FastMEDUSA: A parallelized tool to infer gene regulatory networks

Serdar Bozdag, Aiguo Li, Stefan Wuchty, Howard A. Fine

Research output: Contribution to journalArticle

15 Scopus citations

Abstract

Motivation: In order to construct gene regulatory networks of higher organisms from gene expression and promoter sequence data efficiently, we developed FastMEDUSA. In this parallelized version of the regulatory network-modeling tool MEDUSA, expression and sequence data are shared among a user-defined number of processors on a single multi-core machine or cluster. Our results show that FastMEDUSA allows a more efficient utilization of computational resources. While the determination of a regulatory network of brain tumor in Homo sapiens takes 12 days with MEDUSA, FastMEDUSA obtained the same results in 6h by utilizing 100 processors.

Original languageEnglish (US)
Article numberbtq275
Pages (from-to)1792-1793
Number of pages2
JournalBioinformatics
Volume26
Issue number14
DOIs
StatePublished - May 30 2010

ASJC Scopus subject areas

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

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