Exploring Chemical Reaction Space with Machine Learning Models: Representation and Feature Perspective

Chemical reactions serve as foundational building blocks for organic chemistry and drug design. In the era of large AI models, data-driven approaches have emerged to innovate the design of novel reactions, optimize existing ones for higher yields, and discover new pathways for synthesizing chemical...

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Veröffentlicht in:	Journal of chemical information and modeling 2024-04, Vol.64 (8), p.2955-2970
Hauptverfasser:	Ding, Yuheng, Qiang, Bo, Chen, Qixuan, Liu, Yiqiao, Zhang, Liangren, Liu, Zhenming
Format:	Artikel
Sprache:	eng
Schlagworte:	Chemical fingerprinting Chemical reactions Chemical synthesis Design optimization Machine Learning Models, Chemical Organic chemistry Representations
Online-Zugang:	Volltext
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