molecular Biology, 1981