K. Inaba

853 total citations · 1 hit paper
9 papers, 708 citations indexed

About

K. Inaba is a scholar working on Immunology, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, K. Inaba has authored 9 papers receiving a total of 708 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Immunology, 3 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Molecular Biology. Recurrent topics in K. Inaba's work include Immunotherapy and Immune Responses (7 papers), T-cell and B-cell Immunology (3 papers) and Monoclonal and Polyclonal Antibodies Research (3 papers). K. Inaba is often cited by papers focused on Immunotherapy and Immune Responses (7 papers), T-cell and B-cell Immunology (3 papers) and Monoclonal and Polyclonal Antibodies Research (3 papers). K. Inaba collaborates with scholars based in Japan and United States. K. Inaba's co-authors include Ralph M. Steinman, R M Steinman, Nikolaus Romani, S Koide, Y Katsura, Haruhiko Ehara, T Izumi, Yasuhisa Kimura, Kei Takahashi and Katsuo Kumagai and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Experimental Medicine and The FASEB Journal.

In The Last Decade

K. Inaba

9 papers receiving 680 citations

Hit Papers

Dendritic cells in the T‐cell areas of lymphoid organs 1997 2026 2006 2016 1997 100 200 300 400

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
K. Inaba Japan 7 617 107 105 53 39 9 708
Sally R. Masters United States 7 627 1.0× 87 0.8× 88 0.8× 47 0.9× 47 1.2× 8 755
Machiko Atsuta Japan 8 788 1.3× 125 1.2× 167 1.6× 34 0.6× 36 0.9× 9 919
Ralph M. Steinman United States 7 592 1.0× 178 1.7× 118 1.1× 38 0.7× 25 0.6× 7 690
Pia Björck United States 13 761 1.2× 130 1.2× 115 1.1× 42 0.8× 50 1.3× 20 850
D.B. Fearnley New Zealand 12 643 1.0× 146 1.4× 133 1.3× 21 0.4× 39 1.0× 15 729
Astrid Lanoue United Kingdom 6 541 0.9× 136 1.3× 85 0.8× 24 0.5× 62 1.6× 6 639
Susan F. Grammer United States 12 407 0.7× 99 0.9× 65 0.6× 74 1.4× 69 1.8× 15 531
Giacomo Galati Italy 10 702 1.1× 227 2.1× 105 1.0× 59 1.1× 47 1.2× 13 881
A M Kruisbeek United States 17 750 1.2× 120 1.1× 131 1.2× 45 0.8× 151 3.9× 26 903
C. Kinet-Denoël Belgium 13 476 0.8× 54 0.5× 50 0.5× 42 0.8× 80 2.1× 32 579

Countries citing papers authored by K. Inaba

Since Specialization
Citations

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

Fields of papers citing papers by K. Inaba

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of K. Inaba

This figure shows the co-authorship network connecting the top 25 collaborators of K. Inaba. A scholar is included among the top collaborators of K. Inaba based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with K. Inaba. K. Inaba is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Kimura, Yasuhisa, et al.. (2010). Invariant NKT cell anergy is induced by a strong TCR-mediated signal plus co-stimulation. International Immunology. 22(11). 905–913. 40 indexed citations
2.
Steinman, Ralph M., et al.. (1997). Dendritic cells in the T‐cell areas of lymphoid organs. Immunological Reviews. 156(1). 25–37. 470 indexed citations breakdown →
3.
Yamaguchi, Yuki, et al.. (1996). Contrasting effects of TGFβ1 and TNFα on the development of dendritic cells from mouse bone marrow. The FASEB Journal. 10(6). 1483. 1 indexed citations
4.
Umezu, Hajime, M. Naito, K. Inaba, & Kei Takahashi. (1995). Ultrastructural and immunophenotypic differentiation of dendritic cells from mouse bone marrow cultures supplemented with granulocyte/macrophage colony-stimulating factor (GM-CSF).. PubMed. 27(2). 227–34. 3 indexed citations
5.
Inaba, K., Nikolaus Romani, & R M Steinman. (1989). An antigen-independent contact mechanism as an early step in T cell-proliferative responses to dendritic cells.. The Journal of Experimental Medicine. 170(2). 527–542. 99 indexed citations
6.
Miyama-Inaba, Muneo, Tatsuharu Ohno, K. Inaba, et al.. (1987). Inhibitory mechanism of the proliferative response of B lymphocytes: suppression of the proliferation induced by anti-mu antibody and BSF1 by immune complexes.. PubMed. 61(1). 43–50. 7 indexed citations
7.
Steinman, Ralph M. & K. Inaba. (1985). Stimulation of the primary mixed leukocyte reaction.. PubMed. 5(4). 331–48. 42 indexed citations
8.
Inaba, K., S Koide, & Ralph M. Steinman. (1985). Properties of memory T lymphocytes isolated from the mixed leukocyte reaction.. Proceedings of the National Academy of Sciences. 82(22). 7686–7690. 28 indexed citations
9.
Katsura, Y, et al.. (1977). Cell-Mediated and Humoral Immune Responses in Mice. International Archives of Allergy and Immunology. 53(4). 329–340. 18 indexed citations

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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