An integrated approach to reconstructing genome-scale transcriptional regulatory networks.

ABSTRACT: Transcriptional regulatory networks (TRNs) program cells to dynamically alter their gene expression in response to changing internal or environmental conditions. In this study, we develop a novel workflow for generating large-scale TRN models that integrates comparative genomics data, global gene expression analyses, and intrinsic properties of transcription factors (TFs). An assessment of this workflow using benchmark datasets for the well-studied γ-proteobacterium Escherichia coli showed that it outperforms expression-based inference approaches, having a significantly larger area under the precision-recall curve. Further analysis indicated that this integrated workflow captures different aspects of the E. coli TRN than expression-based approaches, potentially making them highly complemen

SUBMITTER: Imam S 

PROVIDER: S-EPMC4344238 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature