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      PATRIC, the bacterial bioinformatics database and analysis resource

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          Abstract

          The Pathosystems Resource Integration Center (PATRIC) is the all-bacterial Bioinformatics Resource Center (BRC) ( http://www.patricbrc.org). A joint effort by two of the original National Institute of Allergy and Infectious Diseases-funded BRCs, PATRIC provides researchers with an online resource that stores and integrates a variety of data types [e.g. genomics, transcriptomics, protein–protein interactions (PPIs), three-dimensional protein structures and sequence typing data] and associated metadata. Datatypes are summarized for individual genomes and across taxonomic levels. All genomes in PATRIC, currently more than 10 000, are consistently annotated using RAST, the Rapid Annotations using Subsystems Technology. Summaries of different data types are also provided for individual genes, where comparisons of different annotations are available, and also include available transcriptomic data. PATRIC provides a variety of ways for researchers to find data of interest and a private workspace where they can store both genomic and gene associations, and their own private data. Both private and public data can be analyzed together using a suite of tools to perform comparative genomic or transcriptomic analysis. PATRIC also includes integrated information related to disease and PPIs. All the data and integrated analysis and visualization tools are freely available. This manuscript describes updates to the PATRIC since its initial report in the 2007 NAR Database Issue.

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          Most cited references31

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          The Proteomics Identifications (PRIDE) database and associated tools: status in 2013

          The PRoteomics IDEntifications (PRIDE, http://www.ebi.ac.uk/pride) database at the European Bioinformatics Institute is one of the most prominent data repositories of mass spectrometry (MS)-based proteomics data. Here, we summarize recent developments in the PRIDE database and related tools. First, we provide up-to-date statistics in data content, splitting the figures by groups of organisms and species, including peptide and protein identifications, and post-translational modifications. We then describe the tools that are part of the PRIDE submission pipeline, especially the recently developed PRIDE Converter 2 (new submission tool) and PRIDE Inspector (visualization and analysis tool). We also give an update about the integration of PRIDE with other MS proteomics resources in the context of the ProteomeXchange consortium. Finally, we briefly review the quality control efforts that are ongoing at present and outline our future plans.
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            NCBI Reference Sequences (RefSeq): current status, new features and genome annotation policy

            The National Center for Biotechnology Information (NCBI) Reference Sequence (RefSeq) database is a collection of genomic, transcript and protein sequence records. These records are selected and curated from public sequence archives and represent a significant reduction in redundancy compared to the volume of data archived by the International Nucleotide Sequence Database Collaboration. The database includes over 16 000 organisms, 2.4 × 106 genomic records, 13 × 106 proteins and 2 × 106 RNA records spanning prokaryotes, eukaryotes and viruses (RefSeq release 49, September 2011). The RefSeq database is maintained by a combined approach of automated analyses, collaboration and manual curation to generate an up-to-date representation of the sequence, its features, names and cross-links to related sources of information. We report here on recent growth, the status of curating the human RefSeq data set, more extensive feature annotation and current policy for eukaryotic genome annotation via the NCBI annotation pipeline. More information about the resource is available online (see http://www.ncbi.nlm.nih.gov/RefSeq/).
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              ARDB—Antibiotic Resistance Genes Database

              The treatment of infections is increasingly compromised by the ability of bacteria to develop resistance to antibiotics through mutations or through the acquisition of resistance genes. Antibiotic resistance genes also have the potential to be used for bio-terror purposes through genetically modified organisms. In order to facilitate the identification and characterization of these genes, we have created a manually curated database—the Antibiotic Resistance Genes Database (ARDB)—unifying most of the publicly available information on antibiotic resistance. Each gene and resistance type is annotated with rich information, including resistance profile, mechanism of action, ontology, COG and CDD annotations, as well as external links to sequence and protein databases. Our database also supports sequence similarity searches and implements an initial version of a tool for characterizing common mutations that confer antibiotic resistance. The information we provide can be used as compendium of antibiotic resistance factors as well as to identify the resistance genes of newly sequenced genes, genomes, or metagenomes. Currently, ARDB contains resistance information for 13 293 genes, 377 types, 257 antibiotics, 632 genomes, 933 species and 124 genera. ARDB is available at http://ardb.cbcb.umd.edu/.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                January 2014
                12 November 2013
                12 November 2013
                : 42
                : D1 , Database issue
                : D581-D591
                Affiliations
                1Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, 2Computation Institute, University of Chicago, Chicago, IL 60637, USA, 3Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60637, USA, 4Grado Department of Industrial & Systems Engineering, Virginia Tech, Blacksburg, VA 24060, USA, 5Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, USA, 6Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527, USA, 7Computing, Environment, and Life Sciences, Argonne National Laboratory, Argonne, IL 60637, USA and 8Nestlé Institute of Health Sciences SA, Campus EPFL, Quartier de L'innovation, Lausanne, Switzerland
                Author notes
                *To whom correspondence should be addressed. Tel: +1 540 231 1263; Fax: +1 540 231 2606; Email: wattam@ 123456vbi.vt.edu

                Present address: Alice R. Wattam, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA.

                Article
                gkt1099
                10.1093/nar/gkt1099
                3965095
                24225323
                b7844ad6-84c6-4ba7-b06b-caabfb4fe0ac
                © The Author(s) 2013. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 11 September 2013
                : 18 October 2013
                : 18 October 2013
                Page count
                Pages: 11
                Categories
                IV. Viruses, bacteria, protozoa and fungi
                Custom metadata
                1 January 2014

                Genetics
                Genetics

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