S. M. Dubinett

444 citations
20 papers · 370 indexed · h-index 9

S. M. Dubinett

20 papers receiving 360 citations

Peers

S. M. Dubinett
Comparison fields: 5 of 57
  • Immunology 213
  • Oncology 173
  • Biotechnology 49
  • Genetics 112
  • Molecular Biology 137
Replace Kazuko Tsuneoka with:
Kazuko Tsuneoka Japan
C C Ting United States
Arvin Yang United States
Lisa Geiselhart United States
Marco Migliaccio Switzerland
Myrthel E. Hargrove United States
Margaret Musser United States
Shinichiro Kawabe Japan
W.R. Gerritsen United States
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Citations per field
00.5×2.9×
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Citations per year

Countries citing papers authored by S. M. Dubinett

Since Specialization
Citations

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

Fields of papers citing papers by S. M. Dubinett

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S. M. Dubinett. 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 S. M. Dubinett. The network helps show where S. M. Dubinett may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20115
2 20105
3 20102
4 20102
5 20088
6
Dendritic cells augment granulocyte-macrophage colony-stimulating factor (GM-CSF)/herpes simplex virus thymidine kinase-mediated gene therapy of lung cancer.
199922
7
Interleukin-7 gene transfer in non-small-cell lung cancer decreases tumor proliferation, modifies cell surface molecule expression, and enhances antitumor reactivity.
199721
8 199751
9 199527
10
TNF-alpha-induced antiproliferation is not dependent on the autocrine action of TGF-beta 1 in a thyroid cancer cell line.
19944
11 199333
12 19931
13 19932
14
Cytokine immunotherapy of non-small cell lung cancer.
199315
15 199342
16 19931
17
Genetic modification of a murine fibrosarcoma to produce interleukin 7 stimulates host cell infiltration and tumor immunity.
199299
18 19921
19 199225
20
Efficacy of adjuvant interleukin-2 after excision of BALB/c fibrosarcomas.
19894

About S. M. Dubinett

S. M. Dubinett is a scholar working on Biotechnology, Oncology and Immunology, having authored 20 papers that have together received 370 indexed citations. Recurring topics across this work include Immunotherapy and Immune Responses (7 papers), Virus-based gene therapy research (6 papers), Cancer Research and Treatments (5 papers), Lung Cancer Treatments and Mutations (4 papers), Cytokine Signaling Pathways and Interactions (4 papers), TGF-β signaling in diseases (3 papers), HER2/EGFR in Cancer Research (3 papers) and CAR-T cell therapy research (2 papers). The work is most often cited by research in Immunology (213 citations), Oncology (173 citations) and Biotechnology (49 citations). S. M. Dubinett has collaborated with scholars based in United States and Canada. Frequent co-authors include Diane G. Kelley, Donna E. Hogge, Marina Stolina, Shawkat Dhanani, Li Zhu, Jinxiang Wang, G J Dougherty, Min Huang, Min Huang and Sherven Sharma. Their work appears in journals such as Journal of Clinical Oncology, Blood and The Journal of 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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