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      Scaffold Hunter: a comprehensive visual analytics framework for drug discovery

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          Abstract

          The era of big data is influencing the way how rational drug discovery and the development of bioactive molecules is performed and versatile tools are needed to assist in molecular design workflows. Scaffold Hunter is a flexible visual analytics framework for the analysis of chemical compound data and combines techniques from several fields such as data mining and information visualization. The framework allows analyzing high-dimensional chemical compound data in an interactive fashion, combining intuitive visualizations with automated analysis methods including versatile clustering methods. Originally designed to analyze the scaffold tree, Scaffold Hunter is continuously revised and extended. We describe recent extensions that significantly increase the applicability for a variety of tasks.

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          Most cited references30

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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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            The History of the Cluster Heat Map

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              PubChem BioAssay: 2014 update

              PubChem’s BioAssay database (http://pubchem.ncbi.nlm.nih.gov) is a public repository for archiving biological tests of small molecules generated through high-throughput screening experiments, medicinal chemistry studies, chemical biology research and drug discovery programs. In addition, the BioAssay database contains data from high-throughput RNA interference screening aimed at identifying critical genes responsible for a biological process or disease condition. The mission of PubChem is to serve the community by providing free and easy access to all deposited data. To this end, PubChem BioAssay is integrated into the National Center for Biotechnology Information retrieval system, making them searchable by Entrez queries and cross-linked to other biomedical information archived at National Center for Biotechnology Information. Moreover, PubChem BioAssay provides web-based and programmatic tools allowing users to search, access and analyze bioassay test results and metadata. In this work, we provide an update for the PubChem BioAssay resource, such as information content growth, new developments supporting data integration and search, and the recently deployed PubChem Upload to streamline chemical structure and bioassay submissions.
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                Author and article information

                Contributors
                till2.schaefer@tu-dortmund.de
                nils.kriege@tu-dortmund.de
                lina.humbeck@tu-dortmund.de
                karsten.klein@uni-konstanz.de
                oliver.koch@tu-dortmund.de , oliver.koch@agkoch.de
                petra.mutzel@tu-dortmund.de
                Journal
                J Cheminform
                J Cheminform
                Journal of Cheminformatics
                Springer International Publishing (Cham )
                1758-2946
                11 May 2017
                11 May 2017
                2017
                : 9
                : 28
                Affiliations
                [1 ]ISNI 0000 0001 0416 9637, GRID grid.5675.1, Faculty of Chemistry and Chemical Biology, , TU Dortmund University, ; Otto-Hahn-Str. 6, Dortmund, 44227 Germany
                [2 ]ISNI 0000 0001 0416 9637, GRID grid.5675.1, Department of Computer Science, , TU Dortmund University, ; Otto-Hahn-Str. 14, Dortmund, 44227 Germany
                [3 ]ISNI 0000 0001 0658 7699, GRID grid.9811.1, Department of Computer and Information Science, , University of Konstanz, ; Universitaetsstrasse 10, Konstanz, 78464 Germany
                Author information
                http://orcid.org/0000-0003-1709-1925
                http://orcid.org/0000-0003-2645-947X
                http://orcid.org/0000-0003-3151-9158
                http://orcid.org/0000-0002-8345-5806
                http://orcid.org/0000-0001-9228-217X
                http://orcid.org/0000-0001-7621-971X
                Article
                213
                10.1186/s13321-017-0213-3
                5425364
                29086162
                05a47c15-ae69-426e-aab6-91c67819c90f
                © The Author(s) 2017

                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.

                History
                : 16 October 2016
                : 10 April 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft;
                Award ID: SPP 1736
                Award ID: SPP 1736
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100002347, Bundesministerium für Bildung und Forschung;
                Award ID: 1316053
                Award Recipient :
                Categories
                Software
                Custom metadata
                © The Author(s) 2017

                Chemoinformatics
                visualization,chemical space,scaffold tree,molecule cloud,clustering
                Chemoinformatics
                visualization, chemical space, scaffold tree, molecule cloud, clustering

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