By the company they keep: interaction networks define the binding ability of transcription factors

Nucleic Acids Res. 2015 Oct 30;43(19):e125. doi: 10.1093/nar/gkv607. Epub 2015 Jun 18.

Abstract

Access to genome-wide data provides the opportunity to address questions concerning the ability of transcription factors (TFs) to assemble in distinct macromolecular complexes. Here, we introduce the PAnDA (Protein And DNA Associations) approach to characterize DNA associations with human TFs using expression profiles, protein-protein interactions and recognition motifs. Our method predicts TF binding events with >0.80 accuracy revealing cell-specific regulatory patterns that can be exploited for future investigations. Even when the precise DNA-binding motifs of a specific TF are not available, the information derived from protein-protein networks is sufficient to perform high-confidence predictions (area under the ROC curve of 0.89). PAnDA is freely available at http://service.tartaglialab.com/new_submission/panda.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Amino Acid Motifs
  • Binding Sites
  • DNA / metabolism
  • DNA-Binding Proteins / chemistry
  • DNA-Binding Proteins / metabolism
  • Gene Expression Profiling
  • Humans
  • Protein Binding
  • Protein Interaction Maps*
  • Sequence Analysis, DNA
  • Transcription Factors / chemistry
  • Transcription Factors / metabolism*

Substances

  • DNA-Binding Proteins
  • Transcription Factors
  • DNA