Prioritizing predicted cis-regulatory elements for co-expressed gene sets based on Lasso regression models

Annu Int Conf IEEE Eng Med Biol Soc. 2011:2011:6853-6. doi: 10.1109/IEMBS.2011.6091690.

Abstract

Computational prediction of cis-regulatory elements for a set of co-expressed genes based on sequence analysis provides an overwhelming volume of potential transcription factor binding sites. It presents a challenge to prioritize transcription factors for regulatory functional studies. A novel approach based on the use of Lasso regression models is proposed to address this problem. We examine the ability of the Lasso model using time-course microarray data obtained from a comprehensive study of gene expression profiles in skin and mucosal wounds in mouse over all stages of wound healing.

MeSH terms

  • Animals
  • Binding Sites
  • Cluster Analysis
  • Computational Biology / methods*
  • Gene Expression Profiling*
  • Gene Expression Regulation*
  • Humans
  • Mice
  • Models, Genetic
  • Models, Statistical
  • Mucous Membrane / metabolism
  • Oligonucleotide Array Sequence Analysis / methods*
  • Promoter Regions, Genetic
  • Regression Analysis
  • Skin / metabolism
  • Transcription Factors / chemistry*
  • Transcription Factors / metabolism

Substances

  • Transcription Factors