Cartography-Driven Molecular Generation with ChemSpace Atlas

被引：0
|
作者：
Bonachera, Fanny [1 ]
Volkov, Mikhail [1 ]
Horvath, Dragos [1 ]
Marcou, Gilles [1 ]
Klimchuk, Olga [1 ]
Varnek, Alexandre [1 ]
机构：
[1] Univ Strasbourg, UniStra, CNRS, UMR7140,Lab Chemoinformat, Strasbourg, France
来源：
AI IN DRUG DISCOVERY, AIDD 2024 | 2025年 / 14894卷
关键词：
Chemoinformatics; Big Data; Deep Learning;
D O I：
10.1007/978-3-031-72381-0
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The ChemSpace Atlas is a user-friendly tool developed to answer the challenges of drug discovery in the context of Big Data, with the use of Generative Topographic Mapping. Here, we present a new addition to the functionalities offered by the ChemSpace Atlas: an autoencoder-based de novo molecular generator.
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页码：161 / 164
页数：4
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