To improve the recovery of gene-gene and marker-gene (eQTL) interaction networks from microarray and genetic data, we propose a new procedure for learning Bayesian networks. This a...
Background: With the abundant information produced by microarray technology, various approaches have been proposed to infer transcriptional regulatory networks. However, few appro...
Grace S. Shieh, Chung-Ming Chen, Ching-Yun Yu, Jui...
Background: In many approaches to the inference and modeling of regulatory interactions using microarray data, the expression of the gene coding for the transcription factor is co...
Bayesian network structure learning is a useful tool for elucidation of regulatory structures of biomolecular pathways. The approach however is limited by its acyclicity constraint...
S. Itani, Karen Sachs, Garry P. Nolan, M. A. Dahle...
Many different approaches have been developed to model and simulate gene regulatory networks. We proposed the following categories for gene regulatory network models: network part...