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Parallel and Distributed Processing Symposium, International (2008)
Miami, FL, USA
Apr. 14, 2008 to Apr. 18, 2008
ISBN: 978-1-4244-1693-6
pp: 1-8
Mohammad Shafiullah , College of Information Technology, University of Nebraska at Omaha, USA
Hesham Ali , Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE 68182-0694 USA
Kathryn Dempsey , College of Information Technology, University of Nebraska at Omaha, USA
Dhundy Bastola , College of Information Technology, University of Nebraska at Omaha, USA
Daniel Quest , Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE 68182-0694 USA
ABSTRACT
Computational discovery of cis-regulatorymotifs has become one of the more challenging problems in bioinformatics. In recent years, over 150 methods have been proposed as solutions, however, it remains difficult to characterize the advantages and disadvantages of these approaches because of the wide variability of approaches and datasets. Although biologists desire a set of parameters and a program most appropriate for cis-regulatory discovery in their domain of interest, compiling such a list is a great computational challenge. First, a discovery pipeline for 150+ methods must be automated and then each dataset of interest must used to grade the methods. Automation is challenging because these programs are intended to be used over a small set of sites and consequently have many manual steps intended to help the user in fine-tuning the program to specific problems or organisms. If a program is fine-tuned to parameters other than those used in the original paper, it is not guaranteed to have the same sensitivity and specificity. Consequently, there are few methods that rank motif discovery tools. This paper proposes a parallel framework for the automation and evaluation of cis-regulatory motif discovery tools. This evaluation platform can both run and benchmark motif discovery tools over a wide range of parameters and is the first method to consider both multiple binding locations within a regulatory region and regulatory regions of orthologous genes. Because of the large amount of tests required, we implemented this platform on a computing cluster to increase performance.
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CITATION
Mohammad Shafiullah, Hesham Ali, Kathryn Dempsey, Dhundy Bastola, Daniel Quest, "A parallel architecture for regulatory motif algorithm assessment", Parallel and Distributed Processing Symposium, International, vol. 00, no. , pp. 1-8, 2008, doi:10.1109/IPDPS.2008.4536178
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