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.

引用

页码：161 / 164

页数：4

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