1,127
views
0
recommends
+1 Recommend
0 collections
    4
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

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

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          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.

          Related collections

          Most cited references37

          • Record: found
          • Abstract: found
          • Article: not found

          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Comparative metagenomics of microbial communities.

            The species complexity of microbial communities and challenges in culturing representative isolates make it difficult to obtain assembled genomes. Here we characterize and compare the metabolic capabilities of terrestrial and marine microbial communities using largely unassembled sequence data obtained by shotgun sequencing DNA isolated from the various environments. Quantitative gene content analysis reveals habitat-specific fingerprints that reflect known characteristics of the sampled environments. The identification of environment-specific genes through a gene-centric comparative analysis presents new opportunities for interpreting and diagnosing environments.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              The Gene Ontology Annotation (GOA) Database: sharing knowledge in Uniprot with Gene Ontology.

              The Gene Ontology Annotation (GOA) database (http://www.ebi.ac.uk/GOA) aims to provide high-quality electronic and manual annotations to the UniProt Knowledgebase (Swiss-Prot, TrEMBL and PIR-PSD) using the standardized vocabulary of the Gene Ontology (GO). As a supplementary archive of GO annotation, GOA promotes a high level of integration of the knowledge represented in UniProt with other databases. This is achieved by converting UniProt annotation into a recognized computational format. GOA provides annotated entries for nearly 60,000 species (GOA-SPTr) and is the largest and most comprehensive open-source contributor of annotations to the GO Consortium annotation effort. By integrating GO annotations from other model organism groups, GOA consolidates specialized knowledge and expertise to ensure the data remain a key reference for up-to-date biological information. Furthermore, the GOA database fully endorses the Human Proteomics Initiative by prioritizing the annotation of proteins likely to benefit human health and disease. In addition to a non-redundant set of annotations to the human proteome (GOA-Human) and monthly releases of its GO annotation for all species (GOA-SPTr), a series of GO mapping files and specific cross-references in other databases are also regularly distributed. GOA can be queried through a simple user-friendly web interface or downloaded in a parsable format via the EBI and GO FTP websites. The GOA data set can be used to enhance the annotation of particular model organism or gene expression data sets, although increasingly it has been used to evaluate GO predictions generated from text mining or protein interaction experiments. In 2004, the GOA team will build on its success and will continue to supplement the functional annotation of UniProt and work towards enhancing the ability of scientists to access all available biological information. Researchers wishing to query or contribute to the GOA project are encouraged to email: goa@ebi.ac.uk.
                Bookmark

                Author and article information

                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
                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
                Article
                gkn176
                10.1093/nar/gkn176
                2425479
                18445632
                719ca2a9-719c-4506-a668-e08829077ff6
                © 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.

                History
                : 9 November 2007
                : 25 March 2008
                : 26 March 2008
                Categories
                Computational Biology

                Genetics
                Genetics

                Comments

                Comment on this article