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Runyu Jing

Observed names: Jing, R., Jing, Runyu, Run Jing, jing, runyu
ORCID: 0000-0003-3375-1014
Observed ORCID: 0000-0003-3375-1014
OpenAlex ID: A5063197812
DeepACP: A Novel Computational Approach for Accurate Identification of Anticancer Peptides by Deep Learning Algorithm
2020 · Lezheng Yu, Runyu Jing, et al. · Molecular Therapy — Nucleic Acids · 90
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The applications of deep learning algorithms on in silico druggable proteins identification
2022 · Lezheng Yu, Li Xue, et al. · Journal of Advanced Research · 49
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autoBioSeqpy: A Deep Learning Tool for the Classification of Biological Sequences
2020 · Runyu Jing, Yizhou Li, et al. · Journal of Chemical Information and Modeling · 35
Comparative Analysis of Oncogenes Identified by Microarray and RNA-Sequencing as Biomarkers for Clinical Prognosis
2015 · Yuan Liu, Runyu Jing, et al. · Biomarkers in Medicine · 27
Combination use of protein–protein interaction network topological features improves the predictive scores of deleterious non-synonymous single-nucleotide polymorphisms
2014 · Yiming Wu, Runyu Jing, et al. · Amino Acids · 24
GenAI synthesis of histopathological images from Raman imaging for intraoperative tongue squamous cell carcinoma assessment
2025 · Bing Yan, Zhining Wen, et al. · International Journal of Oral Science · 18
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DeepT3 2.0: improving type III secreted effector predictions by an integrative deep learning framework
2021 · Runyu Jing, Tingke Wen, et al. · NAR Genomics and Bioinformatics · 18
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DeepT3_4: A Hybrid Deep Neural Network Model for the Distinction Between Bacterial Type III and IV Secreted Effectors
2021 · Lezheng Yu, Fengjuan Liu, et al. · Frontiers in Microbiology · 18
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Identifying diagnostic indicators for type 2 diabetes mellitus from physical examination using interpretable machine learning approach
2024 · Xiang Lv, Jiesi Luo, et al. · Frontiers in Endocrinology · 17
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layerUMAP: A tool for visualizing and understanding deep learning models in biological sequence classification using UMAP
2022 · Runyu Jing, Li Xue, et al. · iScience · 17
Machine learning to guide the use of plasma technology for antibiotic degradation
2024 · Li Xue, Runyu Jing, et al. · Journal of Hazardous Materials · 15
Narrowing the Gap Between In Vitro and In Vivo Genetic Profiles by Deconvoluting Toxicogenomic Data In Silico
2020 · Yuan Liu, Runyu Jing, et al. · Frontiers in Pharmacology · 14
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Classification of multi-family enzymes by multi-label machine learning and sequence-based descriptors
2014 · Yuelong Wang, Runyu Jing, et al. · Analytical Methods · 14
Systematic Analysis and Accurate Identification of DNA N4-Methylcytosine Sites by Deep Learning
2022 · Lezheng Yu, Yonglin Zhang, et al. · Frontiers in Microbiology · 13
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Functional annotation of sixty-five type-2 diabetes risk SNPs and its application in risk prediction
2017 · Yiming Wu, Runyu Jing, et al. · Scientific Reports · 11
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Multimodal deep learning for allergenic proteins prediction
2025 · Lezheng Yu, Yuxin Luo, et al. · BMC Biology · 10
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A new strategy for exploring the hierarchical structure of cancers by adaptively partitioning functional modules from gene expression network
2016 · Junmei Xu, Runyu Jing, et al. · Scientific Reports · 8
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Identifying oncogenes as features for clinical cancer prognosis by Bayesian nonparametric variable selection algorithm
2015 · Huijun Wang, Liqiu Huang, et al. · Chemometrics and Intelligent Laboratory Systems · 8
Predicting deleterious non-synonymous single nucleotide polymorphisms in signal peptides based on hybrid sequence attributes
2011 · Wenli Qin, Yizhou Li, et al. · Computational Biology and Chemistry · 8
Evaluation and development of deep neural networks for RNA 5-Methyluridine classifications using autoBioSeqpy
2023 · Lezheng Yu, Yonglin Zhang, et al. · Frontiers in Microbiology · 7
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Unveiling diagnostic information for type 2 diabetes through interpretable machine learning
2024 · Xiang Lv, Jiesi Luo, et al. · Information Sciences · 6
Fast and Efficient Design of Deep Neural Networks for Predicting N7-Methylguanosine Sites Using autoBioSeqpy
2023 · Yonglin Zhang, Lezheng Yu, et al. · ACS Omega · 6
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EnsembleDL-ATG: Identifying autophagy proteins by integrating their sequence and evolutionary information using an ensemble deep learning framework
2023 · Lezheng Yu, Yonglin Zhang, et al. · Computational and Structural Biotechnology Journal · 6
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Robust multi-class model constructed for rapid quality control of Cordyceps sinensis
2021 · Hui Guo, Xing Yang, et al. · Microchemical Journal · 6
Ensemble Methods with Voting Protocols Exhibit Superior Performance for Predicting Cancer Clinical Endpoints and Providing More Complete Coverage of Disease-Related Genes
2018 · Runyu Jing, Yu Liang, et al. · International Journal of Genomics · 6
Works count: 55
Citation count: 498
H-index: 13
I10-index: 16
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