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. SiGN-L1 also implements the Network Profiler that realizes the analysis of individual differences of gene networks with respect to the extra individual index called modulator.



Beta: Release 1.1.0 (Released on Sep 10 2020 JST)


Manual : User reference manual.
Download : Download page.


The methodological details and the example (application) of the analysis can be found in "Shimamura, T., Imoto, S., Shimada, Y., Hosono, Y., Niida, A., Nagasaki, M., Yamaguchi, R., Takahashi, T., Miyano, S. (2011). A novel network profiling analysis reveals system changes in epithelial-mesenchymal transition, PLoS ONE 6(6), e20804" and "Shimamura. T., Imoto. S., Yamaguchi. R., Fujita. A., Nagasaki. M., Miyano. S. (2009). Recursive regularization for inferring gene networks from time-course gene expression profiles, BMC Systems Biology 3, 41."