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Performance evaluation for MOTIFSIM.
Ngoc Tam L Tran1, Chun-Hsi Huang1
1Department of Computer Science and Engineering, University of Connecticut, Storrs, CT 06269 USA.
Biological Procedures Online
|December 22, 2018
Summary
Using multiple motif finders and the MOTIFSIM tool enhances DNA motif detection by identifying common, biologically significant motifs. MOTIFSIM outperforms other comparison methods and clustering tools.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Motif discovery tools yield varied results due to differing strategies.
- Common motifs identified by multiple tools are more likely biologically significant.
Purpose of the Study:
- Evaluate the performance of the MOTIFSIM tool for identifying common significant motifs.
- Compare MOTIFSIM's pair-wise comparison and clustering capabilities against established methods.
Main Methods:
- Assessed MOTIFSIM's pair-wise comparison against Smith-Waterman and four distance metrics.
- Compared MOTIFSIM's motif clustering performance with RSAT Matrix-clustering.
- Evaluated nineteen motif finders and MOTIFSIM's reliability in identifying common motifs.
Main Results:
- MOTIFSIM demonstrated superior performance in pair-wise comparisons over Smith-Waterman and distance metrics.
- MOTIFSIM achieved comparable or better results than RSAT Matrix-clustering in motif clustering.
- Combining multiple motif finders with MOTIFSIM improved DNA motif detection outcomes.
Conclusions:
- MOTIFSIM is a reliable tool for enhancing DNA motif detection by consolidating results from multiple motif finders.
- The study validates the utility of using multiple tools and MOTIFSIM for robust motif discovery.
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