Ying-Ju Lin

1.3k total citations
50 papers, 982 citations indexed

About

Ying-Ju Lin is a scholar working on Molecular Biology, Infectious Diseases and Genetics. According to data from OpenAlex, Ying-Ju Lin has authored 50 papers receiving a total of 982 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 8 papers in Infectious Diseases and 7 papers in Genetics. Recurrent topics in Ying-Ju Lin's work include HIV Research and Treatment (6 papers), Genetic Associations and Epidemiology (6 papers) and Ginseng Biological Effects and Applications (4 papers). Ying-Ju Lin is often cited by papers focused on HIV Research and Treatment (6 papers), Genetic Associations and Epidemiology (6 papers) and Ginseng Biological Effects and Applications (4 papers). Ying-Ju Lin collaborates with scholars based in Taiwan, United States and China. Ying-Ju Lin's co-authors include Elizabeth E. Ramsey, Tracy A. Christianson, Joni K. Doherty, Rebecca Holmes, Edward J. Keenan, Gail M. Clinton, Suh‐Chin Wu, Fuu‐Jen Tsai, Chih‐Ho Lai and Lei Wan and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and The Journal of Clinical Endocrinology & Metabolism.

In The Last Decade

Ying-Ju Lin

48 papers receiving 965 citations

Peers

Ying-Ju Lin
Comparison fields: 5 of 116
  • Molecular Biology 316
  • Oncology 233
  • Radiology, Nuclear Medicine and Imaging 162
  • Immunology 99
  • Health, Toxicology and Mutagenesis 85
Replace Ikue Hayashi with:
Ikue Hayashi Japan
Theodore Vougiouklakis Greece
Liying Zhang China
Peter C. Mann United States
Amílcar Sabino Damazo Brazil
L. David Wise United States
Janka Bábíčková Slovakia
Ping Zheng China
Yuxi Liu China
Jiann‐Jou Yang Taiwan
Ikue Hayashi Japan View profile →
Citations per field, relative to Ying-Ju Lin
Ying-Ju Lin · 1×
Citations per year, relative to Ying-Ju Lin
Ying-Ju Lin · 1×

Countries citing papers authored by Ying-Ju Lin

Since Specialization
Citations

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

Fields of papers citing papers by Ying-Ju Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ying-Ju Lin

This figure shows the co-authorship network connecting the top 25 collaborators of Ying-Ju Lin. A scholar is included among the top collaborators of Ying-Ju Lin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ying-Ju Lin. Ying-Ju Lin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 6
2 3
3 0
4 16
5 1
6 3
7 1
8 5
9 14
10 10
11 7
12 12
13 22
14 9
15 29
16 25
17
1
18 19
19 33
20 51

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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