Feng Ye

6.2k citations
148 papers · 4.7k indexed · 2 hit papers · h-index 32
Topics
Cell Adhesion Molecules Research (20 papers)Platelet Disorders and Treatments (9 papers)MicroRNA in disease regulation (9 papers)

In The Last Decade

Feng Ye

142 papers receiving 4.7k citations

Hit Papers

Exosomal miRNA-19b-3p of tubular epithelial cells promote...201920262021202320192022100200300

Peers

Feng Ye
Comparison fields: 5 of 144
  • Molecular Biology 2.3k
  • Immunology and Allergy 1.2k
  • Cell Biology 816
  • Cancer Research 766
  • Oncology 740
Replace Scott B. Shappell with:
Scott B. Shappell United States
Steven M. Dudek United States
Roy Zent United States
Olivier Kocher United States
Brenda R. Kwak Switzerland
Li‐Yan Xu China
Hermann‐Josef Gröne Germany
Jagat Narula United States
Wolfgang Bergmeier United States
Hong‐Jian Zhu Australia
Feng Ye relative to Scott B. Shappell United States Scott B. Shappell's profile →
Citations per field
00.5×11×
Scott B. Shappell · 1×
Citations per year

Countries citing papers authored by Feng Ye

Since Specialization
Citations

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

Fields of papers citing papers by Feng Ye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Feng Ye

This figure shows the co-authorship network connecting the top 25 collaborators of Feng Ye. A scholar is included among the top collaborators of Feng Ye 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 Feng Ye. Feng Ye is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 4
4 21
5 9
6 25
7
The Single‐Cell Landscape of Intratumoral Heterogeneity and The Immunosuppressive Microenvironment in Liver and Brain Metastases of Breast Cancerbreakdown →
191
8 28
9 31
10 19
11 10
12 18
13 47
14 11
15
Exosomal miRNA-19b-3p of tubular epithelial cells promotes M1 macrophage activation in kidney injurybreakdown →
314
16 20
17 39
18 204
19
[Design and application of medical knowledge model on SAGE].
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20 4

About Feng Ye

Feng Ye is a scholar working on Immunology and Allergy, Nephrology and Cancer Research, having authored 148 papers that have together received 4.7k indexed citations. Recurring topics across this work include Cell Adhesion Molecules Research (20 papers), Platelet Disorders and Treatments (9 papers) and MicroRNA in disease regulation (9 papers). The work is most often cited by research in Immunology and Allergy (1.2k citations), Cancer Research (766 citations) and Cell Biology (816 citations). Feng Ye has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Mark H. Ginsberg, Chungho Kim, Bi‐Cheng Liu, David R. Critchley, Lin‐Li Lv, Brian G. Petrich, Tao‐Tao Tang, Hai-Feng Ni, Zuo‐Lin Li and Huaizeng Chen. Their work appears in journals such as Cell, Journal of Biological Chemistry and The Journal of Experimental Medicine.

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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