High-throughput functional annotation and data mining with the Blast2GO suite

Functional genomics technologies have been widely adopted in the biological research of both model and non-model species. An efficient functional annotation of DNA or protein sequences is a major requirement for the successful application of these approaches as functional information on gene p...

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Autores principales: Gotz, Stefan, García-Gómez, Juan M., Terol, Javier, Williams, Tim D., Nagaraj, Shivashankar H., Nueda, María J., Robles, Montserrat, Talón, Manuel, Dopazo, Joaquín, Conesa, Ana
Formato: article
Lenguaje:Inglés
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:http://hdl.handle.net/20.500.11939/6426
https://academic.oup.com/nar/article/36/10/3420/2410320
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author Gotz, Stefan
García-Gómez, Juan M.
Terol, Javier
Williams, Tim D.
Nagaraj, Shivashankar H.
Nueda, María J.
Robles, Montserrat
Talón, Manuel
Dopazo, Joaquín
Conesa, Ana
author_browse Conesa, Ana
Dopazo, Joaquín
García-Gómez, Juan M.
Gotz, Stefan
Nagaraj, Shivashankar H.
Nueda, María J.
Robles, Montserrat
Talón, Manuel
Terol, Javier
Williams, Tim D.
author_facet Gotz, Stefan
García-Gómez, Juan M.
Terol, Javier
Williams, Tim D.
Nagaraj, Shivashankar H.
Nueda, María J.
Robles, Montserrat
Talón, Manuel
Dopazo, Joaquín
Conesa, Ana
author_sort Gotz, Stefan
collection ReDivia
description Functional genomics technologies have been widely adopted in the biological research of both model and non-model species. An efficient functional annotation of DNA or protein sequences is a major requirement for the successful application of these approaches as functional information on gene products is often the key to the interpretation of experimental results. Therefore, there is an increasing need for bioinformatics resources which are able to cope with large amount of sequence data, produce valuable annotation results and are easily accessible to laboratories where functional genomics projects are being undertaken. We present the Blast2GO suite as an integrated and biologistoriented solution for the high-throughput and automatic functional annotation of DNA or protein sequences based on the Gene Ontology vocabulary. The most outstanding Blast2GO features are: (i) the combination of various annotation strategies and tools controlling type and intensity of annotation, (ii) the numerous graphical features such as the interactive GO-graph visualization for gene-set function profiling or descriptive charts, (iii) the general sequence management features and (iv) highthroughput capabilities. We used the Blast2GO framework to carry out a detailed analysis of annotation behaviour through homology transfer and its impact in functional genomics research. Our aim is to offer biologists useful information to take into account when addressing the task of functionally characterizing their sequence data.
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spelling ReDivia64262025-04-25T14:47:03Z High-throughput functional annotation and data mining with the Blast2GO suite Gotz, Stefan García-Gómez, Juan M. Terol, Javier Williams, Tim D. Nagaraj, Shivashankar H. Nueda, María J. Robles, Montserrat Talón, Manuel Dopazo, Joaquín Conesa, Ana U10 Mathematical and statistical methods Functional genomics technologies have been widely adopted in the biological research of both model and non-model species. An efficient functional annotation of DNA or protein sequences is a major requirement for the successful application of these approaches as functional information on gene products is often the key to the interpretation of experimental results. Therefore, there is an increasing need for bioinformatics resources which are able to cope with large amount of sequence data, produce valuable annotation results and are easily accessible to laboratories where functional genomics projects are being undertaken. We present the Blast2GO suite as an integrated and biologistoriented solution for the high-throughput and automatic functional annotation of DNA or protein sequences based on the Gene Ontology vocabulary. The most outstanding Blast2GO features are: (i) the combination of various annotation strategies and tools controlling type and intensity of annotation, (ii) the numerous graphical features such as the interactive GO-graph visualization for gene-set function profiling or descriptive charts, (iii) the general sequence management features and (iv) highthroughput capabilities. We used the Blast2GO framework to carry out a detailed analysis of annotation behaviour through homology transfer and its impact in functional genomics research. Our aim is to offer biologists useful information to take into account when addressing the task of functionally characterizing their sequence data. 2020-05-07T14:45:25Z 2020-05-07T14:45:25Z 2008 article publishedVersion Götz, S., García-Gómez, J. M., Terol, J., Williams, T. D., Nagaraj, S. H., Nueda, M. J., ... & Conesa, A. (2008). High-throughput functional annotation and data mining with the Blast2GO suite. Nucleic acids research, 36(10), 3420-3435. 0305-1048 http://hdl.handle.net/20.500.11939/6426 10.1093/nar/gkn176 https://academic.oup.com/nar/article/36/10/3420/2410320 en Atribución-NoComercial-SinDerivadas 3.0 España http://creativecommons.org/licenses/by-nc-nd/3.0/es/ Oxford University Press electronico
spellingShingle U10 Mathematical and statistical methods
Gotz, Stefan
García-Gómez, Juan M.
Terol, Javier
Williams, Tim D.
Nagaraj, Shivashankar H.
Nueda, María J.
Robles, Montserrat
Talón, Manuel
Dopazo, Joaquín
Conesa, Ana
High-throughput functional annotation and data mining with the Blast2GO suite
title High-throughput functional annotation and data mining with the Blast2GO suite
title_full High-throughput functional annotation and data mining with the Blast2GO suite
title_fullStr High-throughput functional annotation and data mining with the Blast2GO suite
title_full_unstemmed High-throughput functional annotation and data mining with the Blast2GO suite
title_short High-throughput functional annotation and data mining with the Blast2GO suite
title_sort high throughput functional annotation and data mining with the blast2go suite
topic U10 Mathematical and statistical methods
url http://hdl.handle.net/20.500.11939/6426
https://academic.oup.com/nar/article/36/10/3420/2410320
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