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Property Prediction

Property prediction involves forecasting or estimating a molecule's inherent physical and chemical properties based on information derived from its structural characteristics. It facilitates high-throughput evaluation of an extensive array of molecular properties, enabling the virtual screening of compounds. Additionally, it provides the means to predict the unknown attributes of new molecules, thereby bolstering research efficiency and reducing development times.

Papers

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Showing 411–420 of 691 papers

TitleStatusHype
Knowledge-aware contrastive heterogeneous molecular graph learning—0
Knowledge-aware Contrastive Molecular Graph Learning—0
Knowledge graph-enhanced molecular contrastive learning with functional prompt—0
Knowledge-informed Molecular Learning: A Survey on Paradigm Transfer—0
Language model driven: a PROTAC generation pipeline with dual constraints of structure and property—0
Language models in molecular discovery—0
Large Language Model Agent for Modular Task Execution in Drug Discovery—0
Latent Tree Decomposition Parsers for AMR-to-Text Generation—0
Learning Invariances in Neural Networks from Training Data—0
Learning Metal Microstructural Heterogeneity through Spatial Mapping of Diffraction Latent Space Features—0
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