Linlin Zhuo

749 total citations
46 papers, 431 citations indexed

About

Linlin Zhuo is a scholar working on Molecular Biology, Cancer Research and Computational Theory and Mathematics. According to data from OpenAlex, Linlin Zhuo has authored 46 papers receiving a total of 431 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Molecular Biology, 15 papers in Cancer Research and 11 papers in Computational Theory and Mathematics. Recurrent topics in Linlin Zhuo's work include Cancer-related molecular mechanisms research (11 papers), Computational Drug Discovery Methods (11 papers) and MicroRNA in disease regulation (8 papers). Linlin Zhuo is often cited by papers focused on Cancer-related molecular mechanisms research (11 papers), Computational Drug Discovery Methods (11 papers) and MicroRNA in disease regulation (8 papers). Linlin Zhuo collaborates with scholars based in China, Macao and United States. Linlin Zhuo's co-authors include Xiangzheng Fu, Quan Zou, Xiaojun Yao, Mingzhe Liu, Xinze Lian, Qi Ren, Zhen Li, Qingquan Liao, Zejun Li and Tao Wang and has published in prestigious journals such as Bioinformatics, Expert Systems with Applications and IEEE Access.

In The Last Decade

Linlin Zhuo

42 papers receiving 426 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Linlin Zhuo China	13	342	163	104	52	36	46	431
Peiran Jiang China	9	369 1.1×	50 0.3×	124 1.2×	40 0.8×	76 2.1×	12	583
Ziqi Pan China	13	263 0.8×	48 0.3×	111 1.1×	42 0.8×	47 1.3×	28	502
Shuting Jin China	14	507 1.5×	69 0.4×	357 3.4×	139 2.7×	88 2.4×	31	739
Huaicheng Sun China	7	233 0.7×	93 0.6×	82 0.8×	14 0.3×	31 0.9×	10	366
Junru Jin China	14	552 1.6×	71 0.4×	135 1.3×	61 1.2×	66 1.8×	24	654
Yixiao Zhai China	8	268 0.8×	39 0.2×	48 0.5×	24 0.5×	21 0.6×	15	341
Guofei Ren China	7	368 1.1×	273 1.7×	64 0.6×	16 0.3×	14 0.4×	7	433
Xiangeng Wang China	11	325 1.0×	34 0.2×	190 1.8×	75 1.4×	31 0.9×	17	446
Yajie Meng China	14	524 1.5×	124 0.8×	372 3.6×	45 0.9×	85 2.4×	36	717

Countries citing papers authored by Linlin Zhuo

Since Specialization

Citations

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

Fields of papers citing papers by Linlin Zhuo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Linlin Zhuo. 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 Linlin Zhuo. The network helps show where Linlin Zhuo may publish in the future.

Co-authorship network of co-authors of Linlin Zhuo

This figure shows the co-authorship network connecting the top 25 collaborators of Linlin Zhuo. A scholar is included among the top collaborators of Linlin Zhuo 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 Linlin Zhuo. Linlin Zhuo 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

Zhuo, Linlin, Jinpeng Zhang, K. C. Ho, et al.. (2025). Internal electric field steering S-scheme charge transfer in ZnIn2S4/COF boosts H2O2 photosynthesis from water and air for sustainable disinfection. npj Clean Water. 8(1). 15 indexed citations

Zhuo, Linlin, et al.. (2025). SGPS-IMR: Efficiently inferring microbial resistance using self-supervised graph perturbation strategy. Expert Systems with Applications. 283. 127785–127785. 1 indexed citations

Wang, Shanshan, et al.. (2025). GH-UNet: group-wise hybrid convolution-VIT for robust medical image segmentation. npj Digital Medicine. 8(1). 426–426.

Cai, Lijun, et al.. (2024). AEGNN-M:A 3D Graph-Spatial Co-Representation Model for Molecular Property Prediction. IEEE Journal of Biomedical and Health Informatics. 29(3). 1726–1734. 10 indexed citations

Zhang, Xinyu, Mingzhe Liu, Zhen Li, et al.. (2024). Fusion of multi-source relationships and topology to infer lncRNA-protein interactions. Molecular Therapy — Nucleic Acids. 35(2). 102187–102187. 15 indexed citations

Zhu, Yangbin, et al.. (2024). Efficient Deep Model Ensemble Framework for Drug-Target Interaction Prediction. The Journal of Physical Chemistry Letters. 15(30). 7681–7693. 14 indexed citations

Liao, Qingquan, et al.. (2024). Revisiting drug–protein interaction prediction: a novel global–local perspective. Bioinformatics. 40(5). 20 indexed citations

Wang, Jue D., et al.. (2024). MKAN-MMI: empowering traditional medicine-microbe interaction prediction with masked graph autoencoders and KANs. Frontiers in Pharmacology. 15. 1484639–1484639.

Wang, Tao, et al.. (2024). MultiCBlo: Enhancing predictions of compound-induced inhibition of cardiac ion channels with advanced multimodal learning. International Journal of Biological Macromolecules. 276(Pt 2). 133825–133825. 6 indexed citations

10.

Liao, Qingquan, et al.. (2024). Multi-source data integration for explainable miRNA-driven drug discovery. Future Generation Computer Systems. 160. 109–119. 2 indexed citations

11.

Zhao, Yan, Chun-Chun Wang, Fei Chu, et al.. (2024). RFEM: A framework for essential microRNA identification in mice based on rotation forest and multiple feature fusion. Computers in Biology and Medicine. 171. 108177–108177. 9 indexed citations

12.

Wang, Longyue, Linlin Zhuo, Xiangzheng Fu, et al.. (2024). BloodPatrol: Revolutionizing Blood Cancer Diagnosis - Advanced Real-Time Detection Leveraging Deep Learning & Cloud Technologies. IEEE Journal of Biomedical and Health Informatics. PP. 1–11. 2 indexed citations

13.

Wang, Hao, et al.. (2024). CardiOT: Towards Interpretable Drug Cardiotoxicity Prediction Using Optimal Transport and Kolmogorov--Arnold Networks. IEEE Journal of Biomedical and Health Informatics. 29(3). 1759–1770. 3 indexed citations

14.

Zhuo, Linlin, et al.. (2023). HeadTailTransfer: An efficient sampling method to improve the performance of graph neural network method in predicting sparse ncRNA–protein interactions. Computers in Biology and Medicine. 157. 106783–106783. 18 indexed citations

15.

Xu, Lei, et al.. (2023). SGAE-MDA: Exploring the MiRNA-disease associations in herbal medicines based on semi-supervised graph autoencoder. Methods. 221. 73–81. 3 indexed citations

16.

Zhuo, Linlin, Rui Wang, Xiangzheng Fu, & Xiaojun Yao. (2023). StableDNAm: towards a stable and efficient model for predicting DNA methylation based on adaptive feature correction learning. BMC Genomics. 24(1). 742–742. 6 indexed citations

17.

Zhuo, Linlin, et al.. (2023). GCFMCL: predicting miRNA-drug sensitivity using graph collaborative filtering and multi-view contrastive learning. Briefings in Bioinformatics. 24(4). 22 indexed citations

18.

Liao, Qingquan, et al.. (2023). Prediction of miRNA-disease associations in microbes based on graph convolutional networks and autoencoders. Frontiers in Microbiology. 14. 1170559–1170559. 11 indexed citations

19.

Zhuo, Linlin, et al.. (2023). Joint deep autoencoder and subgraph augmentation for inferring microbial responses to drugs. Briefings in Bioinformatics. 25(1). 29 indexed citations

20.

Wang, Zhenqian, et al.. (2022). A DNN Operation Scheme Based on IPSO for UAV-Assisted MEC Networks. 31. 596–601. 1 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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