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Oxford University Press
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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 6 h by utilizing 100 processors. Availability: Source code and documentation of FastMEDUSA are available at https://wiki.nci.nih.gov/display/NOBbioinf/FastMEDUSA Contact: firstname.lastname@example.org Supplementary information: Supplementary data are available at Bioinformatics online.
Bozdag, Serdar; Li, Aiguo; Wuchty, Stefan; and Fine, Howard A., "FastMEDUSA: A Parallelized Tool to Infer Gene Regulatory Networks" (2010). Mathematics, Statistics and Computer Science Faculty Research and Publications. 72.