Jun Wan

822 citations
48 papers · 490 · h-index 15

Impact in

Papers in

    • Advanced biosensing and bioanalysis techniques 7
    • RNA Interference and Gene Delivery 4
    • Blood Coagulation and Thrombosis Mechanisms 7
    • Hemophilia Treatment and Research 4
    • Platelet Disorders and Treatments 3

Jun Wan

44 papers receiving 486 citations

Peers

Jun Wan
Comparison fields: 5 of 84
  • Internal Medicine 20
  • Hematology 50
  • Hepatology 28
  • Genetics 36
  • Molecular Biology 200
Replace Ephraem Leitner with:
Ephraem Leitner Australia
Longhui Qiu United States
G. Wiedemann Germany
Jingjing Shang China
Alicia S. Eustes United States
Akinaga Sonoda Japan
Ruibin Huang China
E. A. te Velde Netherlands
Yuri Kopolovic Israel
Hiroyasu Kobayashi Japan
Jun Wan relative to Ephraem Leitner Australia Ephraem Leitner's profile →
Citations per field
00.5×
Ephraem Leitner · 1×
Citations per year

Countries citing papers authored by Jun Wan

Since Specialization
Citations

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

Fields of papers citing papers by Jun Wan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202147
2 201546
3 201632
4 201730
5 201729
6 202027
7 201423
8 202318
9 201518
10 202018
11 201318
12 202116
13 202315
14 202215
15 201915
16 202014
17 20249
18 20119
19 20218
20 20098

About Jun Wan

Jun Wan is a scholar working on Molecular Biology, Hematology, Pulmonary and Respiratory Medicine, Surgery and Genetics, having authored 48 papers that have together received 490 indexed citations. Recurring topics across this work include Advanced biosensing and bioanalysis techniques (7 papers), Blood Coagulation and Thrombosis Mechanisms (7 papers), Intracranial Aneurysms: Treatment and Complications (5 papers), Hemophilia Treatment and Research (4 papers), RNA Interference and Gene Delivery (4 papers), Coagulation, Bradykinin, Polyphosphates, and Angioedema (4 papers), Traumatic Brain Injury and Neurovascular Disturbances (3 papers) and Platelet Disorders and Treatments (3 papers). The work is most often cited by research in Internal Medicine (20 citations), Hematology (50 citations), Hepatology (28 citations), Genetics (36 citations) and Molecular Biology (200 citations). Jun Wan has collaborated with scholars based in China, Netherlands and United States. Frequent co-authors include Kemin Wang, Qiuping Guo, Qin Xie, Baoyin Yuan, Mark Roest, Bas de Laat, Yuyu Tan, Zhixiang Huang, Xiangxian Meng and Wei Wu. Their work appears in journals such as Medicine, Journal of Thrombosis and Haemostasis, Blood Advances, PLoS ONE and Scientific Reports.

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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