ChemPlot, a Python']Python Library for Chemical Space Visualization

被引:0
作者
Sorkun, Murat Cihan
Mullaj, Dajt
Koelman, J. M. Vianney A.
Er, Sueleyman [1 ]
机构
[1] DIFFER Dutch Inst Fundamental Energy Res, De Zaale 20, NL-5612 AJ Eindhoven, Netherlands
来源
CHEMISTRY-METHODS | 2022年 / 2卷 / 07期
基金
荷兰研究理事会;
关键词
chemical space visualization; cheminformatics; molecular similarity; !text type='Python']Python[!/text; tailored similarity;
D O I
10.1002/cmtd.202200038
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Invited for this month's cover is the Autonomous Energy Materials Discovery [AMD] Group of Dr. Suleyman Er at DIFFER, and colleagues at CCER and Eindhoven University of Technology (Netherlands). The cover picture shows the ChemPlot-visualized reduced chemical space of molecules enhanced with two-dimensional illustrations of molecules. In addition to being easy-to-use, free and open source, a noteworthy feature of ChemPlot is the application of tailored similarity for the property-sensitive visualization of chemical spaces. ChemPlot streamlines the analysis of molecular datasets by reducing the information to human perception level, tackling the activity/property cliff problem, and facilitating the assessment of the applicability domain of machine learning models in molecular studies. Read the full text of their Research Article at 10.1002/cmtd.202200005.
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页数:2
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