Takeshi Murata

426 total citations
26 papers, 296 citations indexed

About

Takeshi Murata is a scholar working on Cancer Research, Oncology and Pathology and Forensic Medicine. According to data from OpenAlex, Takeshi Murata has authored 26 papers receiving a total of 296 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Cancer Research, 10 papers in Oncology and 8 papers in Pathology and Forensic Medicine. Recurrent topics in Takeshi Murata's work include Breast Cancer Treatment Studies (12 papers), Breast Lesions and Carcinomas (8 papers) and HER2/EGFR in Cancer Research (6 papers). Takeshi Murata is often cited by papers focused on Breast Cancer Treatment Studies (12 papers), Breast Lesions and Carcinomas (8 papers) and HER2/EGFR in Cancer Research (6 papers). Takeshi Murata collaborates with scholars based in Japan, United States and United Kingdom. Takeshi Murata's co-authors include Tetsu Hayashida, Hiromitsu Jinno, Akiko Matsumoto, Tomoko Seki, Yuko Kitagawa, Maiko Takahashi, Yuko Kitagawa, Masahiro Sugimoto, Koji Okabayashi and Makoto Sunamura and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Oncology and JNCI Journal of the National Cancer Institute.

In The Last Decade

Takeshi Murata

22 papers receiving 289 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Takeshi Murata Japan 10 119 116 94 44 36 26 296
Chin‐Wen Chi Taiwan 9 87 0.7× 75 0.6× 179 1.9× 35 0.8× 23 0.6× 11 372
Laura Steel United States 7 120 1.0× 128 1.1× 184 2.0× 55 1.3× 51 1.4× 9 449
Dehong Zou China 11 115 1.0× 166 1.4× 143 1.5× 35 0.8× 16 0.4× 31 348
Xiang Sun China 9 60 0.5× 137 1.2× 206 2.2× 39 0.9× 19 0.5× 13 302
Julia Benzel Germany 9 92 0.8× 71 0.6× 115 1.2× 22 0.5× 28 0.8× 18 263
Jinguang Wang China 7 88 0.7× 64 0.6× 143 1.5× 49 1.1× 37 1.0× 22 312
Tieying Dong China 8 125 1.1× 120 1.0× 171 1.8× 39 0.9× 19 0.5× 9 324
Pascale Fisel Germany 9 161 1.4× 163 1.4× 357 3.8× 89 2.0× 65 1.8× 10 508
Tae Hyun Kim South Korea 10 90 0.8× 92 0.8× 156 1.7× 27 0.6× 11 0.3× 14 294
Junmei Jia China 13 83 0.7× 96 0.8× 182 1.9× 44 1.0× 19 0.5× 30 336

Countries citing papers authored by Takeshi Murata

Since Specialization
Citations

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

Fields of papers citing papers by Takeshi Murata

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Takeshi Murata

This figure shows the co-authorship network connecting the top 25 collaborators of Takeshi Murata. A scholar is included among the top collaborators of Takeshi Murata 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 Takeshi Murata. Takeshi Murata 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.
Suzuki, K., Masae Konno, Yuma Kawasaki, et al.. (2024). Light-driven anion-pumping rhodopsin with unique cytoplasmic anion-release mechanism. Journal of Biological Chemistry. 300(10). 107797–107797.
2.
Shimoi, Tatsunori, Ayumi Saito, Yuki Kojima, et al.. (2023). Discordance in PD-L1 expression using 22C3 and SP142 assays between primary and metastatic triple-negative breast cancer. Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin. 483(6). 855–863. 5 indexed citations
4.
Murata, Takeshi, Masayuki Yoshida, Sho Shiino, et al.. (2023). A prediction model for distant metastasis after isolated locoregional recurrence of breast cancer. Breast Cancer Research and Treatment. 199(1). 57–66. 5 indexed citations
5.
Murata, Takeshi, Masayuki Yoshida, Sho Shiino, et al.. (2023). Prognostic impact of HER2-low positivity in patients with HR-positive, HER2-negative, node-positive early breast cancer. Scientific Reports. 13(1). 19669–19669. 4 indexed citations
7.
Yazaki, Shu, Roberto Salgado, Tatsunori Shimoi, et al.. (2022). Impact of adjuvant chemotherapy and radiotherapy on tumour-infiltrating lymphocytes and PD-L1 expression in metastatic breast cancer. British Journal of Cancer. 128(4). 568–575. 9 indexed citations
10.
Yoshida, Masayuki, et al.. (2022). A case of ALK-positive histiocytosis with multiple lesions in the unilateral breast. International Journal of Surgery Case Reports. 97(C). 107435–107435. 3 indexed citations
11.
Murata, Takeshi, Sho Shiino, Kenjiro Jimbo, et al.. (2020). Development and Validation of a Preoperative Scoring System to Distinguish Between Nonadvanced and Advanced Axillary Lymph Node Metastasis in Patients With Early-stage Breast Cancer. Clinical Breast Cancer. 21(4). e302–e311. 10 indexed citations
12.
Jimbo, Kenjiro, Takayuki Kinoshita, Takeshi Murata, et al.. (2019). Prediction score model for non-sentinel and four or more nodal metastases using a combined method of one-step nucleic acid amplification and histology in sentinel node-positive breast cancer patients. European Journal of Surgical Oncology. 46(4). 516–521. 6 indexed citations
13.
Murata, Takeshi, Miku Kaneko, Sana Ota, et al.. (2019). Salivary metabolomics with alternative decision tree-based machine learning methods for breast cancer discrimination. Breast Cancer Research and Treatment. 177(3). 591–601. 69 indexed citations
14.
Takayama, Shin, Kaishi Satomi, Masayuki Yoshida, et al.. (2019). Spontaneous regression of occult breast cancer with axillary lymph node metastasis. International Journal of Surgery Case Reports. 63(C). 75–79. 7 indexed citations
15.
Matsumoto, Akiko, Hiromitsu Jinno, Takeshi Murata, et al.. (2014). Prognostic implications of receptor discordance between primary and recurrent breast cancer. International Journal of Clinical Oncology. 20(4). 701–708. 29 indexed citations
16.
Nagayama, Aiko, Tetsu Hayashida, Hiromitsu Jinno, et al.. (2014). Comparative Effectiveness of Neoadjuvant Therapy for HER2–Positive Breast Cancer: A Network Meta-Analysis. JNCI Journal of the National Cancer Institute. 106(9). 57 indexed citations
17.
Jinno, Hiromitsu, Takeshi Murata, Makoto Sunamura, et al.. (2014). Identification of Breast Cancer-Specific Signatures in Saliva Metabolites Using Capillary Electrophoresis Mass Spectrometry. Annals of Oncology. 25. iv407–iv407.
18.
Irie, Yoshifumi, et al.. (2007). Toki‐to protects dopaminergic neurons in the substantia nigra from neurotoxicity of MPTP in mice. Phytotherapy Research. 21(9). 868–873. 15 indexed citations
19.
Murata, Takeshi, Takuro Ariga, M Oshima, & T. Miyatake. (1978). Characterization of trimethylsilyl derivatives of cerebrosides by direct inlet-chemical ionization mass spectrometry.. Journal of Lipid Research. 19(3). 370–374. 15 indexed citations
20.
Oshima, Mieko, Toshio Ariga, & Takeshi Murata. (1977). Combined gas chromatography-chemical ionization mass spectrometry of sphingolipids. I. Glucosyl sphingosine, ceramides and cerebrosides of the spleen in Gaucher's disease. Chemistry and Physics of Lipids. 19(4). 289–299. 14 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026