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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...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2007
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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. |
format | Text |
id | pubmed-1852410 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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