Inference of gene regulatory networks from time series data
Reverse engineering of gene regulatory relationships from genomics datais a crucial task to dissect the complex underlying regulatory mechanismoccurring in a cell. From a computational point of view thereconstruction of gene regulatory networks is an undetermined problem asthe large number of possible solutions is typically high in contrast tothe number of available independent data points. Many possible solutionscan fit the available data, explaining the data equally well, but onlyone of them can be the biologically true solution. Several strategieshave been proposed in literature to reduce the search space and/orextend the amount of independent information. Moreover, several methodshave been developed to infer gene networks from steady-state data, muchless literature is produced about time-course data, so the developmentof algorithms to infer gene networks from time-series measurements is acurrent challenge into bioinformatics research area. Here I will present two recently proposed algorithms, the first termedTimeDelay-ARACNE tries to extract dependencies between pairs of genesat different time…