Liming Cheng

2.5k total citations · 1 hit paper
85 papers, 1.7k citations indexed

About

Liming Cheng is a scholar working on Pathology and Forensic Medicine, Surgery and Pharmacology. According to data from OpenAlex, Liming Cheng has authored 85 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Pathology and Forensic Medicine, 45 papers in Surgery and 15 papers in Pharmacology. Recurrent topics in Liming Cheng's work include Spine and Intervertebral Disc Pathology (30 papers), Spinal Fractures and Fixation Techniques (21 papers) and Spinal Cord Injury Research (19 papers). Liming Cheng is often cited by papers focused on Spine and Intervertebral Disc Pathology (30 papers), Spinal Fractures and Fixation Techniques (21 papers) and Spinal Cord Injury Research (19 papers). Liming Cheng collaborates with scholars based in China, United States and Germany. Liming Cheng's co-authors include Rongrong Zhu, Yilong Ren, Zhaojie Wang, Xiaolie He, Wei Xu, Xiao Hu, Bei Ma, Runzhi Huang, Jingwei Zhao and Yan Yu and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and ACS Nano.

In The Last Decade

Liming Cheng

80 papers receiving 1.7k citations

Hit Papers

Spinal cord injury: molecular mechanisms and therapeutic ... 2023 2026 2024 2025 2023 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Liming Cheng China 21 679 509 418 354 222 85 1.7k
Mao Pang China 26 725 1.1× 535 1.1× 494 1.2× 379 1.1× 215 1.0× 62 1.8k
Muhammad Dain Yazid Malaysia 17 555 0.8× 272 0.5× 566 1.4× 285 0.8× 155 0.7× 65 1.8k
Chiung‐Chyi Shen Taiwan 30 370 0.5× 660 1.3× 762 1.8× 313 0.9× 182 0.8× 152 2.9k
Xiaojian Cao China 28 568 0.8× 551 1.1× 614 1.5× 233 0.7× 114 0.5× 101 2.1k
Abhay Varma United States 24 580 0.9× 298 0.6× 399 1.0× 247 0.7× 171 0.8× 55 1.5k
Oliver Hausmann Switzerland 20 819 1.2× 374 0.7× 328 0.8× 264 0.7× 52 0.2× 46 1.7k
Lucia Machová Urdzíková Czechia 22 797 1.2× 384 0.8× 439 1.1× 652 1.8× 195 0.9× 45 1.9k
Jen‐Tsung Yang Taiwan 25 292 0.4× 263 0.5× 368 0.9× 194 0.5× 154 0.7× 104 1.8k
Yue Tu China 24 200 0.3× 200 0.4× 533 1.3× 313 0.9× 233 1.0× 56 1.5k
Seil Sohn South Korea 25 650 1.0× 719 1.4× 299 0.7× 159 0.4× 197 0.9× 89 1.8k

Countries citing papers authored by Liming Cheng

Since Specialization
Citations

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

Fields of papers citing papers by Liming Cheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Liming Cheng

This figure shows the co-authorship network connecting the top 25 collaborators of Liming Cheng. A scholar is included among the top collaborators of Liming Cheng 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 Liming Cheng. Liming Cheng 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.
Cheng, Liming, Xiaojing Du, Teng Huang, et al.. (2025). Bioinformatics Analysis and Expression Profiling Under Abiotic Stress of the DREB Gene Family in Glycyrrhiza uralensis. International Journal of Molecular Sciences. 26(18). 9235–9235. 1 indexed citations
2.
Zhao, Qing, Yanjing Zhu, Yilong Ren, et al.. (2024). Targeting resident astrocytes attenuates neuropathic pain after spinal cord injury. eLife. 13. 1 indexed citations
3.
Chen, Jin, Yilong Ren, Yi Li, et al.. (2024). Role of durotomy on function outcome, tissue sparing, inflammation, and tissue stiffness after spinal cord injury in rats. SHILAP Revista de lepidopterología. 5(4). e530–e530. 1 indexed citations
4.
Zhao, Qing, Yanjing Zhu, Yilong Ren, et al.. (2024). Targeting resident astrocytes attenuates neuropathic pain after spinal cord injury. eLife. 13. 3 indexed citations
5.
Wang, Zhao‐Qi, Zhaojie Wang, Xuening Pang, et al.. (2023). LDH-doped gelatin-chitosan scaffold with aligned microchannels improves anti-inflammation and neuronal regeneration with guided axonal growth for effectively recovering spinal cord injury. Applied Materials Today. 34. 101884–101884. 9 indexed citations
6.
Pan, Jie, et al.. (2023). tsRNA-04002 alleviates intervertebral disk degeneration by targeting PRKCA to inhibit apoptosis of nucleus pulposus cells. Journal of Orthopaedic Surgery and Research. 18(1). 413–413. 8 indexed citations
7.
Hu, Xiao, Jingwei Zhao, Yanjing Zhu, et al.. (2023). Development of a nomogram model for prediction of new adjacent vertebral compression fractures after vertebroplasty. BMC Surgery. 23(1). 197–197. 6 indexed citations
9.
Wu, Zhourui, Ran Zhu, Yan Yu, et al.. (2023). Spinal cord injury-activated C/EBPβ-AEP axis mediates cognitive impairment through APP C586/Tau N368 fragments spreading. Progress in Neurobiology. 227. 102467–102467. 10 indexed citations
10.
Zhang, Chunxue, Liqiang Zhou, Zhen Wang, et al.. (2021). Eradication of specific donor-dependent variations of mesenchymal stem cells in immunomodulation to enhance therapeutic values. Cell Death and Disease. 12(4). 357–357. 39 indexed citations
11.
Huang, Runzhi, Rui Zhu, Shuyuan Xian, et al.. (2021). Identification of Key eRNAs for Spinal Cord Injury by Integrated Multinomial Bioinformatics Analysis. Frontiers in Cell and Developmental Biology. 9. 728242–728242. 9 indexed citations
12.
Xi, Xin, et al.. (2021). Is reduction or arthrodesis in situ the optimal choice for adolescent spondylolisthesis?—a systematic review and meta- analysis. Annals of Palliative Medicine. 10(8). 8523–8535. 2 indexed citations
13.
Wei, Xiaochun, et al.. (2020). Identifing the gender-specific genes and pathways in osteoarthritis by bioinfromatics. Osteoarthritis and Cartilage. 28. S207–S208. 1 indexed citations
14.
Huang, Runzhi, Tong Meng, Rui Zhu, et al.. (2020). The Integrated Transcriptome Bioinformatics Analysis Identifies Key Genes and Cellular Components for Spinal Cord Injury-Related Neuropathic Pain. Frontiers in Bioengineering and Biotechnology. 8. 101–101. 7 indexed citations
15.
Li, Haotian, Xinran Zhang, Qi Xi, Zhu Xu, & Liming Cheng. (2019). Icariin Inhibits Endoplasmic Reticulum Stress-induced Neuronal Apoptosis after Spinal Cord Injury through Modulating the PI3K/AKT Signaling Pathway. International Journal of Biological Sciences. 15(2). 277–286. 75 indexed citations
16.
Ren, Yilong, Yan Ao, Timothy M. O’Shea, et al.. (2017). Ependymal cell contribution to scar formation after spinal cord injury is minimal, local and dependent on direct ependymal injury. Scientific Reports. 7(1). 41122–41122. 109 indexed citations
17.
Cheng, Liming, et al.. (2016). Risk Factors for the Postoperative Transfusion of Allogeneic Blood in Orthopedics Patients With Intraoperative Blood Salvage. Medicine. 95(8). e2866–e2866. 7 indexed citations
19.
Huang, Lei, Liming Cheng, Russell O Kosik, et al.. (2014). Analysis of Curricular Reform Practices at Chinese Medical Schools. Teaching and Learning in Medicine. 26(4). 412–419. 19 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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