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      Database resources of the National Center for Biotechnology Information

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          Abstract

          The National Center for Biotechnology Information (NCBI) provides a large suite of online resources for biological information and data, including the GenBank ® nucleic acid sequence database and the PubMed database of citations and abstracts published in life science journals. The Entrez system provides search and retrieval operations for most of these data from 38 distinct databases. The E-utilities serve as the programming interface for the Entrez system. Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized data sets. New resources released in the past year include PubMed Labs and a new sequence database search. Resources that were updated in the past year include PubMed, PMC, Bookshelf, genome data viewer, Assembly, prokaryotic genomes, Genome, BioProject, dbSNP, dbVar, BLAST databases, igBLAST, iCn3D and PubChem. All of these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.

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          GenBank

          Dennis A Benson, Mark Cavanaugh, Karen Clark … (2017)
          Abstract GenBank® (www.ncbi.nlm.nih.gov/genbank/) is a comprehensive database that contains publicly available nucleotide sequences for 400 000 formally described species. These sequences are obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects, including whole genome shotgun and environmental sampling projects. Most submissions are made using BankIt, the National Center for Biotechnology Information (NCBI) Submission Portal, or the tool tbl2asn. GenBank staff assign accession numbers upon data receipt. Daily data exchange with the European Nucleotide Archive and the DNA Data Bank of Japan ensures worldwide coverage. GenBank is accessible through the NCBI Nucleotide database, which links to related information such as taxonomy, genomes, protein sequences and structures, and biomedical journal literature in PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP. Recent updates include changes to sequence identifiers, submission wizards for 16S and Influenza sequences, and an Identical Protein Groups resource.
          Article 0 comments Cited 307 times – based on 0 reviews     Review now
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            Is Open Access

            SKESA: strategic k-mer extension for scrupulous assemblies

            Alexandre Souvorov, Richa Agarwala, David Lipman (2018)
            SKESA is a DeBruijn graph-based de-novo assembler designed for assembling reads of microbial genomes sequenced using Illumina. Comparison with SPAdes and MegaHit shows that SKESA produces assemblies that have high sequence quality and contiguity, handles low-level contamination in reads, is fast, and produces an identical assembly for the same input when assembled multiple times with the same or different compute resources. SKESA has been used for assembling over 272,000 read sets in the Sequence Read Archive at NCBI and for real-time pathogen detection. Source code for SKESA is freely available at https://github.com/ncbi/SKESA/releases. Electronic supplementary material The online version of this article (10.1186/s13059-018-1540-z) contains supplementary material, which is available to authorized users.
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              Track data hubs enable visualization of user-defined genome-wide annotations on the UCSC Genome Browser

              Brian Raney, Timothy Dreszer, Galt Barber … (2013)
              Summary: Track data hubs provide an efficient mechanism for visualizing remotely hosted Internet-accessible collections of genome annotations. Hub datasets can be organized, configured and fully integrated into the University of California Santa Cruz (UCSC) Genome Browser and accessed through the familiar browser interface. For the first time, individuals can use the complete browser feature set to view custom datasets without the overhead of setting up and maintaining a mirror. Availability and implementation: Source code for the BigWig, BigBed and Genome Browser software is freely available for non-commercial use at http://hgdownload.cse.ucsc.edu/admin/jksrc.zip, implemented in C and supported on Linux. Binaries for the BigWig and BigBed creation and parsing utilities may be downloaded at http://hgdownload.cse.ucsc.edu/admin/exe/. Binary Alignment/Map (BAM) and Variant Call Format (VCF)/tabix utilities are available from http://samtools.sourceforge.net/ and http://vcftools.sourceforge.net/. The UCSC Genome Browser is publicly accessible at http://genome.ucsc.edu. Contact: donnak@soe.ucsc.edu
              Article 0 comments Cited 239 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): Nucleic Acids Res
                Journal ID (iso-abbrev): Nucleic Acids Res
                Journal ID (publisher-id): nar
                Title: Nucleic Acids Research
                Publisher: Oxford University Press
                ISSN (Print): 0305-1048
                ISSN (Electronic): 1362-4962
                Publication date (Print): 08 January 2019
                Publication date (Electronic): 05 November 2018
                Publication date PMC-release: 05 November 2018
                Volume: 47
                Issue: Database issue , Database issue
                Pages: D23-D28
                Affiliations
                National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
                Author notes
                To whom correspondence should be addressed. Tel: +1 301 496 2475; Fax: +1 301 480 9241; Email: sayers@ 123456ncbi.nlm.nih.gov
                Article
                Publisher ID: gky1069
                DOI: 10.1093/nar/gky1069
                PMC ID: 6323993
                PubMed ID: 30395293
                SO-VID: 7d69046d-e783-4e8f-b21c-53c500c3a7ed
                Copyright © Published by Oxford University Press on behalf of Nucleic Acids Research 2018.
                License:

                This work is written by (a) US Government employee(s) and is in the public domain in the US.

                History
                Date accepted : 18 October 2018
                Date revision received : 17 October 2018
                Date received : 19 September 2018
                Page count
                Pages: 6
                Funding
                Funded by: National Institutes of Health 10.13039/100000002
                Categories
                Subject: Database Issue

                ScienceOpen disciplines: Genetics
                Data availability:
                ScienceOpen disciplines: Genetics

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