Masahiro Takada

4.5k total citations
146 papers, 2.5k citations indexed

About

Masahiro Takada is a scholar working on Oncology, Cancer Research and Molecular Biology. According to data from OpenAlex, Masahiro Takada has authored 146 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Oncology, 32 papers in Cancer Research and 31 papers in Molecular Biology. Recurrent topics in Masahiro Takada's work include Breast Cancer Treatment Studies (28 papers), Breast Lesions and Carcinomas (13 papers) and Enzyme Production and Characterization (12 papers). Masahiro Takada is often cited by papers focused on Breast Cancer Treatment Studies (28 papers), Breast Lesions and Carcinomas (13 papers) and Enzyme Production and Characterization (12 papers). Masahiro Takada collaborates with scholars based in Japan, United States and United Kingdom. Masahiro Takada's co-authors include Masakazu Toi, Teruaki YUZURIHA, Kouichi Katayama, Norio Shibata, Satoru Ikenoya, Masako Kataoka, Kazuhiko Katayama, Yasufumi Asao, Yoshiaki Matsumoto and Kaori Togashi and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Masahiro Takada

136 papers receiving 2.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Masahiro Takada Japan 31 706 560 412 403 370 146 2.5k
Jian Zhang China 33 1.3k 1.9× 554 1.0× 364 0.9× 575 1.4× 353 1.0× 246 4.0k
Xiaolin Li China 31 1.0k 1.5× 573 1.0× 131 0.3× 158 0.4× 302 0.8× 96 2.7k
David J. Kerr United Kingdom 21 748 1.1× 159 0.3× 320 0.8× 238 0.6× 790 2.1× 38 2.4k
Parmeswaran Diagaradjane United States 24 1.3k 1.8× 989 1.8× 267 0.6× 152 0.4× 406 1.1× 51 3.1k
Natarajan Venkatesan United States 32 1.7k 2.4× 180 0.3× 345 0.8× 222 0.6× 866 2.3× 87 3.4k
Yongmei Xie China 35 1.6k 2.2× 342 0.6× 74 0.2× 518 1.3× 492 1.3× 159 3.7k
Qing‐Li Zhao Japan 31 1.1k 1.6× 927 1.7× 374 0.9× 172 0.4× 292 0.8× 122 2.9k
David J. Yang United States 34 687 1.0× 221 0.4× 1.4k 3.3× 218 0.5× 760 2.1× 145 3.7k
Xiaowen Liang China 30 906 1.3× 1.0k 1.9× 113 0.3× 97 0.2× 411 1.1× 107 3.4k
Hiroyuki Koide Japan 25 1.3k 1.8× 609 1.1× 166 0.4× 161 0.4× 123 0.3× 64 2.8k

Countries citing papers authored by Masahiro Takada

Since Specialization
Citations

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

Fields of papers citing papers by Masahiro Takada

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Masahiro Takada

This figure shows the co-authorship network connecting the top 25 collaborators of Masahiro Takada. A scholar is included among the top collaborators of Masahiro Takada 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 Masahiro Takada. Masahiro Takada 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.
Kinoshita, Haruyuki, Hiroshi Sugino, Masashi Kodama, et al.. (2025). The Addition of Vericiguat to Sacubitril/Valsartan Improved the Composite Endpoint. Add a Finishing Touch on Heart Failure Medical Therapy By Vericiguat as Secret Ingredient. European Journal of Heart Failure. 27(12). 2841–2843.
2.
3.
Kinoshita, Haruyuki, et al.. (2024). Examination of the Suitability of Vericiguat in Non-Heart Failure with Preserved Ejection Fraction Patients with Improved Ejection Fraction. Journal of Clinical Medicine. 13(17). 5264–5264. 1 indexed citations
4.
Takada, Masahiro, et al.. (2023). Effects on the Process and Outcome Indicators of the Carbapenem License System and the Full-time Pharmacist Following Meropenem Supply Disruption. Japanese Journal of Infection Prevention and Control. 38(6). 272–277. 1 indexed citations
5.
6.
Nishimichi, Takahiro, Masahiro Takada, Ken Osato, et al.. (2021). DarkEmulator: Cosmological emulation code for halo clustering statistics. Astrophysics Source Code Library. 3 indexed citations
7.
Takada, Masahiro, Masahiro Sugimoto, Norikazu Masuda, et al.. (2018). Prediction of postoperative disease-free survival and brain metastasis for HER2-positive breast cancer patients treated with neoadjuvant chemotherapy plus trastuzumab using a machine learning algorithm. Breast Cancer Research and Treatment. 172(3). 611–618. 18 indexed citations
8.
Iwata, Hiroji, Norikazu Masuda, Naohito Yamamoto, et al.. (2015). Outcomes of trastuzumab therapy in HER2-positive early breast cancer patients. International Journal of Clinical Oncology. 20(4). 709–722. 5 indexed citations
9.
Sugimoto, Masahiro, Masahiro Takada, & Masakazu Toi. (2014). Development of Web Tools to Predict Axillary lymph Node Metastasis and Pathological Response to Neoadjuvant Chemotherapy in Breast Cancer Patients. The International Journal of Biological Markers. 29(4). 372–379. 6 indexed citations
10.
11.
Takada, Masahiro. (2007). Molecular Design of the Carbohydrate Active Enzyme Inhibitors Revealed by Enzymatic Methods. Journal of Applied Glycoscience. 54(1). 55–61. 1 indexed citations
12.
Terunuma, Hiroshi, et al.. (2005). Potential role of NK cells in tumor growth and metastasis of breast cancer cells in NOD/SCID/γcnull (NOG) mice: Implication of immune therapy. Cancer Research. 65. 1105–1105. 1 indexed citations
13.
Takada, Masahiro & K. Ogawa. (2004). Enzymatic Syntheses of Cycloalkyl .BETA.-D-Glucopyranosides and Their Inhibition Activity for Plant .BETA.-Glucosidase. Journal of Applied Glycoscience. 51(3). 197–202. 1 indexed citations
14.
Takada, Masahiro. (2003). Biochemical and Genetic Analyses of a Novel gamma-Cyclodextrin Glucanotransferase from an Alkalophilic Bacillus clarkii 7364. The Journal of Biochemistry. 133(3). 317–324. 46 indexed citations
15.
Takada, Masahiro, et al.. (1999). Clinical and Basic Evaluation of Side Effect for Skin Irritation among Three Nitrate Patch Preparations for Ischemic Heart Disease.. Japanese Journal of Hospital Pharmacy. 25(5). 495–501. 1 indexed citations
16.
Takada, Masahiro, et al.. (1994). [Respiratory arrest following diazepam administration during spinal anesthesia in a patient with myotonic dystrophy].. PubMed. 43(6). 934–7. 1 indexed citations
17.
Hashimoto, Ryo, et al.. (1992). Effects of Unilateral Hypothalamic Lesion on Serum Gonadotropin in Hemiovariectomized Rats(COMMUNICATION). ZOOLOGICAL SCIENCE. 9(1). 223–226. 1 indexed citations
18.
Takada, Masahiro, et al.. (1986). T_3-induced differentiation of the active Na transport system across the skin of Ambystoma mexicanum (Urodela) : Endocrinology. ZOOLOGICAL SCIENCE. 3(6). 1086. 1 indexed citations
19.
Takada, Masahiro, Satoru Ikenoya, Teruaki YUZURIHA, & Kouichi Katayama. (1984). [17] Simultaneous determination of reduced and oxidized ubiquinones. Methods in enzymology on CD-ROM/Methods in enzymology. 105. 147–155. 85 indexed citations
20.
Takada, Masahiro, et al.. (1983). Beta-Alanine in the Puparial Case of Drosophila melanogaster. 28(1). 17–26. 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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