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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

Showing 1120 of 691 papers

TitleStatusHype
M^3-20M: A Large-Scale Multi-Modal Molecule Dataset for AI-driven Drug Design and DiscoveryCode2
A Systematic Survey of Chemical Pre-trained ModelsCode2
Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language ModelsCode2
MHG-GNN: Combination of Molecular Hypergraph Grammar with Graph Neural NetworkCode2
Generative Artificial Intelligence for Navigating Synthesizable Chemical SpaceCode2
Identity-aware Graph Neural NetworksCode2
Deconstructing equivariant representations in molecular systemsCode2
Descriptor-based Foundation Models for Molecular Property PredictionCode2
A Text-guided Protein Design FrameworkCode2
Analyzing Learned Molecular Representations for Property PredictionCode2
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