Integrating Large-Scale Functional Genomic Data to Dissect the Complexity of Yeast Regulatory Networks

ABSTRACT: A major goal of biology is the construction of networks that predict complex system behavior. We combine multiple types of molecular data, including genotypic, expression, transcription factor binding site (TFBS), and protein-protein interaction (PPI) data previously generated from a number of yeast experiments in order to reconstruct causal gene networks. Networks based on different types of data are compared using metrics devised to assess the predictive power of a network. A network reconstructed by integrating genotypic, TFBS and PPI data is shown to be the most predictive. This network is used to predict causal regulators responsible for hot spots of gene expression activity in a segregating yeast population. The network is also shown to elucidate the mechanisms by which causal re

ORGANISM(S): Saccharomyces cerevisiae

SUBMITTER: Erin Smith 

PROVIDER: E-GEOD-11111 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress