ReLMole: Molecular Representation Learning Based on Two-Level Graph Similarities

Molecular representation is a critical part of various prediction tasks for physicochemical properties of molecules and drug design. As graph notations are common in expressing the structural information of chemical compounds, graph neural networks (GNNs) have become the mainstream backbone model fo...

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Veröffentlicht in:	Journal of chemical information and modeling 2022-11, Vol.62 (22), p.5361-5372
Hauptverfasser:	Ji, Zewei, Shi, Runhan, Lu, Jiarui, Li, Fang, Yang, Yang
Format:	Artikel
Sprache:	eng
Schlagworte:	Chemical compounds Domains Graph neural networks Graphical representations Learning Machine Learning and Deep Learning Similarity
Online-Zugang:	Volltext
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