Ming Yan

1.9k citations
62 papers · 1.5k · h-index 26

Impact in

Papers in

Ming Yan

61 papers receiving 1.5k citations

Peers

Ming Yan
Comparison fields: 5 of 124
  • Sensory Systems 71
  • Pathology and Forensic Medicine 195
  • Cancer Research 164
  • Molecular Biology 721
  • Filtration and Separation 20
Replace Xuwen Liu with:
Xuwen Liu China
Yun‐Wen Chen Taiwan
Masahiko Saito Japan
Nicholas J. Izzo United States
Ke‐Yu Deng China
Thomas Ulas Germany
Karin Steinbach Germany
Chie Watanabe Japan
Yingbin Ge China
Ming Yan relative to Xuwen Liu China Xuwen Liu's profile →
Citations per field
00.5×4.8×
Xuwen Liu · 1×
Citations per year

Countries citing papers authored by Ming Yan

Since Specialization
Citations

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

Fields of papers citing papers by Ming Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ming Yan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ming Yan Line = papers co-authored together Ming Yan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 62 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003119
2 201174
3 201971
4 201161
5 201055
6 200752
7 201148
8 200945
9 201143
10 201843
11 201141
12 201341
13 201241
14 201538
15
A novel mutation in CRYAB associated with autosomal dominant congenital nuclear cataract in a Chinese family.
200936
16 201535
17 202233
18 200933
19 201232
20 201530

About Ming Yan

Ming Yan is a scholar working on Molecular Biology, Pathology and Forensic Medicine, Oncology, Rheumatology and Biomedical Engineering, having authored 62 papers that have together received 1.5k indexed citations. Recurring topics across this work include Spine and Intervertebral Disc Pathology (7 papers), Cancer Cells and Metastasis (5 papers), Spondyloarthritis Studies and Treatments (4 papers), Glioma Diagnosis and Treatment (4 papers), Osteoarthritis Treatment and Mechanisms (3 papers), Ubiquitin and proteasome pathways (3 papers), Epigenetics and DNA Methylation (3 papers) and Heat shock proteins research (3 papers). The work is most often cited by research in Sensory Systems (71 citations), Pathology and Forensic Medicine (195 citations), Cancer Research (164 citations), Molecular Biology (721 citations) and Filtration and Separation (20 citations). Ming Yan has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Min Yang, Zhuojing Luo, Jingzhi Li, Bingdong Sha, Zhengxu Ye, Ronghua Li, Xingkuan Bu, Guangqian Xing, Min‐Xin Guan and Xuezhong Liu. Their work appears in journals such as Frontiers in Cell and Developmental Biology, Biochemical and Biophysical Research Communications, PLoS ONE, Frontiers in Immunology and Spine.

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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