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Workflow management systems for gene sequence analysis and evolutionary studies – A Review

Post ‘omic’ era has resulted in the development of many primary, secondary and derived databases. Many analytical and visualization bioinformatics tools have been developed to manage and analyze the data available through large sequencing projects. Availability of heterogeneous databases and tools m...

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Detalles Bibliográficos
Autores principales: Sharma, Anu, Rai, Anil, Lal, SB
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Biomedical Informatics 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3732438/
https://www.ncbi.nlm.nih.gov/pubmed/23930017
http://dx.doi.org/10.6026/97320630009663
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author Sharma, Anu
Rai, Anil
Lal, SB
author_facet Sharma, Anu
Rai, Anil
Lal, SB
author_sort Sharma, Anu
collection PubMed
description Post ‘omic’ era has resulted in the development of many primary, secondary and derived databases. Many analytical and visualization bioinformatics tools have been developed to manage and analyze the data available through large sequencing projects. Availability of heterogeneous databases and tools make it difficult for researchers to access information from varied sources and run different bioinformatics tools to get desired analysis done. Building integrated bioinformatics platforms is one of the most challenging tasks that bioinformatics community is facing. Integration of various databases, tools and algorithm is a challenging problem to deal with. This article describes the bioinformatics analysis workflow management systems that are developed in the area of gene sequence analysis and phylogeny. This article will be useful for biotechnologists, molecular biologists, computer scientists and statisticians engaged in computational biology and bioinformatics research.
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spelling pubmed-37324382013-08-08 Workflow management systems for gene sequence analysis and evolutionary studies – A Review Sharma, Anu Rai, Anil Lal, SB Bioinformation Current Trends Post ‘omic’ era has resulted in the development of many primary, secondary and derived databases. Many analytical and visualization bioinformatics tools have been developed to manage and analyze the data available through large sequencing projects. Availability of heterogeneous databases and tools make it difficult for researchers to access information from varied sources and run different bioinformatics tools to get desired analysis done. Building integrated bioinformatics platforms is one of the most challenging tasks that bioinformatics community is facing. Integration of various databases, tools and algorithm is a challenging problem to deal with. This article describes the bioinformatics analysis workflow management systems that are developed in the area of gene sequence analysis and phylogeny. This article will be useful for biotechnologists, molecular biologists, computer scientists and statisticians engaged in computational biology and bioinformatics research. Biomedical Informatics 2013-07-17 /pmc/articles/PMC3732438/ /pubmed/23930017 http://dx.doi.org/10.6026/97320630009663 Text en © 2013 Biomedical Informatics 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 Current Trends
Sharma, Anu
Rai, Anil
Lal, SB
Workflow management systems for gene sequence analysis and evolutionary studies – A Review
title Workflow management systems for gene sequence analysis and evolutionary studies – A Review
title_full Workflow management systems for gene sequence analysis and evolutionary studies – A Review
title_fullStr Workflow management systems for gene sequence analysis and evolutionary studies – A Review
title_full_unstemmed Workflow management systems for gene sequence analysis and evolutionary studies – A Review
title_short Workflow management systems for gene sequence analysis and evolutionary studies – A Review
title_sort workflow management systems for gene sequence analysis and evolutionary studies – a review
topic Current Trends
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3732438/
https://www.ncbi.nlm.nih.gov/pubmed/23930017
http://dx.doi.org/10.6026/97320630009663
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