Pengyong Han

Orcid: 0000-0002-0017-0785

According to our database1, Pengyong Han authored at least 21 papers between 2020 and 2023.

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

Timeline

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Bibliography

2023
Applying machine learning to screen for acute myocardial infarction-related biomarkers and immune infiltration features and validate it clinically and experimentally.
Int. J. Imaging Syst. Technol., November, 2023

Adversarial dense graph convolutional networks for single-cell classification.
Bioinform., February, 2023

Predicting MiRNA-Disease Associations by Graph Representation Learning Based on Jumping Knowledge Networks.
IEEE ACM Trans. Comput. Biol. Bioinform., 2023

ADARES: A Single-cell Classification Model Based on Adversarial Data Augmentation and Residual Networks.
Proceedings of the 6th International Conference on Signal Processing and Machine Learning, 2023

A Graph Neural Network with Multiple Auxiliary Tasks for Accurate Single Cell Classiଁcation.
Proceedings of the 6th International Conference on Signal Processing and Machine Learning, 2023

2022
GCMCDTI: Graph convolutional autoencoder framework for predicting drug-target interactions based on matrix completion.
J. Bioinform. Comput. Biol., 2022

Identification of feature genes and pathways for Alzheimer's disease via WGCNA and LASSO regression.
Frontiers Comput. Neurosci., 2022

Prediction of MiRNA-Disease Association Based on Higher-Order Graph Convolutional Networks.
Proceedings of the Intelligent Computing Theories and Application, 2022

Identification and Evaluation of Key Biomarkers of Acute Myocardial Infarction by Machine Learning.
Proceedings of the Intelligent Computing Theories and Application, 2022

A Novel Cuprotosis-Related Gene Signature Predicts Survival Outcomes in Patients with Clear-Cell Renal Cell Carcinoma.
Proceedings of the Intelligent Computing Theories and Application, 2022

Research on the Potential Mechanism of Rhizoma Drynariae in the Treatment of Periodontitis Based on Network Pharmacology.
Proceedings of the Intelligent Computing Theories and Application, 2022

The CNV Predict Model in Esophagus Cancer.
Proceedings of the Intelligent Computing Theories and Application, 2022

A Novel Cuprotosis-Related lncRNA Signature Predicts Survival Outcomes in Patients with Glioblastoma.
Proceedings of the Intelligent Computing Theories and Application, 2022

The Prognosis Model of Clear Cell Renal Cell Carcinoma Based on Allograft Rejection Markers.
Proceedings of the Intelligent Computing Theories and Application, 2022

Glioblastoma Subtyping by Immuogenomics.
Proceedings of the Intelligent Computing Theories and Application, 2022

Elucidating Quantum Semi-empirical Based QSAR, for Predicting Tannins' Anti-oxidant Activity with the Help of Artificial Neural Network.
Proceedings of the Intelligent Computing Theories and Application, 2022

Bioinformatic Analysis of Clear Cell Renal Carcinoma via ATAC-Seq and RNA-Seq.
Proceedings of the Intelligent Computing Theories and Application, 2022

2021
eTumorMetastasis: A Network-based Algorithm Predicts Clinical Outcomes Using Whole-exome Sequencing Data of Cancer Patients.
Genom. Proteom. Bioinform., 2021

Delineating QSAR Descriptors to Explore the Inherent Properties of Naturally Occurring Polyphenols, Responsible for Alpha-Synuclein Amyloid Disaggregation Scheming Towards Effective Therapeutics Against Parkinson's Disorder.
Proceedings of the Intelligent Computing Theories and Application, 2021

Study on the Mechanism of Cistanche in the Treatment of Colorectal Cancer Based on Network Pharmacology.
Proceedings of the Intelligent Computing Theories and Application, 2021

2020
Expression and Gene Regulation Network of ELF3 in Breast Invasive Carcinoma Based on Data Mining.
Proceedings of the Intelligent Computing Theories and Application, 2020


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