Mingjun Yu

520 citations
23 papers · 278 · h-index 10

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
    • Circular RNAs in diseases
    • RNA modifications and cancer
    • RNA Research and Splicing

Papers in

Mingjun Yu

21 papers receiving 276 citations

Peers

Mingjun Yu
Comparison fields: 5 of 75
  • Cancer Research 147
  • Molecular Biology 167
  • Aging 4
  • Neurology 17
  • Epidemiology 61
Replace Shijia Yu with:
Shijia Yu China
P.S. Fenwick United Kingdom
Feihong Lin China
Xue Zeng China
Julius L. Decano United States
Haixia Hu China
Ana Mompeón Spain
Dongyao Hou China
Deqin Wu China
Amruta Singh India
Mingjun Yu relative to Shijia Yu China Shijia Yu's profile →
Citations per field
00.5×1.5×
Shijia Yu · 1×
Citations per year

Countries citing papers authored by Mingjun Yu

Since Specialization
Citations

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

Fields of papers citing papers by Mingjun Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019109
2 202034
3 202117
4 202015
5 201915
6 202015
7 201812
8 202010
9 202110
10 20239
11 20196
12 20195
13
[Mycoplasma genitalium lipid-associated membrane proteins induce human monocytic cell express proinflammatory cytokines and apoptosis by activating nuclear factor kappaB].
20075
14 20254
15 20214
16 20222
17 20182
18 20221
19 20141
20 20211

About Mingjun Yu

Mingjun Yu is a scholar working on Cancer Research, Molecular Biology, Organic Chemistry, Epidemiology and Genetics, having authored 23 papers that have together received 278 indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (8 papers), MicroRNA in disease regulation (3 papers), Peptidase Inhibition and Analysis (2 papers), Synthesis and biological activity (2 papers), Synthesis and Biological Evaluation (2 papers), Bioactive Compounds and Antitumor Agents (2 papers), Hippo pathway signaling and YAP/TAZ (2 papers) and Neuroinflammation and Neurodegeneration Mechanisms (2 papers). The work is most often cited by research in Cancer Research (147 citations), Molecular Biology (167 citations), Aging (4 citations), Neurology (17 citations) and Epidemiology (61 citations). Mingjun Yu has collaborated with scholars based in China and United States. Frequent co-authors include Shijia Yu, Zhongqi Bu, Juan Feng, Lulu Wen, Xin He, Pingping He, Wen Zhou, Yunhui Liu, Duo Chen and Risheng Yao. Their work appears in journals such as Anti-Cancer Agents in Medicinal Chemistry, Journal of Cellular and Molecular Medicine, Journal of Molecular Neuroscience, Journal of Cancer and Chemical and Pharmaceutical Bulletin.

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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