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

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      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.

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      Most cited references 42

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      Basic local alignment search tool.

      A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
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        Gene ontology: tool for the unification of biology. The Gene Ontology Consortium.

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          Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research.

          We present here Blast2GO (B2G), a research tool designed with the main purpose of enabling Gene Ontology (GO) based data mining on sequence data for which no GO annotation is yet available. B2G joints in one application GO annotation based on similarity searches with statistical analysis and highlighted visualization on directed acyclic graphs. This tool offers a suitable platform for functional genomics research in non-model species. B2G is an intuitive and interactive desktop application that allows monitoring and comprehension of the whole annotation and analysis process. Blast2GO is freely available via Java Web Start at http://www.blast2go.de. http://www.blast2go.de -> Evaluation.
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            Author and article information

            Affiliations
            1Bioinformatics Department, Centro de Investigación Principe Felipe (CIPF), Valencia, 2Center for Biomedical Research on Rare Diseases (CIBERER), Valencia, 3Biomedical Informatics Group, IBIME-ITACA, Universidad Politécnica de Valencia, Valencia, 4Centro de Genómica, Instituto Valenciano de Investigaciones Agrarias (IVIA), Moncada, Spain, 5School of Biosciences, University of Birmingham, Edgbaston, Birmingham, UK, 6Department of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, Australia, 7Departamento de Estadística e Investigación Operativa, Universidad de Alicante, Alicante and 8Functional Genomics Node (National Institute for Bioinformatics, INB), Valencia, Spain
            Author notes
            *To whom correspondence should be addressed. +34 96 32 89 680+34 96 32 89 574 aconesa@ 123456cipf.es
            Journal
            Nucleic Acids Res
            Nucleic Acids Res
            nar
            nar
            Nucleic Acids Research
            Oxford University Press
            0305-1048
            1362-4962
            June 2008
            29 April 2008
            29 April 2008
            : 36
            : 10
            : 3420-3435
            18445632 2425479 10.1093/nar/gkn176 gkn176
            © 2008 The Author(s)

            This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

            Categories
            Computational Biology

            Genetics

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