Abstract- In this paper we address the problem of finding valid solutions for the problem of inferring gene regulatory networks. Different approaches to directly infer the depende...
Christian Spieth, Felix Streichert, Nora Speer, An...
Background: Inference of gene regulatory networks is a key goal in the quest for understanding fundamental cellular processes and revealing underlying relations among genes. With ...
Ioannis A. Maraziotis, Andrei Dragomir, Dimitris T...
This article deals with the identification of gene regulatory networks from experimental data using a statistical machine learning approach. A stochastic model of gene interactio...
Modern approaches to treating genetic disorders, cancers and even epidemics rely on a detailed understanding of the underlying gene signaling network. Previous work has used time s...
David Oviatt, Mark J. Clement, Quinn Snell, Kennet...
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...