TY - JOUR
T1 - MTAP
T2 - The motif tool assessment platform
AU - Quest, Daniel
AU - Dempsey, Kathryn
AU - Shafiullah, Mohammad
AU - Bastola, Dhundy
AU - Ali, Hesham
N1 - Funding Information:
This research project was made possible by the NSF grant number EPS-0091900 and the NIH grant number P20 RR16469 from the INBRE Program of the National Center for Research Resources.
PY - 2008/8/12
Y1 - 2008/8/12
N2 - Background: 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. Results: 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, E. coli and B. subtilis. Conclusion: 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 http://biobase.ist.unomaha.edu/.
AB - Background: 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. Results: 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, E. coli and B. subtilis. Conclusion: 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 http://biobase.ist.unomaha.edu/.
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U2 - 10.1186/1471-2105-9-S9-S6
DO - 10.1186/1471-2105-9-S9-S6
M3 - Article
C2 - 18793470
AN - SCOPUS:49649108913
SN - 1471-2105
VL - 9
JO - BMC Bioinformatics
JF - BMC Bioinformatics
IS - SUPPL. 9
M1 - S6
ER -