Chen Sang

2.7k citations
41 papers · 1.8k indexed · h-index 16

Impact in

Papers in

    • Muscle Physiology and Disorders 7
    • RNA modifications and cancer 4
    • MicroRNA in disease regulation 5
    • Cancer, Lipids, and Metabolism 4
    • Cancer-related molecular mechanisms research 4

Chen Sang

36 papers receiving 1.8k citations

Peers

Chen Sang
Comparison fields: 5 of 118
  • Cellular and Molecular Neuroscience 841
  • Aging 70
  • Genetics 344
  • Molecular Biology 1.2k
  • Neurology 213
Replace Eric O. Williams with:
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Chen Sang relative to Eric O. Williams United States Eric O. Williams's profile →
Citations per field
00.5×5.0×
Eric O. Williams · 1×
Citations per year

Countries citing papers authored by Chen Sang

Since Specialization
Citations

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

Fields of papers citing papers by Chen Sang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002352
2 2005313
3 2003205
4 2003201
5 2005180
6 199176
7 201271
8 201961
9 202136
10
Katsuno, M. et al. Leuprorelin rescues polyglutamine-dependent phenotypes in a transgenic mouse model of spinal and bulbar muscular atrophy. Nat. Med. 9, 768−773
200335
11 202133
12 201826
13 201325
14 202020
15 201916
16 201016
17 202215
18 201114
19 200213
20 201013

About Chen Sang

Chen Sang is a scholar working on Molecular Biology, Cancer Research, Surgery, Cellular and Molecular Neuroscience and Pulmonary and Respiratory Medicine, having authored 41 papers that have together received 1.8k indexed citations. Recurring topics across this work include Genetic Neurodegenerative Diseases (7 papers), Muscle Physiology and Disorders (7 papers), MicroRNA in disease regulation (5 papers), Cancer, Lipids, and Metabolism (4 papers), Corrosion Behavior and Inhibition (4 papers), RNA modifications and cancer (4 papers), Spaceflight effects on biology (4 papers) and Cancer-related molecular mechanisms research (4 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (841 citations), Aging (70 citations), Genetics (344 citations), Molecular Biology (1.2k citations) and Neurology (213 citations). Chen Sang has collaborated with scholars based in China, Japan and Switzerland. Frequent co-authors include Manabu Doyu, Hiroaki Adachi, Masahisa Katsuno, Gen Sobue, Makoto Minamiyama, Yasushi Kobayashi, Akira Inukai, Fumiaki Tanaka, Masahiro Waza and Hisayoshi Niwa. Their work appears in journals such as Nature Medicine, Acta Astronautica, Scientific Reports, Journal of Biomechanics and Nature Communications.

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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