Abstract. Computational inference of transcriptional regulatory networks remains a challenging problem, in part due to the lack of strong network models. In this paper we present e...
Inferring transcriptional regulatory networks from geneexpression data remains a challenging problem, in part because of the noisy nature of the data and the lack of strong networ...
Background: Gene regulatory networks play essential roles in living organisms to control growth, keep internal metabolism running and respond to external environmental changes. Un...
Background: Microarray data discretization is a basic preprocess for many algorithms of gene regulatory network inference. Some common discretization methods in informatics are us...
Yong Li, Lili Liu, Xi Bai, Hua Cai, Wei Ji, Dianji...
Background: Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mecha...