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      • Record: found
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      CLIMB (the Cloud Infrastructure for Microbial Bioinformatics): an online resource for the medical microbiology community

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          Abstract

          The increasing availability and decreasing cost of high-throughput sequencing has transformed academic medical microbiology, delivering an explosion in available genomes while also driving advances in bioinformatics. However, many microbiologists are unable to exploit the resulting large genomics datasets because they do not have access to relevant computational resources and to an appropriate bioinformatics infrastructure. Here, we present the Cloud Infrastructure for Microbial Bioinformatics (CLIMB) facility, a shared computing infrastructure that has been designed from the ground up to provide an environment where microbiologists can share and reuse methods and data.

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          Biology: The big challenges of big data.

          Vivien Marx (2013)
          Article 0 comments Cited 309 times – based on 0 reviews     Review now
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            The iPlant Collaborative: Cyberinfrastructure for Plant Biology

            Stephen A. Goff, Matthew Vaughn, Sheldon McKay … (2011)
            The iPlant Collaborative (iPlant) is a United States National Science Foundation (NSF) funded project that aims to create an innovative, comprehensive, and foundational cyberinfrastructure in support of plant biology research (PSCIC, 2006). iPlant is developing cyberinfrastructure that uniquely enables scientists throughout the diverse fields that comprise plant biology to address Grand Challenges in new ways, to stimulate and facilitate cross-disciplinary research, to promote biology and computer science research interactions, and to train the next generation of scientists on the use of cyberinfrastructure in research and education. Meeting humanity's projected demands for agricultural and forest products and the expectation that natural ecosystems be managed sustainably will require synergies from the application of information technologies. The iPlant cyberinfrastructure design is based on an unprecedented period of research community input, and leverages developments in high-performance computing, data storage, and cyberinfrastructure for the physical sciences. iPlant is an open-source project with application programming interfaces that allow the community to extend the infrastructure to meet its needs. iPlant is sponsoring community-driven workshops addressing specific scientific questions via analysis tool integration and hypothesis testing. These workshops teach researchers how to add bioinformatics tools and/or datasets into the iPlant cyberinfrastructure enabling plant scientists to perform complex analyses on large datasets without the need to master the command-line or high-performance computational services.
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              Species-wide whole genome sequencing reveals historical global spread and recent local persistence in Shigella flexneri

              Thomas R. Connor, François-Xavier Weill, Kaisar Talukder … (2015)
              Shigella flexneri is the most common cause of bacterial dysentery in low-income countries. Despite this, S. flexneri remains largely unexplored from a genomic standpoint and is still described using a vocabulary based on serotyping reactions developed over half-a-century ago. Here we combine whole genome sequencing with geographical and temporal data to examine the natural history of the species. Our analysis subdivides S. flexneri into seven phylogenetic groups (PGs); each containing two-or-more serotypes and characterised by distinct virulence gene complement and geographic range. Within the S. flexneri PGs we identify geographically restricted sub-lineages that appear to have persistently colonised regions for many decades to over 100 years. Although we found abundant evidence of antimicrobial resistance (AMR) determinant acquisition, our dataset shows no evidence of subsequent intercontinental spread of antimicrobial resistant strains. The pattern of colonisation and AMR gene acquisition suggest that S. flexneri has a distinct life-cycle involving local persistence. DOI: http://dx.doi.org/10.7554/eLife.07335.001
              Article 0 comments Cited 58 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): Microb Genom
                Journal ID (iso-abbrev): Microb Genom
                Journal ID (publisher-id): MGen
                Title: Microbial Genomics
                Publisher: Microbiology Society
                ISSN (Electronic): 2057-5858
                Publication date Collection: September 2016
                Publication date (Electronic): 20 September 2016
                Volume: 2
                Issue: 9
                Electronic Location Identifier: e000086
                Affiliations
                [ 1​ ]Cardiff University School of Biosciences, The Sir Martin Evans Building, Cardiff University , Cardiff CF10 2AX, UK
                [ 2​ ]Institute of Microbiology and Infection, University of Birmingham , Birmingham B15 2TT, UK
                [ 3​ ]IT Services (Research Computing), University of Birmingham , Birmingham B15 2TT, UK
                [ 4​ ]Centre for Scientific Computing, University of Warwick , Coventry CV4 7AL, UK
                [ 5​ ]College of Medicine, Swansea University , Swansea, UK
                [ 6​ ]Advanced Research Computing@Cardiff (ARCCA) , Cardiff University, UK
                [ 7​ ]Microbiology and Infection Unit, Warwick Medical School, University of Warwick , Coventry, UK
                [ 8​ ]The Milner Centre for Evolution, Department of Biology and Biochemistry, University of Bath , Bath BA2 7AY, UK
                Author notes
                Correspondence Thomas R. Connor ( ConnorTR@ 123456cardiff.ac.uk )
                Nicholas J. Loman ( n.j.loman@ 123456bham.ac.uk )
                [†]

                These authors contributed equally to this work.

                All supporting data, code and protocols have been provided within the article or through

                supplementary data files.

                Article
                Publisher ID: mgen000086
                DOI: 10.1099/mgen.0.000086
                PMC ID: 5537631
                PubMed ID: 28785418
                SO-VID: fe997741-2171-4935-a01d-cbb545a77ecb
                Copyright © © 2016 The Authors
                License:

                This is an open access article under the terms of the Creative Commons Attribution 4.04.0 International License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 26 July 2016
                Date accepted : 21 August 2016
                Funding
                Funded by: Medical Research Council
                Award ID: MR/L015080/1
                Funded by: Medical Research Council
                Award ID: MR/L015080/1
                Funded by: Biotechnology and Biological Sciences Research Council
                Award ID: BB/L024209/1
                Funded by: Biotechnology and Biological Sciences Research Council
                Award ID: BB/L024209/1
                Funded by: Cardiff University
                Award ID: CUROP
                Funded by: Medical Research Council
                Award ID: MR/L015080/1
                Funded by: Medical Research Council
                Award ID: MR/L015080/1
                Funded by: Biotechnology and Biological Sciences Research Council
                Award ID: BB/L024209/1
                Funded by: Medical Research Council
                Award ID: MR/L015080/1
                Funded by: Medical Research Council
                Award ID: MR/L015080/1
                Funded by: Medical Research Council
                Award ID: MR/L015080/1
                Categories
                Subject: Short Paper
                Subject: Systems Microbiology: Pangenome analysis, big-data approaches
                Custom metadata
                OpenAccessEmbargo 0

                Keywords: cloud computing,bioinformatics,infrastructure,metagenomics,population genomics,virtual laboratory
                Data availability:
                Keywords: cloud computing, bioinformatics, infrastructure, metagenomics, population genomics, virtual laboratory

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