Background: The evolution of high throughput technologies that measure gene expression levels has created a data base for inferring GRNs (a process also known as reverse engineeri...
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...
Models of biological systems and phenomena are of high scientific interest and practical relevance, but not always easy to obtain due to their inherent complexity. To gain the re...
Markus Durzinsky, Annegret Wagler, Robert Weismant...
In this paper we present an evolutionary approach for inferring the structure and dynamics in gene circuits from observed expression kinetics. For representing the regulatory inte...
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...