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• W2148838356 abstract "Gene regulatory networks, or simply gene networks (GNs), have shown to be a promising approach that the bioinformatics community has been developing for studying regulatory mechanisms in biological systems. GNs are built from the genome-wide high-through- put gene expression data that are often available from DNA microarray experiments. Conceptually, GNs are (un)directed graphs, where the nodes correspond to the genes and a link between a pair of genes denotes a regulatory interaction that occurs at transcriptional level. In the present study, we had two objectives: 1) to develop a framework for GN recon- struction based on a Bayesian network model that captures direct inter- actions between genes through nonparametric regression with B-splines, and 2) to demonstrate the potential of GNs in the analysis of expression data of a real biological system, the yeast pheromone response pathway. Our framework also included a number of search schemes to learn the network. We present an intuitive notion of GN theory as well as the detailed mathematical foundations of the model. A comprehensive anal-" @default.
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• W2148838356 date "2006-03-31" @default.
• W2148838356 modified "2023-09-22" @default.
• W2148838356 title "Gene networks as a tool to understand transcriptional regulation." @default.
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