Mingyao Yang

6.4k citations
110 papers · 4.6k · h-index 35

Impact in

Papers in

    • Gut microbiota and health 12
    • Genomics and Phylogenetic Studies 10
    • Mitochondrial Function and Pathology 8
    • Genetics, Aging, and Longevity in Model Organisms 25

Mingyao Yang

109 papers receiving 4.5k citations

Peers

Mingyao Yang
Comparison fields: 5 of 136
  • Aging 465
  • Clinical Biochemistry 488
  • Cellular and Molecular Neuroscience 1.1k
  • Endocrine and Autonomic Systems 277
  • Molecular Biology 2.4k
Replace Alberto Sanz with:
Alberto Sanz Spain
Tracy G. Anthony United States
Judd M. Aiken United States
John Tower United States
William B. Mair United States
Marco Groth Germany
Douglas R. Cavener United States
Shinya Yamamoto United States
Michaël Rera France
Zsolt Tallóczy United States
Mingyao Yang relative to Alberto Sanz Spain Alberto Sanz's profile →
Citations per field
00.5×3.4×
Alberto Sanz · 1×
Citations per year

Countries citing papers authored by Mingyao Yang

Since Specialization
Citations

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

Fields of papers citing papers by Mingyao Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 110 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1995302
2 2013266
3 2015243
4 2002208
5 2006176
6 2003158
7 1997151
8 1999151
9 2017141
10 2005133
11 2019131
12 1995122
13 2015112
14 2010106
15 201997
16 202094
17 202292
18 202192
19 201388
20 199783

About Mingyao Yang

Mingyao Yang is a scholar working on Molecular Biology, Aging, Cancer Research, Cellular and Molecular Neuroscience and Immunology, having authored 110 papers that have together received 4.6k indexed citations. Recurring topics across this work include Genetics, Aging, and Longevity in Model Organisms (25 papers), Neurobiology and Insect Physiology Research (17 papers), Cancer-related molecular mechanisms research (17 papers), Gut microbiota and health (12 papers), Circadian rhythm and melatonin (10 papers), Genomics and Phylogenetic Studies (10 papers), Mitochondrial Function and Pathology (8 papers) and Insect Utilization and Effects (7 papers). The work is most often cited by research in Aging (465 citations), Clinical Biochemistry (488 citations), Cellular and Molecular Neuroscience (1.1k citations), Endocrine and Autonomic Systems (277 citations) and Molecular Biology (2.4k citations). Mingyao Yang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Xiaolan Fan, J. Douglas Armstrong, Kim Kaiser, Ian Holt, Howard T. Jacobs, Diyan Li, Deying Yang, Uma Gaur, Aurelio Reyes and Mark Bowmaker. Their work appears in journals such as International Journal of Molecular Sciences, Aging, PLoS ONE, Mechanisms of Ageing and Development and Experimental Gerontology.

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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