Exploring Deep Learning for Metalloporphyrins: Databases, Molecular Representations, and Model Architectures

Exploring Deep Learning for Metalloporphyrins: Databases, Molecular Representations, and Model Architectures

Metalloporphyrins have been studied as biomimetic catalysts for more than 120 years and have accumulated a large amount of data, which provides a solid foundation for deep learning to discover chemical trends and structure–function relationships. In this study, key components of deep learning of met...

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Bibliographic Details
Main Authors: An Su, Chengwei Zhang, Yuan-Bin She, Yun-Fang Yang
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Catalysts
Subjects:
metalloporphyrin
database
molecular representation
deep learning
property prediction
Online Access:https://www.mdpi.com/2073-4344/12/11/1485

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