SiGN-SSM 1.3.0 / SiGN-L1 1.1.0
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 a supercomputer, 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 extracting the differentially regulated genes from time series expression profiles.
SiGN-L1 is network estimation software using sparse learning. It uses L1-regularization for simultaneous parameter estimation and model selection of statistical graphical models such as graphical Gaussian models and vector autoregressive models.
- Windows / Linux / Mac OsX
:: MORE INFORMATION
Tamada, Y., Yamaguchi, R., Imoto, S., Hirose, O., Yoshida, R., Nagasaki, M., and Miyano, S. (2011).
SiGN-SSM: open source parallel software for estimating gene networks with state space models.
Bioinformatics. 2011 Apr 15;27(8):1172-3. doi: 10.1093/bioinformatics/btr078.
Genome Inform. 2011;25(1):40-52.
Sign: large-scale gene network estimation environment for high performance computing.
Tamada Y, Shimamura T, Yamaguchi R, Imoto S, Nagasaki M, Miyano S.