Ming Ni

442 total citations
15 papers, 342 citations indexed

About

Ming Ni is a scholar working on Surgery, Molecular Biology and Genetics. According to data from OpenAlex, Ming Ni has authored 15 papers receiving a total of 342 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Surgery, 3 papers in Molecular Biology and 3 papers in Genetics. Recurrent topics in Ming Ni's work include Glioma Diagnosis and Treatment (3 papers), Circular RNAs in diseases (3 papers) and Orthopaedic implants and arthroplasty (2 papers). Ming Ni is often cited by papers focused on Glioma Diagnosis and Treatment (3 papers), Circular RNAs in diseases (3 papers) and Orthopaedic implants and arthroplasty (2 papers). Ming Ni collaborates with scholars based in China, Philippines and United States. Ming Ni's co-authors include Rachel R Caspi, Robert B. Nussenblatt, Gerald J. Chader, Barbara Wiggert, Chi‐Chao Chan, Hua Fan, Peizhi Ma, Yuanlong Li, Fengqin Fang and Jun Sun and has published in prestigious journals such as Neuroscience, Medicine and The International Journal of Biochemistry & Cell Biology.

In The Last Decade

Ming Ni

13 papers receiving 341 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ming Ni China 6 132 128 115 87 72 15 342
Mehdi Motallebipour Sweden 7 357 2.7× 339 2.6× 32 0.3× 57 0.7× 18 0.3× 7 659
Yaru Su China 10 69 0.5× 253 2.0× 47 0.4× 115 1.3× 10 0.1× 19 387
Naoko Hiroshiba Japan 10 313 2.4× 138 1.1× 122 1.1× 10 0.1× 40 0.6× 11 473
Harutyun Melkonyan Germany 13 97 0.7× 232 1.8× 133 1.2× 50 0.6× 43 0.6× 20 363
Yang Jiang China 9 20 0.2× 166 1.3× 28 0.2× 123 1.4× 17 0.2× 23 307
Valeria E. Lorenc United States 13 263 2.0× 271 2.1× 48 0.4× 25 0.3× 6 0.1× 15 458
S J Kenealy United States 8 193 1.5× 183 1.4× 63 0.5× 18 0.2× 28 0.4× 13 386
Prudence N. Gatt Australia 8 24 0.2× 79 0.6× 88 0.8× 16 0.2× 108 1.5× 13 358
Yumiko Saishin United States 10 440 3.3× 336 2.6× 30 0.3× 31 0.4× 13 0.2× 10 639
Jennifer Kelly United States 4 158 1.2× 120 0.9× 153 1.3× 31 0.4× 7 0.1× 5 397

Countries citing papers authored by Ming Ni

Since Specialization
Citations

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

Fields of papers citing papers by Ming Ni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming Ni

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

All Works

15 of 15 papers shown
1.
Zhao, Hongwei, et al.. (2025). Comparative Analysis of Generative Artificial Intelligence Systems in Solving Clinical Pharmacy Problems: Mixed Methods Study. JMIR Medical Informatics. 13. e76128–e76128. 1 indexed citations
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Li, Yuanlong, Hua Fan, Ming Ni, et al.. (2023). Targeting lncRNA NEAT1 Hampers Alzheimer’s Disease Progression. Neuroscience. 529. 88–98. 7 indexed citations
7.
Li, Yuanlong, Xiong Han, Hua Fan, et al.. (2022). Circular RNA AXL increases neuron injury and inflammation through targeting microRNA-328 mediated BACE1 in Alzheimer’s disease. Neuroscience Letters. 776. 136531–136531. 27 indexed citations
8.
Long, Cheng, et al.. (2022). Implication of Changes in the Imaging Measurements after Mechanically Aligned Total Knee Arthroplasty. Orthopaedic Surgery. 14(12). 3322–3329. 1 indexed citations
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Li, Yuanlong, Hua Fan, Jun Sun, et al.. (2020). Circular RNA expression profile of Alzheimer’s disease and its clinical significance as biomarkers for the disease risk and progression. The International Journal of Biochemistry & Cell Biology. 123. 105747–105747. 81 indexed citations
11.
Kang, Peng, et al.. (2020). Clinical Characteristics and Surgical Features of Intracranial Fibrosarcoma. Journal of Craniofacial Surgery. 31(3). 825–828. 1 indexed citations
12.
Ni, Ming, et al.. (2020). Polymyxin B-induced rhabdomyolysis. Medicine. 99(43). e22924–e22924. 2 indexed citations
13.
Feng, Ying, Ming Ni, Yonggang Wang, & Liyong Zhong. (2018). Comparison of neuroendocrine dysfunction in patients with adamantinomatous and papillary craniopharyngiomas. Experimental and Therapeutic Medicine. 17(1). 51–56. 20 indexed citations
14.
Zhong, Liyong, et al.. (2015). Clinical research on neuroendocrine dysfunction and grading of neuroendocrine function in children with craniopharyngioma. Chin J Postgrad Med. 38(9). 674–679. 1 indexed citations
15.
Chan, Chi‐Chao, Rachel R Caspi, Ming Ni, et al.. (1990). Pathology of experimental autoimmune uveoretinitis in mice. Journal of Autoimmunity. 3(3). 247–255. 177 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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