Background: Identifying candidate genes in genetic networks is important for understanding regulation and biological function. Large gene expression datasets contain relevant info...
Anup Parikh, Eryong Huang, Christopher Dinh, Blaz ...
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...
Exploring gene regulatory network is a key topic in molecular biology. In this paper, we present a new dynamic Bayesian network (DBN) framework embedded with structural expectatio...
Background: The regulation of gene expression is achieved through gene regulatory networks (GRNs) in which collections of genes interact with one another and other substances in a...
Peng Li, Chaoyang Zhang, Edward J. Perkins, Ping G...
Background: Inferring gene regulatory networks from data requires the development of algorithms devoted to structure extraction. When only static data are available, gene interact...