Stephen Yu

419 citations
8 papers · 291 · h-index 5

Impact in

    • Cancer-related Molecular Pathways
    • Cancer Genomics and Diagnostics
    • Cancer, Hypoxia, and Metabolism

Papers in

    • CAR-T cell therapy research 3
    • Cancer-related Molecular Pathways 1
    • Protein Degradation and Inhibitors 1

Stephen Yu

7 papers receiving 289 citations

Peers

Stephen Yu
Comparison fields: 5 of 42
  • Oncology 207
  • Cancer Research 111
  • Biotechnology 32
  • Pathology and Forensic Medicine 45
  • Molecular Biology 167
Replace J Y J Wang with:
J Y J Wang United States
You Lu China
Barbara Huegli Switzerland
Melanie Dujka United States
Yiren Xiao United States
Hiu Fung Yuen Singapore
M. Nieves Calvo-Vidal United States
Ildiko Grandal Canada
Christian M. Vidal United States
William G. Bornman United States
Stephen Yu relative to J Y J Wang United States J Y J Wang's profile →
Citations per field
00.5×8.7×
J Y J Wang · 1×
Citations per year

Countries citing papers authored by Stephen Yu

Since Specialization
Citations

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

Fields of papers citing papers by Stephen Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

8 of 8 papers shown
#Work
1 2013219
2 201642
3 201812
4 201911
5 20184
6 20242
7 20211
8 20250

About Stephen Yu

Stephen Yu is a scholar working on Oncology, Molecular Biology, Pathology and Forensic Medicine, Radiology, Nuclear Medicine and Imaging and Hematology, having authored 8 papers that have together received 291 indexed citations. Recurring topics across this work include CAR-T cell therapy research (3 papers), Lymphoma Diagnosis and Treatment (2 papers), Monoclonal and Polyclonal Antibodies Research (2 papers), Multiple Myeloma Research and Treatments (2 papers), Renal Diseases and Glomerulopathies (1 paper), Cancer Genomics and Diagnostics (1 paper), Protein Degradation and Inhibitors (1 paper) and Cancer-related Molecular Pathways (1 paper). The work is most often cited by research in Oncology (207 citations), Cancer Research (111 citations), Biotechnology (32 citations), Pathology and Forensic Medicine (45 citations) and Molecular Biology (167 citations). Stephen Yu has collaborated with scholars based in United States and Canada. Frequent co-authors include Ute M. Moll, Suheng Xu, N D Marchenko, Walter Hanel, Wen-Kai Weng, Daniel Fornika, Nathalie A. Johnson, Miguel Alcaide, Kevin Bushell and Brad H. Nelson. Their work appears in journals such as Blood, Clinical Chemistry, Molecular Cancer Therapeutics, PLoS ONE and Cell Death and Differentiation.

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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