De Cheng

684 citations
24 papers · 516 · h-index 14

Impact in

  • Aging top 10%
    • Animal Genetics and Reproduction
    • Mesenchymal stem cell research

Papers in

    • Pluripotent Stem Cells Research 12
    • CRISPR and Genetic Engineering 11
    • Renal and related cancers 4
    • RNA Interference and Gene Delivery 3
    • Telomeres, Telomerase, and Senescence 8

De Cheng

23 papers receiving 509 citations

Peers

De Cheng
Comparison fields: 5 of 69
  • Aging 24
  • Genetics 53
  • Molecular Biology 357
  • Reproductive Medicine 41
  • Physiology 113
Replace Guangzhen Ji with:
Guangzhen Ji China
Deqiang Ding China
Erica Yada Japan
JW Shay United States
Buhe Nashun China
Justyna Józefczuk Germany
Sicong Zeng China
Wanhua Xie China
Tanya Halvorsen United States
De Cheng relative to Guangzhen Ji China Guangzhen Ji's profile →
Citations per field
00.5×1.5×2.2×
Guangzhen Ji · 1×
Citations per year

Countries citing papers authored by De Cheng

Since Specialization
Citations

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

Fields of papers citing papers by De Cheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201261
2 201258
3 201158
4 201448
5 201331
6 201731
7 201630
8 201128
9 201327
10 201518
11 201716
12 201216
13 201614
14 201214
15 201412
16 202011
17 201911
18 20218
19 20118
20 20128

About De Cheng

De Cheng is a scholar working on Molecular Biology, Physiology, Surgery, Public Health, Environmental and Occupational Health and Genetics, having authored 24 papers that have together received 516 indexed citations. Recurring topics across this work include Pluripotent Stem Cells Research (12 papers), CRISPR and Genetic Engineering (11 papers), Telomeres, Telomerase, and Senescence (8 papers), Renal and related cancers (4 papers), Animal Genetics and Reproduction (3 papers), RNA Interference and Gene Delivery (3 papers), Tissue Engineering and Regenerative Medicine (3 papers) and Reproductive Biology and Fertility (3 papers). The work is most often cited by research in Aging (24 citations), Genetics (53 citations), Molecular Biology (357 citations), Reproductive Medicine (41 citations) and Physiology (113 citations). De Cheng has collaborated with scholars based in China and United States. Frequent co-authors include Huayan Wang, Jiyue Zhu, Yuanjun Zhao, Xing Gao, Yajun Liu, Fan Zhang, Xiaoling Ma, Shuwen Wang, Shuwen Wang and Yi Gao. Their work appears in journals such as PLoS ONE, Scientific Reports, Biochemical and Biophysical Research Communications, Nature Communications and The FASEB 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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