Scinovex
article Open AccessTop 10% cited

Quantifying similarity between motifs

Genome biology · 2007 · Vol. 8(2) · pp. R24–R24
Shobhit GuptaJ StamatoyannopoulosTimothy L. BaileyWilliam Stafford Noble

Abstract

A common question within the context of de novo motif discovery is whether a newly discovered, putative motif resembles any previously discovered motif in an existing database. To answer this question, we define a statistical measure of motif-motif similarity, and we describe an algorithm, called Tomtom, for searching a database of motifs with a given query motif. Experimental simulations demonstrate the accuracy of Tomtom's E values and its effectiveness in finding similar motifs.

Genomics and Chromatin DynamicsGenomics and Phylogenetic StudiesRNA and protein synthesis mechanismsMotif (music)Sequence motifBiologyComputational biologyStructural motifEvolutionary biologyBioinformaticsGeneticsGene

MeSH terms

AlgorithmsSoftwareSequence HomologyComputational BiologyAmino Acid MotifsDatabases, Genetic
Citations
2,201
FWCI
6.17
field-weighted impact
References
25
Percentile
97%
vs. same field & year
Citations per year
Cited by
MEME SUITE: tools for motif discovery and searching
Nucleic Acids Research · 2009 · 11,293 citations
The MEME Suite
Nucleic Acids Research · 2015 · 5,223 citations
Related articles
Quantifying similarity between motifs
Genome biology · 2007 · 2,201 citations
Citation Network

How this paper connects to the literature. Drag to explore, click any node to open that paper.

Quantifying similarity between motifs · Scinovex