Connectivity in the Yeast Cell Cycle Transcription Network: Inferences from Neural Networks

Abstract

A current challenge is to develop computational approaches to infer gene network regulatory relationships based on multiple types of large-scale functional genomic data. We find that single-layer feed-forward artificial neural network (ANN) models can effectively discover gene network structure by integrating global in vivo protein:DNA interaction data… (More)
DOI: 10.1371/journal.pcbi.0020169

Topics

12 Figures and Tables

Cite this paper

@article{Hart2006ConnectivityIT, title={Connectivity in the Yeast Cell Cycle Transcription Network: Inferences from Neural Networks}, author={Christopher E. Hart and Eric Mjolsness and Barbara J. Wold}, journal={PLoS Computational Biology}, year={2006}, volume={2}, pages={3273 - 3297} }