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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 601–610 of 691 papers

TitleStatusHype
ApisTox: a new benchmark dataset for the classification of small molecules toxicity on honey beesCode0
Domain-Adversarial Multi-Task Framework for Novel Therapeutic Property Prediction of CompoundsCode0
Large-Scale Knowledge Integration for Enhanced Molecular Property PredictionCode0
Accelerating Material Property Prediction using Generically Complete Isometry InvariantsCode0
Multimodal machine learning with large language embedding model for polymer property predictionCode0
Multimodal Model with Text and Drug Embeddings for Adverse Drug Reaction ClassificationCode0
Knowledge-enhanced Relation Graph and Task Sampling for Few-shot Molecular Property PredictionCode0
Coarse-Grained Configurational Polymer Fingerprints for Property Prediction using Machine LearningCode0
Multipath Graph Convolutional Neural NetworksCode0
Multi-Peptide: Multimodality Leveraged Language-Graph Learning of Peptide PropertiesCode0
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