Chun Tu

982 citations
9 papers · 755 · h-index 8

Impact in

  • Immunology top 10%
    • T-cell and B-cell Immunology
    • Immune Cell Function and Interaction
    • Immunotherapy and Immune Responses
    • Cell Adhesion Molecules Research

Papers in

    • Glycosylation and Glycoproteins Research 2
    • Ubiquitin and proteasome pathways 2
    • Retinal Development and Disorders 1
    • Protein Degradation and Inhibitors 1
    • Cellular transport and secretion 3
    • Cellular Mechanics and Interactions 2

Chun Tu

9 papers receiving 742 citations

Peers

Chun Tu
Comparison fields: 5 of 80
  • Immunology 359
  • Immunology and Allergy 86
  • Cell Biology 145
  • Oncology 151
  • Molecular Biology 329
Replace Gemma Texidó with:
Gemma Texidó Italy
May Dang-Lawson Canada
Karel Drbal Czechia
Aldo Borroto Spain
Hyewon Phee United States
Maki Touma Japan
Tom Crabbe United Kingdom
Kathrin Kläsener Germany
Alagarsamy Lakku Reddi United States
Frederick Rosenberger United States
Chun Tu relative to Gemma Texidó Italy Gemma Texidó's profile →
Citations per field
00.5×1.5×2.5×
Gemma Texidó · 1×
Citations per year

Countries citing papers authored by Chun Tu

Since Specialization
Citations

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

Fields of papers citing papers by Chun Tu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

9 of 9 papers shown
#Work
1 2003444
2 200892
3 200974
4 201059
5
Activation of Keap1/Nrf2 signaling pathway by nuclear epidermal growth factor receptor in cancer cells.
201435
6 200923
7 201414
8 201113
9 20001

About Chun Tu

Chun Tu is a scholar working on Molecular Biology, Cell Biology, Genetics, Pulmonary and Respiratory Medicine and Animal Science and Zoology, having authored 9 papers that have together received 755 indexed citations. Recurring topics across this work include Cellular transport and secretion (3 papers), Glycosylation and Glycoproteins Research (2 papers), Ubiquitin and proteasome pathways (2 papers), Cellular Mechanics and Interactions (2 papers), Retinal Development and Disorders (1 paper), Animal Nutrition and Physiology (1 paper), Protein Degradation and Inhibitors (1 paper) and Genetic Mapping and Diversity in Plants and Animals (1 paper). The work is most often cited by research in Immunology (359 citations), Immunology and Allergy (86 citations), Cell Biology (145 citations), Oncology (151 citations) and Molecular Biology (329 citations). Chun Tu has collaborated with scholars based in United States, Japan and Taiwan. Frequent co-authors include Hamid Band, Aaron R. Dinner, Osami Kanagawa, Subhadip Raychaudhuri, Tasha N. Sims, Gabriele Campi, Richard Burack, Mary A. Markiewicz, Michael L. Dustin and Arup K. Chakraborty. Their work appears in journals such as Gene, The International Journal of Biochemistry & Cell Biology, Journal of Biological Chemistry, Science and Proceedings of the National Academy of Sciences.

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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