Cheng Chen

Orcid: 0000-0002-4354-5508

Affiliations:
  • Qingdao University of Science and Technology, Qingdao, China


According to our database1, Cheng Chen authored at least 12 papers between 2019 and 2023.

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

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2023
RPI-CapsuleGAN: Predicting RNA-protein interactions through an interpretable generative adversarial capsule network.
Pattern Recognit., September, 2023

BiGRUD-SA: Protein S-sulfenylation sites prediction based on BiGRU and self-attention.
Comput. Biol. Medicine, September, 2023

Prediction of protein-protein interactions based on ensemble residual convolutional neural network.
Comput. Biol. Medicine, 2023

2021
Prediction of protein-protein interactions based on elastic net and deep forest.
Expert Syst. Appl., 2021

DNN-DTIs: Improved drug-target interactions prediction using XGBoost feature selection and deep neural network.
Comput. Biol. Medicine, 2021

Jointly Learning to Align and Aggregate with Cross Attention Pooling for Peptide-MHC Class I Binding Prediction.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

2020
SulSite-GTB: identification of protein S-sulfenylation sites by fusing multiple feature information and gradient tree boosting.
Neural Comput. Appl., 2020

GTB-PPI: Predict Protein-protein Interactions Based on L1-regularized Logistic Regression and Gradient Tree Boosting.
Genom. Proteom. Bioinform., 2020

Improving protein-protein interactions prediction accuracy using XGBoost feature selection and stacked ensemble classifier.
Comput. Biol. Medicine, 2020

SubMito-XGBoost: predicting protein submitochondrial localization by fusing multiple feature information and eXtreme gradient boosting.
Bioinform., 2020

2019
Protein-protein interaction sites prediction by ensemble random forests with synthetic minority oversampling technique.
Bioinform., 2019

Predicting Golgi-Resident Protein Types Using Conditional Covariance Minimization With XGBoost Based on Multiple Features Fusion.
IEEE Access, 2019


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