Lin Ye

7.6k citations
264 papers · 5.2k · h-index 38

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
  • Oncology top 2%
    • Cancer Cells and Metastasis
    • Cancer-related Molecular Pathways

Papers in

    • TGF-β signaling in diseases 27
    • RNA Research and Splicing 11
    • Bone Metabolism and Diseases 10
    • Connective Tissue Growth Factor Research 10
    • Ubiquitin and proteasome pathways 9
    • Cancer Cells and Metastasis 14
    • Bone health and treatments 10

Lin Ye

254 papers receiving 5.1k citations

Peers

Lin Ye
Comparison fields: 5 of 152
  • Cancer Research 808
  • Oncology 1.1k
  • Molecular Biology 2.7k
  • Cell Biology 464
  • Immunology and Allergy 131
Replace Zhixiang Wang with:
Zhixiang Wang Canada
Futoshi Okada Japan
Ross D. Hannan Australia
Claudio Arra Italy
Yanru Wang China
Zhiyong Wang China
Didier Decaudin France
Grazia Graziani Italy
Michael Cox Canada
Marie A. Bogoyevitch Australia
Lin Ye relative to Zhixiang Wang Canada Zhixiang Wang's profile →
Citations per field
00.5×1.5×1.9×
Zhixiang Wang · 1×
Citations per year

Countries citing papers authored by Lin Ye

Since Specialization
Citations

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

Fields of papers citing papers by Lin Ye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 264 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010173
2 2015124
3 2008119
4 2007118
5 2003108
6 2011102
7 200899
8 201598
9 200887
10 200386
11 200782
12 199576
13 200872
14 201667
15 201466
16 201064
17 201462
18 200762
19 199962
20 201460

About Lin Ye

Lin Ye is a scholar working on Molecular Biology, Oncology, Cancer Research, Cell Biology and Pulmonary and Respiratory Medicine, having authored 264 papers that have together received 5.2k indexed citations. Recurring topics across this work include TGF-β signaling in diseases (27 papers), Cancer Cells and Metastasis (14 papers), RNA Research and Splicing (11 papers), Bone Metabolism and Diseases (10 papers), MicroRNA in disease regulation (10 papers), Bone health and treatments (10 papers), Connective Tissue Growth Factor Research (10 papers) and Ubiquitin and proteasome pathways (9 papers). The work is most often cited by research in Cancer Research (808 citations), Oncology (1.1k citations), Molecular Biology (2.7k citations), Cell Biology (464 citations) and Immunology and Allergy (131 citations). Lin Ye has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Wen G. Jiang, Andrew J. Sanders, Howard Kynaston, Lin-Yu Lu, Thomas L. Saunders, Malcolm D. Mason, Xiaochun Yu, Ke Ji, Malcolm Mason and Ping‐Hui Sun. Their work appears in journals such as International Journal of Oncology, Oncology Reports, International Journal of Molecular Medicine, Anticancer Research and Cancer 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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