Kumiko Kagawa

2.0k total citations
100 papers, 1.4k citations indexed

About

Kumiko Kagawa is a scholar working on Hematology, Molecular Biology and Oncology. According to data from OpenAlex, Kumiko Kagawa has authored 100 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Hematology, 27 papers in Molecular Biology and 19 papers in Oncology. Recurrent topics in Kumiko Kagawa's work include Multiple Myeloma Research and Treatments (25 papers), Laser-induced spectroscopy and plasma (11 papers) and Peptidase Inhibition and Analysis (9 papers). Kumiko Kagawa is often cited by papers focused on Multiple Myeloma Research and Treatments (25 papers), Laser-induced spectroscopy and plasma (11 papers) and Peptidase Inhibition and Analysis (9 papers). Kumiko Kagawa collaborates with scholars based in Japan, Indonesia and United States. Kumiko Kagawa's co-authors include Masahiro Abe, Koo Hendrik Kurniawan, Shuji Ozaki, Hirokazu Miki, Toshio Matsumoto, Shingen Nakamura, Kyoko Takeuchi, Takeshi Harada, Asuka Oda and Shiro Fujii and has published in prestigious journals such as Blood, Applied Physics Letters and PLoS ONE.

In The Last Decade

Kumiko Kagawa

93 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kumiko Kagawa Japan 22 403 319 283 267 185 100 1.4k
Takashi Nakazawa Japan 25 964 2.4× 204 0.6× 157 0.6× 38 0.1× 66 0.4× 136 3.1k
Toshikazu Yamaguchi Japan 27 591 1.5× 730 2.3× 81 0.3× 51 0.2× 77 0.4× 120 2.4k
J Tsai United States 15 589 1.5× 121 0.4× 102 0.4× 72 0.3× 587 3.2× 29 3.1k
Ewa Stępień Poland 32 1.2k 3.0× 188 0.6× 248 0.9× 171 0.6× 22 0.1× 160 3.2k
Richard Hodgson United Kingdom 35 477 1.2× 89 0.3× 162 0.6× 23 0.1× 36 0.2× 145 3.4k
Chunyi Liu China 26 293 0.7× 49 0.2× 91 0.3× 339 1.3× 239 1.3× 109 1.9k
Miloš D. Miljković United States 31 869 2.2× 644 2.0× 33 0.1× 115 0.4× 1.1k 6.2× 84 3.3k
Randall W. Nelson United States 43 2.7k 6.6× 204 0.6× 103 0.4× 20 0.1× 173 0.9× 118 4.7k
Annette McWilliams Canada 32 781 1.9× 400 1.3× 16 0.1× 76 0.3× 704 3.8× 90 4.7k
Shōji Kobayashi Japan 27 516 1.3× 383 1.2× 15 0.1× 72 0.3× 27 0.1× 196 2.5k

Countries citing papers authored by Kumiko Kagawa

Since Specialization
Citations

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

Fields of papers citing papers by Kumiko Kagawa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kumiko Kagawa

This figure shows the co-authorship network connecting the top 25 collaborators of Kumiko Kagawa. A scholar is included among the top collaborators of Kumiko Kagawa 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 Kumiko Kagawa. Kumiko Kagawa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Inoue, Yusuke, Jumpei Teramachi, Asuka Oda, et al.. (2024). Elotuzumab‐mediated ADCC with Th1‐like Vγ9Vδ2 T cells to disrupt myeloma–osteoclast interaction. Cancer Science. 116(2). 559–563. 1 indexed citations
2.
Yamada, Hiroki, Naoto Okada, Shingen Nakamura, et al.. (2022). A machine learning model using SNPs obtained from a genome-wide association study predicts the onset of vincristine-induced peripheral neuropathy. The Pharmacogenomics Journal. 22(4). 241–246. 1 indexed citations
3.
Harada, Takeshi, Hiroto Ohguchi, Asuka Oda, et al.. (2022). Novel antimyeloma therapeutic option with inhibition of the HDAC1-IRF4 axis and PIM kinase. Blood Advances. 7(6). 1019–1032. 2 indexed citations
4.
Inoue, Tatsuro, Takashi Saito, Masafumi Nakamura, et al.. (2022). Allogeneic haematopoietic stem cell transplantation and patient falls: impact of lower extremity muscle strength. BMJ Supportive & Palliative Care. 15(3). 379–386.
5.
Kagawa, Kumiko, Takashi Saito, Kimiko Sogabe, et al.. (2021). Allogeneic haematopoietic stem cell transplantation—clinical outcomes: impact of leg muscle strength. BMJ Supportive & Palliative Care. 16(1). 180–187. 6 indexed citations
6.
Nakamura, Shingen, Momoyo Azuma, Kimiko Sogabe, et al.. (2018). Steroid pulse therapy in patients with encephalopathy associated with severe fever with thrombocytopenia syndrome. Journal of Infection and Chemotherapy. 24(5). 389–392. 32 indexed citations
7.
Miki, Hirokazu, Takeshi Harada, Qu Cui, et al.. (2016). Expansion of γδT Cells By New Generation IMiDs and Their Cytotoxicity Against Myeloma Progenitors. Blood. 128(22). 2107–2107. 1 indexed citations
8.
Harada, Takeshi, Shuji Ozaki, Asuka Oda, et al.. (2013). Association of Th1 and Th2 cytokines with transient inflammatory reaction during lenalidomide plus dexamethasone therapy in multiple myeloma. International Journal of Hematology. 97(6). 743–748. 20 indexed citations
9.
Harada, Takeshi, Shuji Ozaki, Asuka Oda, et al.. (2013). Combination with a Defucosylated Anti-HM1.24 Monoclonal Antibody plus Lenalidomide Induces Marked ADCC against Myeloma Cells and Their Progenitors. PLoS ONE. 8(12). e83905–e83905. 13 indexed citations
10.
Kagawa, Kumiko, et al.. (2013). Dual-band multi-aperture enhanced redox imaging of colonic adenomas for endoscopes with a high-performance CMOS imager. PubMed. 2013. 1414–1417. 3 indexed citations
11.
Nakano, Ayako, Masahiro Abe, Daisuke Tsuji, et al.. (2011). Inhibition of Hexokinase II Inactivates ABC Transporters and Restores Drug Sensitivity in Myeloma Cells. Blood. 118(21). 135–135. 1 indexed citations
12.
Takeuchi, Kyoko, Masahiro Abe, Masahiro Hiasa, et al.. (2010). TGF-β Inhibition Restores Terminal Osteoblast Differentiation to Suppress Myeloma Growth. PLoS ONE. 5(3). e9870–e9870. 108 indexed citations
13.
Ozaki, Shuji, Osamu Tanaka, Shiro Fujii, et al.. (2007). Therapy with Bortezomib plus Dexamethasone Induces Osteoblast Activation in Responsive Patients with Multiple Myeloma. International Journal of Hematology. 86(2). 180–185. 42 indexed citations
14.
Nakagaki, Takao, et al.. (2004). Technology Trend of Chemically Recuperated Gas Turbine. 55(11). 1190–1195. 1 indexed citations
15.
Yamazaki, Hideya, et al.. (1998). 5 Gy irradiation does not alter the expression level of WT1 (Wilms tumor gene) in K562 and ML1.. PubMed. 18(4A). 2495–7. 1 indexed citations
16.
Okabe, Atsuyuki, Kumiko Kagawa, Yutaka Okazaki, et al.. (1996). A narrow track MR head for high density tape recording. IEEE Transactions on Magnetics. 32(5). 3404–3406. 8 indexed citations
17.
Kagawa, Kumiko, et al.. (1995). VIBRATION ANALYSIS OF A LARGE UNDERWATER SHELL OF REVOLUTION. The Proceedings of the ... International Offshore and Polar Engineering Conference. 4. 300–307. 1 indexed citations
18.
Itoh, Yoshito, et al.. (1992). Elevated interleukin-6 and gamma-globulin during interferon therapy of hepatitis B.. PubMed. 87(10). 1485–7. 17 indexed citations
19.
Akamatsu, Shigeru, et al.. (1990). [Evaluation of physiological mitral regurgitant flow using transesophageal Doppler echocardiography].. PubMed. 20(2). 341–8. 2 indexed citations
20.
Kagawa, Kumiko. (1977). A STUDY OF WAVE INDUCED VIBRATIONS. 15. 82–94. 1 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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