Construction of gene regulatory networks using biclustering and Bayesian networks.

ABSTRACT:

Background

Understanding gene interactions in complex living systems can be seen as the ultimate goal of the systems biology revolution. Hence, to elucidate disease ontology fully and to reduce the cost of drug development, gene regulatory networks (GRNs) have to be constructed. During the last decade, many GRN inference algorithms based on genome-wide data have been developed to unravel the complexity of gene regulation. Time series transcriptomic data measured by genome-wide DNA microarrays are traditionally used for GRN modelling. One of the major problems with microarrays is that a dataset consists of relatively few time points with respect to the large number of genes. Dimensionality is one of the interesting problems in GRN modelling.

Results

In this paper, we develop

SUBMITTER: Alakwaa FM 

PROVIDER: S-EPMC3231811 | biostudies-literature | 2011 Oct

REPOSITORIES: biostudies-literature