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Using DNase digestion data to accurately identify transcription factor binding sites.

Publication ,  Journal Article
Luo, K; Hartemink, AJ
Published in: Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
January 2013

Identifying binding sites of transcription factors (TFs) is a key task in deciphering transcriptional regulation. ChIP-based methods are used to survey the genomic locations of a single TF in each experiment. But methods combining DNase digestion data with TF binding specificity information could potentially be used to survey the locations of many TFs in the same experiment, provided such methods permit reasonable levels of sensitivity and specificity. Here, we present a simple such method that outperforms a leading recent method, centipede, marginally in human but dramatically in yeast (average auROC across 20 TFs increases from 74% to 94%). Our method is based on logistic regression and thus benefits from supervision, but we show that partially and completely unsupervised variants perform nearly as well. Because the number of parameters in our method is at least an order of magnitude smaller than CENTIPEDE, we dub it MILLIPEDE.

Duke Scholars

Published In

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing

EISSN

2335-6936

ISSN

2335-6928

Publication Date

January 2013

Start / End Page

80 / 91

Related Subject Headings

  • Transcription Factors
  • Software
  • Saccharomyces cerevisiae Proteins
  • Models, Biological
  • Logistic Models
  • Humans
  • Deoxyribonucleases
  • Databases, Genetic
  • Computational Biology
  • Chromatin Immunoprecipitation
 

Citation

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Luo, K., & Hartemink, A. J. (2013). Using DNase digestion data to accurately identify transcription factor binding sites. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 80–91.
Luo, Kaixuan, and Alexander J. Hartemink. “Using DNase digestion data to accurately identify transcription factor binding sites.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, January 2013, 80–91.
Luo K, Hartemink AJ. Using DNase digestion data to accurately identify transcription factor binding sites. Pacific Symposium on Biocomputing Pacific Symposium on Biocomputing. 2013 Jan;80–91.
Luo, Kaixuan, and Alexander J. Hartemink. “Using DNase digestion data to accurately identify transcription factor binding sites.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, Jan. 2013, pp. 80–91.
Luo K, Hartemink AJ. Using DNase digestion data to accurately identify transcription factor binding sites. Pacific Symposium on Biocomputing Pacific Symposium on Biocomputing. 2013 Jan;80–91.

Published In

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing

EISSN

2335-6936

ISSN

2335-6928

Publication Date

January 2013

Start / End Page

80 / 91

Related Subject Headings

  • Transcription Factors
  • Software
  • Saccharomyces cerevisiae Proteins
  • Models, Biological
  • Logistic Models
  • Humans
  • Deoxyribonucleases
  • Databases, Genetic
  • Computational Biology
  • Chromatin Immunoprecipitation