Ming Yi

1.6k citations
61 papers · 1.1k · h-index 22

Impact in

Papers in

Ming Yi

57 papers receiving 1.1k citations

Peers

Ming Yi
Comparison fields: 5 of 90
  • Behavioral Neuroscience 108
  • Cellular and Molecular Neuroscience 341
  • Physiology 440
  • Complementary and alternative medicine 125
  • Cognitive Neuroscience 191
Replace Xiaobing Zhang with:
Xiaobing Zhang United States
Yu‐Lin Dong China
Xiao-Ding Cao China
Anke Tappe‐Theodor Germany
Chia‐Chuan Wang Taiwan
Ceng Luo China
Valeria P. Carlini Argentina
Huxing Cui United States
Adalberto A. Castro Brazil
C. Reyes‐Vázquez Mexico
Ming Yi relative to Xiaobing Zhang United States Xiaobing Zhang's profile →
Citations per field
00.5×1.5×2.0×
Xiaobing Zhang · 1×
Citations per year

Countries citing papers authored by Ming Yi

Since Specialization
Citations

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

Fields of papers citing papers by Ming Yi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ming Yi, 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 Yi Line = papers co-authored together Ming Yi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201795
2 201953
3 201150
4 201650
5 201744
6 201842
7 201539
8 201837
9 201834
10 201732
11 202232
12 201931
13 201830
14 202228
15 202028
16 201627
17 201726
18 202024
19 201924
20 201824

About Ming Yi

Ming Yi is a scholar working on Physiology, Cellular and Molecular Neuroscience, Molecular Biology, Cognitive Neuroscience and Behavioral Neuroscience, having authored 61 papers that have together received 1.1k indexed citations. Recurring topics across this work include Pain Mechanisms and Treatments (25 papers), Neuroscience and Neuropharmacology Research (13 papers), Stress Responses and Cortisol (9 papers), Memory and Neural Mechanisms (7 papers), Acupuncture Treatment Research Studies (6 papers), Ion channel regulation and function (5 papers), Neuroscience and Neural Engineering (4 papers) and Neuroendocrine regulation and behavior (3 papers). The work is most often cited by research in Behavioral Neuroscience (108 citations), Cellular and Molecular Neuroscience (341 citations), Physiology (440 citations), Complementary and alternative medicine (125 citations) and Cognitive Neuroscience (191 citations). Ming Yi has collaborated with scholars based in China, United States and Montenegro. Frequent co-authors include You Wan, Feng‐Yuan Liu, Shuang Cui, Longyu Ma, Feifei Liao, Haolin Zhang, Yu Zhang, Fengyu Liu, Jie Cai and Jie Zheng. Their work appears in journals such as Neuroscience Bulletin, Cell Reports, Frontiers in Neuroscience, The Journal of Physiology and Acupuncture in Medicine.

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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