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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 226–250 of 691 papers

TitleStatusHype
Flexible dual-branched message passing neural network for quantum mechanical property prediction with molecular conformationCode0
ApisTox: a new benchmark dataset for the classification of small molecules toxicity on honey beesCode0
CLOUD: A Scalable and Physics-Informed Foundation Model for Crystal Representation LearningCode0
MUBen: Benchmarking the Uncertainty of Molecular Representation ModelsCode0
Multi-Peptide: Multimodality Leveraged Language-Graph Learning of Peptide PropertiesCode0
Outlier-Based Domain of Applicability Identification for Materials Property Prediction ModelsCode0
Molecule Property Prediction and Classification with Graph HypernetworksCode0
From Abstract to Actionable: Pairwise Shapley Values for Explainable AICode0
Molecule Property Prediction Based on Spatial Graph EmbeddingCode0
MoleculeCLA: Rethinking Molecular Benchmark via Computational Ligand-Target Binding AnalysisCode0
Explaining Graph Neural Networks with Large Language Models: A Counterfactual Perspective for Molecular Property PredictionCode0
Multimodal machine learning with large language embedding model for polymer property predictionCode0
An open unified deep graph learning framework for discovering drug leadsCode0
MolMetaLM: a Physicochemical Knowledge-Guided Molecular Meta Language ModelCode0
Molecular Property Prediction: A Multilevel Quantum Interactions Modeling PerspectiveCode0
Molecular Graph Contrastive Learning with Line GraphCode0
Molecular Graph Representation Learning Integrating Large Language Models with Domain-specific Small ModelsCode0
Molecular geometric deep learningCode0
Molecular Graph Representation Learning via Structural Similarity InformationCode0
MolPLA: A Molecular Pretraining Framework for Learning Cores, R-Groups and their Linker JointsCode0
Establishing Deep InfoMax as an effective self-supervised learning methodology in materials informaticsCode0
MolCap-Arena: A Comprehensive Captioning Benchmark on Language-Enhanced Molecular Property PredictionCode0
Equivariant Parameter Sharing for Porous Crystalline MaterialsCode0
Equivariant Message Passing Neural Network for Crystal Material DiscoveryCode0
Rethinking Gradient-Based Methods: Multi-Property Materials Design Beyond Differentiable TargetsCode0
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