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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 1–25 of 691 papers

TitleStatusHype
Molecular Fingerprints Are Strong Models for Peptide Function PredictionCode3
DARWIN 1.5: Large Language Models as Materials Science Adapted LearnersCode3
Scikit-fingerprints: easy and efficient computation of molecular fingerprints in PythonCode3
A Review of Large Language Models and Autonomous Agents in ChemistryCode3
^2DFT: A Universal Quantum Chemistry Dataset of Drug-Like Molecules and a Benchmark for Neural Network PotentialsCode3
A Python library for efficient computation of molecular fingerprintsCode3
Leveraging Biomolecule and Natural Language through Multi-Modal Learning: A SurveyCode3
Uni-QSAR: an Auto-ML Tool for Molecular Property PredictionCode3
Highly Accurate Quantum Chemical Property Prediction with Uni-Mol+Code3
TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug DiscoveryCode3
Descriptor-based Foundation Models for Molecular Property PredictionCode2
CrystalFormer-RL: Reinforcement Fine-Tuning for Materials DesignCode2
M^3-20M: A Large-Scale Multi-Modal Molecule Dataset for AI-driven Drug Design and DiscoveryCode2
Deconstructing equivariant representations in molecular systemsCode2
Generative Artificial Intelligence for Navigating Synthesizable Chemical SpaceCode2
ProtT3: Protein-to-Text Generation for Text-based Protein UnderstandingCode2
Generalizable, Fast, and Accurate DeepQSPR with fastpropCode2
Triplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph TransformersCode2
Multi-Modal Representation Learning for Molecular Property Prediction: Sequence, Graph, GeometryCode2
Improving Molecular Properties Prediction Through Latent Space FusionCode2
MHG-GNN: Combination of Molecular Hypergraph Grammar with Graph Neural NetworkCode2
Temporal Graph Benchmark for Machine Learning on Temporal GraphsCode2
SGFormer: Simplifying and Empowering Transformers for Large-Graph RepresentationsCode2
Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language ModelsCode2
A Text-guided Protein Design FrameworkCode2
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