Jun Ke

90 total papers · 925 total citations
47 papers, 501 citations indexed

About

Jun Ke is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Jun Ke has authored 47 papers receiving a total of 501 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Cardiology and Cardiovascular Medicine, 10 papers in Molecular Biology and 10 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Jun Ke's work include Cancer-related molecular mechanisms research (4 papers), Circular RNAs in diseases (4 papers) and Birth, Development, and Health (4 papers). Jun Ke is often cited by papers focused on Cancer-related molecular mechanisms research (4 papers), Circular RNAs in diseases (4 papers) and Birth, Development, and Health (4 papers). Jun Ke collaborates with scholars based in China, United States and France. Jun Ke's co-authors include Gargi Patel, Aditya Bardia, Joohyuk Sohn, William Jacot, Cristina Saura, Laura Biganzoli, Rebecca Dent, Kan Yonemori, Carlos H. Barrios and Seock‐Ah Im and has published in prestigious journals such as New England Journal of Medicine, Journal of Clinical Oncology and PLoS ONE.

In The Last Decade

Jun Ke

44 papers receiving 497 citations

Hit Papers

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Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Jun Ke 168 104 95 89 85 47 501
Hüseyin Engin 139 0.8× 139 1.3× 108 1.1× 53 0.6× 32 0.4× 50 453
Fang Xie 132 0.8× 213 2.0× 83 0.9× 84 0.9× 84 1.0× 73 586
Jing Ren 157 0.9× 111 1.1× 115 1.2× 43 0.5× 40 0.5× 57 591
Yuko Ishikawa 148 0.9× 92 0.9× 65 0.7× 166 1.9× 50 0.6× 44 501
Lijuan Ding 142 0.8× 213 2.0× 60 0.6× 74 0.8× 41 0.5× 36 488
Jia Liu 107 0.6× 135 1.3× 47 0.5× 46 0.5× 41 0.5× 48 496
Le‐Tian Huang 180 1.1× 162 1.6× 256 2.7× 97 1.1× 59 0.7× 51 572
Brian Hayes 112 0.7× 78 0.8× 130 1.4× 79 0.9× 33 0.4× 48 502
Ricardo Chirino 103 0.6× 181 1.7× 63 0.7× 98 1.1× 27 0.3× 37 585
Jun Guo 135 0.8× 211 2.0× 89 0.9× 59 0.7× 25 0.3× 51 569

Countries citing papers authored by Jun Ke

Since Specialization
Citations

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

Fields of papers citing papers by Jun Ke

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun Ke

This figure shows the co-authorship network connecting the top 25 collaborators of Jun Ke. A scholar is included among the top collaborators of Jun Ke based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jun Ke. Jun Ke is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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