Reconstructing transcriptional regulatory networks through genomics data

  • Sun N
  • Zhao H
  • 1


    Mendeley users who have this article in their library.
  • N/A


    Citations of this article.


One central problem in biology is to understand how gene expression is regulated under different conditions. Microarray gene expression data and other high throughput data have made it possible to dissect transcriptional regulatory networks at the genomics level. Owing to the very large number of genes that need to be studied, the relatively small number of data sets available, the noise in the data and the different natures of the distinct data types, network inference presents great challenges. In this article, we review statistical and computational methods that have been developed in the last decade in response to genomics data for inferring transcriptional regulatory networks.

Author-supplied keywords

  • Computational Biology
  • Data Interpretation: Statistical
  • Gene Expression Profiling
  • Gene Regulatory Networks
  • Genomics
  • Humans
  • Normal Distribution

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document


  • N Sun

  • H Zhao

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free