Genome wide predictions of miRNA regulation by transcription factors.

Journal: Bioinformatics (Oxford, England)
Published Date:

Abstract

MOTIVATION: Reconstructing regulatory networks from expression and interaction data is a major goal of systems biology. While much work has focused on trying to experimentally and computationally determine the set of transcription-factors (TFs) and microRNAs (miRNAs) that regulate genes in these networks, relatively little work has focused on inferring the regulation of miRNAs by TFs. Such regulation can play an important role in several biological processes including development and disease. The main challenge for predicting such interactions is the very small positive training set currently available. Another challenge is the fact that a large fraction of miRNAs are encoded within genes making it hard to determine the specific way in which they are regulated.

Authors

  • Matthew Ruffalo
    Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA 15213.
  • Ziv Bar-Joseph
    Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA 15213.