文章基本信息

标题：Scaffold Hunter: a comprehensive visual analytics framework for drug discovery
本地全文：下载
作者：Till Schäfer ; Nils Kriege ; Lina Humbeck 等
期刊名称：Journal of Cheminformatics
印刷版ISSN：1758-2946
电子版ISSN：1758-2946
出版年度：2017
卷号：9
期号：1
页码：28
DOI：10.1186/s13321-017-0213-3
语种：English
出版社：BioMed Central
摘要：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.
关键词：Visualization ; Chemical space ; Scaffold tree ; Molecule cloud ; Clustering