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...
— In this paper we address the problem of predicting gene activities by finding gene regulatory dependencies in experimental DNA microarray data. Only few approaches to infer th...
Christian Spieth, Felix Streichert, Nora Speer, Ch...
Quantification of selective pressures on regulatory sequences is a central question in studying the evolution of gene regulatory networks. Previous methods focus primarily on sing...
Hybrid algorithms that combine genetic algorithms with the Nelder-Mead simplex algorithm have been effective in solving certain optimization problems. In this article, we apply a s...
Praveen Koduru, Sanjoy Das, Stephen Welch, Judith ...
This paper addresses the inference of the transcriptional regulatory network of Bacillus subtilis. Two inference approaches, a linear, additive model and a non-linear power-law mo...
Anshuman Gupta, Jeffrey D. Varner, Costas D. Maran...