Jun Feng

247 papers receiving 6.6k citations

Jun Feng's Hit Papers

Selective Inhibition of Oncogenic KRAS Output with Small Molecules Targeting the Inactive State 2016 · 549 citations
5490+3+6Years since publication100200300400500

Peers

Jun Feng
Comparison fields: 5 of 144
  • Biochemistry 404
  • Behavioral Neuroscience 182
  • Pathology and Forensic Medicine 760
  • Cardiology and Cardiovascular Medicine 930
  • Biological Psychiatry 104
Replace Joanna L Sharman with:
Joanna L Sharman United Kingdom
Steven H. Graham United States
Angelo Parini France
Xiaoqiang Yao Hong Kong
Volker Vallon United States
Luke I. Szweda United States
Albert Y. Sun United States
Masatsugu Horiuchi Japan
Ajay Verma United States
Yuichiro Yamada Japan
Jun Feng relative to Joanna L Sharman United Kingdom Joanna L Sharman's profile →
Citations per field
00.5×3.4×
Joanna L Sharman · 1×
Citations per year

Countries citing papers authored by Jun Feng

Since Specialization
Citations

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

Fields of papers citing papers by Jun Feng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 262 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Selective Inhibition of Oncogenic KRAS Output with Small Molecules Targeting the Inactive State
Hit paper breakdown →
2016549
2 2007330
3 2010264
4 2011238
5 2001222
6 2008218
7 2017180
8 2009131
9 2018104
10 2012102
11 201796
12 200996
13 200093
14 201592
15 201091
16 200784
17 200582
18 200280
19 200978
20 200677

About Jun Feng

Jun Feng is a scholar working on Molecular Biology, Pathology and Forensic Medicine, Physiology, Cardiology and Cardiovascular Medicine and Surgery, having authored 262 papers that have together received 6.7k indexed citations. Recurring topics across this work include Cardiac Ischemia and Reperfusion (37 papers), Nitric Oxide and Endothelin Effects (20 papers), Angiogenesis and VEGF in Cancer (9 papers), Receptor Mechanisms and Signaling (9 papers), Neuropeptides and Animal Physiology (7 papers), Cardiac and Coronary Surgery Techniques (7 papers), Computational Drug Discovery Methods (7 papers) and Adipose Tissue and Metabolism (6 papers). The work is most often cited by research in Biochemistry (404 citations), Behavioral Neuroscience (182 citations), Pathology and Forensic Medicine (760 citations), Cardiology and Cardiovascular Medicine (930 citations) and Biological Psychiatry (104 citations). Jun Feng has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Frank W. Sellke, Cesario Bianchi, Richard Clements, Neel R. Sodha, Michael P. Robich, Yamei Tang, Yuhong Liu, Munir Boodhwani, Csaba Szabó and Shigetoshi Mieno. Their work appears in journals such as Circulation, Surgery, Journal of Thoracic and Cardiovascular Surgery, The Annals of Thoracic Surgery and Journal of Surgical Research.

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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