SiGN-SSM: Open source parallel software for estimating gene networks with state space models

Yoshinori Tamada, Rui Yamaguchi, Seiya Imoto, Osamu Hirose, Ryo Yoshida, Masao Nagasaki, Satoru Miyano

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

Summary: SiGN-SSM is an 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 a 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.

Original languageEnglish
Article numberbtr078
Pages (from-to)1172-1173
Number of pages2
JournalBioinformatics
Volume27
Issue number8
DOIs
Publication statusPublished - 2011 Apr

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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