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Performance evaluation of DNA Motif discovery programs
Methods for the identification of transcription factor binding sites have proved to be useful for deciphering genetic regulatory networks. The strengths and weaknesses for a number of available web tools are not fully understood. Here, we designed a comprehensive set of performance measures and benc...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Biomedical Informatics Publishing Group
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2646190/ https://www.ncbi.nlm.nih.gov/pubmed/19255635 |
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author | Singh, Chandra Prakash Khan, Feroz Mishra, Bhartendu Nath Chauhan, Durg Singh |
author_facet | Singh, Chandra Prakash Khan, Feroz Mishra, Bhartendu Nath Chauhan, Durg Singh |
author_sort | Singh, Chandra Prakash |
collection | PubMed |
description | Methods for the identification of transcription factor binding sites have proved to be useful for deciphering genetic regulatory networks. The strengths and weaknesses for a number of available web tools are not fully understood. Here, we designed a comprehensive set of performance measures and benchmarked sequence-based motif discovery tools using large scale datasets (derived from Escherichia coli genome and RegulonDB database). The benchmark study showed that nucleotide based and binding site based prediction accuracy is often low and activator binding site based prediction accuracy is high. |
format | Text |
id | pubmed-2646190 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Biomedical Informatics Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-26461902009-03-02 Performance evaluation of DNA Motif discovery programs Singh, Chandra Prakash Khan, Feroz Mishra, Bhartendu Nath Chauhan, Durg Singh Bioinformation Hypothesis Methods for the identification of transcription factor binding sites have proved to be useful for deciphering genetic regulatory networks. The strengths and weaknesses for a number of available web tools are not fully understood. Here, we designed a comprehensive set of performance measures and benchmarked sequence-based motif discovery tools using large scale datasets (derived from Escherichia coli genome and RegulonDB database). The benchmark study showed that nucleotide based and binding site based prediction accuracy is often low and activator binding site based prediction accuracy is high. Biomedical Informatics Publishing Group 2008-12-31 /pmc/articles/PMC2646190/ /pubmed/19255635 Text en © 2008 Biomedical Informatics Publishing Group This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited. |
spellingShingle | Hypothesis Singh, Chandra Prakash Khan, Feroz Mishra, Bhartendu Nath Chauhan, Durg Singh Performance evaluation of DNA Motif discovery programs |
title | Performance evaluation of DNA Motif discovery programs |
title_full | Performance evaluation of DNA Motif discovery programs |
title_fullStr | Performance evaluation of DNA Motif discovery programs |
title_full_unstemmed | Performance evaluation of DNA Motif discovery programs |
title_short | Performance evaluation of DNA Motif discovery programs |
title_sort | performance evaluation of dna motif discovery programs |
topic | Hypothesis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2646190/ https://www.ncbi.nlm.nih.gov/pubmed/19255635 |
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