Lun Tan

608 citations
28 papers · 442 · h-index 13

Impact in

Papers in

Lun Tan

26 papers receiving 439 citations

Peers

Lun Tan
Comparison fields: 5 of 72
  • Cardiology and Cardiovascular Medicine 63
  • Molecular Biology 180
  • Clinical Biochemistry 13
  • Pulmonary and Respiratory Medicine 53
  • Cancer Research 25
Replace Sumihiko Hagita with:
Sumihiko Hagita Japan
Ruizheng Shi China
Aninda Basu United States
Ya-Nan Shu China
Xiangxiao Li China
Nataliya Pidkovka United States
A.V. Krushinsky Russia
Maryvonne Moisant France
Ettickan Boopathi United States
Lun Tan relative to Sumihiko Hagita Japan Sumihiko Hagita's profile →
Citations per field
00.5×2.6×
Sumihiko Hagita · 1×
Citations per year

Countries citing papers authored by Lun Tan

Since Specialization
Citations

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

Fields of papers citing papers by Lun Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202260
2 201755
3 201652
4 202328
5 201728
6 201726
7 201825
8 201625
9 201619
10 201818
11 201715
12 201914
13 201612
14 201511
15
Correlation of HER2 codon 655 polymorphism with cardiotoxicity risk in Chinese HER2-positive breast cancer patients undergoing epirubicin/cyclophosphamide followed by docetaxel plus trastuzumab adjuvant chemotherapy.
20209
16 20238
17 20218
18 20247
19 20156
20 20245

About Lun Tan

Lun Tan is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine, Organic Chemistry, Pulmonary and Respiratory Medicine and Oncology, having authored 28 papers that have together received 442 indexed citations. Recurring topics across this work include Synthesis and biological activity (5 papers), Cardiac electrophysiology and arrhythmias (4 papers), Cancer therapeutics and mechanisms (4 papers), Aortic Disease and Treatment Approaches (3 papers), Protein Kinase Regulation and GTPase Signaling (3 papers), HER2/EGFR in Cancer Research (3 papers), Aortic aneurysm repair treatments (3 papers) and Quinazolinone synthesis and applications (2 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (63 citations), Molecular Biology (180 citations), Clinical Biochemistry (13 citations), Pulmonary and Respiratory Medicine (53 citations) and Cancer Research (25 citations). Lun Tan has collaborated with scholars based in China, United States and Poland. Frequent co-authors include Dao Wen Wang, Jin Huang, Yuxi Wang, Rufei Shen, Jifa Zhang, Lina Zhang, Yuanxiang Zhao, Houjuan Zuo, Liang Ouyang and Lei Liu. Their work appears in journals such as European Journal of Medicinal Chemistry, Journal of Medicinal Chemistry, Biochemical and Biophysical Research Communications, Medicine and Stem Cells and Development.

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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