FastMEDUSA: A Parallelized Tool to Infer Gene Regulatory Networks

Authors

Serdar Bozdag, Marquette UniversityFollow
Aiguo Li, National Institutes of HealthFollow
Stefan Wuchty, National Institutes of Health
Howard A. Fine, National Institutes of Health

Document Type

Article

Language

eng

Format of Original

2 p.

Publication Date

7-15-2010

Publisher

Oxford University Press

Source Publication

Bioinformatics

Source ISSN

1367-4803

Original Item ID

doi: 10.1093/bioinformatics/btq275

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 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: hfine@mail.nih.gov Supplementary information: Supplementary data are available at Bioinformatics online.

Comments

Published version. Bioinformatics, Vol. 26, No. 14 (July 15, 2010): 1792-1793. DOI. © 2010 Oxford University Press. Used with permission.

Recommended Citation

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.
https://epublications.marquette.edu/mscs_fac/72