Jiucun Wang

9.6k total citations · 1 hit paper
241 papers, 4.7k citations indexed

About

Jiucun Wang is a scholar working on Molecular Biology, Pathology and Forensic Medicine and Genetics. According to data from OpenAlex, Jiucun Wang has authored 241 papers receiving a total of 4.7k indexed citations (citations by other indexed papers that have themselves been cited), including 123 papers in Molecular Biology, 51 papers in Pathology and Forensic Medicine and 41 papers in Genetics. Recurrent topics in Jiucun Wang's work include Systemic Sclerosis and Related Diseases (37 papers), Cancer-related molecular mechanisms research (23 papers) and RNA modifications and cancer (19 papers). Jiucun Wang is often cited by papers focused on Systemic Sclerosis and Related Diseases (37 papers), Cancer-related molecular mechanisms research (23 papers) and RNA modifications and cancer (19 papers). Jiucun Wang collaborates with scholars based in China, United States and Germany. Jiucun Wang's co-authors include Jin Li, Yanyun Ma, Shicheng Guo, Weilin Pu, Hejian Zou, Haiyan Chu, Xiaodong Zhou, Qingmei Liu, Xiaofeng Wang and Wenyu Wu and has published in prestigious journals such as Nature Medicine, Nature Genetics and The Journal of Experimental Medicine.

In The Last Decade

Jiucun Wang

224 papers receiving 4.6k citations

Hit Papers

Landscape of pathogenic mutations in premature ovarian in... 2023 2026 2024 2025 2023 25 50 75 100

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jiucun Wang China 37 2.4k 955 670 620 594 241 4.7k
Mika Watanabe Japan 43 1.8k 0.8× 1.1k 1.1× 748 1.1× 1.3k 2.1× 548 0.9× 344 6.9k
Shi Wei United States 38 2.5k 1.0× 976 1.0× 338 0.5× 876 1.4× 594 1.0× 274 5.5k
Vladislav Volarević Serbia 42 2.6k 1.1× 862 0.9× 469 0.7× 494 0.8× 1.2k 2.1× 121 6.6k
Yasuteru Muragaki Japan 43 3.4k 1.4× 789 0.8× 316 0.5× 646 1.0× 487 0.8× 145 7.0k
Tommy Martinsson Sweden 49 3.3k 1.4× 1.3k 1.3× 469 0.7× 497 0.8× 1.0k 1.7× 202 6.3k
Masayoshi Kobune Japan 45 2.9k 1.2× 684 0.7× 371 0.6× 530 0.9× 638 1.1× 173 7.0k
Melpo Christofidou‐Solomidou United States 45 2.1k 0.9× 624 0.7× 408 0.6× 809 1.3× 779 1.3× 110 5.3k
H. William Schnaper United States 42 3.1k 1.3× 1.1k 1.2× 434 0.6× 648 1.0× 553 0.9× 84 6.1k
Eunice S. Wang United States 46 3.0k 1.3× 636 0.7× 611 0.9× 214 0.3× 1.1k 1.9× 343 7.1k
Liying Zhang China 35 2.8k 1.2× 1.5k 1.6× 801 1.2× 1.0k 1.7× 808 1.4× 198 7.2k

Countries citing papers authored by Jiucun Wang

Since Specialization
Citations

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

Fields of papers citing papers by Jiucun Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiucun Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Jiucun Wang. A scholar is included among the top collaborators of Jiucun Wang 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 Jiucun Wang. Jiucun Wang 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
2.
Zhang, Zhao, Mu Li, Jingze Tan, et al.. (2025). FPQuant: A deep learning-based scalable framework for fingerprint phenomics quantification in large-scale biometric population studies. Pattern Recognition. 173. 112808–112808.
4.
Li, Zhijian, Wenjie Xie, Wenjing Ye, et al.. (2025). Spatial multiomics decipher fibroblast–macrophage dynamics in systemic sclerosis. Annals of the Rheumatic Diseases. 84(7). 1231–1245. 3 indexed citations
5.
Li, Yinan, Andrea‐Hermina Györfi, Minrui Liang, et al.. (2025). Spatially informed phenotyping by cyclic-in-situ-hybridisation identifies novel fibroblast populations and their pathogenic niches in systemic sclerosis. Annals of the Rheumatic Diseases. 84(11). 1852–1864. 1 indexed citations
6.
Yan, Shi, et al.. (2024). Mitochondrial DNA Genomes Reveal Relaxed Purifying Selection During Human Population Expansion after the Last Glacial Maximum. Molecular Biology and Evolution. 41(9). 1 indexed citations
7.
Zhou, Yi, Jing Lü, Lianyi Han, et al.. (2024). Optimizing Skin Surface Metabolomics: A Comprehensive Evaluation of Sampling Methods, Extraction Solvents, and Analytical Techniques. Journal of Investigative Dermatology. 145(5). 1166–1179. 1 indexed citations
8.
Jiang, Shuai, Qing Zhang, Lu Bai, et al.. (2024). Iron metabolism and arthritis: Exploring connections and therapeutic avenues. Chinese Medical Journal. 137(14). 1651–1662. 6 indexed citations
9.
Zhang, Xiao‐Yong, Yanyan Liu, Shuo Tao, et al.. (2023). Downregulation of mGluR1-mediated signaling underlying autistic-like core symptoms in Shank1 P1812L-knock-in mice. Translational Psychiatry. 13(1). 329–329. 2 indexed citations
10.
Velier, Mélanie, Stéphanie Simoncini, A. Benyamine, et al.. (2023). Adipose Tissue and Adipose-Tissue-Derived Cell Therapies for the Treatment of the Face and Hands of Patients Suffering from Systemic Sclerosis. Biomedicines. 11(2). 348–348. 9 indexed citations
11.
Peng, Qianqian, Yu Liu, Canfeng Zhang, et al.. (2022). Genetic Variants in Telomerase Reverse Transcriptase Contribute to Solar Lentigines. Journal of Investigative Dermatology. 143(6). 1062–1072.e25. 3 indexed citations
12.
Kang, Jujiao, Yi Wang, Jiucun Wang, et al.. (2022). Associations between polygenic risk scores and amplitude of low-frequency fluctuation of inferior frontal gyrus in schizophrenia. Journal of Psychiatric Research. 147. 4–12. 10 indexed citations
13.
Zhao, Qi, et al.. (2022). Skin Microbiome, Metabolome and Skin Phenome, from the Perspectives of Skin as an Ecosystem. PubMed. 2(6). 363–382. 43 indexed citations
14.
Ding, Hao, et al.. (2021). RASAL2 Deficiency Attenuates Hepatic Steatosis by Promoting Hepatic VLDL Secretion via the AKT/TET1/MTTP Axis. Journal of Clinical and Translational Hepatology. 0(0). 0–0. 3 indexed citations
15.
Pu, Weilin, Rui Zhang, Yanyun Ma, et al.. (2021). Genetic Associations of Non–Major Histocompatibility Complex Susceptibility Loci with Systemic Sclerosis in a Han Chinese Population. Journal of Investigative Dermatology. 142(7). 2039–2042.e7. 1 indexed citations
16.
Zhu, Sibo, Kelin Xu, Yanfeng Jiang, et al.. (2021). The gut microbiome in subclinical atherosclerosis: a population-based multiphenotype analysis. Lara D. Veeken. 61(1). 258–269. 19 indexed citations
17.
Györfi, Andrea‐Hermina, Alexandru‐Emil Matei, Maximilian Fuchs, et al.. (2021). Engrailed 1 coordinates cytoskeletal reorganization to induce myofibroblast differentiation. The Journal of Experimental Medicine. 218(9). 33 indexed citations
18.
Kang, Jujiao, Zeyu Jiao, Yi Wang, et al.. (2020). Polygenic risk for autism spectrum disorder affects left amygdala activity and negative emotion in schizophrenia. Translational Psychiatry. 10(1). 322–322. 5 indexed citations
19.
Wu, Junjie, Yuhao Zhou, Jun Ying, et al.. (2012). Predictive Value of XRCC1 Gene Polymorphisms on Platinum-Based Chemotherapy in Advanced Non–Small Cell Lung Cancer Patients: A Systematic Review and Meta-analysis. Clinical Cancer Research. 18(14). 3972–3981. 42 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026