Ju-Lun Yang

452 citations
34 papers · 357 · h-index 13

Impact in

    • CAR-T cell therapy research
    • Peptidase Inhibition and Analysis
    • Virus-based gene therapy research

Papers in

    • CAR-T cell therapy research 5
    • Cancer-related Molecular Pathways 4
    • Cancer Immunotherapy and Biomarkers 3
    • Protein Kinase Regulation and GTPase Signaling 4
    • Ubiquitin and proteasome pathways 2
    • RNA Interference and Gene Delivery 2

Ju-Lun Yang

33 papers receiving 353 citations

Peers

Ju-Lun Yang
Comparison fields: 5 of 73
  • Oncology 114
  • Genetics 91
  • Biotechnology 24
  • Cancer Research 36
  • Molecular Biology 176
Replace Timothy A. Olson with:
Timothy A. Olson United States
Mónica Vicente-Pascual Spain
William H. Jackson United States
Richard Kirkman United States
Chan Zhu China
Mathieu Drouin Canada
Gang Shi China
L Danhauser United States
Matthias Bozza Germany
Ju-Lun Yang relative to Timothy A. Olson United States Timothy A. Olson's profile →
Citations per field
00.5×
Timothy A. Olson · 1×
Citations per year

Countries citing papers authored by Ju-Lun Yang

Since Specialization
Citations

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

Fields of papers citing papers by Ju-Lun Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201041
2 201334
3 201527
4 201623
5 201119
6 201818
7 202317
8 201715
9 202114
10 201514
11 201614
12 201913
13 202112
14 201612
15 201710
16 201810
17 20217
18 20217
19 20187
20 20226

About Ju-Lun Yang

Ju-Lun Yang is a scholar working on Oncology, Molecular Biology, Genetics, Radiology, Nuclear Medicine and Imaging and Cancer Research, having authored 34 papers that have together received 357 indexed citations. Recurring topics across this work include Virus-based gene therapy research (8 papers), Monoclonal and Polyclonal Antibodies Research (5 papers), CAR-T cell therapy research (5 papers), Cancer-related Molecular Pathways (4 papers), Protein Kinase Regulation and GTPase Signaling (4 papers), Cancer Immunotherapy and Biomarkers (3 papers), Ubiquitin and proteasome pathways (2 papers) and RNA Interference and Gene Delivery (2 papers). The work is most often cited by research in Oncology (114 citations), Genetics (91 citations), Biotechnology (24 citations), Cancer Research (36 citations) and Molecular Biology (176 citations). Ju-Lun Yang has collaborated with scholars based in China and United States. Frequent co-authors include Qiang Feng, Shuling Song, Wenxing Zhao, Yue Chen, Fang Dai, Jing Cui, Lianzhen Li, Tao Li, Jin Lei and Tao Li. Their work appears in journals such as BMC Cancer, PLoS ONE, International Journal of Molecular Medicine, Journal of Cancer and International Journal of Oncology.

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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