Jin Ye

5.1k citations
105 papers · 4.0k · h-index 33

Impact in

Papers in

    • Lipid Membrane Structure and Behavior 15
    • Sphingolipid Metabolism and Signaling 14
    • Ubiquitin and proteasome pathways 6
    • Cholesterol and Lipid Metabolism 18

Jin Ye

98 papers receiving 4.0k citations

Peers

Jin Ye
Comparison fields: 5 of 115
  • Biochemistry 458
  • Hepatology 447
  • Cell Biology 777
  • Cancer Research 497
  • Molecular Biology 2.0k
Replace David A. Rudnick with:
David A. Rudnick United States
Carlos Enrich Spain
Alfred S.L. Cheng Hong Kong
Albert Pol Spain
Hyock Joo Kwon United States
Takefumi Doi Japan
Hyam L. Leffert United States
Bailin Zhang China
Shangzhe Xu United States
David P. Aden United States
Jin Ye relative to David A. Rudnick United States David A. Rudnick's profile →
Citations per field
00.5×10×14×
David A. Rudnick · 1×
Citations per year

Countries citing papers authored by Jin Ye

Since Specialization
Citations

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

Fields of papers citing papers by Jin Ye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 105 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007429
2 2018276
3 2002208
4 2006208
5 1999199
6 2004159
7 2004145
8 2006139
9 2000113
10 2012109
11 2023104
12 201090
13 200790
14 200787
15 200884
16 202183
17 201474
18 200573
19 200764
20 201360

About Jin Ye

Jin Ye is a scholar working on Molecular Biology, Surgery, Cell Biology, Cancer Research and Biochemistry, having authored 105 papers that have together received 4.0k indexed citations. Recurring topics across this work include Cholesterol and Lipid Metabolism (18 papers), Lipid Membrane Structure and Behavior (15 papers), Sphingolipid Metabolism and Signaling (14 papers), Endoplasmic Reticulum Stress and Disease (11 papers), Lipid metabolism and biosynthesis (10 papers), Cancer, Lipids, and Metabolism (9 papers), Ferroptosis and cancer prognosis (7 papers) and Ubiquitin and proteasome pathways (6 papers). The work is most often cited by research in Biochemistry (458 citations), Hepatology (447 citations), Cell Biology (777 citations), Cancer Research (497 citations) and Molecular Biology (2.0k citations). Jin Ye has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Yvonne Lange, Theodore L. Steck, Joon No Lee, Russell A. DeBose‐Boyd, Hua Huang, Yan Chen, Michael S. Brown, Joseph L. Goldstein, Michael Gale and David M. Owen. Their work appears in journals such as Journal of Biological Chemistry, Proceedings of the National Academy of Sciences, Journal of Lipid Research, Molecular Cell and PLoS ONE.

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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