Cargando…
Measuring similarities between transcription factor binding sites
BACKGROUND: Collections of transcription factor binding profiles (Transfac, Jaspar) are essential to identify regulatory elements in DNA sequences. Subsets of highly similar profiles complicate large scale analysis of transcription factor binding sites. RESULTS: We propose to identify and group simi...
Autores principales: | , , |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2005
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1261160/ https://www.ncbi.nlm.nih.gov/pubmed/16191190 http://dx.doi.org/10.1186/1471-2105-6-237 |
_version_ | 1782125866538500096 |
---|---|
author | Kielbasa, Szymon M Gonze, Didier Herzel, Hanspeter |
author_facet | Kielbasa, Szymon M Gonze, Didier Herzel, Hanspeter |
author_sort | Kielbasa, Szymon M |
collection | PubMed |
description | BACKGROUND: Collections of transcription factor binding profiles (Transfac, Jaspar) are essential to identify regulatory elements in DNA sequences. Subsets of highly similar profiles complicate large scale analysis of transcription factor binding sites. RESULTS: We propose to identify and group similar profiles using two independent similarity measures: χ(2 )distances between position frequency matrices (PFMs) and correlation coefficients between position weight matrices (PWMs) scores. CONCLUSION: We show that these measures complement each other and allow to associate Jaspar and Transfac matrices. Clusters of highly similar matrices are identified and can be used to optimise the search for regulatory elements. Moreover, the application of the measures is illustrated by assigning E-box matrices of a SELEX experiment and of experimentally characterised binding sites of circadian clock genes to the Myc-Max cluster. |
format | Text |
id | pubmed-1261160 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2005 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-12611602005-10-27 Measuring similarities between transcription factor binding sites Kielbasa, Szymon M Gonze, Didier Herzel, Hanspeter BMC Bioinformatics Software BACKGROUND: Collections of transcription factor binding profiles (Transfac, Jaspar) are essential to identify regulatory elements in DNA sequences. Subsets of highly similar profiles complicate large scale analysis of transcription factor binding sites. RESULTS: We propose to identify and group similar profiles using two independent similarity measures: χ(2 )distances between position frequency matrices (PFMs) and correlation coefficients between position weight matrices (PWMs) scores. CONCLUSION: We show that these measures complement each other and allow to associate Jaspar and Transfac matrices. Clusters of highly similar matrices are identified and can be used to optimise the search for regulatory elements. Moreover, the application of the measures is illustrated by assigning E-box matrices of a SELEX experiment and of experimentally characterised binding sites of circadian clock genes to the Myc-Max cluster. BioMed Central 2005-09-28 /pmc/articles/PMC1261160/ /pubmed/16191190 http://dx.doi.org/10.1186/1471-2105-6-237 Text en Copyright © 2005 Kielbasa 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 | Software Kielbasa, Szymon M Gonze, Didier Herzel, Hanspeter Measuring similarities between transcription factor binding sites |
title | Measuring similarities between transcription factor binding sites |
title_full | Measuring similarities between transcription factor binding sites |
title_fullStr | Measuring similarities between transcription factor binding sites |
title_full_unstemmed | Measuring similarities between transcription factor binding sites |
title_short | Measuring similarities between transcription factor binding sites |
title_sort | measuring similarities between transcription factor binding sites |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1261160/ https://www.ncbi.nlm.nih.gov/pubmed/16191190 http://dx.doi.org/10.1186/1471-2105-6-237 |
work_keys_str_mv | AT kielbasaszymonm measuringsimilaritiesbetweentranscriptionfactorbindingsites AT gonzedidier measuringsimilaritiesbetweentranscriptionfactorbindingsites AT herzelhanspeter measuringsimilaritiesbetweentranscriptionfactorbindingsites |