Computational methods for discovering gene networks from expression data

Computational methods for discovering gene networks from expression data

Designing and conducting experiments are routine practices for modern biologists. The real challenge, especially in the post-genome era, usually comes not from acquiring data, but from subsequent activities such as data processing, analysis, knowledge generation and gaining insight into the research question of interest. The approach of inferring gene regulatory networks (GRNs) has been flouris...

Computational Methods of Discovering Gene Modules and Constructing Regulatory Networks

Computational Strategy for Discovering Druggable Gene Networks from Genome-Wide RNA Expression Profiles

We propose a computational strategy for discovering gene networks affected by a chemical compound. Two kinds of DNA microarray data are assumed to be used: One dataset is short time-course data that measure responses of genes following an experimental treatment. The other dataset is obtained by several hundred single gene knock-downs. These two datasets provide three kinds of information; (i) A...

Classification and Comparison of Methods for Discovering Coverage Loss Areas in Wireless Sensor Networks

In recent years, wireless sensor networks data is taken into consideration as an ideal source, in terms of speed, accuracy and cost, in order to study the Earth's surface. One of the most important challenges in this area, is the signaling network coverage and finding holes. In recent years, wireless sensor networks data is taken into consideration as an ideal source, in terms of speed, accurac...

Discovering molecular pathways from protein interaction and gene expression data

In this paper, we describe an approach for identifying 'pathways' from gene expression and protein interaction data. Our approach is based on the assumption that many pathways exhibit two properties: their genes exhibit a similar gene expression profile, and the protein products of the genes often interact. Our approach is based on a unified probabilistic model, which is learned from the data u...