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      Easy retrieval of single amino-acid polymorphisms and phenotype information using SwissVar

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          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

          Summary: The SwissVar portal provides access to a comprehensive collection of single amino acid polymorphisms and diseases in the UniProtKB/Swiss-Prot database via a unique search engine. In particular, it gives direct access to the newly improved Swiss-Prot variant pages. The key strength of this portal is that it provides a possibility to query for similar diseases, as well as the underlying protein products and the molecular details of each variant. In the context of the recently proposed molecular view on diseases, the SwissVar portal should be in a unique position to provide valuable information for researchers and to advance research in this area.

          Availability: The SwissVar portal is available at www.expasy.org/swissvar

          Contact: anais.mottaz@ 123456isb-sib.ch ; lina.yip@ 123456isb-sib.ch

          Supplementary information: Supplementary data are available at Bioinformatics online.

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          A human phenome-interactome network of protein complexes implicated in genetic disorders.

          Kasper Lage, E Olof Karlberg, Zenia Størling … (2007)
          We performed a systematic, large-scale analysis of human protein complexes comprising gene products implicated in many different categories of human disease to create a phenome-interactome network. This was done by integrating quality-controlled interactions of human proteins with a validated, computationally derived phenotype similarity score, permitting identification of previously unknown complexes likely to be associated with disease. Using a phenomic ranking of protein complexes linked to human disease, we developed a Bayesian predictor that in 298 of 669 linkage intervals correctly ranks the known disease-causing protein as the top candidate, and in 870 intervals with no identified disease-causing gene, provides novel candidates implicated in disorders such as retinitis pigmentosa, epithelial ovarian cancer, inflammatory bowel disease, amyotrophic lateral sclerosis, Alzheimer disease, type 2 diabetes and coronary heart disease. Our publicly available draft of protein complexes associated with pathology comprises 506 complexes, which reveal functional relationships between disease-promoting genes that will inform future experimentation.
          Article 0 comments Cited 318 times – based on 0 reviews     Review now
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            The Universal Protein Resource (UniProt) 2009

            Amos Bairoch, Claire O'Donovan (2009)
            The mission of UniProt is to provide the scientific community with a comprehensive, high-quality and freely accessible resource of protein sequence and functional information that is essential for modern biological research. UniProt is produced by the UniProt Consortium which consists of groups from the European Bioinformatics Institute, the Protein Information Resource and the Swiss Institute of Bioinformatics. The core activities include manual curation of protein sequences assisted by computational analysis, sequence archiving, a user-friendly UniProt website and the provision of additional value-added information through cross-references to other databases. UniProt is comprised of four major components, each optimized for different uses: the UniProt Archive, the UniProt Knowledgebase, the UniProt Reference Clusters and the UniProt Metagenomic and Environmental Sequence Database. One of the key achievements of the UniProt consortium in 2008 is the completion of the first draft of the complete human proteome in UniProtKB/Swiss-Prot. This manually annotated representation of all currently known human protein-coding genes was made available in UniProt release 14.0 with 20 325 entries. UniProt is updated and distributed every three weeks and can be accessed online for searches or downloaded at www.uniprot.org.
            Article 0 comments Cited 225 times – based on 0 reviews     Review now
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              Pathogenic or not? And if so, then how? Studying the effects of missense mutations using bioinformatics methods.

              Mauno Vihinen, Janita Thusberg (2009)
              Many gene defects are relatively easy to identify experimentally, but obtaining information about the effects of sequence variations and elucidation of the detailed molecular mechanisms of genetic diseases will be among the next major efforts in mutation research. Amino acid substitutions may have diverse effects on protein structure and function; thus, a detailed analysis of the mutations is essential. Experimental study of the molecular effects of mutations is laborious, whereas useful and reliable information about the effects of amino acid substitutions can readily be obtained by theoretical methods. Experimentally defined structures and molecular modeling can be used as a basis for interpretation of the mutations. The effects of missense mutations can be analyzed even when the 3D structure of the protein has not been determined, although structure-based analyses are more reliable. Structural analyses include studies of the contacts between residues, their implication for the stability of the protein, and the effects of the introduced residues. Investigations of steric and stereochemical consequences of substitutions provide insights on the molecular fit of the introduced residue. Mutations that change the electrostatic surface potential of a protein have wide-ranging effects. Analyses of the effects of mutations on interactions with ligands and partners have been performed for elucidation of functional mutations. We have employed numerous methods for predicting the effects of amino acid substitutions. We discuss the applicability of these methods in the analysis of genes, proteins, and diseases to reveal protein structure-function relationships, which is essential to gain insights into disease genotype-phenotype correlations. Copyright 2009 Wiley-Liss, Inc.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Bioinformatics
                Journal ID (publisher-id): bioinformatics
                Journal ID (hwp): bioinfo
                Title: Bioinformatics
                Publisher: Oxford University Press
                ISSN (Print): 1367-4803
                ISSN (Electronic): 1367-4811
                Publication date (Print): 15 March 2010
                Publication date (Electronic): 26 January 2010
                Publication date PMC-release: 26 January 2010
                Volume: 26
                Issue: 6
                Pages: 851-852
                Affiliations
                1 Swiss Institute of Bioinformatics and 2 Department of Structural Biology and Bioinformatics, Centre Médical Universitaire, 1, rue Michel-Servet, 1211 Geneva 4, Switzerland
                Author notes
                * To whom correspondence should be addressed.

                Associate Editor: Dmitrij Frishman

                Article
                Publisher ID: btq028
                DOI: 10.1093/bioinformatics/btq028
                PMC ID: 2832822
                PubMed ID: 20106818
                SO-VID: 7e998ec9-d4f4-4075-a1f8-0548ac704e77
                Copyright © © The Author(s) 2010. Published by Oxford University Press.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 24 November 2009
                Date revision received : 18 January 2010
                Date accepted : 19 January 2010
                Categories
                Subject: Applications Note
                Subject: Databases and Ontologies

                ScienceOpen disciplines: Bioinformatics & Computational biology
                Data availability:
                ScienceOpen disciplines: Bioinformatics & Computational biology

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