Many statistical methods have been proposed to estimate causal models in classical situations with fewer variables than observations. However, modern datasets including gene expres...
- Gene regulatory networks allow us to study and understand genes’ roles in biological processes. Among others, regulatory networks help to identify pathway initiator genes and t...
Bayesian networks are commonly used in cognitive student modeling and assessment. They typically represent the item-concepts relationships, where items are observable responses to ...
Building genetic regulatory networks from time series data of gene expression patterns is an important topic in bioinformatics. Probabilistic Boolean networks (PBNs) have been deve...
Abstract. The generation of network topologies with specific, userspecified statistical properties is the aim of this paper. This is achieved through the use of an artifical Gene R...