Jun Hu
Affiliations:- University of Michigan, Department of Computational Medicine and Bioinformatics, Ann Arbor, MI, USA
- Nanjing University of Science and Technology, School of Computer Science and Engineering, China
According to our database1,
Jun Hu
authored at least 13 papers
between 2012 and 2019.
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Bibliography
2019
ResPRE: high-accuracy protein contact prediction by coupling precision matrix with deep residual neural networks.
Bioinform., 2019
2018
ATPbind: Accurate Protein-ATP Binding Site Prediction by Combining Sequence-Profiling and Structure-Based Comparisons.
J. Chem. Inf. Model., 2018
LS-align: an atom-level, flexible ligand structural alignment algorithm for high-throughput virtual screening.
Bioinform., 2018
2017
Predicting Protein-DNA Binding Residues by Weightedly Combining Sequence-Based Features and Boosting Multiple SVMs.
IEEE ACM Trans. Comput. Biol. Bioinform., 2017
Enhancing Protein-ATP and Protein-ADP Binding Sites Prediction Using Supervised Instance-Transfer Learning.
Proceedings of the 4th IAPR Asian Conference on Pattern Recognition, 2017
2016
KNN-based dynamic query-driven sample rescaling strategy for class imbalance learning.
Neurocomputing, 2016
GPCR-drug interactions prediction using random forest with drug-association-matrix-based post-processing procedure.
Comput. Biol. Chem., 2016
2015
Disulfide Connectivity Prediction Based on Modelled Protein 3D Structural Information and Random Forest Regression.
IEEE ACM Trans. Comput. Biol. Bioinform., 2015
2014
Enhancing protein-vitamin binding residues prediction by multiple heterogeneous subspace SVMs ensemble.
BMC Bioinform., 2014
2013
Designing Template-Free Predictor for Targeting Protein-Ligand Binding Sites with Classifier Ensemble and Spatial Clustering.
IEEE ACM Trans. Comput. Biol. Bioinform., 2013
TargetATPsite: A template-free method for ATP-binding sites prediction with residue evolution image sparse representation and classifier ensemble.
J. Comput. Chem., 2013
Improving protein-ATP binding residues prediction by boosting SVMs with random under-sampling.
Neurocomputing, 2013
2012
Proceedings of the Intelligent Science and Intelligent Data Engineering, 2012