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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 110 of 691 papers

TitleStatusHype
Molecular Fingerprints Are Strong Models for Peptide Function PredictionCode3
DARWIN 1.5: Large Language Models as Materials Science Adapted LearnersCode3
Scikit-fingerprints: easy and efficient computation of molecular fingerprints in PythonCode3
A Review of Large Language Models and Autonomous Agents in ChemistryCode3
^2DFT: A Universal Quantum Chemistry Dataset of Drug-Like Molecules and a Benchmark for Neural Network PotentialsCode3
A Python library for efficient computation of molecular fingerprintsCode3
Leveraging Biomolecule and Natural Language through Multi-Modal Learning: A SurveyCode3
Uni-QSAR: an Auto-ML Tool for Molecular Property PredictionCode3
Highly Accurate Quantum Chemical Property Prediction with Uni-Mol+Code3
TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug DiscoveryCode3
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