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支架猎手:一个用于药物发现的综合可视化分析框架。

Scaffold Hunter: a comprehensive visual analytics framework for drug discovery.

作者信息

Schäfer Till, Kriege Nils, Humbeck Lina, Klein Karsten, Koch Oliver, Mutzel Petra

机构信息

Department of Computer Science, TU Dortmund University, Otto-Hahn-Str. 14, Dortmund, 44227, Germany.

Faculty of Chemistry and Chemical Biology, TU Dortmund University, Otto-Hahn-Str. 6, Dortmund, 44227, Germany.

出版信息

J Cheminform. 2017 May 11;9(1):28. doi: 10.1186/s13321-017-0213-3.

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.

摘要

大数据时代正在影响合理药物发现和生物活性分子开发的开展方式,需要多种工具来辅助分子设计工作流程。支架猎手(Scaffold Hunter)是一个用于分析化合物数据的灵活视觉分析框架,它结合了数据挖掘和信息可视化等多个领域的技术。该框架允许以交互方式分析高维化合物数据,将直观的可视化与包括多种聚类方法在内的自动化分析方法相结合。支架猎手最初设计用于分析支架树,目前正在不断修订和扩展。我们描述了最近的扩展,这些扩展显著提高了其在各种任务中的适用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5ad/5425364/b6a5cdba57e5/13321_2017_213_Fig1_HTML.jpg

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