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Integrating concept of pharmacophore with graph neural networks for chemical property prediction and interpretation. JOURNAL OF CHEMINFORMATICS. AUG 4 2022. DOI10.1186/s13321-022-00634-3 . pdf |
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Geometry-enhanced molecular representation learning for property prediction. NATURE MACHINE INTELLIGENCE. FEB 2022. DOI 10.1038/s42256-021-00438-4 pdf |
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Deep learning methods for molecular representation and property prediction. DRUG DISCOVERY TODAY.DEC 2022. DOI10.1016/j.drudis.2022.103373 pdf |
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ReLMole: Molecular Representation Learning Based on Two-Level Graph Similarities. JOURNAL OF CHEMICAL INFORMATION AND MODELING. OCT 2022. DOI 10.1021/acs.jcim.2c00798 |
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Cross-dependent graph neural networks for molecular property prediction. BIOINFORMATICS. MAR 28 2022. DOI 10.1093/bioinformatics/btac039 |
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Geometry-enhanced molecular representation learning for property prediction. NATURE MACHINE INTELLIGENCE. FEB 2022. DOI 10.1038/s42256-021-00438-4. pdf |
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A general optimization protocol for molecular property prediction using a deep learning network. BRIEFINGS IN BIOINFORMATICS. JAN 17 2022. DOI 10.1093/bib/bbab367 |
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A compact review of molecular property prediction with graph neural networks. Drug discovery today. Technologies. 2020-Dec. DOI 10.1016/j.ddtec.2020.11.009 pdf |
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A fingerprints based molecular property prediction method using the BERT model. JOURNAL OF CHEMINFORMATICS. OCT 21 2022. DOI10.1186/s13321-022-00650-3 . pdf |
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MultiGran-SMILES: multi-granularity SMILES learning for molecular property prediction. BIOINFORMATICS. SEP 30 2022. DOI 10.1093/bioinformatics/btac550 |
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Molecular substructure graph attention network for molecular property identification in drug discovery. PATTERN RECOGNITION. AUG 2022. DOI 10.1016/j.patcog.2022.108659 pdf |
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FP-GNN: a versatile deep learning architecture for enhanced molecular property prediction. BRIEFINGS IN BIOINFORMATICS. SEP 2022. DOI 10.1093/bib/bbac408 pdf |
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Introducing block design in graph neural networks for molecular properties prediction. Chemical Engineering Journal. 2021. pdf |
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Machine learning methods for pK(a) prediction of small molecules: Advances and challenges. DRUG DISCOVERY TODAY. 2022 pdf
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An Accurate Approach for Computational pKa Determination of Phenolic Compounds. MOLECULES. 2022. pdf |
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MolGpka: A Web Server for Small Molecule pK(a) Prediction Using a Graph-Convolutional Neural Network. JOURNAL OF CHEMICAL INFORMATION AND MODELING. 2021 |
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Rapid and Accurate Prediction of pK(a) Values of C-H Acids Using Graph Convolutional Neural Networks. JOURNAL OF THE AMERICAN CHEMICAL SOCIETY. 2019 |
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ADMETlab 2.0: an integrated online platform for accurate and comprehensive predictions of ADMET properties. NUCLEIC ACIDS RESEARCH. 2021 |
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