Zhong-Hao Ren

450 total citations
21 papers, 309 citations indexed

About

Zhong-Hao Ren is a scholar working on Molecular Biology, Computational Theory and Mathematics and Cancer Research. According to data from OpenAlex, Zhong-Hao Ren has authored 21 papers receiving a total of 309 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 9 papers in Computational Theory and Mathematics and 9 papers in Cancer Research. Recurrent topics in Zhong-Hao Ren's work include Computational Drug Discovery Methods (9 papers), Cancer-related molecular mechanisms research (8 papers) and Machine Learning in Bioinformatics (7 papers). Zhong-Hao Ren is often cited by papers focused on Computational Drug Discovery Methods (9 papers), Cancer-related molecular mechanisms research (8 papers) and Machine Learning in Bioinformatics (7 papers). Zhong-Hao Ren collaborates with scholars based in China, Sweden and Saudi Arabia. Zhong-Hao Ren's co-authors include Chang-Qing Yu, Zhu‐Hong You, Jie Pan, Xinfei Wang, Liping Li, Wenzhun Huang, Liping Li, Liping Li, Lei Wang and Bo-Wei Zhao and has published in prestigious journals such as Nature Communications, Molecules and Journal of Chemical Information and Modeling.

In The Last Decade

Zhong-Hao Ren

20 papers receiving 306 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhong-Hao Ren China 9 270 161 101 25 25 21 309
Guofei Ren China 7 368 1.4× 273 1.7× 64 0.6× 16 0.6× 14 0.6× 7 433
Hossein Sharifi-Noghabi Canada 5 272 1.0× 71 0.4× 152 1.5× 44 1.8× 40 1.6× 6 347
Xiongfei Tian China 10 258 1.0× 139 0.9× 66 0.7× 7 0.3× 12 0.5× 11 329
Muhammad Ammad-ud-din Finland 8 205 0.8× 42 0.3× 160 1.6× 27 1.1× 31 1.2× 14 289
Na‐Na Guan China 9 785 2.9× 592 3.7× 199 2.0× 41 1.6× 26 1.0× 14 909
Yihe Pang China 8 355 1.3× 39 0.2× 60 0.6× 30 1.2× 27 1.1× 11 401
Qiguo Dai China 12 589 2.2× 429 2.7× 61 0.6× 11 0.4× 29 1.2× 24 670
Ruijiang Li China 7 178 0.7× 45 0.3× 49 0.5× 14 0.6× 13 0.5× 13 249
Qijin Yin China 9 217 0.8× 24 0.1× 70 0.7× 17 0.7× 12 0.5× 11 267

Countries citing papers authored by Zhong-Hao Ren

Since Specialization
Citations

This map shows the geographic impact of Zhong-Hao Ren'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 Zhong-Hao Ren with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhong-Hao Ren more than expected).

Fields of papers citing papers by Zhong-Hao Ren

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Zhong-Hao Ren. 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 Zhong-Hao Ren. The network helps show where Zhong-Hao Ren may publish in the future.

Co-authorship network of co-authors of Zhong-Hao Ren

This figure shows the co-authorship network connecting the top 25 collaborators of Zhong-Hao Ren. A scholar is included among the top collaborators of Zhong-Hao Ren 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 Zhong-Hao Ren. Zhong-Hao Ren is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Ren, Zhong-Hao, et al.. (2025). Predicting rare drug-drug interaction events with dual-granular structure-adaptive and pair variational representation. Nature Communications. 16(1). 3997–3997. 5 indexed citations
3.
Ren, Zhong-Hao, et al.. (2024). A spatial hierarchical network learning framework for drug repositioning allowing interpretation from macro to micro scale. Communications Biology. 7(1). 1413–1413. 5 indexed citations
4.
Yu, Chang-Qing, Xinfei Wang, Liping Li, et al.. (2024). RBNE-CMI: An Efficient Method for Predicting circRNA-miRNA Interactions via Multiattribute Incomplete Heterogeneous Network Embedding. Journal of Chemical Information and Modeling. 64(18). 7163–7172. 6 indexed citations
5.
Wang, Xinfei, Chang-Qing Yu, Zhu‐Hong You, et al.. (2023). A feature extraction method based on noise reduction for circRNA-miRNA interaction prediction combining multi-structure features in the association networks. Briefings in Bioinformatics. 24(3). 28 indexed citations
6.
Ren, Zhong-Hao, Quan Zou, Chang-Qing Yu, et al.. (2023). DeepMPF: deep learning framework for predicting drug–target interactions based on multi-modal representation with meta-path semantic analysis. Journal of Translational Medicine. 21(1). 48–48. 28 indexed citations
7.
Yu, Chang-Qing, et al.. (2023). LPIH2V: LncRNA-protein interactions prediction using HIN2Vec based on heterogeneous networks model. Frontiers in Genetics. 14. 1122909–1122909. 6 indexed citations
8.
Ren, Zhong-Hao, Chang-Qing Yu, Liping Li, et al.. (2023). SiSGC: A Drug Repositioning Prediction Model Based on Heterogeneous Simplifying Graph Convolution. Journal of Chemical Information and Modeling. 64(1). 238–249. 4 indexed citations
9.
Yu, Chang-Qing, Yan Qiao, Liping Li, et al.. (2022). MFIDMA: A Multiple Information Integration Model for the Prediction of Drug–miRNA Associations. Biology. 12(1). 41–41. 8 indexed citations
10.
11.
You, Zhu‐Hong, Lei Wang, Chang-Qing Yu, et al.. (2022). A novel circRNA-miRNA association prediction model based on structural deep neural network embedding. Briefings in Bioinformatics. 23(5). 41 indexed citations
12.
Ren, Zhong-Hao, et al.. (2022). SAWRPI: A Stacking Ensemble Framework With Adaptive Weight for Predicting ncRNA-Protein Interactions Using Sequence Information. Frontiers in Genetics. 13. 839540–839540. 5 indexed citations
13.
Yu, Chang-Qing, et al.. (2022). BNEMDI: A Novel MicroRNA–Drug Interaction Prediction Model Based on Multi-Source Information With a Large-Scale Biological Network. Frontiers in Genetics. 13. 919264–919264. 5 indexed citations
14.
Wang, Xinfei, Chang-Qing Yu, Liping Li, et al.. (2022). KGDCMI: A New Approach for Predicting circRNA–miRNA Interactions From Multi-Source Information Extraction and Deep Learning. Frontiers in Genetics. 13. 958096–958096. 40 indexed citations
15.
Ren, Zhong-Hao, et al.. (2022). BioDKG–DDI: predicting drug–drug interactions based on drug knowledge graph fusing biochemical information. Briefings in Functional Genomics. 21(3). 216–229. 34 indexed citations
16.
17.
Pan, Jie, et al.. (2021). Prediction of Drug–Target Interactions by Combining Dual-Tree Complex Wavelet Transform with Ensemble Learning Method. Molecules. 26(17). 5359–5359. 3 indexed citations
18.
Pan, Jie, et al.. (2021). Sequence-Based Prediction of Plant Protein-Protein Interactions by Combining Discrete Sine Transformation With Rotation Forest. Evolutionary Bioinformatics. 17. 3243611219–3243611219. 6 indexed citations
19.
Pan, Jie, et al.. (2021). FWHT-RF: A Novel Computational Approach to Predict Plant Protein-Protein Interactions via an Ensemble Learning Method. Scientific Programming. 2021. 1–11. 7 indexed citations
20.

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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