Mayumi Kamada

1.5k total citations · 1 hit paper
39 papers, 1.0k citations indexed

About

Mayumi Kamada is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Mayumi Kamada has authored 39 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 8 papers in Cancer Research and 6 papers in Oncology. Recurrent topics in Mayumi Kamada's work include Protein Structure and Dynamics (9 papers), Cancer Genomics and Diagnostics (8 papers) and Bioinformatics and Genomic Networks (7 papers). Mayumi Kamada is often cited by papers focused on Protein Structure and Dynamics (9 papers), Cancer Genomics and Diagnostics (8 papers) and Bioinformatics and Genomic Networks (7 papers). Mayumi Kamada collaborates with scholars based in Japan, United States and Australia. Mayumi Kamada's co-authors include Yasushi Okuno, Naoya Fujita, Mitsugu Araki, Naohiko Inase, Ken Uchibori, Shigeo Sato, Ryohei Katayama, Tatsuya Akutsu, Ernst‐Walter Knapp and S. S. Koide and has published in prestigious journals such as Nature Communications, Journal of Clinical Oncology and PLoS ONE.

In The Last Decade

Mayumi Kamada

35 papers receiving 1.0k citations

Hit Papers

Brigatinib combined with anti-EGFR antibody overcomes osi... 2017 2026 2020 2023 2017 100 200 300

Peers

Mayumi Kamada
David A. Moore United Kingdom
Russell B. Myers United States
Qiong Zou China
Mayumi Kamada
Citations per year, relative to Mayumi Kamada Mayumi Kamada (= 1×) peers Takayo Ota

Countries citing papers authored by Mayumi Kamada

Since Specialization
Citations

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

Fields of papers citing papers by Mayumi Kamada

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mayumi Kamada

This figure shows the co-authorship network connecting the top 25 collaborators of Mayumi Kamada. A scholar is included among the top collaborators of Mayumi Kamada 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 Mayumi Kamada. Mayumi Kamada 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.
Kamada, Mayumi & Yosuke Kawai. (2025). Clinical Variant Databases and Machine Learning Prediction Supporting Genomic Medicine. Methods in molecular biology. 2963. 147–158.
2.
Kamada, Mayumi, et al.. (2023). Network-based prediction approach for cancer-specific driver missense mutations using a graph neural network. BMC Bioinformatics. 24(1). 383–383. 3 indexed citations
3.
Yamada, Atsushi, Yoshihiro Yamamoto, Sachiko Minamiguchi, et al.. (2022). Clinicopathological and molecular characterization of deficient mismatch repair colorectal cancer. Human Pathology. 130. 1–9. 2 indexed citations
4.
Ohashi, Shinya, Mayumi Kamada, Tomoki Saito, et al.. (2019). Combination treatment with highly bioavailable curcumin and NQO1 inhibitor exhibits potent antitumor effects on esophageal squamous cell carcinoma. Journal of Gastroenterology. 54(8). 687–698. 28 indexed citations
5.
Kamada, Mayumi, Masahiko Nakatsui, Ryosuke Kojima, et al.. (2019). MGeND: an integrated database for Japanese clinical and genomic information. Human Genome Variation. 6(1). 53–53. 10 indexed citations
6.
Kou, Tadayuki, Masashi Kanai, Mayumi Kamada, et al.. (2018). A Platform for Comprehensive Genomic Profiling in Human Cancers and Pharmacogenomics Therapy Selection. Methods in molecular biology. 1825. 413–424.
7.
Uchibori, Ken, Naohiko Inase, Mitsugu Araki, et al.. (2017). Brigatinib combined with anti-EGFR antibody overcomes osimertinib resistance in EGFR-mutated non-small-cell lung cancer. Nature Communications. 8(1). 14768–14768. 329 indexed citations breakdown →
8.
Murakami, Ryusuke, Noriomi Matsumura, J.B. Brown, et al.. (2017). Exome Sequencing Landscape Analysis in Ovarian Clear Cell Carcinoma Shed Light on Key Chromosomal Regions and Mutation Gene Networks. American Journal Of Pathology. 187(10). 2246–2258. 99 indexed citations
9.
Kou, Tadayuki, Masashi Kanai, Yoshihiro Yamamoto, et al.. (2017). Clinical sequencing using a next‐generation sequencing‐based multiplex gene assay in patients with advanced solid tumors. Cancer Science. 108(7). 1440–1446. 45 indexed citations
10.
Kondo, Tomohiro, Masashi Kanai, Tadayuki Kou, et al.. (2017). Impact of BRCAness on the efficacy of oxaliplatin-based chemotherapy in patients with unresectable pancreatic cancer.. Journal of Clinical Oncology. 35(4_suppl). 250–250. 4 indexed citations
11.
Kamada, Mayumi, et al.. (2015). Whole-Genome Sequencing and Comparative Genome Analysis of Bacillus subtilis Strains Isolated from Non-Salted Fermented Soybean Foods. PLoS ONE. 10(10). e0141369–e0141369. 36 indexed citations
12.
Kamada, Mayumi, et al.. (2014). Prediction of Protein-Protein Interaction Strength Using Domain Features with Supervised Regression. The Scientific World JOURNAL. 2014. 1–7. 10 indexed citations
13.
Kamada, Mayumi, et al.. (2014). Whole Genome Complete Resequencing of Bacillus subtilis Natto by Combining Long Reads with High-Quality Short Reads. PLoS ONE. 9(10). e109999–e109999. 38 indexed citations
14.
Kamada, Mayumi, et al.. (2013). Inferring Strengths of Protein-Protein Interactions Using Support Vector Regression. 2013(1). 1–4. 2 indexed citations
15.
Kamada, Mayumi, et al.. (2011). Prediction using step-wise L1, L2 regularization and feature selection for small data sets with large number of features. BMC Bioinformatics. 12(1). 412–412. 93 indexed citations
16.
Hayashida, Morihiro, Mayumi Kamada, Jiangning Song, & Tatsuya Akutsu. (2011). Conditional random field approach to prediction of protein-protein interactions using domain information. BMC Systems Biology. 5(Suppl 1). S8–S8. 31 indexed citations
17.
Bandivdekar, A. H., et al.. (2004). Studies with Synthetic Peptides of 80 kDa Human Sperm Antigen (80 kDa HSA). American Journal of Reproductive Immunology. 51(2). 106–111. 11 indexed citations
18.
Koide, S. S., Lingling Wang, & Mayumi Kamada. (2000). Antisperm Antibodies Associated with Infertility: Properties and Encoding Genes of Target Antigens. Proceedings of The Society for Experimental Biology and Medicine. 224(3). 123–132. 50 indexed citations
19.
Sakurai, Makoto, H. Okamura, Makoto Watanabe, et al.. (1998). Upgraded IR beamline at UVSOR. Journal of Synchrotron Radiation. 5(3). 578–580. 4 indexed citations
20.
Iida, Aritoshi, Motoaki Seki, Mayumi Kamada, Yasuyuki Yamada, & Hiromichi Morikawa. (1990). Gene delivery into cultured plant cells by DNA-coated gold particles accelerated by a pneumatic particle gun. Theoretical and Applied Genetics. 80(6). 813–816. 52 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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