Dejun Jiang
Orcid: 0000-0002-2035-5074Affiliations:
- Zhejiang University, Hangzhou, Zhejiang, China
According to our database1,
Dejun Jiang
authored at least 18 papers
between 2020 and 2024.
Collaborative distances:
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Bibliography
2024
Comprehensive Evaluation of 10 Docking Programs on a Diverse Set of Protein-Cyclic Peptide Complexes.
J. Chem. Inf. Model., 2024
Enhancing Multi-species Liver Microsomal Stability Prediction through Artificial Intelligence.
J. Chem. Inf. Model., 2024
CoRR, 2024
2023
J. Cheminformatics, December, 2023
Landslide Monitoring along the Dadu River in Sichuan Based on Sentinel-1 Multi-Temporal InSAR.
Sensors, April, 2023
Nat. Comput. Sci., 2023
Infinite Physical Monkey: Do Deep Learning Methods Really Perform Better in Conformation Generation?
CoRR, 2023
2022
An adaptive graph learning method for automated molecular interactions and properties predictions.
Nat. Mach. Intell., 2022
Knowledge-based BERT: a method to extract molecular features like computational chemists.
Briefings Bioinform., 2022
Out-of-the-box deep learning prediction of quantum-mechanical partial charges by graph representation and transfer learning.
Briefings Bioinform., 2022
2021
<i>DeepChargePredictor</i>: a web server for predicting QM-based atomic charges via <i>state-of-the-art</i> machine-learning algorithms.
Bioinform., November, 2021
Multi-constraint molecular generation based on conditional transformer, knowledge distillation and reinforcement learning.
Nat. Mach. Intell., 2021
VAD-MM/GBSA: A Variable Atomic Dielectric MM/GBSA Model for Improved Accuracy in Protein-Ligand Binding Free Energy Calculations.
J. Chem. Inf. Model., 2021
Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models.
J. Cheminformatics, 2021
Identification of active molecules against Mycobacterium tuberculosis through machine learning.
Briefings Bioinform., 2021
Do we need different machine learning algorithms for QSAR modeling? A comprehensive assessment of 16 machine learning algorithms on 14 QSAR data sets.
Briefings Bioinform., 2021
Hyperbolic relational graph convolution networks plus: a simple but highly efficient QSAR-modeling method.
Briefings Bioinform., 2021
2020
ADMET evaluation in drug discovery. 20. Prediction of breast cancer resistance protein inhibition through machine learning.
J. Cheminformatics, 2020