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      The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update

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          Abstract

          Galaxy (homepage: https://galaxyproject.org, main public server: https://usegalaxy.org) is a web-based scientific analysis platform used by tens of thousands of scientists across the world to analyze large biomedical datasets such as those found in genomics, proteomics, metabolomics and imaging. Started in 2005, Galaxy continues to focus on three key challenges of data-driven biomedical science: making analyses accessible to all researchers, ensuring analyses are completely reproducible, and making it simple to communicate analyses so that they can be reused and extended. During the last two years, the Galaxy team and the open-source community around Galaxy have made substantial improvements to Galaxy's core framework, user interface, tools, and training materials. Framework and user interface improvements now enable Galaxy to be used for analyzing tens of thousands of datasets, and >5500 tools are now available from the Galaxy ToolShed. The Galaxy community has led an effort to create numerous high-quality tutorials focused on common types of genomic analyses. The Galaxy developer and user communities continue to grow and be integral to Galaxy's development. The number of Galaxy public servers, developers contributing to the Galaxy framework and its tools, and users of the main Galaxy server have all increased substantially.

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          Most cited references28

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          High-resolution TADs reveal DNA sequences underlying genome organization in flies

          Despite an abundance of new studies about topologically associating domains (TADs), the role of genetic information in TAD formation is still not fully understood. Here we use our software, HiCExplorer (hicexplorer.readthedocs.io) to annotate >2800 high-resolution (570 bp) TAD boundaries in Drosophila melanogaster. We identify eight DNA motifs enriched at boundaries, including a motif bound by the M1BP protein, and two new boundary motifs. In contrast to mammals, the CTCF motif is only enriched on a small fraction of boundaries flanking inactive chromatin while most active boundaries contain the motifs bound by the M1BP or Beaf-32 proteins. We demonstrate that boundaries can be accurately predicted using only the motif sequences at open chromatin sites. We propose that DNA sequence guides the genome architecture by allocation of boundary proteins in the genome. Finally, we present an interactive online database to access and explore the spatial organization of fly, mouse and human genomes, available at http://chorogenome.ie-freiburg.mpg.de.
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            NGL Viewer: a web application for molecular visualization

            The NGL Viewer (http://proteinformatics.charite.de/ngl) is a web application for the visualization of macromolecular structures. By fully adopting capabilities of modern web browsers, such as WebGL, for molecular graphics, the viewer can interactively display large molecular complexes and is also unaffected by the retirement of third-party plug-ins like Flash and Java Applets. Generally, the web application offers comprehensive molecular visualization through a graphical user interface so that life scientists can easily access and profit from available structural data. It supports common structural file-formats (e.g. PDB, mmCIF) and a variety of molecular representations (e.g. ‘cartoon, spacefill, licorice’). Moreover, the viewer can be embedded in other web sites to provide specialized visualizations of entries in structural databases or results of structure-related calculations.
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              The Taverna workflow suite: designing and executing workflows of Web Services on the desktop, web or in the cloud

              The Taverna workflow tool suite (http://www.taverna.org.uk) is designed to combine distributed Web Services and/or local tools into complex analysis pipelines. These pipelines can be executed on local desktop machines or through larger infrastructure (such as supercomputers, Grids or cloud environments), using the Taverna Server. In bioinformatics, Taverna workflows are typically used in the areas of high-throughput omics analyses (for example, proteomics or transcriptomics), or for evidence gathering methods involving text mining or data mining. Through Taverna, scientists have access to several thousand different tools and resources that are freely available from a large range of life science institutions. Once constructed, the workflows are reusable, executable bioinformatics protocols that can be shared, reused and repurposed. A repository of public workflows is available at http://www.myexperiment.org. This article provides an update to the Taverna tool suite, highlighting new features and developments in the workbench and the Taverna Server.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                02 July 2018
                22 May 2018
                22 May 2018
                : 46
                : Web Server issue
                : W537-W544
                Affiliations
                [1 ]Department of Biology, Johns Hopkins University, Baltimore, MD, USA
                [2 ]Department of Computer Science, Albert-Ludwigs-University, Freiburg, Freiburg, Germany
                [3 ]Institut Curie, PSL Research University, Paris, France
                [4 ]Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA, USA
                [5 ]Center for Biological Systems Analysis (ZBSA), University of Freiburg, Freiburg, Germany
                [6 ]Department of Pathology, Erasmus Medical Center, Rotterdam, The Netherlands
                [7 ]Department of Biomedical Engineering, Oregon Health and Science University, OR, USA
                [8 ]Earlham Institute, Norwich Research Park, Norwich, UK
                [9 ]Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
                Author notes
                To whom correspondence should be addressed. Tel: +1 216 445 4336; Fax: +1 216 636 0009; Email: blanked2@ 123456ccf.org

                The authors wish it to be known that, in their opinion, all authors should be regarded as Joint First Authors.

                Author information
                http://orcid.org/0000-0002-3079-6586
                http://orcid.org/0000-0002-6833-9049
                Article
                gky379
                10.1093/nar/gky379
                6030816
                29790989
                baac9ad8-6d0a-4f6c-a8ec-73cc4773bd78
                © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 02 May 2018
                : 25 April 2018
                : 01 February 2018
                Page count
                Pages: 8
                Funding
                Funded by: National Institutes of Health 10.13039/100000002
                Award ID: HG006620
                Award ID: HG005133
                Award ID: HG004909
                Award ID: HG005542
                Funded by: NSF 10.13039/100003187
                Award ID: DBI 0543285
                Award ID: 0850103
                Award ID: 1661497
                Categories
                Web Server Issue

                Genetics
                Genetics

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