Jun Xu

Orcid: 0000-0002-1075-0337

Affiliations:
  • Sun Yat-Sen University, Research Center for Drug Discovery, Guangzhou, China


According to our database1, Jun Xu authored at least 30 papers between 2011 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2024
FerroLigandDB: A Ferroptosis Ligand Database of Structure-Activity Relations.
J. Chem. Inf. Model., 2024

dMXP: A <i>De Novo</i> Small-Molecule 3D Structure Predictor with Graph Attention Networks.
J. Chem. Inf. Model., 2024

2022
Glycerol is Released from a New Path in MGL Lipase Catalytic Process.
J. Chem. Inf. Model., 2022

2021
Kinase Inhibitor Scaffold Hopping with Deep Learning Approaches.
J. Chem. Inf. Model., 2021

2020
Perspectives on Supercomputing and Artificial Intelligence Applications in Drug Discovery.
Supercomput. Front. Innov., 2020

Publisher Correction: Predicting drug-protein interaction using quasi-visual question answering system.
Nat. Mach. Intell., 2020

Predicting drug-protein interaction using quasi-visual question answering system.
Nat. Mach. Intell., 2020

Predicting Retrosynthetic Reactions Using Self-Corrected Transformer Neural Networks.
J. Chem. Inf. Model., 2020

Predicting the Feasibility of Copper(I)-Catalyzed Alkyne-Azide Cycloaddition Reactions Using a Recurrent Neural Network with a Self-Attention Mechanism.
J. Chem. Inf. Model., 2020

2019
Identifying Structure-Property Relationships through SMILES Syntax Analysis with Self-Attention Mechanism.
J. Chem. Inf. Model., 2019

DeepChemStable: Chemical Stability Prediction with an Attention-Based Graph Convolution Network.
J. Chem. Inf. Model., 2019

Structurally Selective Mechanism of Liver X Receptor Ligand: In Silico and In Vitro Studies.
J. Chem. Inf. Model., 2019

QBMG: quasi-biogenic molecule generator with deep recurrent neural network.
J. Cheminformatics, 2019

Predicting Retrosynthetic Reaction using Self-Corrected Transformer Neural Networks.
CoRR, 2019

2018
TCMAnalyzer: A Chemo- and Bioinformatics Web Service for Analyzing Traditional Chinese Medicine.
J. Chem. Inf. Model., 2018

Discovering new PI3Kα inhibitors with a strategy of combining ligand-based and structure-based virtual screening.
J. Comput. Aided Mol. Des., 2018

HHVSF: A Framework to Accelerate Drug-Based High-Throughput Virtual Screening on High-Performance Computers.
Proceedings of the Supercomputing Frontiers - 4th Asian Conference, 2018

2017
Predicting DPP-IV inhibitors with machine learning approaches.
J. Comput. Aided Mol. Des., 2017

PTS: a pharmaceutical target seeker.
Database J. Biol. Databases Curation, 2017

2016
ASDB: a resource for probing protein functions with small molecules.
Bioinform., 2016

2015
Discovering New Acetylcholinesterase Inhibitors by Mining the <i>Buzhongyiqi</i> Decoction Recipe Data.
J. Chem. Inf. Model., 2015

2014
Discovering New Agents Active against Methicillin-Resistant <i>Staphylococcus aureus</i> with Ligand-Based Approaches.
J. Chem. Inf. Model., 2014

gWEGA: GPU-accelerated WEGA for molecular superposition and shape comparison.
J. Comput. Chem., 2014

ChemStable: a web server for rule-embedded naïve Bayesian learning approach to predict compound stability.
J. Comput. Aided Mol. Des., 2014

2013
Enhancing Molecular Shape Comparison by Weighted Gaussian Functions.
J. Chem. Inf. Model., 2013

Discovery of New Selective Human Aldose Reductase Inhibitors through Virtual Screening Multiple Binding Pocket Conformations.
J. Chem. Inf. Model., 2013

Molecular Dynamics-Based Virtual Screening: Accelerating the Drug Discovery Process by High-Performance Computing.
J. Chem. Inf. Model., 2013

2012
On the Value of Homology Models for Virtual Screening: Discovering hCXCR3 Antagonists by Pharmacophore-Based and Structure-Based Approaches.
J. Chem. Inf. Model., 2012

2011
Three-Dimensional Pharmacophore Modeling of Liver-X Receptor Agonists.
J. Chem. Inf. Model., 2011

A New Protocol for Predicting Novel GSK-3β ATP Competitive Inhibitors.
J. Chem. Inf. Model., 2011


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