Transcription factor binding site identification using the self-organizing map

Shaun Mahony, David Hendrix, Aaron Golden, Terry J. Smith, Daniel S. Rokhsar

Research output: Contribution to journalArticle

60 Citations (Scopus)

Abstract

Motivation: The automatic identification of over-represented motifs present in a collection of sequences continues to be a challenging problem in computational biology. In this paper, we propose a self-organizing map of position weight matrices as an alternative method for motif discovery. The advantage of this approach is that it can be used to simultaneously characterize every feature present in the dataset, thus lessening the chance that weaker signals will be missed. Features identified are ranked in terms of over-representation relative to a background model. Results: We present an implementation of this approach, named SOMBRERO (self-organizing map for biological regulatory element recognition and ordering), which is capable of discovering multiple distinct motifs present in a single dataset. Demonstrated here are the advantages of our approach on various datasets and SOMBRERO's improved performance over two popular motif-finding programs, MEME and AlignACE.

Original languageEnglish (US)
Pages (from-to)1807-1814
Number of pages8
JournalBioinformatics
Volume21
Issue number9
DOIs
StatePublished - May 1 2005
Externally publishedYes

Fingerprint

Transcription factors
Self organizing maps
Self-organizing Map
Binding sites
Transcription Factor
Transcription Factors
Binding Sites
Motif Discovery
Computational Biology
Position-Specific Scoring Matrices
Continue
Distinct
Alternatives
Datasets
Model
Background

ASJC Scopus subject areas

  • Clinical Biochemistry
  • Computer Science Applications
  • Computational Theory and Mathematics

Cite this

Mahony, S., Hendrix, D., Golden, A., Smith, T. J., & Rokhsar, D. S. (2005). Transcription factor binding site identification using the self-organizing map. Bioinformatics, 21(9), 1807-1814. https://doi.org/10.1093/bioinformatics/bti256

Transcription factor binding site identification using the self-organizing map. / Mahony, Shaun; Hendrix, David; Golden, Aaron; Smith, Terry J.; Rokhsar, Daniel S.

In: Bioinformatics, Vol. 21, No. 9, 01.05.2005, p. 1807-1814.

Research output: Contribution to journalArticle

Mahony, S, Hendrix, D, Golden, A, Smith, TJ & Rokhsar, DS 2005, 'Transcription factor binding site identification using the self-organizing map', Bioinformatics, vol. 21, no. 9, pp. 1807-1814. https://doi.org/10.1093/bioinformatics/bti256
Mahony, Shaun ; Hendrix, David ; Golden, Aaron ; Smith, Terry J. ; Rokhsar, Daniel S. / Transcription factor binding site identification using the self-organizing map. In: Bioinformatics. 2005 ; Vol. 21, No. 9. pp. 1807-1814.
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