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      Bioboxes: standardised containers for interchangeable bioinformatics software

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          Abstract

          Software is now both central and essential to modern biology, yet lack of availability, difficult installations, and complex user interfaces make software hard to obtain and use. Containerisation, as exemplified by the Docker platform, has the potential to solve the problems associated with sharing software. We propose bioboxes: containers with standardised interfaces to make bioinformatics software interchangeable.

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          Most cited references 7

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          Creating a bioinformatics nation.

           Lincoln Stein (2002)
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            An introduction to Docker for reproducible research, with examples from the R environment

            As computational work becomes more and more integral to many aspects of scientific research, computational reproducibility has become an issue of increasing importance to computer systems researchers and domain scientists alike. Though computational reproducibility seems more straight forward than replicating physical experiments, the complex and rapidly changing nature of computer environments makes being able to reproduce and extend such work a serious challenge. In this paper, I explore common reasons that code developed for one research project cannot be successfully executed or extended by subsequent researchers. I review current approaches to these issues, including virtual machines and workflow systems, and their limitations. I then examine how the popular emerging technology Docker combines several areas from systems research - such as operating system virtualization, cross-platform portability, modular re-usable elements, versioning, and a `DevOps' philosophy, to address these challenges. I illustrate this with several examples of Docker use with a focus on the R statistical environment.
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              Scholarly Context Not Found: One in Five Articles Suffers from Reference Rot

              The emergence of the web has fundamentally affected most aspects of information communication, including scholarly communication. The immediacy that characterizes publishing information to the web, as well as accessing it, allows for a dramatic increase in the speed of dissemination of scholarly knowledge. But, the transition from a paper-based to a web-based scholarly communication system also poses challenges. In this paper, we focus on reference rot, the combination of link rot and content drift to which references to web resources included in Science, Technology, and Medicine (STM) articles are subject. We investigate the extent to which reference rot impacts the ability to revisit the web context that surrounds STM articles some time after their publication. We do so on the basis of a vast collection of articles from three corpora that span publication years 1997 to 2012. For over one million references to web resources extracted from over 3.5 million articles, we determine whether the HTTP URI is still responsive on the live web and whether web archives contain an archived snapshot representative of the state the referenced resource had at the time it was referenced. We observe that the fraction of articles containing references to web resources is growing steadily over time. We find one out of five STM articles suffering from reference rot, meaning it is impossible to revisit the web context that surrounds them some time after their publication. When only considering STM articles that contain references to web resources, this fraction increases to seven out of ten. We suggest that, in order to safeguard the long-term integrity of the web-based scholarly record, robust solutions to combat the reference rot problem are required. In conclusion, we provide a brief insight into the directions that are explored with this regard in the context of the Hiberlink project.
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                Author and article information

                Affiliations
                [ ]Faculty of Technology and Center for Biotechnology, Bielefeld University, 33615 Bielefeld, Germany
                [ ]Computational Biology of Infection Research, Helmholtz Centre for Infection Research, 38124 Braunschweig, Germany
                [ ]DOE Joint Genome Institute, Walnut Creek, CA 94598 USA
                Contributors
                pbelmann@cebitec.uni-bielefeld.de
                johannes.droege@uni-duesseldorf.de
                andreas@cebitec.uni-bielefeld.de
                alice.mchardy@uni-duesseldorf.de
                asczyrba@cebitec.uni-bielefeld.de
                mail@michaelbarton.me.uk
                Journal
                Gigascience
                Gigascience
                GigaScience
                BioMed Central (London )
                2047-217X
                15 October 2015
                15 October 2015
                2015
                : 4
                4607242 87 10.1186/s13742-015-0087-0
                © Belmann et al. 2015

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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