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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 221230 of 691 papers

TitleStatusHype
Adapting Differential Molecular Representation with Hierarchical Prompts for Multi-label Property PredictionCode0
A General Approach for Determining Applicability Domain of Machine Learning Models0
Explainable Molecular Property Prediction: Aligning Chemical Concepts with Predictions via Language Models0
PatchProt: Hydrophobic patch prediction using protein foundation modelsCode0
E(n) Equivariant Topological Neural NetworksCode1
Knowledge-enhanced Relation Graph and Task Sampling for Few-shot Molecular Property PredictionCode0
GLaD: Synergizing Molecular Graphs and Language Descriptors for Enhanced Power Conversion Efficiency Prediction in Organic Photovoltaic Devices0
Multi-Type Point Cloud Autoencoder: A Complete Equivariant Embedding for Molecule Conformation and PoseCode1
ProtT3: Protein-to-Text Generation for Text-based Protein UnderstandingCode2
Dynamic In-context Learning with Conversational Models for Data Extraction and Materials Property PredictionCode1
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