Mingchun Li

149 papers receiving 3.0k citations

Peers

Mingchun Li
Comparison fields: 5 of 131
  • Infectious Diseases 962
  • Biochemistry 143
  • Molecular Biology 1.3k
  • Epidemiology 578
  • Microbiology 95
Replace Huw D. Williams with:
Huw D. Williams United Kingdom
Nagatoshi Fujiwara Japan
Takashi Suzuki Japan
Markus Nagl Austria
Marisa Colone Italy
Birgit Maria Koch Germany
Gary R. Gray United States
Anil Kumar Verma India
Sander H. J. Smits Germany
Per Olof Ljungdahl Sweden
Mingchun Li relative to Huw D. Williams United Kingdom Huw D. Williams's profile →
Citations per field
00.5×2×2.9×
Huw D. Williams · 1×
Citations per year

Countries citing papers authored by Mingchun Li

Since Specialization
Citations

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

Fields of papers citing papers by Mingchun Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 153 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004215
2 2016177
3 200896
4 200487
5 201769
6 201666
7 200460
8 201159
9 201358
10 201657
11 200354
12 201253
13
Anemoside B4 exerts anti-cancer effect by inducing apoptosis and autophagy through inhibiton of PI3K/Akt/mTOR pathway in hepatocellular carcinoma.
201952
14 201848
15 201247
16 201442
17 202041
18 201440
19 201340
20 200938

About Mingchun Li

Mingchun Li is a scholar working on Infectious Diseases, Biochemistry, Molecular Biology, Epidemiology and Oncology, having authored 153 papers that have together received 3.1k indexed citations. Recurring topics across this work include Antifungal resistance and susceptibility (54 papers), Lipid metabolism and biosynthesis (19 papers), Fungal Infections and Studies (16 papers), Peptidase Inhibition and Analysis (15 papers), Autophagy in Disease and Therapy (14 papers), Microbial Metabolic Engineering and Bioproduction (14 papers), Fungal and yeast genetics research (13 papers) and Endoplasmic Reticulum Stress and Disease (10 papers). The work is most often cited by research in Infectious Diseases (962 citations), Biochemistry (143 citations), Molecular Biology (1.3k citations), Epidemiology (578 citations) and Microbiology (95 citations). Mingchun Li has collaborated with scholars based in China, United States and France. Frequent co-authors include Qilin Yu, Laijun Xing, Dana A. Davis, Bing Zhang, Biao Zhang, Ning Xu, SAMUEL J. MARTIN, Xiaohui Ding, Chang Jia and Eric S. Bensen. Their work appears in journals such as Fungal Genetics and Biology, FEMS Yeast Research, Biochemical and Biophysical Research Communications, Mycopathologia and Chemico-Biological Interactions.

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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