Gang Lin

53 total papers · 1.2k total citations
42 papers, 1.0k citations indexed

About

Gang Lin is a scholar working on Immunology, Molecular Biology and Oncology. According to data from OpenAlex, Gang Lin has authored 42 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Immunology, 16 papers in Molecular Biology and 11 papers in Oncology. Recurrent topics in Gang Lin's work include interferon and immune responses (17 papers), Aquaculture disease management and microbiota (8 papers) and Cytokine Signaling Pathways and Interactions (8 papers). Gang Lin is often cited by papers focused on interferon and immune responses (17 papers), Aquaculture disease management and microbiota (8 papers) and Cytokine Signaling Pathways and Interactions (8 papers). Gang Lin collaborates with scholars based in China and United States. Gang Lin's co-authors include Guoyao Wu, Junjun Wang, Defa Li, Xiaoqiu Wang, Zhenlong Wu, Zhaolai Dai, Chengyu Hu, Shengdi Hu, Huaijun Zhou and Bin Wang and has published in prestigious journals such as The Journal of Immunology, Biochemical and Biophysical Research Communications and Journal of Nutrition.

In The Last Decade

Gang Lin

42 papers receiving 1.0k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Gang Lin 452 341 147 137 137 42 1.0k
Chuan Yan 448 1.0× 179 0.5× 61 0.4× 162 1.2× 66 0.5× 34 1.1k
Ping Kang 357 0.8× 177 0.5× 100 0.7× 71 0.5× 137 1.0× 31 1.0k
Jianbo Hu 269 0.6× 336 1.0× 88 0.6× 38 0.3× 224 1.6× 32 1.1k
Enrique Salas‐Vidal 643 1.4× 186 0.5× 57 0.4× 82 0.6× 61 0.4× 28 1.2k
Yanzhou Yang 348 0.8× 145 0.4× 59 0.4× 124 0.9× 56 0.4× 44 946
R. F. Kampschmidt 240 0.5× 285 0.8× 32 0.2× 55 0.4× 118 0.9× 63 1.1k
Lei An 492 1.1× 205 0.6× 188 1.3× 97 0.7× 76 0.6× 65 1.1k
Maobi Zhu 291 0.6× 99 0.3× 312 2.1× 80 0.6× 228 1.7× 29 1.2k
Pamela M. J. O’Connor 399 0.9× 130 0.4× 51 0.3× 41 0.3× 298 2.2× 25 1.2k
David G. Jose 204 0.5× 259 0.8× 41 0.3× 41 0.3× 123 0.9× 48 995

Countries citing papers authored by Gang Lin

Since Specialization
Citations

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

Fields of papers citing papers by Gang Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gang Lin

This figure shows the co-authorship network connecting the top 25 collaborators of Gang Lin. A scholar is included among the top collaborators of Gang 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 Gang Lin. Gang Lin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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