Ming Ge

664 citations
25 papers · 201 · h-index 9

Impact in

Papers in

Ming Ge

21 papers receiving 197 citations

Peers

Ming Ge
Comparison fields: 5 of 81
  • Cellular and Molecular Neuroscience 80
  • Neurology 33
  • Sensory Systems 16
  • Cognitive Neuroscience 51
  • Behavioral Neuroscience 9
Replace Ziyue Wang with:
Ziyue Wang China
Yingjie Li China
Hiroshi Oishi Japan
Wenjing He China
Parisa Farzanehfar Australia
Ibrahim T. Mughrabi United States
Sergio Castaño-Castaño Spain
Chuang‐Kuo Wu United States
Amanda Deligtisch United States
Longtu Chen United States
Ming Ge relative to Ziyue Wang China Ziyue Wang's profile →
Citations per field
00.5×3.2×
Ziyue Wang · 1×
Citations per year

Countries citing papers authored by Ming Ge

Since Specialization
Citations

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

Fields of papers citing papers by Ming Ge

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201046
2 201036
3 201125
4 202215
5 202314
6 200911
7 202010
8 202410
9 20228
10 20236
11 20245
12 20252
13 20232
14 20242
15 19912
16 20152
17 20241
18 20131
19 20221
20 19891

About Ming Ge

Ming Ge is a scholar working on Cellular and Molecular Neuroscience, Mechanical Engineering, Molecular Biology, Control and Systems Engineering and Computer Vision and Pattern Recognition, having authored 25 papers that have together received 201 indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (2 papers), Advanced Photocatalysis Techniques (2 papers), Air Quality and Health Impacts (2 papers), Neuroscience and Neuropharmacology Research (2 papers), Gas Sensing Nanomaterials and Sensors (2 papers), Genomics, phytochemicals, and oxidative stress (2 papers), Climate Change and Health Impacts (2 papers) and Advanced Materials and Mechanics (1 paper). The work is most often cited by research in Cellular and Molecular Neuroscience (80 citations), Neurology (33 citations), Sensory Systems (16 citations), Cognitive Neuroscience (51 citations) and Behavioral Neuroscience (9 citations). Ming Ge has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Sudong Guan, Li Huang, Jinhui Wang, Yan Zhu, Na Chen, Fengyu Zhang, Hong Ni, Na Chen, Changchun Pan and Yong-Zai Lu. Their work appears in journals such as Biochemical and Biophysical Research Communications, Journal of Process Control, The Pediatric Infectious Disease Journal, World Neurosurgery and Polymer Journal.

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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