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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 2650 of 691 papers

TitleStatusHype
Generalizable, Fast, and Accurate DeepQSPR with fastpropCode2
Generative Artificial Intelligence for Navigating Synthesizable Chemical SpaceCode2
Identity-aware Graph Neural NetworksCode2
Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language ModelsCode2
ADMET property prediction through combinations of molecular fingerprintsCode1
Directed Graph Grammars for Sequence-based LearningCode1
Dual-view Molecule Pre-trainingCode1
DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and moleculesCode1
DGL-LifeSci: An Open-Source Toolkit for Deep Learning on Graphs in Life ScienceCode1
Dynamic In-context Learning with Conversational Models for Data Extraction and Materials Property PredictionCode1
Data-Centric Learning from Unlabeled Graphs with Diffusion ModelCode1
3D-MolT5: Leveraging Discrete Structural Information for Molecule-Text ModelingCode1
CrysMMNet: Multimodal Representation for Crystal Property PredictionCode1
Any-Property-Conditional Molecule Generation with Self-Criticism using Spanning TreesCode1
CrysGNN : Distilling pre-trained knowledge to enhance property prediction for crystalline materialsCode1
Deep learning-based denoising for fast time-resolved flame emission spectroscopy in high-pressure combustion environmentCode1
E(n) Equivariant Topological Neural NetworksCode1
An algorithmic framework for synthetic cost-aware decision making in molecular designCode1
ChiENN: Embracing Molecular Chirality with Graph Neural NetworksCode1
CHILI: Chemically-Informed Large-scale Inorganic Nanomaterials Dataset for Advancing Graph Machine LearningCode1
A Molecular Multimodal Foundation Model Associating Molecule Graphs with Natural LanguageCode1
Chemical-Reaction-Aware Molecule Representation LearningCode1
Copolymer Informatics with Multi-Task Deep Neural NetworksCode1
ChemLLM: A Chemical Large Language ModelCode1
Can Large Language Models Understand Molecules?Code1
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