Yang Li
Orcid: 0000-0003-2480-1972Affiliations:
- Nanjing University of Science and Technology, School of Computer Science and Engineering, China
- University of Michigan, Department of Computational Medicine and Bioinformatics, Ann Arbor, MI, USA
According to our database1,
Yang Li
authored at least 19 papers
between 2015 and 2024.
Collaborative distances:
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Timeline
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Bibliography
2024
Dataset for "A Comparative Review of Deep Learning Methods for RNA Tertiary Structure Prediction".
Dataset, December, 2024
Dataset for "A Comparative Review of Deep Learning Methods for RNA Tertiary Structure Prediction".
Dataset, November, 2024
CoRR, 2024
2022
Fast and accurate Ab Initio Protein structure prediction using deep learning potentials.
PLoS Comput. Biol., September, 2022
Nat. Comput. Sci., 2022
DEMO2: Assemble multi-domain protein structures by coupling analogous template alignments with deep-learning inter-domain restraint prediction.
Nucleic Acids Res., 2022
LOMETS3: integrating deep learning and profile alignment for advanced protein template recognition and function annotation.
Nucleic Acids Res., 2022
2021
Deducing high-accuracy protein contact-maps from a triplet of coevolutionary matrices through deep residual convolutional networks.
PLoS Comput. Biol., 2021
2020
SSCpred: Single-Sequence-Based Protein Contact Prediction Using Deep Fully Convolutional Network.
J. Chem. Inf. Model., 2020
FUpred: detecting protein domains through deep-learning-based contact map prediction.
Bioinform., 2020
DeepMSA: constructing deep multiple sequence alignment to improve contact prediction and fold-recognition for distant-homology proteins.
Bioinform., 2020
2019
Detecting distant-homology protein structures by aligning deep neural-network based contact maps.
PLoS Comput. Biol., 2019
LOMETS2: improved meta-threading server for fold-recognition and structure-based function annotation for distant-homology proteins.
Nucleic Acids Res., 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
2017
Predicting Protein-DNA Binding Residues by Weightedly Combining Sequence-Based Features and Boosting Multiple SVMs.
IEEE ACM Trans. Comput. Biol. Bioinform., 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