Chin‐Yo Lin

4.5k citations
90 papers · 3.2k · h-index 30

Impact in

    • Cancer-related molecular mechanisms research
  • Genetics top 2%
    • Estrogen and related hormone effects

Papers in

    • Genomics and Chromatin Dynamics 7
    • RNA Research and Splicing 4
    • Estrogen and related hormone effects 25

Chin‐Yo Lin

86 papers receiving 3.1k citations

Peers

Chin‐Yo Lin
Comparison fields: 5 of 126
  • Cancer Research 707
  • Genetics 793
  • Molecular Biology 1.9k
  • Cell Biology 424
  • Oncology 656
Replace Jin‐San Zhang with:
Jin‐San Zhang China
Sudharsana Rao Ande Canada
Benjamin Yat‐Ming Yung Taiwan
R. Bamezai India
Edward A. O’Neill United States
Farhat L. Khanim United Kingdom
Meiyun Fan United States
Michael Butterworth United States
Susan E. Kane United States
Yunfeng Li China
Chin‐Yo Lin relative to Jin‐San Zhang China Jin‐San Zhang's profile →
Citations per field
00.5×1.5×2.5×
Jin‐San Zhang · 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 90 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004243
2 2004192
3 2010183
4 2002162
5 2014155
6 2015143
7 2005139
8 2006137
9 2008124
10 2009122
11 2000109
12 200198
13 201788
14 200781
15 201480
16 201370
17 200561
18 201259
19 200651
20 201649

About Chin‐Yo Lin

Chin‐Yo Lin is a scholar working on Molecular Biology, Genetics, Oncology, Surgery and Cancer Research, having authored 90 papers that have together received 3.2k indexed citations. Recurring topics across this work include Estrogen and related hormone effects (25 papers), Cholesterol and Lipid Metabolism (10 papers), Drug Transport and Resistance Mechanisms (8 papers), Cancer, Lipids, and Metabolism (7 papers), Genomics and Chromatin Dynamics (7 papers), Cytokine Signaling Pathways and Interactions (6 papers), RNA Research and Splicing (4 papers) and Microtubule and mitosis dynamics (4 papers). The work is most often cited by research in Cancer Research (707 citations), Genetics (793 citations), Molecular Biology (1.9k citations), Cell Biology (424 citations) and Oncology (656 citations). Chin‐Yo Lin has collaborated with scholars based in United States, Taiwan and Singapore. Frequent co-authors include Jan-Ακε Gustafsson, Raymond L. Erikson, Edison T. Liu, Cecilia Williams, Leonard Lipovich, Rory Johnson, Young‐Joo Jang, Lance D. Miller, Sheng Ma and Vinsensius B. Vega. Their work appears in journals such as Cancer Research, Proceedings of the National Academy of Sciences, Annals of Oncology, Oncogene and Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms.

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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