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...
—Often groups of genes in regulatory networks, also called modules, work collaboratively on similar functions. Mathematically, the modules in a regulatory network has often been ...
Ferhat Ay, Thang N. Dinh, My T. Thai, Tamer Kahvec...
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...
In this paper we address the problem of finding gene regulatory networks from experimental DNA microarray data. We focus on the evaluation of the performance of different mathemat...
Abstract. This paper presents a method for regulatory network reconstruction from experimental data. We propose a mathematical model for regulatory interactions, based on the work ...
Reverse-engineering of gene networks using linear models often results in an underdetermined system because of excessive unknown parameters. In addition, the practical utility of ...
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...
For studying gene regulatory and protein signaling networks, we have developed an interactive map for the Pseudomonas aeruginosa genome. We first represent genes, proteins and the...
We present what we believe is the first attempt to physically reconstruct the exploratory mechanism of genetic regulatory networks. Feedback plays a crucial role during developme...
Inferring transcriptional regulatory networks from geneexpression data remains a challenging problem, in part because of the noisy nature of the data and the lack of strong networ...