Runyu Jing

479 total citations
46 papers, 314 citations indexed

About

Runyu Jing is a scholar working on Molecular Biology, Computational Theory and Mathematics and Cancer Research. According to data from OpenAlex, Runyu Jing has authored 46 papers receiving a total of 314 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Molecular Biology, 6 papers in Computational Theory and Mathematics and 6 papers in Cancer Research. Recurrent topics in Runyu Jing's work include Machine Learning in Bioinformatics (18 papers), RNA and protein synthesis mechanisms (9 papers) and Bioinformatics and Genomic Networks (8 papers). Runyu Jing is often cited by papers focused on Machine Learning in Bioinformatics (18 papers), RNA and protein synthesis mechanisms (9 papers) and Bioinformatics and Genomic Networks (8 papers). Runyu Jing collaborates with scholars based in China and United States. Runyu Jing's co-authors include Jiesi Luo, Yizhou Li, Lezheng Yu, Fengjuan Liu, Menglong Li, Xue Li, Zhining Wen, Fengjuan Liu, Yonglin Zhang and Yuan Liu and has published in prestigious journals such as PLoS ONE, Scientific Reports and ACS Applied Materials & Interfaces.

In The Last Decade

Runyu Jing

42 papers receiving 310 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Runyu Jing China	10	247	57	27	23	14	46	314
Fang Ge China	14	404 1.6×	70 1.2×	19 0.7×	69 3.0×	23 1.6×	38	474
Jiu-Xin Tan China	7	452 1.8×	45 0.8×	70 2.6×	13 0.6×	24 1.7×	8	502
Ankita Singh India	10	250 1.0×	24 0.4×	37 1.4×	9 0.4×	9 0.6×	23	338
Tingzhong Tian China	8	198 0.8×	87 1.5×	32 1.2×	12 0.5×	10 0.7×	12	259
Zimei Zhang China	10	473 1.9×	63 1.1×	113 4.2×	19 0.8×	25 1.8×	26	621
Wenjia He China	8	271 1.1×	36 0.6×	23 0.9×	47 2.0×	35 2.5×	14	320
Shen Niu China	11	269 1.1×	37 0.6×	8 0.3×	7 0.3×	12 0.9×	14	303
Shi-Shi Yuan China	9	260 1.1×	34 0.6×	33 1.2×	26 1.1×	22 1.6×	10	317
Dukka B. KC United States	14	266 1.1×	23 0.4×	5 0.2×	9 0.4×	20 1.4×	22	356

Countries citing papers authored by Runyu Jing

Since Specialization

Citations

This map shows the geographic impact of Runyu Jing's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Runyu Jing with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Runyu Jing more than expected).

Fields of papers citing papers by Runyu Jing

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Runyu Jing. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Runyu Jing. The network helps show where Runyu Jing may publish in the future.

Co-authorship network of co-authors of Runyu Jing

This figure shows the co-authorship network connecting the top 25 collaborators of Runyu Jing. A scholar is included among the top collaborators of Runyu Jing based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Runyu Jing. Runyu Jing is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Yang, Lin, et al.. (2025). Enhanced energy-storage properties in Gd3 + -modified BiFeO3-BaTiO3-based high-entropy ceramics. Journal of the European Ceramic Society. 46(4). 117916–117916.

Jing, Runyu, Yanmei Xu, & Ruizhi Liu. (2025). Data element, big data and enterprise innovation: Evidence from data trading platforms and national big data comprehensive pilot zones. International Review of Financial Analysis. 105. 104426–104426. 2 indexed citations

Yu, Lezheng, et al.. (2025). Multimodal deep learning for allergenic proteins prediction. BMC Biology. 23(1). 232–232.

Wang, Xiaoxia, Runyu Jing, Renfu Shao, et al.. (2025). Research progress on non-coding RNA regulatory networks and targeted therapy in diabetic nephropathy. Frontiers in Endocrinology. 16. 1625307–1625307. 1 indexed citations

Zhang, Yonglin, Lezheng Yu, Li C. Xue, et al.. (2025). Optimizing lipocalin sequence classification with ensemble deep learning models. PLoS ONE. 20(4). e0319329–e0319329. 1 indexed citations

Wang, Xiaoxia, Yangyang Shi, Renfu Shao, et al.. (2025). Molecular mechanisms and targeted therapy of progranulin in metabolic diseases. Frontiers in Endocrinology. 16. 1553794–1553794.

Luo, Jiesi, et al.. (2024). Unveiling diagnostic information for type 2 diabetes through interpretable machine learning. Information Sciences. 690. 121582–121582. 1 indexed citations

Luo, Jiesi, Xue Bai, Pijun Yan, et al.. (2024). Identifying diagnostic indicators for type 2 diabetes mellitus from physical examination using interpretable machine learning approach. Frontiers in Endocrinology. 15. 1376220–1376220. 2 indexed citations

Yu, Lezheng, Yonglin Zhang, Xue Li, et al.. (2023). EnsembleDL-ATG: Identifying autophagy proteins by integrating their sequence and evolutionary information using an ensemble deep learning framework. Computational and Structural Biotechnology Journal. 21. 4836–4848. 4 indexed citations

10.

Luo, Jiesi, et al.. (2023). Sequence-based malware detection using a single-bidirectional graph embedding and multi-task learning framework. Journal of Computer Security. 32(2). 141–163. 1 indexed citations

11.

Jing, Runyu, Li C. Xue, Menglong Li, Lezheng Yu, & Jiesi Luo. (2022). layerUMAP: A tool for visualizing and understanding deep learning models in biological sequence classification using UMAP. iScience. 25(12). 105530–105530. 10 indexed citations

12.

Yu, Lezheng, Xue Li, Fengjuan Liu, et al.. (2022). The applications of deep learning algorithms on in silico druggable proteins identification. Journal of Advanced Research. 41. 219–231. 33 indexed citations

13.

Lu, Yu, Yiming Wu, Yuan Liu, et al.. (2021). Prediction of disease‐associated functional variants in noncoding regions through a comprehensive analysis by integrating datasets and features. Human Mutation. 42(6). 667–684. 2 indexed citations

14.

Liu, Yuan, Runyu Jing, Zhining Wen, & Menglong Li. (2020). Narrowing the Gap Between In Vitro and In Vivo Genetic Profiles by Deconvoluting Toxicogenomic Data In Silico. Frontiers in Pharmacology. 10. 1489–1489. 8 indexed citations

15.

He, Li, Yifan Zhou, Yiru Zhao, et al.. (2020). Improving Model Performance on the Stratification of Breast Cancer Patients by Integrating Multiscale Genomic Features. BioMed Research International. 2020(1). 1475368–1475368. 2 indexed citations

16.

Wu, Yiming, Runyu Jing, Yongcheng Dong, et al.. (2017). Functional annotation of sixty-five type-2 diabetes risk SNPs and its application in risk prediction. Scientific Reports. 7(1). 43709–43709. 5 indexed citations

17.

Dai, Xing, Runyu Jing, Yanzhi Guo, et al.. (2015). Predicting the Druggability of Protein-Protein Interactions Based on Sequence and Structure Features of Active Pockets. Current Pharmaceutical Design. 21(21). 3051–3061. 3 indexed citations

18.

Wu, Yiming, Runyu Jing, Jiang Lin, et al.. (2014). Combination use of protein–protein interaction network topological features improves the predictive scores of deleterious non-synonymous single-nucleotide polymorphisms. Amino Acids. 46(8). 2025–2035. 18 indexed citations

19.

Sun, Jing, Runyu Jing, Yuelong Wang, et al.. (2013). PPM-Dom: A novel method for domain position prediction. Computational Biology and Chemistry. 47. 8–15. 2 indexed citations

20.

Li, Yizhou, Juan Li, Lezheng Yu, et al.. (2011). Predicting deleterious non-synonymous single nucleotide polymorphisms in signal peptides based on hybrid sequence attributes. Computational Biology and Chemistry. 36. 31–35. 7 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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