Kai Yan

3.2k citations
51 papers · 1.3k · h-index 20

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
    • Breast Cancer Treatment Studies
    • Cancer Genomics and Diagnostics
  • Oncology top 10%
    • HER2/EGFR in Cancer Research
    • Cancer Immunotherapy and Biomarkers

Papers in

Kai Yan

47 papers receiving 1.3k citations

Peers

Kai Yan
Comparison fields: 5 of 93
  • Cancer Research 522
  • Oncology 307
  • Internal Medicine 35
  • Immunology 163
  • Molecular Biology 532
Replace Aneeta Patel with:
Aneeta Patel United States
Magdolna Dank Hungary
Antonella Spila Italy
Elvira Stacher Austria
Ana L. Gomes United Kingdom
Osamu Kitahara Japan
Donal Hollywood Ireland
Eleni Andreopoulou United States
Madalina Tuluc United States
Kai Yan relative to Aneeta Patel United States Aneeta Patel's profile →
Citations per field
00.5×9.5×
Aneeta Patel · 1×
Citations per year

Countries citing papers authored by Kai Yan

Since Specialization
Citations

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

Fields of papers citing papers by Kai Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009250
2 2017148
3 201995
4 201084
5 201557
6 200851
7 202349
8 201744
9 202038
10 202036
11 201534
12 202133
13 202431
14 200730
15 201429
16 201027
17 201223
18 201823
19 201322
20 201421

About Kai Yan

Kai Yan is a scholar working on Immunology, Molecular Biology, Oncology, Cancer Research and Pulmonary and Respiratory Medicine, having authored 51 papers that have together received 1.3k indexed citations. Recurring topics across this work include Immune cells in cancer (4 papers), Hepatocellular Carcinoma Treatment and Prognosis (4 papers), Cancer-related molecular mechanisms research (4 papers), Immune Cell Function and Interaction (4 papers), HER2/EGFR in Cancer Research (3 papers), Ferroptosis and cancer prognosis (3 papers), Cancer Immunotherapy and Biomarkers (3 papers) and Quantum Mechanics and Applications (2 papers). The work is most often cited by research in Cancer Research (522 citations), Oncology (307 citations), Internal Medicine (35 citations), Immunology (163 citations) and Molecular Biology (532 citations). Kai Yan has collaborated with scholars based in China, United States and France. Frequent co-authors include W. Fraser Symmans, Lajos Pusztai, Gabriel N. Hortobágyi, Jie Tian, Wenzheng Shi, Yuanfang Zhu, Cornelia Liedtke, Fabrice André, Attila Tordai and Catherine Richon. Their work appears in journals such as Frontiers in Immunology, Journal of Clinical Oncology, PLoS ONE, Breast Cancer Research 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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