I‐Ying Lin

543 citations
14 papers · 419 · h-index 12

Impact in

    • Immune Cell Function and Interaction
    • T-cell and B-cell Immunology
    • Galectins and Cancer Biology
    • Immunotherapy and Immune Responses
    • Curcumin's Biomedical Applications

Papers in

    • CRISPR and Genetic Engineering 3
    • Pluripotent Stem Cells Research 2
    • Ubiquitin and proteasome pathways 1
    • Glycosylation and Glycoproteins Research 1
    • Gene expression and cancer classification 1
    • Immune Cell Function and Interaction 3
    • T-cell and B-cell Immunology 2

I‐Ying Lin

14 papers receiving 416 citations

Peers

I‐Ying Lin
Comparison fields: 5 of 67
  • Immunology 174
  • Molecular Medicine 24
  • Rheumatology 59
  • Molecular Biology 201
  • Cancer Research 39
Replace S. Carrère with:
S. Carrère France
Roberta Mazzone Italy
Yousef R. Badran United States
Giuseppe Tortolina Italy
Emilia Alina Barbu United States
Junshan Hao United States
Souhir Mestiri Tunisia
Michael Croft United States
Natalie McGregor United States
Angélique Pichot France
I‐Ying Lin relative to S. Carrère France S. Carrère's profile →
Citations per field
00.5×11.7×
S. Carrère · 1×
Citations per year

Countries citing papers authored by I‐Ying Lin

Since Specialization
Citations

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

Fields of papers citing papers by I‐Ying Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

14 of 14 papers shown
#Work
1 201959
2 200847
3 201045
4 201442
5 200935
6 201932
7 201331
8 201831
9 201426
10 202221
11 201519
12 201219
13 202111
14 20251

About I‐Ying Lin

I‐Ying Lin is a scholar working on Molecular Biology, Immunology, Surgery, Pathology and Forensic Medicine and Oncology, having authored 14 papers that have together received 419 indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (3 papers), CRISPR and Genetic Engineering (3 papers), Pluripotent Stem Cells Research (2 papers), T-cell and B-cell Immunology (2 papers), Advanced Proteomics Techniques and Applications (1 paper), Ubiquitin and proteasome pathways (1 paper), Glycosylation and Glycoproteins Research (1 paper) and Gene expression and cancer classification (1 paper). The work is most often cited by research in Immunology (174 citations), Molecular Medicine (24 citations), Rheumatology (59 citations), Molecular Biology (201 citations) and Cancer Research (39 citations). I‐Ying Lin has collaborated with scholars based in Taiwan, United States and Germany. Frequent co-authors include Kuo‐I Lin, Kuo-Hsuan Hung, Chin‐Hsiu Liu, Chih‐Ming Tsai, Shie-Liang Hsieh, Tsui-Ling Hsu, Shu‐Chun Lin, Kuo‐Wei Chang, Pei-Shih Hung and Likai Chen. Their work appears in journals such as Frontiers in Immunology, The Journal of Immunology, Briefings in Bioinformatics, EMBO Reports and Journal of Clinical Investigation.

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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