Daniel Stephen Green

600 citations
23 papers · 705 · h-index 13

Impact in

  • Biophysics top 5%
    • Advanced Fluorescence Microscopy Techniques
    • Cell Image Analysis Techniques
  • Immunology top 10%
    • Mast cells and histamine
    • interferon and immune responses
    • Immune cells in cancer
    • T-cell and B-cell Immunology
    • Immunotherapy and Immune Responses

Papers in

    • Immune cells in cancer 5
    • interferon and immune responses 4
    • Immunotherapy and Immune Responses 4
    • T-cell and B-cell Immunology 3
    • Ovarian cancer diagnosis and treatment 4

Daniel Stephen Green

23 papers receiving 691 citations

Peers

Daniel Stephen Green
Comparison fields: 5 of 78
  • Biophysics 89
  • Immunology 241
  • Oncology 69
  • Reproductive Medicine 31
  • Immunology and Allergy 14
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Stephen Green

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Stephen Green

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017146
2 2020123
3 2007114
4 200794
5 201625
6 201825
7 201920
8 201920
9 200918
10 201217
11 201315
12 202215
13 200413
14 201412
15 201611
16 201910
17 20028
18 20126
19 20216
20 20082

About Daniel Stephen Green

Daniel Stephen Green is a scholar working on Immunology, Reproductive Medicine, Oncology, Virology and Physiology, having authored 23 papers that have together received 705 indexed citations. Recurring topics across this work include Immune cells in cancer (5 papers), interferon and immune responses (4 papers), Ovarian cancer diagnosis and treatment (4 papers), Immunotherapy and Immune Responses (4 papers), T-cell and B-cell Immunology (3 papers), Pulmonary Hypertension Research and Treatments (2 papers), Sphingolipid Metabolism and Signaling (2 papers) and Chemokine receptors and signaling (2 papers). The work is most often cited by research in Biophysics (89 citations), Immunology (241 citations), Oncology (69 citations), Reproductive Medicine (31 citations) and Immunology and Allergy (14 citations). Daniel Stephen Green has collaborated with scholars based in United States, Brazil and China. Frequent co-authors include Howard A. Young, Julio C. Valencia, William W. Cruikshank, Ross K. Morgan, Hardy Kornfeld, Shilpa Rahangdale, Kathryn C. Zoon, Christina M. Annunziata, Ana Tablante Nunes and Jillian M. Richmond. Their work appears in journals such as The Journal of Immunology, Cytokine, Journal of Translational Medicine, Journal of Interferon & Cytokine Research and Journal of Virology.

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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