MTAP: The Motif Tool Assessment Platform
<p>Abstract</p> <p>Background</p> <p>In recent years, substantial effort has been applied to de novo regulatory motif discovery. At this time, more than 150 software tools exist to detect regulatory binding sites given a set of genomic sequences. As the number of softwa...
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doaj-fffccdd30cc44e9ab9056f3d8fc4fdd92020-11-25T01:26:20ZengBMCBMC Bioinformatics1471-21052008-08-019Suppl 9S610.1186/1471-2105-9-S9-S6MTAP: The Motif Tool Assessment PlatformShafiullah MohammadDempsey KathrynQuest DanielBastola DhundyAli Hesham<p>Abstract</p> <p>Background</p> <p>In recent years, substantial effort has been applied to de novo regulatory motif discovery. At this time, more than 150 software tools exist to detect regulatory binding sites given a set of genomic sequences. As the number of software packages increases, it becomes more important to identify the tools with the best performance characteristics for specific problem domains. Identifying the correct tool is difficult because of the great variability in motif detection software. Consequently, many labs spend considerable effort testing methods to find one that works well in their problem of interest.</p> <p>Results</p> <p>In this work, we propose a method (MTAP) that substantially reduces the effort required to assess de novo regulatory motif discovery software. MTAP differs from previous attempts at regulatory motif assessment in that it automates motif discovery tool pipelines (something that traditionally required many manual steps), automatically constructs orthologous upstream sequences, and provides automated benchmarks for many popular tools. As a proof of concept, we have run benchmarks over human, mouse, fly, yeast, <it>E. coli </it>and <it>B. subtilis</it>.</p> <p>Conclusion</p> <p>MTAP presents a new approach to the challenging problem of assessing regulatory motif discovery methods. The most current version of MTAP can be downloaded from <url>http://biobase.ist.unomaha.edu/</url></p> |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Shafiullah Mohammad Dempsey Kathryn Quest Daniel Bastola Dhundy Ali Hesham |
spellingShingle |
Shafiullah Mohammad Dempsey Kathryn Quest Daniel Bastola Dhundy Ali Hesham MTAP: The Motif Tool Assessment Platform BMC Bioinformatics |
author_facet |
Shafiullah Mohammad Dempsey Kathryn Quest Daniel Bastola Dhundy Ali Hesham |
author_sort |
Shafiullah Mohammad |
title |
MTAP: The Motif Tool Assessment Platform |
title_short |
MTAP: The Motif Tool Assessment Platform |
title_full |
MTAP: The Motif Tool Assessment Platform |
title_fullStr |
MTAP: The Motif Tool Assessment Platform |
title_full_unstemmed |
MTAP: The Motif Tool Assessment Platform |
title_sort |
mtap: the motif tool assessment platform |
publisher |
BMC |
series |
BMC Bioinformatics |
issn |
1471-2105 |
publishDate |
2008-08-01 |
description |
<p>Abstract</p> <p>Background</p> <p>In recent years, substantial effort has been applied to de novo regulatory motif discovery. At this time, more than 150 software tools exist to detect regulatory binding sites given a set of genomic sequences. As the number of software packages increases, it becomes more important to identify the tools with the best performance characteristics for specific problem domains. Identifying the correct tool is difficult because of the great variability in motif detection software. Consequently, many labs spend considerable effort testing methods to find one that works well in their problem of interest.</p> <p>Results</p> <p>In this work, we propose a method (MTAP) that substantially reduces the effort required to assess de novo regulatory motif discovery software. MTAP differs from previous attempts at regulatory motif assessment in that it automates motif discovery tool pipelines (something that traditionally required many manual steps), automatically constructs orthologous upstream sequences, and provides automated benchmarks for many popular tools. As a proof of concept, we have run benchmarks over human, mouse, fly, yeast, <it>E. coli </it>and <it>B. subtilis</it>.</p> <p>Conclusion</p> <p>MTAP presents a new approach to the challenging problem of assessing regulatory motif discovery methods. The most current version of MTAP can be downloaded from <url>http://biobase.ist.unomaha.edu/</url></p> |
work_keys_str_mv |
AT shafiullahmohammad mtapthemotiftoolassessmentplatform AT dempseykathryn mtapthemotiftoolassessmentplatform AT questdaniel mtapthemotiftoolassessmentplatform AT bastoladhundy mtapthemotiftoolassessmentplatform AT alihesham mtapthemotiftoolassessmentplatform |
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