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      The PANTHER database of protein families, subfamilies, functions and pathways

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          Abstract

          PANTHER is a large collection of protein families that have been subdivided into functionally related subfamilies, using human expertise. These subfamilies model the divergence of specific functions within protein families, allowing more accurate association with function (ontology terms and pathways), as well as inference of amino acids important for functional specificity. Hidden Markov models (HMMs) are built for each family and subfamily for classifying additional protein sequences. The latest version, 5.0, contains 6683 protein families, divided into 31 705 subfamilies, covering ∼90% of mammalian protein-coding genes. PANTHER 5.0 includes a number of significant improvements over previous versions, most notably (i) representation of pathways (primarily signaling pathways) and association with subfamilies and individual protein sequences; (ii) an improved methodology for defining the PANTHER families and subfamilies, and for building the HMMs; (iii) resources for scoring sequences against PANTHER HMMs both over the web and locally; and (iv) a number of new web resources to facilitate analysis of large gene lists, including data generated from high-throughput expression experiments. Efforts are underway to add PANTHER to the InterPro suite of databases, and to make PANTHER consistent with the PIRSF database. PANTHER is now publicly available without restriction at http://panther.appliedbiosystems.com.

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          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.
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              PANTHER: a browsable database of gene products organized by biological function, using curated protein family and subfamily classification.

              P. Thomas (2003)
              The PANTHER database was designed for high-throughput analysis of protein sequences. One of the key features is a simplified ontology of protein function, which allows browsing of the database by biological functions. Biologist curators have associated the ontology terms with groups of protein sequences rather than individual sequences. Statistical models (Hidden Markov Models, or HMMs) are built from each of these groups. The advantage of this approach is that new sequences can be automatically classified as they become available. To ensure accurate functional classification, HMMs are constructed not only for families, but also for functionally distinct subfamilies. Multiple sequence alignments and phylogenetic trees, including curator-assigned information, are available for each family. The current version of the PANTHER database includes training sequences from all organisms in the GenBank non-redundant protein database, and the HMMs have been used to classify gene products across the entire genomes of human, and Drosophila melanogaster. The ontology terms and protein families and subfamilies, as well as Drosophila gene c;assifications, can be browsed and searched for free. Due to outstanding contractual obligations, access to human gene classifications and to protein family trees and multiple sequence alignments will temporarily require a nominal registration fee. PANTHER is publicly available on the web at http://panther.celera.com.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                1 January 2005
                17 December 2004
                : 33
                : Database Issue
                : D284-D288
                Affiliations
                Computational Biology, Applied Biosystems, 850 Lincoln Center Drive, Foster City, CA 94404, USA and [1 ]The Systems Biology Institute and ERATO-SORST Kitano Symbiotic Systems Project/Japan Science and Technology Agency, Suite 6A, M31, 6-31-15 Jingumae, Shibuya, Tokyo 150-0001, Japan
                Author notes
                [*]

                To whom correspondence should be addressed. Tel: +1 650 554 2723; Fax: +1 650 554 2344; Email: paul.thomas@ 123456appliedbiosystems.com

                [a]

                The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use permissions, please contact journals.permissions@ 123456oupjournals.org .

                [a]

                © 2005, the authors

                Article
                gki078
                10.1093/nar/gki078
                540032
                15608197
                a25ed835-8e4a-4c8d-b673-6cd43ef1d861
                Copyright © 2005 Oxford University Press
                History
                : 15 September 2004
                : 8 October 2004
                : 8 October 2004
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                Genetics
                Genetics

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