Ke Wan

1.0k citations
18 papers · 809 · h-index 8

Impact in

  • Aging top 5%
    • DNA Repair Mechanisms
    • Epigenetics and DNA Methylation
    • CRISPR and Genetic Engineering
    • Cancer-related gene regulation
    • Histone Deacetylase Inhibitors Research
    • Genomics and Chromatin Dynamics

Papers in

    • DNA Repair Mechanisms 4
    • Genomics and Chromatin Dynamics 2
    • CRISPR and Genetic Engineering 2
    • Plant Molecular Biology Research 2

Ke Wan

17 papers receiving 804 citations

Peers

Ke Wan
Comparison fields: 5 of 82
  • Aging 45
  • Molecular Biology 642
  • Physiology 188
  • Hematology 34
  • Neurology 44
Replace Mahya Mehrmohamadi with:
Mahya Mehrmohamadi United States
Michael Ewing United States
Noa Reis Israel
Patricia G. Tu United States
Dorien Haesen Belgium
Ragini Bhargava United States
Xianming Kong United States
Yinglu Li China
Duran Sürün Germany
Daniël Blom United States
Ke Wan relative to Mahya Mehrmohamadi United States Mahya Mehrmohamadi's profile →
Citations per field
00.5×8.8×
Mahya Mehrmohamadi · 1×
Citations per year

Countries citing papers authored by Ke Wan

Since Specialization
Citations

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

Fields of papers citing papers by Ke Wan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1 2006228
2 2012222
3 2009116
4 201397
5 201062
6 201036
7 201616
8 202110
9 20167
10 20165
11 20243
12 20242
13 20241
14 20231
15 20131
16 20241
17 20241
18 20230

About Ke Wan

Ke Wan is a scholar working on Molecular Biology, Plant Science, Computer Vision and Pattern Recognition, Cell Biology and Physiology, having authored 18 papers that have together received 809 indexed citations. Recurring topics across this work include DNA Repair Mechanisms (4 papers), Microtubule and mitosis dynamics (2 papers), Genetics, Aging, and Longevity in Model Organisms (2 papers), Plant Molecular Biology Research (2 papers), Telomeres, Telomerase, and Senescence (2 papers), Genomics and Chromatin Dynamics (2 papers), CRISPR and Genetic Engineering (2 papers) and Robotics and Sensor-Based Localization (1 paper). The work is most often cited by research in Aging (45 citations), Molecular Biology (642 citations), Physiology (188 citations), Hematology (34 citations) and Neurology (44 citations). Ke Wan has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Ming Lei, Yuting Yang, Yong Chen, Bingbing Wan, Yi Zhang, Feng Wang, Ming Lei, Kenichi Yamane, Neal F. Lue and Natalia A. Veniaminova. Their work appears in journals such as Aquaculture, Cell Research, Cell Reports, Nucleic Acids Research and Proceedings of the National Academy of Sciences.

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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