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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 481–490 of 691 papers

TitleStatusHype
QCS-ADME: Quantum Circuit Search for Drug Property Prediction with Imbalanced Data and Regression Adaptation—0
Quantum Machine Learning in Drug Discovery: Applications in Academia and Pharmaceutical Industries—0
QUBO-inspired Molecular Fingerprint for Chemical Property Prediction—0
Question Rephrasing for Quantifying Uncertainty in Large Language Models: Applications in Molecular Chemistry Tasks—0
Quotient Complex Transformer (QCformer) for Perovskite Data Analysis—0
Recent Developments in GNNs for Drug Discovery—0
ReGNet: Reciprocal Space-Aware Long-Range Modeling for Crystalline Property Prediction—0
Regression with Large Language Models for Materials and Molecular Property Prediction—0
Representing Molecules as Random Walks Over Interpretable Grammars—0
Reprogramming Pretrained Language Models for Protein Sequence Representation Learning—0
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