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Quantifying similarity between motifs

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 To...

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Detalles Bibliográficos
Autores principales: Gupta, Shobhit, Stamatoyannopoulos, John A, Bailey, Timothy L, Noble, William Stafford
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1852410/
https://www.ncbi.nlm.nih.gov/pubmed/17324271
http://dx.doi.org/10.1186/gb-2007-8-2-r24
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author Gupta, Shobhit
Stamatoyannopoulos, John A
Bailey, Timothy L
Noble, William Stafford
author_facet Gupta, Shobhit
Stamatoyannopoulos, John A
Bailey, Timothy L
Noble, William Stafford
author_sort Gupta, Shobhit
collection PubMed
description 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.
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spelling pubmed-18524102007-04-18 Quantifying similarity between motifs Gupta, Shobhit Stamatoyannopoulos, John A Bailey, Timothy L Noble, William Stafford Genome Biol Method 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. BioMed Central 2007 2007-02-26 /pmc/articles/PMC1852410/ /pubmed/17324271 http://dx.doi.org/10.1186/gb-2007-8-2-r24 Text en Copyright © 2007 Gupta et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Method
Gupta, Shobhit
Stamatoyannopoulos, John A
Bailey, Timothy L
Noble, William Stafford
Quantifying similarity between motifs
title Quantifying similarity between motifs
title_full Quantifying similarity between motifs
title_fullStr Quantifying similarity between motifs
title_full_unstemmed Quantifying similarity between motifs
title_short Quantifying similarity between motifs
title_sort quantifying similarity between motifs
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1852410/
https://www.ncbi.nlm.nih.gov/pubmed/17324271
http://dx.doi.org/10.1186/gb-2007-8-2-r24
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