Life Sciences Commons^™

An Ensemble Learning Approach To Reverse-Engineering Transcriptional Regulatory Networks From Time-Series Gene Expression Data, Jianhua Ruan, Youping Deng, Edward J. Perkins, Weixiong Zhang

Faculty Publications

Background

One of the most challenging tasks in the post-genomic era is to reconstruct the transcriptional regulatory networks. The goal is to reveal, for each gene that responds to a certain biological event, which transcription factors affect its expression, and how a set of transcription factors coordinate to accomplish temporal and spatial specific regulations.

Results

Here we propose a supervised machine learning approach to address these questions. We focus our study on the gene transcriptional regulation of the cell cycle in the budding yeast, thanks to the large amount of data available and relatively well-understood biology, although the main ideas …