Liang-Chuan Wang

53 total papers · 1.1k total citations
14 papers, 862 citations indexed

About

Liang-Chuan Wang is a scholar working on Oncology, Immunology and Molecular Biology. According to data from OpenAlex, Liang-Chuan Wang has authored 14 papers receiving a total of 862 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Oncology, 7 papers in Immunology and 3 papers in Molecular Biology. Recurrent topics in Liang-Chuan Wang's work include CAR-T cell therapy research (7 papers), Cancer Immunotherapy and Biomarkers (5 papers) and Immune Cell Function and Interaction (4 papers). Liang-Chuan Wang is often cited by papers focused on CAR-T cell therapy research (7 papers), Cancer Immunotherapy and Biomarkers (5 papers) and Immune Cell Function and Interaction (4 papers). Liang-Chuan Wang collaborates with scholars based in United States, Croatia and South Korea. Liang-Chuan Wang's co-authors include Steven Μ. Albelda, Edmund K. Moon, Michael C. Milone, Veena Kapoor, Carl H. June, Ellen Puré, Jing Sun, Douglas V. Dolfi, Caleph B. Wilson and John Scholler and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and SHILAP Revista de lepidopterología.

In The Last Decade

Liang-Chuan Wang

12 papers receiving 849 citations

Author Peers

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

Author Last Decade Papers Cites
Liang-Chuan Wang 672 371 227 227 163 14 862
Mitchell Thorn 713 1.1× 432 1.2× 167 0.7× 220 1.0× 187 1.1× 17 972
Samuel Haile 550 0.8× 365 1.0× 201 0.9× 151 0.7× 88 0.5× 14 875
Hillary G. Caruso 538 0.8× 293 0.8× 271 1.2× 234 1.0× 120 0.7× 14 805
Alba Rodríguez-García 617 0.9× 378 1.0× 280 1.2× 179 0.8× 244 1.5× 17 856
Marie-Andrée Forget 733 1.1× 495 1.3× 263 1.2× 129 0.6× 150 0.9× 12 934
Sunitha Kakarla 930 1.4× 400 1.1× 275 1.2× 296 1.3× 228 1.4× 13 1.0k
Claudia Gerken 645 1.0× 291 0.8× 204 0.9× 164 0.7× 222 1.4× 14 782
Skyler P. Rietberg 748 1.1× 303 0.8× 319 1.4× 292 1.3× 182 1.1× 8 977
Konstantin Dobrenkov 556 0.8× 362 1.0× 235 1.0× 131 0.6× 190 1.2× 28 824
Parisa Malekzadeh 642 1.0× 376 1.0× 196 0.9× 150 0.7× 101 0.6× 14 787

Countries citing papers authored by Liang-Chuan Wang

Since Specialization
Citations

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

Fields of papers citing papers by Liang-Chuan Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Liang-Chuan Wang. 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 Liang-Chuan Wang. The network helps show where Liang-Chuan Wang may publish in the future.

Co-authorship network of co-authors of Liang-Chuan Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Liang-Chuan Wang. A scholar is included among the top collaborators of Liang-Chuan Wang 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 Liang-Chuan Wang. Liang-Chuan Wang 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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