Sho Ikeda

901 total citations
46 papers, 683 citations indexed

About

Sho Ikeda is a scholar working on Molecular Biology, Hematology and Immunology. According to data from OpenAlex, Sho Ikeda has authored 46 papers receiving a total of 683 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 14 papers in Hematology and 11 papers in Immunology. Recurrent topics in Sho Ikeda's work include Multiple Myeloma Research and Treatments (12 papers), T-cell and Retrovirus Studies (9 papers) and Cutaneous lymphoproliferative disorders research (9 papers). Sho Ikeda is often cited by papers focused on Multiple Myeloma Research and Treatments (12 papers), T-cell and Retrovirus Studies (9 papers) and Cutaneous lymphoproliferative disorders research (9 papers). Sho Ikeda collaborates with scholars based in Japan, United States and Norway. Sho Ikeda's co-authors include Hiroyuki Tagawa, Akihiro Kitadate, Naoto Takahashi, Kenichi Sawada, Kazuaki Teshima, Miho Nara, Atsushi Watanabe, Junsuke Yamashita, Makoto Sugaya and Tomomitsu Miyagaki and has published in prestigious journals such as SHILAP Revista de lepidopterología, Blood and Journal of Applied Physics.

In The Last Decade

Sho Ikeda

40 papers receiving 678 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sho Ikeda Japan 15 416 237 148 131 125 46 683
Giulia Spallone Italy 12 237 0.6× 72 0.3× 218 1.5× 136 1.0× 21 0.2× 27 609
Mohsen Sheykhhasan Iran 13 214 0.5× 124 0.5× 89 0.6× 186 1.4× 47 0.4× 35 557
Sim L. Tung United Kingdom 12 351 0.8× 182 0.8× 597 4.0× 130 1.0× 40 0.3× 15 910
Karen R. McLachlan United States 10 377 0.9× 38 0.2× 153 1.0× 130 1.0× 66 0.5× 22 660
Yisheng Fang United States 16 296 0.7× 207 0.9× 67 0.5× 171 1.3× 8 0.1× 45 737
Rocco Alfredo Satriano Italy 12 105 0.3× 43 0.2× 142 1.0× 249 1.9× 38 0.3× 20 509
Anand Balasubramani United States 6 184 0.4× 59 0.2× 350 2.4× 92 0.7× 99 0.8× 38 591
Geoff Strutton Australia 15 194 0.5× 41 0.2× 162 1.1× 145 1.1× 26 0.2× 22 660
Shuen-Kuei Liao Taiwan 13 315 0.8× 95 0.4× 115 0.8× 182 1.4× 32 0.3× 18 679
Maite Iglesias Spain 13 321 0.8× 178 0.8× 152 1.0× 261 2.0× 9 0.1× 16 670

Countries citing papers authored by Sho Ikeda

Since Specialization
Citations

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

Fields of papers citing papers by Sho Ikeda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sho Ikeda

This figure shows the co-authorship network connecting the top 25 collaborators of Sho Ikeda. A scholar is included among the top collaborators of Sho Ikeda 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 Sho Ikeda. Sho Ikeda 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.
Osada, Naoki, Hirokazu Kubota, Hiroo Koyama, et al.. (2025). Discovery of a novel class NSD2 inhibitor for multiple myeloma with t(4;14)+. PubMed. 2(2). 100091–100091. 1 indexed citations
2.
Yamada, Masahiro, et al.. (2024). Comprehensive analysis of microRNAs modulated by histone deacetylase inhibitors identifies microRNA-7-5p with anti-myeloma effect. International Journal of Hematology. 120(3). 325–336. 1 indexed citations
3.
4.
Abe, Ko, Sho Ikeda, Miho Nara, et al.. (2023). Hypoxia‐induced oxidative stress promotes therapy resistance via upregulation of heme oxygenase‐1 in multiple myeloma. Cancer Medicine. 12(8). 9709–9722. 9 indexed citations
5.
6.
Osada, Naoki, Jiro Kikuchi, Hidekatsu Iha, et al.. (2023). c‐FOS is an integral component of the IKZF1 transactivator complex and mediates lenalidomide resistance in multiple myeloma. Clinical and Translational Medicine. 13(8). e1364–e1364. 7 indexed citations
7.
Ikeda, Sho, et al.. (2022). Downregulation of miR‐26 promotes invasion and metastasis via targeting interleukin‐22 in cutaneous T‐cell lymphoma. Cancer Science. 113(4). 1208–1219. 12 indexed citations
8.
Kikuchi, Jiro, Sho Ikeda, Takahiro Kobayashi, et al.. (2022). EMD originates from hyaluronan-induced homophilic interactions of CD44 variant-expressing MM cells under shear stress. Blood Advances. 7(4). 508–524. 5 indexed citations
9.
Ikeda, Sho & Hiroyuki Tagawa. (2021). Impact of hypoxia on the pathogenesis and therapy resistance in multiple myeloma. Cancer Science. 112(10). 3995–4004. 23 indexed citations
10.
Abe, Yoshiaki, Sho Ikeda, Akihiro Kitadate, et al.. (2019). Low hexokinase-2 expression-associated false-negative 18F-FDG PET/CT as a potential prognostic predictor in patients with multiple myeloma. European Journal of Nuclear Medicine and Molecular Imaging. 46(6). 1345–1350. 32 indexed citations
11.
Goni, Miguel, et al.. (2018). A technique to measure the thermal resistance at the interface between a micron size particle and its matrix in composite materials. Journal of Applied Physics. 124(10). 3 indexed citations
12.
Goni, Miguel, et al.. (2018). Frequency domain thermoreflectance technique for measuring the thermal conductivity of individual micro-particles. Review of Scientific Instruments. 89(7). 74901–74901. 14 indexed citations
13.
Kitadate, Akihiro, Sho Ikeda, Naoto Takahashi, et al.. (2017). Histone deacetylase inhibitors downregulate CCR4 expression and decrease mogamulizumab efficacy in CCR4-positive mature T-cell lymphomas. Haematologica. 103(1). 126–135. 19 indexed citations
14.
Ikeda, Sho, Akihiro Kitadate, H Saitoh, et al.. (2017). Hypoxia‐inducible microRNA‐210 regulates the DIMT1‐IRF4 oncogenic axis in multiple myeloma. Cancer Science. 108(4). 641–652. 30 indexed citations
15.
Ikeda, Sho, Akihiro Kitadate, Miho Nara, et al.. (2016). Disruption of CCL20-CCR6 interaction inhibits metastasis of advanced cutaneous T-cell lymphoma. Oncotarget. 7(12). 13563–13574. 20 indexed citations
16.
Kitadate, Akihiro, Sho Ikeda, Junsuke Yamashita, et al.. (2016). Histone Deacetylase Inhibitors Inhibit Metastasis By Restoring a Tumor Suppressive microRNA, Mir-150 in Advanced Cutaneous T-Cell Lymphoma. Blood. 128(22). 4113–4113. 1 indexed citations
17.
Kitadate, Akihiro, Sho Ikeda, Kazuaki Teshima, et al.. (2015). MicroRNA-16 mediates the regulation of a senescence–apoptosis switch in cutaneous T-cell and other non-Hodgkin lymphomas. Oncogene. 35(28). 3692–3704. 47 indexed citations
18.
Ikeda, Sho & Hiroyuki Tagawa. (2014). Dysregulation of microRNAs and their association in the pathogenesis of T-cell lymphoma/leukemias. International Journal of Hematology. 99(5). 542–552. 8 indexed citations
19.
Teshima, Kazuaki, Miho Nara, Atsushi Watanabe, et al.. (2013). Dysregulation of BMI1 and microRNA-16 collaborate to enhance an anti-apoptotic potential in the side population of refractory mantle cell lymphoma. Oncogene. 33(17). 2191–2203. 45 indexed citations
20.
Takahashi, Naoto, Kazuaki Teshima, Masumi Fujishima, et al.. (2012). Safety and efficacy of low-dose liposomal amphotericin B as empirical antifungal therapy for patients with prolonged neutropenia. International Journal of Clinical Oncology. 18(6). 983–987. 6 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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