Chun-Ming Lin

61 papers receiving 1.7k citations

Peers

Chun-Ming Lin
Comparison fields: 5 of 113
  • Animal Science and Zoology 1.1k
  • Infectious Diseases 1.1k
  • Genetics 813
  • Anesthesiology and Pain Medicine 68
  • Developmental Neuroscience 37
Replace Jung-Eun Park with:
Jung-Eun Park South Korea
David Zeman United States
Wenming Jiang China
Guangliang Liu China
Enrique Calvo Spain
F. J. Pallarés Spain
Joseph M. Hyser United States
Sherry Cox United States
Yafang Zhu China
Jesús Rodríguez‐Díaz Spain
Chun-Ming Lin relative to Jung-Eun Park South Korea Jung-Eun Park's profile →
Citations per field
00.5×12.3×
Jung-Eun Park · 1×
Citations per year

Countries citing papers authored by Chun-Ming Lin

Since Specialization
Citations

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

Fields of papers citing papers by Chun-Ming Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 64 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016236
2 2014157
3 2004111
4 2015101
5 201784
6 201580
7 201675
8 200568
9 201754
10 200753
11 201548
12 199044
13 201139
14 201935
15 199334
16 200433
17 200732
18 200432
19 200931
20 201228

About Chun-Ming Lin

Chun-Ming Lin is a scholar working on Animal Science and Zoology, Infectious Diseases, Genetics, Immunology and Cardiology and Cardiovascular Medicine, having authored 64 papers that have together received 1.8k indexed citations. Recurring topics across this work include Animal Virus Infections Studies (28 papers), Virus-based gene therapy research (24 papers), Viral gastroenteritis research and epidemiology (23 papers), Viral Infections and Immunology Research (6 papers), Immunotherapy and Immune Responses (6 papers), T-cell and B-cell Immunology (3 papers), Immune Cell Function and Interaction (3 papers) and Trace Elements in Health (3 papers). The work is most often cited by research in Animal Science and Zoology (1.1k citations), Infectious Diseases (1.1k citations), Genetics (813 citations), Anesthesiology and Pain Medicine (68 citations) and Developmental Neuroscience (37 citations). Chun-Ming Lin has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Linda J. Saif, Qiuhong Wang, Douglas Marthaler, Daniel J. Kosman, Xiang Gao, Anastasia N. Vlasova, Malak A. Esseili, Victor Fei Pang, Chian‐Ren Jeng and Oka T. Their work appears in journals such as Veterinary Microbiology, Veterinary Research, Veterinary Immunology and Immunopathology, Clinical Immunology and Canadian Journal of Anesthesia/Journal canadien d anesthésie.

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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