Combining experts in order to identify binding sites in yeast and mouse genomic data

M. Robinson, C. Gonzalez Castellano, F. Rezwan, R.G. Adams, N. Davey, A.G. Rust, Yi. Sun

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
26 Downloads (Pure)

Abstract

The identification of cis-regulatory binding sites in DNA is a difficult problem in computational biology. To obtain a full understanding of the complex machinery embodied in genetic regulatory networks it is necessary to know both the identity of the regulatory transcription factors together with the location of their binding sites in the genome. We show that using an SVM together with data sampling, to integrate the results of individual algorithms specialised for the prediction of binding site locations, can produce significant improvements upon the original algorithms. These results make more tractable the expensive experimental procedure of actually verifying the predictions.
Original languageEnglish
Pages (from-to)856-861
JournalNeural Networks
Volume21
Issue number6
DOIs
Publication statusPublished - 2008

Keywords

  • Transcription Factor Binding Sites
  • Support Vector Machine

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