Runyu Dong

620 citations
12 papers · 495 · h-index 10

Impact in

  • Physiology top 2%
    • Adenosine and Purinergic Signaling
  • Oncology top 10%
    • Peptidase Inhibition and Analysis

Papers in

    • Peptidase Inhibition and Analysis 4
    • Cancer Immunotherapy and Biomarkers 2
    • Circular RNAs in diseases 2
    • Signaling Pathways in Disease 2

Runyu Dong

12 papers receiving 489 citations

Peers

Runyu Dong
Comparison fields: 5 of 53
  • Physiology 111
  • Oncology 289
  • Cellular and Molecular Neuroscience 117
  • Cancer Research 80
  • Immunology 76
Replace Christina Lutz‐Nicoladoni with:
Christina Lutz‐Nicoladoni Austria
Jared J. Fradette United States
Kai Dittmann Germany
Christie Fanton United States
Steve Eliason United States
Luba Benimetskaya United States
Elena A Feshchenko United States
Julia E. Prescott United States
Gaia Barisione Italy
A. Gillet France
Runyu Dong relative to Christina Lutz‐Nicoladoni Austria Christina Lutz‐Nicoladoni's profile →
Citations per field
00.5×10.1×
Christina Lutz‐Nicoladoni · 1×
Citations per year

Countries citing papers authored by Runyu Dong

Since Specialization
Citations

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

Fields of papers citing papers by Runyu Dong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

12 of 12 papers shown
#Work
1 1996177
2 199799
3 199773
4 202426
5 199824
6 199423
7 202517
8 200417
9 202416
10 201813
11 20245
12 20045

About Runyu Dong

Runyu Dong is a scholar working on Oncology, Molecular Biology, Pulmonary and Respiratory Medicine, Cellular and Molecular Neuroscience and Radiology, Nuclear Medicine and Imaging, having authored 12 papers that have together received 495 indexed citations. Recurring topics across this work include Peptidase Inhibition and Analysis (4 papers), Ferroptosis and cancer prognosis (2 papers), Circular RNAs in diseases (2 papers), Signaling Pathways in Disease (2 papers), Cell Adhesion Molecules Research (2 papers), Cancer Immunotherapy and Biomarkers (2 papers), Monoclonal and Polyclonal Antibodies Research (2 papers) and Neuropeptides and Animal Physiology (2 papers). The work is most often cited by research in Physiology (111 citations), Oncology (289 citations), Cellular and Molecular Neuroscience (117 citations), Cancer Research (80 citations) and Immunology (76 citations). Runyu Dong has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Martin Hegen, Chikao Morimoto, Junichi Kameoka, S F Schlossman, Stuart F. Schlossman, Yan Xu, Toshiaki Tanaka, Kouichi Tachibana, Yasuhiko Munakata and C Morimoto. Their work appears in journals such as Journal of Clinical Oncology, The Journal of Immunology, Advanced Science, Journal of Nanobiotechnology and Molecular Immunology.

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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