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This page lists the software / web service developed by me.
INGOR is general purpose Bayesian network estimation software based on SiGN-BN. It will be available soon at GitHub as open source software.
Visit TCNG web site.
SiGN-BN is gene network estimation software based on Bayesian network and B-spline nonparametric regression. It can estimate regulatory dependencies between genes as gene networks from gene expression data such as individual cell samples, gene knocked-down cell samples, drug-stimulated time series (time course) samples, and so on. For dynamic data such as time series data, SiGN-BN estimates a dynamic Bayesian network which takes dependencies between time points into account. For static data, it estimates a static (ordinal) Bayesian network that assumes each sample is independent from each other and does not consider temporal changes in expression data.
SiGN-SSM is open source gene network estimation software able to run in parallel on PCs and massively parallel supercomputers. The software estimates a state space model (SSM), that is a statistical dynamic model suitable for analyzing short time and/or replicated time series gene expression profiles. SiGN-SSM implements a novel parameter constraint effective to stabilize the estimated models. Also, by using the supercomputers, it is able to determine the gene network structure by the statistical permutation test in a practical time. SiGN-SSM is applicable not only to analyzing temporal regulatory dependencies between genes, but also to the extraction of the differentially regulated genes from time series expression profiles.