Kotoe Katayama

1.2k total citations
30 papers, 303 citations indexed

About

Kotoe Katayama is a scholar working on Complementary and alternative medicine, Molecular Biology and Pharmacology. According to data from OpenAlex, Kotoe Katayama has authored 30 papers receiving a total of 303 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Complementary and alternative medicine, 10 papers in Molecular Biology and 10 papers in Pharmacology. Recurrent topics in Kotoe Katayama's work include Traditional Chinese Medicine Studies (10 papers), Pharmacological Effects of Natural Compounds (7 papers) and SARS-CoV-2 and COVID-19 Research (3 papers). Kotoe Katayama is often cited by papers focused on Traditional Chinese Medicine Studies (10 papers), Pharmacological Effects of Natural Compounds (7 papers) and SARS-CoV-2 and COVID-19 Research (3 papers). Kotoe Katayama collaborates with scholars based in Japan, United Kingdom and United States. Kotoe Katayama's co-authors include Seiya Imoto, Satoru Miyano, Rui Yamaguchi, Kenji Watanabe, K Munakata, Tetsuhiro Yoshino, Masaaki Kitajima, Kiyoshi Yamaguchi, Masaru Mimura and Michio Murakami and has published in prestigious journals such as Nature Communications, The Science of The Total Environment and Scientific Reports.

In The Last Decade

Kotoe Katayama

29 papers receiving 296 citations

Peers

Kotoe Katayama
Zhixin Huang China
Geliang Yang China
Lili Gong China
Yufei Yang China
Xianmei Zhou China
Tingting Chen China
Congying Song China
Alicia Evans South Africa
Zhixin Huang China
Kotoe Katayama
Citations per year, relative to Kotoe Katayama Kotoe Katayama (= 1×) peers Zhixin Huang

Countries citing papers authored by Kotoe Katayama

Since Specialization
Citations

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

Fields of papers citing papers by Kotoe Katayama

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kotoe Katayama

This figure shows the co-authorship network connecting the top 25 collaborators of Kotoe Katayama. A scholar is included among the top collaborators of Kotoe Katayama 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 Kotoe Katayama. Kotoe Katayama 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.
Nakamura, Yusuke, Kazuma Kiyotani, Seiya Imoto, et al.. (2024). Comparative analysis of the B cell receptor repertoire during relapse and remission in patients with multiple sclerosis. Clinical Immunology. 269. 110398–110398. 2 indexed citations
2.
Fukuhara, Shinichiro, T. Imanaka, Koichi Okada, et al.. (2024). KEAP1–NRF2 system regulates age‐related spermatogenesis dysfunction. Reproductive Medicine and Biology. 23(1). e12595–e12595. 4 indexed citations
3.
Yoshino, Tetsuhiro, Kotoe Katayama, Hiroaki HIKIAMI, et al.. (2024). Machine learning model for predicting the cold–heat pattern in Kampo medicine: a multicenter prospective observational study. Frontiers in Pharmacology. 15. 1412593–1412593.
4.
5.
Kawachi, Kae, Xiaoyan Tang, Rika Kasajima, et al.. (2023). Genetic analysis of low-grade adenosquamous carcinoma of the breast progressing to high-grade metaplastic carcinoma. Breast Cancer Research and Treatment. 202(3). 563–573. 3 indexed citations
6.
Suzuki, Masaki, Rika Kasajima, Tomoyuki Yokose, et al.. (2023). KMT2C expression and DNA homologous recombination repair factors in lung cancers with a high-grade fetal adenocarcinoma component. Translational Lung Cancer Research. 12(8). 1738–1751. 2 indexed citations
7.
Koyama, Takahiko, et al.. (2022). Cross-Border Transmissions of the Delta Substrain AY.29 During Tokyo Olympic and Paralympic Games. Frontiers in Microbiology. 13. 883849–883849. 5 indexed citations
8.
Katayama, Kotoe, et al.. (2022). Analyzing integrated network of methylation and gene expression profiles in lung squamous cell carcinoma. Scientific Reports. 12(1). 15799–15799. 4 indexed citations
9.
Shingaki, Sumito, Junji Koya, Mitsuhiro Yuasa, et al.. (2022). Tumor-promoting function and regulatory landscape of PD-L2 in B-cell lymphoma. Leukemia. 37(2). 492–496. 1 indexed citations
10.
Murakami, Michio, Fuminari Miura, Masaaki Kitajima, et al.. (2021). COVID-19 risk assessment at the opening ceremony of the Tokyo 2020 Olympic Games. Microbial Risk Analysis. 19. 100162–100162. 21 indexed citations
11.
Yoshino, Tetsuhiro, Kotoe Katayama, Hiroaki HIKIAMI, et al.. (2020). Discrimination of prediction models between cold-heat and deficiency-excess patterns. Complementary Therapies in Medicine. 49. 102353–102353. 9 indexed citations
12.
Yoshino, Tetsuhiro, Kotoe Katayama, Rui Yamaguchi, et al.. (2019). Classification of patients with cold sensation by a review of systems database: A single-centre observational study. Complementary Therapies in Medicine. 45. 7–13. 3 indexed citations
13.
Katayama, Kotoe, Yoshimichi Nakatsu, Syuzo Kaneko, et al.. (2019). Replication stress triggers microsatellite destabilization and hypermutation leading to clonal expansion in vitro. Nature Communications. 10(1). 3925–3925. 32 indexed citations
14.
Yoshino, Tetsuhiro, Kotoe Katayama, Hiroaki HIKIAMI, et al.. (2019). Prediction of deficiency-excess pattern in Japanese Kampo medicine: Multi-centre data collection. Complementary Therapies in Medicine. 45. 228–233. 7 indexed citations
15.
Yoshino, Tetsuhiro, Kotoe Katayama, K Munakata, et al.. (2016). The Difference between the Two Representative Kampo Formulas for Treating Dysmenorrhea: An Observational Study. Evidence-based Complementary and Alternative Medicine. 2016(1). 3159617–3159617. 16 indexed citations
16.
Yoshino, Tetsuhiro, Kotoe Katayama, K Munakata, et al.. (2016). Predicting Japanese Kampo formulas by analyzing database of medical records: a preliminary observational study. BMC Medical Informatics and Decision Making. 16(1). 118–118. 5 indexed citations
17.
Yoshino, Tetsuhiro, Kotoe Katayama, K Munakata, et al.. (2014). Kampo Traditional Pattern Diagnosis and the Clustering Analysis of Patients with Cold Sensation. The Journal of Alternative and Complementary Medicine. 20(5). A47–A47. 1 indexed citations
18.
Katayama, Kotoe, Rui Yamaguchi, Seiya Imoto, Kenji Watanabe, & Satoru Miyano. (2014). Analysis of Questionnaire for Traditional Medicine and Development of Decision Support System. Evidence-based Complementary and Alternative Medicine. 2014(1). 974139–974139. 7 indexed citations
19.
Munakata, K, Kotoe Katayama, Rui Yamaguchi, et al.. (2014). Clinical Data Mining Related to the Japanese Kampo Concept “Hie” (Oversensitivity to Coldness) in Men and Pre‐ and Postmenopausal Women. Evidence-based Complementary and Alternative Medicine. 2014(1). 832824–832824. 15 indexed citations
20.
Yoshino, Tetsuhiro, Kotoe Katayama, K Munakata, et al.. (2013). Statistical Analysis ofHie(Cold Sensation) andHiesho(Cold Disorder) in Kampo Clinic. Evidence-based Complementary and Alternative Medicine. 2013. 1–8. 33 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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