Rin Nakamura

1.1k citations
10 papers · 149 · h-index 7

Impact in

    • Multiple Myeloma Research and Treatments
    • CAR-T cell therapy research
    • Cancer Immunotherapy and Biomarkers

Papers in

    • Peptidase Inhibition and Analysis 2
    • Cancer Immunotherapy and Biomarkers 2
    • CAR-T cell therapy research 2
    • Multiple Myeloma Research and Treatments 5

Rin Nakamura

10 papers receiving 147 citations

Peers

Rin Nakamura
Comparison fields: 5 of 29
  • Hematology 54
  • Oncology 96
  • Radiology, Nuclear Medicine and Imaging 32
  • Immunology 27
  • Pathology and Forensic Medicine 11
Replace Raphael Teipel with:
Raphael Teipel Germany
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Holly Lee Canada
Omar Saavedra Spain
Jadranka Dragovic United States
Wajeeha Aiman United States
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Claude Chahine France
Ana Alcaraz‐Serna Spain
Rin Nakamura relative to Raphael Teipel Germany Raphael Teipel's profile →
Citations per field
00.5×2.7×
Raphael Teipel · 1×
Citations per year

Countries citing papers authored by Rin Nakamura

Since Specialization
Citations

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

Fields of papers citing papers by Rin Nakamura

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

10 of 10 papers shown
#Work
1 202028
2 202228
3 202327
4 201818
5 201615
6 202414
7 202010
8 20234
9 20144
10 20141

About Rin Nakamura

Rin Nakamura is a scholar working on Oncology, Hematology, Immunology, Surgery and Pulmonary and Respiratory Medicine, having authored 10 papers that have together received 149 indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (5 papers), Peptidase Inhibition and Analysis (2 papers), Chronic Lymphocytic Leukemia Research (2 papers), Cancer Immunotherapy and Biomarkers (2 papers), Immune cells in cancer (2 papers), CAR-T cell therapy research (2 papers), Bladder and Urothelial Cancer Treatments (2 papers) and Ferroptosis and cancer prognosis (1 paper). The work is most often cited by research in Hematology (54 citations), Oncology (96 citations), Radiology, Nuclear Medicine and Imaging (32 citations), Immunology (27 citations) and Pathology and Forensic Medicine (11 citations). Rin Nakamura has collaborated with scholars based in Australia, United States and Canada. Frequent co-authors include Teiko Sumiyoshi, Luciana Molinero, Andrew Spencer, Ching‐Wei Chang, Suzanne Trudel, Priti S. Hegde, Grant R. Goodman, Bharathi Vennapusa, David D. Tran and Yijin Li. Their work appears in journals such as Blood, Journal of Clinical Oncology, HemaSphere, Journal for ImmunoTherapy of Cancer and Applied immunohistochemistry & molecular morphology.

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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