Kina Smith

828 citations
13 papers · 626 · h-index 10

Impact in

  • Immunology top 10%
    • Immunotherapy and Immune Responses
    • Immune Cell Function and Interaction
    • T-cell and B-cell Immunology
    • Immune cells in cancer
    • Wound Healing and Treatments

Papers in

    • Immunotherapy and Immune Responses 8
    • Immune Response and Inflammation 4
    • T-cell and B-cell Immunology 4
    • Immune cells in cancer 2
    • Atherosclerosis and Cardiovascular Diseases 1
    • CAR-T cell therapy research 5
    • Cytokine Signaling Pathways and Interactions 2
    • Cancer Immunotherapy and Biomarkers 2

Kina Smith

13 papers receiving 611 citations

Peers

Kina Smith
Comparison fields: 5 of 84
  • Immunology 359
  • Rehabilitation 77
  • Oncology 217
  • Cancer Research 53
  • Molecular Biology 184
Replace Veronica Basso with:
Veronica Basso Italy
Juan Luis Callejas‐Valera United States
Jami R. Erickson United States
Priya Govindaraju United States
Jeroen W.J. van Kilsdonk Netherlands
Isabel Mirones Spain
Laurel E. Hind United States
Quanhai Li China
Sara R. Hamilton United States
Kina Smith relative to Veronica Basso Italy Veronica Basso's profile →
Citations per field
00.5×1.6×
Veronica Basso · 1×
Citations per year

Countries citing papers authored by Kina Smith

Since Specialization
Citations

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

Fields of papers citing papers by Kina Smith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

13 of 13 papers shown
#Work
1 2007165
2 2004112
3 200779
4 200469
5 200450
6 200341
7 200434
8 200530
9 200419
10 200519
11 20043
12 20043
13 20042

About Kina Smith

Kina Smith is a scholar working on Immunology, Oncology, Molecular Biology, Rehabilitation and Microbiology, having authored 13 papers that have together received 626 indexed citations. Recurring topics across this work include Immunotherapy and Immune Responses (8 papers), CAR-T cell therapy research (5 papers), Immune Response and Inflammation (4 papers), T-cell and B-cell Immunology (4 papers), Cytokine Signaling Pathways and Interactions (2 papers), Immune cells in cancer (2 papers), Cancer Immunotherapy and Biomarkers (2 papers) and Atherosclerosis and Cardiovascular Diseases (1 paper). The work is most often cited by research in Immunology (359 citations), Rehabilitation (77 citations), Oncology (217 citations), Cancer Research (53 citations) and Molecular Biology (184 citations). Kina Smith has collaborated with scholars based in United States, Italy and Germany. Frequent co-authors include Ena Wang, Francesco M. Marincola, Monica C. Panelli, Ping Jin, Dirk Nagorsen, Vladia Monsurrò, Christopher Norwood, Herbert B. Slade, Mitchell E. Stashower and David F. Stroncek. Their work appears in journals such as Journal of Translational Medicine, Genome biology, Current Oncology Reports, BMC Genomics and Expert Opinion on Biological Therapy.

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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