Yuta Ito

850 total citations
53 papers, 554 citations indexed

About

Yuta Ito is a scholar working on Pathology and Forensic Medicine, Oncology and Genetics. According to data from OpenAlex, Yuta Ito has authored 53 papers receiving a total of 554 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Pathology and Forensic Medicine, 12 papers in Oncology and 10 papers in Genetics. Recurrent topics in Yuta Ito's work include Lymphoma Diagnosis and Treatment (15 papers), Chronic Lymphocytic Leukemia Research (6 papers) and Aquaculture Nutrition and Growth (6 papers). Yuta Ito is often cited by papers focused on Lymphoma Diagnosis and Treatment (15 papers), Chronic Lymphocytic Leukemia Research (6 papers) and Aquaculture Nutrition and Growth (6 papers). Yuta Ito collaborates with scholars based in Japan, United States and United Kingdom. Yuta Ito's co-authors include K Shimizu, Yukiko Tsunematsu, Jun Miyauchi, Shinichi Makita, Tsuyoshi Kawano, Akihiko Hara, Yoshihisa Nakano, Hiroshi Inui, Naoshi Hiramatsu and Naoki Harada and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Yuta Ito

45 papers receiving 543 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yuta Ito Japan 13 131 97 96 82 81 53 554
Yixuan Fang China 16 393 3.0× 74 0.8× 103 1.1× 15 0.2× 23 0.3× 50 770
Peisong Ma United States 14 204 1.6× 24 0.2× 183 1.9× 45 0.5× 11 0.1× 33 547
Meixiang Yang China 16 163 1.2× 18 0.2× 39 0.4× 30 0.4× 42 0.5× 18 796
Jilin Ma China 13 167 1.3× 65 0.7× 33 0.3× 54 0.7× 49 0.6× 18 789
M.H. Helfrich United Kingdom 7 266 2.0× 14 0.1× 54 0.6× 38 0.5× 31 0.4× 12 713
M. Fátima Macedo Portugal 12 100 0.8× 47 0.5× 94 1.0× 14 0.2× 12 0.1× 30 404
Agata Poniewierska-Baran Poland 13 217 1.7× 58 0.6× 70 0.7× 20 0.2× 20 0.2× 35 517
Guoping Huang China 10 309 2.4× 118 1.2× 28 0.3× 27 0.3× 26 0.3× 33 611
Zhijuan Lin China 18 508 3.9× 30 0.3× 67 0.7× 35 0.4× 73 0.9× 49 935
G Grusky United States 10 104 0.8× 42 0.4× 61 0.6× 24 0.3× 20 0.2× 14 390

Countries citing papers authored by Yuta Ito

Since Specialization
Citations

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

Fields of papers citing papers by Yuta Ito

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yuta Ito

This figure shows the co-authorship network connecting the top 25 collaborators of Yuta Ito. A scholar is included among the top collaborators of Yuta Ito 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 Yuta Ito. Yuta Ito 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.
Ito, Yuta, Yasunori Kogure, & Keisuke Kataoka. (2025). Biological and Clinical Relevance of Genetic Alterations in Peripheral T-cell Lymphomas. JMA Journal. 8(2). 345–353. 1 indexed citations
2.
Yoshifuji, Kota, Yuki Saito, Mariko Tabata, et al.. (2025). In vivo CRISPR screening reveals cooperation of KMT2D and TP53 deficiencies in B-cell lymphomagenesis. Blood Advances. 9(19). 5040–5055.
3.
Saito, Yuki, Yasunori Kogure, Yuta Ito, et al.. (2024). Pan-Cancer Comparative and Integrative Analyses of Driver Alterations Using Japanese and International Genomic Databases. Cancer Discovery. 14(5). 786–803. 21 indexed citations
4.
Tanaka, Chisato, Naoki Harada, Y. Teraoka, et al.. (2024). Mogrol stimulates G-protein-coupled bile acid receptor 1 (GPBAR1/TGR5) and insulin secretion from pancreatic β-cells and alleviates hyperglycemia in mice. Scientific Reports. 14(1). 3244–3244. 7 indexed citations
5.
Yasunaga, Jun‐ichirou, L. Liang, Shinji Nakaoka, et al.. (2023). Anti‐HTLV‐1 immunity combined with proviral load as predictive biomarkers for adult T‐cell leukemia‐lymphoma. Cancer Science. 115(1). 310–320. 7 indexed citations
6.
Ito, Yuta, Joji Shimono, Keisuke Kawamoto, et al.. (2023). TP53 and CDKN2A alterations Define a Poor Prognostic Subgroup in Patients with Nodal T-Follicular Helper Cell Lymphoma. Blood. 142(Supplement 1). 1630–1630.
7.
8.
Ito, Yuta, Akiko Miyagi Maeshima, Shunsuke Hatta, et al.. (2021). Use of Core-Needle Biopsy for the Diagnosis of Malignant Lymphomas in Clinical Practice. Acta Haematologica. 144(6). 641–648. 9 indexed citations
9.
Maeshima, Akiko Miyagi, Hirokazu Taniguchi, Takahiro Fujino, et al.. (2020). Immunohistochemical CD20-negative change in B-cell non-Hodgkin lymphomas after rituximab-containing therapy. Annals of Hematology. 99(9). 2141–2148. 10 indexed citations
10.
Zhao, Mingming, Satoru Takayama, Miki Nagai, et al.. (2020). Induced Fetal Human Muscle Stem Cells with High Therapeutic Potential in a Mouse Muscular Dystrophy Model. Stem Cell Reports. 15(1). 80–94. 35 indexed citations
11.
Ito, Yuta, Shinichi Makita, Akiko Miyagi Maeshima, et al.. (2018). Paraneoplastic Pemphigus Associated with B-cell Chronic Lymphocytic Leukemia Treated with Ibrutinib and Rituximab. Internal Medicine. 57(16). 2395–2398. 14 indexed citations
12.
Ito, Yuta, et al.. (2017). [Diffuse large B-cell lymphoma complicated with drug-induced vasculitis during administration of pegfilgrastim].. PubMed. 58(11). 2238–2242. 10 indexed citations
13.
14.
Mitani, Takakazu, Yuta Ito, Naoki Harada, et al.. (2014). Resveratrol Reduces the Hypoxia-Induced Resistance to Doxorubicin in Breast Cancer Cells. Journal of Nutritional Science and Vitaminology. 60(2). 122–128. 33 indexed citations
15.
Ryu, Yong‐Woon, Yuta Ito, Naoshi Hiramatsu, et al.. (2013). Molecular Cloning and Transcript Expression of Genes Encoding Two Types of Lipoprotein Lipase in the Ovary of Cutthroat Trout,Oncorhynchus clarki. ZOOLOGICAL SCIENCE. 30(3). 224–237. 11 indexed citations
16.
Luo, Wenshu, Yuta Ito, Hiroko Mizuta, et al.. (2013). Molecular cloning and partial characterization of an ovarian receptor with seven ligand binding repeats, an orthologue of low-density lipoprotein receptor, in the cutthroat trout (Oncorhynchus clarki). Comparative Biochemistry and Physiology Part A Molecular & Integrative Physiology. 166(2). 263–271. 22 indexed citations
17.
Ito, Yuta, Takakazu Mitani, Naoki Harada, et al.. (2013). Identification of Carbonyl Reductase 1 as a Resveratrol-Binding Protein by Affinity Chromatography Using 4'-Amino-3,5-dihydroxy-trans-stilbene. Journal of Nutritional Science and Vitaminology. 59(4). 358–364. 20 indexed citations
18.
Mizuta, Hiroko, Naoshi Hiramatsu, Takashi Todo, et al.. (2011). Molecular Cloning and Localization of Two Classical Ovarian Lipoprotein Receptors in Cutthroat Trout Oncorhynchus clarki. Indian Journal of Science and Technology. 4. 192–193. 2 indexed citations
19.
Ryu, Yong‐Woon, Kyoko Saito, Yuta Ito, et al.. (2011). EXPRESSION OF GENES INVOLVED IN OOCYTE LIPIDATION IN CUTTHROAT TROUT, ONCORHYNCHUS CLARKI. Indian Journal of Science and Technology. 4(1). 203–204. 2 indexed citations
20.
Sato, Motohiro, et al.. (2010). F-18 FDG PET/CT in relapsing polychondritis. Annals of Nuclear Medicine. 24(9). 687–690. 30 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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