Kun Lin

1.1k citations
43 papers · 853 · h-index 19

Impact in

Papers in

Kun Lin

41 papers receiving 830 citations

Peers

Kun Lin
Comparison fields: 5 of 108
  • Modeling and Simulation 83
  • Health, Toxicology and Mutagenesis 135
  • Cancer Research 115
  • Oncology 174
  • Otorhinolaryngology 27
Replace Bolin Wang with:
Bolin Wang China
Sachin Agrawal India
C-J Chen Taiwan
Nicola Fitz-Simon Ireland
Jie Sheng China
Changping Li China
Graham H. Bevan United States
Claire D. Sherman United States
Esther Erdei United States
Vincent L. Freeman United States
Kun Lin relative to Bolin Wang China Bolin Wang's profile →
Citations per field
00.5×9.7×
Bolin Wang · 1×
Citations per year

Countries citing papers authored by Kun Lin

Since Specialization
Citations

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

Fields of papers citing papers by Kun Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005105
2 201454
3 201546
4 200240
5 201436
6 201536
7 201436
8 201833
9 201433
10 201530
11
XRCC1 Arg399Gln gene polymorphism and breast cancer risk: a meta-analysis based on case-control studies.
201130
12 201630
13 201528
14 201527
15 201725
16 201524
17 202124
18 200320
19 201520
20 201518

About Kun Lin

Kun Lin is a scholar working on Cardiology and Cardiovascular Medicine, Health, Toxicology and Mutagenesis, Oncology, Surgery and Cancer Research, having authored 43 papers that have together received 853 indexed citations. Recurring topics across this work include Atrial Fibrillation Management and Outcomes (8 papers), Cardiac Arrhythmias and Treatments (7 papers), Venous Thromboembolism Diagnosis and Management (5 papers), Esophageal Cancer Research and Treatment (4 papers), Global Cancer Incidence and Screening (4 papers), Cancer Risks and Factors (4 papers), Heavy Metal Exposure and Toxicity (3 papers) and Water Treatment and Disinfection (3 papers). The work is most often cited by research in Modeling and Simulation (83 citations), Health, Toxicology and Mutagenesis (135 citations), Cancer Research (115 citations), Oncology (174 citations) and Otorhinolaryngology (27 citations). Kun Lin has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Kusheng Wu, Johan Karlberg, Dyt Fong, Jiaying Fang, William W. Au, Yongning Wu, Zhaoliang Shan, Yutang Wang, Wen‐Ying Shen and Zhong‐Ying Shen. Their work appears in journals such as PLoS ONE, Environmental Science and Pollution Research, International Journal of Cancer, Scientific Reports and Pancreas.

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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