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Related Experiment Video

Updated: Jan 31, 2026

Evaluating the Procedure for Performing Awake Cystometry in a Mouse Model

Evaluating the Procedure for Performing Awake Cystometry in a Mouse Model

Published on: May 20, 2017

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

This summary is machine-generated.

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.

Keywords:

Binding sites DNA motif Merging similar motifs Motif clustering Motif detection tool Motif similarity comparison

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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.