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

Gotz, Stefan, Garcia-Gomez, Juan Miguel, Terol, Javier, Williams, Tim D., Nagaraj, Shivashankar H., Nueda, María José, Robles, Montserrat, Talon, Manuel, Dopazo, Joaquín and Conesa, Ana (2008) High-throughput functional annotation and data mining with the Blast2GO suite. Nucleic Acids Research, 36 10: 3420-3435. doi:10.1093/nar/gkn176

Author Gotz, Stefan
Garcia-Gomez, Juan Miguel
Terol, Javier
Williams, Tim D.
Nagaraj, Shivashankar H.
Nueda, María José
Robles, Montserrat
Talon, Manuel
Dopazo, Joaquín
Conesa, Ana
Title High-throughput functional annotation and data mining with the Blast2GO suite
Journal name Nucleic Acids Research   Check publisher's open access policy
ISSN 0305-1048
Publication date 2008-06-01
Sub-type Article (original research)
DOI 10.1093/nar/gkn176
Open Access Status DOI
Volume 36
Issue 10
Start page 3420
End page 3435
Total pages 16
Place of publication Oxford, United Kingdom
Publisher Oxford University Press
Language eng
Abstract 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 biologist-oriented 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) high-throughput 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.
Keyword Gene ontology annotation
Anonymous Sequence Data
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: Institute for Molecular Bioscience - Publications
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 1246 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 1290 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Wed, 21 Mar 2012, 19:56:04 EST by Susan Allen on behalf of Institute for Molecular Bioscience