Understanding the evolution of a de novo molecule generator via characteristic functional group monitoring

Understanding the evolution of a de novo molecule generator via characteristic functional group monitoring

Recently, artificial intelligence (AI)-enabled de novo molecular generators (DNMGs) have automated molecular design based on data-driven or simulation-based property estimates. In some domains like the game of Go where AI surpassed human intelligence, humans are trying to learn from AI about the bes...

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Bibliographic Details
Main Authors: Takehiro Fujita, Kei Terayama, Masato Sumita, Ryo Tamura, Yasuyuki Nakamura, Masanobu Naito, Koji Tsuda
Format: Article
Language:English
Published: Taylor & Francis Group 2022-12-01
Series:Science and Technology of Advanced Materials
Subjects:
characteristic functional group monitoring
chromophore
De novo molecule generation
deep learning
Online Access:https://www.tandfonline.com/doi/10.1080/14686996.2022.2075240

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