Enhancing chemical reaction search through contrastive representation learning and human-in-the-loop

Enhancing chemical reaction search through contrastive representation learning and human-in-the-loop

Abstract In synthesis planning, identifying and optimizing chemical reactions are important for the successful design of synthetic pathways to target substances. Chemical reaction databases assist chemists in gaining insights into this process. Traditionally, searching for relevant records from a re...

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Bibliographic Details
Main Authors: Youngchun Kwon, Hyunjeong Jeon, Joonhyuk Choi, Youn-Suk Choi, Seokho Kang
Format: Article
Language:English
Published: BMC 2025-04-01
Series:Journal of Cheminformatics
Subjects:
Chemical reaction search
Contrastive learning
Human-in-the-loop
Graph neural network
Online Access:https://doi.org/10.1186/s13321-025-00987-5
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