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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 601–625 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
Towards Data-Efficient Pretraining for Atomic Property PredictionCode0
Isotropic Gaussian Processes on Finite Spaces of GraphsCode0
Towards deep generation of guided wave representations for composite materialsCode0
D-HYPR: Harnessing Neighborhood Modeling and Asymmetry Preservation for Digraph Representation LearningCode0
Interpreting the Syntactic and Social Elements of the Tweet Representations via Elementary Property Prediction TasksCode0
MUST-CNN: A Multilayer Shift-and-Stitch Deep Convolutional Architecture for Sequence-based Protein Structure PredictionCode0
Interpretation of Semantic Tweet RepresentationsCode0
Integrating Predictive and Generative Capabilities by Latent Space Design via the DKL-VAE ModelCode0
Integrating convolutional layers and biformer network with forward-forward and backpropagation trainingCode0
Do Graph Neural Networks Work for High Entropy Alloys?Code0
Towards Faster and More Compact Foundation Models for Molecular Property PredictionCode0
Independent Vector Analysis for Data Fusion Prior to Molecular Property Prediction with Machine LearningCode0
Object-Centric Learning with Slot Mixture ModuleCode0
Improving Molecular Pretraining with Complementary FeaturizationsCode0
An open unified deep graph learning framework for discovering drug leadsCode0
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