Chin‐Yo Lin

4.4k citations
83 papers · 3.6k · h-index 29

Impact in

    • Cancer-related molecular mechanisms research
    • Cancer, Lipids, and Metabolism
  • Genetics top 5%
    • Estrogen and related hormone effects

Papers in

    • Cancer, Lipids, and Metabolism 8
    • Cancer, Hypoxia, and Metabolism 4
    • Estrogen and related hormone effects 20

Chin‐Yo Lin

78 papers receiving 3.5k citations

Peers

Chin‐Yo Lin
Comparison fields: 5 of 127
  • Cancer Research 695
  • Genetics 894
  • Molecular Biology 2.0k
  • Cell Biology 414
  • Oncology 622
Replace Concetta Ambrosino with:
Concetta Ambrosino Italy
Tao Zhou China
Barbara Majello Italy
Zhe Zhang China
David C. Fargo United States
Jesús Espada Spain
Meiyun Fan United States
Cynthia A. Heinlein United States
Helen C. Hurst United Kingdom
Hatem Zayed Qatar
Chin‐Yo Lin relative to Concetta Ambrosino Italy Concetta Ambrosino's profile →
Citations per field
00.5×1.5×2.1×
Concetta Ambrosino · 1×
Citations per year

Countries citing papers authored by Chin‐Yo Lin

Since Specialization
Citations

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

Fields of papers citing papers by Chin‐Yo Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 83 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007371
2 2004263
3 2004208
4 2010190
5 2002171
6 2014166
7 2015150
8 2006141
9 2005139
10 2008129
11 2009126
12 2000110
13 200199
14 201798
15 200786
16 201375
17 200562
18 201260
19 201655
20 200651

About Chin‐Yo Lin

Chin‐Yo Lin is a scholar working on Cancer Research, Genetics, Oncology, Molecular Biology and Surgery, having authored 83 papers that have together received 3.6k indexed citations. Recurring topics across this work include Estrogen and related hormone effects (20 papers), Cholesterol and Lipid Metabolism (10 papers), Cancer, Lipids, and Metabolism (8 papers), Drug Transport and Resistance Mechanisms (8 papers), Cytokine Signaling Pathways and Interactions (5 papers), Reproductive System and Pregnancy (4 papers), Genomics and Chromatin Dynamics (4 papers) and Cancer, Hypoxia, and Metabolism (4 papers). The work is most often cited by research in Cancer Research (695 citations), Genetics (894 citations), Molecular Biology (2.0k citations), Cell Biology (414 citations) and Oncology (622 citations). Chin‐Yo Lin has collaborated with scholars based in United States, Singapore and Sweden. Frequent co-authors include Jan-Ακε Gustafsson, Raymond Leo Erikson, Edison T. Liu, Leonard Lipovich, Rory Johnson, Lance David Miller, Young‐Joo Jang, Cecilia Williams, Vinsensius Berlian Vega and Sheng Ma. Their work appears in journals such as Proceedings of the National Academy of Sciences, Cancer Research, PLoS ONE, Molecular Endocrinology and Annals of Oncology.

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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