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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
Improving Molecular Properties Prediction Through Latent Space FusionCode2
A Systematic Survey of Chemical Pre-trained ModelsCode2
MHG-GNN: Combination of Molecular Hypergraph Grammar with Graph Neural NetworkCode2
Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language ModelsCode2
Generative Artificial Intelligence for Navigating Synthesizable Chemical SpaceCode2
Generalizable, Fast, and Accurate DeepQSPR with fastpropCode2
Deconstructing equivariant representations in molecular systemsCode2
A Text-guided Protein Design FrameworkCode2
Analyzing Learned Molecular Representations for Property PredictionCode2
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