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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...

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Detalles Bibliográficos
Autores principales: Singh, Chandra Prakash, Khan, Feroz, Mishra, Bhartendu Nath, Chauhan, Durg Singh
Formato: Texto
Lenguaje:English
Publicado: Biomedical Informatics Publishing Group 2008
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.
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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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