Mika Sakamoto

424 total citations
17 papers, 136 citations indexed

About

Mika Sakamoto is a scholar working on Molecular Biology, Genetics and Immunology. According to data from OpenAlex, Mika Sakamoto has authored 17 papers receiving a total of 136 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 3 papers in Genetics and 3 papers in Immunology. Recurrent topics in Mika Sakamoto's work include Genomics and Phylogenetic Studies (4 papers), Aquaculture disease management and microbiota (2 papers) and EEG and Brain-Computer Interfaces (2 papers). Mika Sakamoto is often cited by papers focused on Genomics and Phylogenetic Studies (4 papers), Aquaculture disease management and microbiota (2 papers) and EEG and Brain-Computer Interfaces (2 papers). Mika Sakamoto collaborates with scholars based in Japan, Australia and Austria. Mika Sakamoto's co-authors include Yasukazu Nakamura, Takako Mochizuki, Yasuhiro Tanizawa, Yasushi Okada, Takumi Chinen, Daisuke Takao, Michiko Endo, Mariko Esumi, Yasuaki Tokuhashi and Akio Yoshida and has published in prestigious journals such as PLoS ONE, Biochemical and Biophysical Research Communications and Molecular Biology of the Cell.

In The Last Decade

Mika Sakamoto

15 papers receiving 136 citations

Peers

Countries citing papers authored by Mika Sakamoto

Since Specialization

Citations

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

Fields of papers citing papers by Mika Sakamoto

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mika Sakamoto

This figure shows the co-authorship network connecting the top 25 collaborators of Mika Sakamoto. A scholar is included among the top collaborators of Mika Sakamoto 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 Mika Sakamoto. Mika Sakamoto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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17 of 17 papers shown

#	Work	Indexed citations
1	Resveratrol, a food-derived polyphenol, promotes Melanosomal degradation in skin fibroblasts through coordinated activation of autophagy, lysosomal, and antioxidant pathways 2025 ·Journal of Functional Foods ·(unknown), (unknown), Mayuko Koreishi, Mika Sakamoto, Yoshimasa Nakamura, (unknown), Yoshio Tsujino, Ayano Satoh	1
2	MarpolBase: genome database for Marchantia polymorpha featuring high quality reference genome sequences 2025 ·Plant and Cell Physiology ·Yasuhiro Tanizawa, Takako Mochizuki, Masaru Yagura, Mika Sakamoto, Takatomo Fujisawa, Shogo Kawamura, (unknown), Shohei Yamaoka, Ryuichi Nishihama, John L. Bowman, Frédéric Berger, Katsuyuki T. Yamato, Takayuki Kohchi, Yasukazu Nakamura	0
3	MedakaBase as a unified genomic resource platform for medaka fish biology 2025 ·DNA Research ·Kenji Morikami, Yasuhiro Tanizawa, Masaru Yagura, Mika Sakamoto, Shoko Kawamoto, Yasukazu Nakamura, Katsushi Yamaguchi, Shuji Shigenobu, Kiyoshi Naruse, Satoshi Ansai, Shigehiro Kuraku	1
4	Chromosome-scale assembly with improved annotation provides insights into breed-wide genomic structure and diversity in domestic cats 2024 ·Journal of Advanced Research ·Yuki Matsumoto, Claire Chung, Sachiko Isobe, Mika Sakamoto, Xiao Lin, Ting‐Fung Chan, Hideki Hirakawa, Genki Ishihara, Hon‐Ming Lam, Shinobu Nakayama, S. Sasamoto, Yasuhiro Tanizawa, Akiko Watanabe, Kei Watanabe, Masaru Yagura, Yoshihito Niimura, Yasukazu Nakamura	2
5	Fucosyltransferase 8 (FUT8) and core fucose expression in oxidative stress response 2023 ·PLoS ONE ·(unknown), Mika Sakamoto, Mayuko Koreishi, Yoshio Tsujino, Ayano Satoh	6
6	Best Practices for Comprehensive Annotation of Neuropeptides of Gryllus bimaculatus 2023 ·Insects ·Takako Mochizuki, Mika Sakamoto, Yasuhiro Tanizawa, (unknown), Zhen Zhu, Yi Zhou, Keisuke Fukumura, Shinji Nagata, Yasukazu Nakamura	0
7	Gene expression profiles associated with early relapse during first remission induction in canine multicentric high-grade B-cell lymphoma 2023 ·Journal of Veterinary Medical Science ·(unknown), (unknown), Yuko Goto‐Koshino, (unknown), Mika Sakamoto, Takako Mochizuki, (unknown), T. Kobayashi, Asuka Setoguchi, Y Shizuta, Takuya Mizuno, (unknown), (unknown), Hajime Tsujimoto, (unknown), (unknown), Yasukazu Nakamura, Hirotaka Tomiyasu	2
8	A practical assembly guideline for genomes with various levels of heterozygosity 2023 ·Briefings in Bioinformatics ·Takako Mochizuki, Mika Sakamoto, Yasuhiro Tanizawa, Takuro Nakayama, Goro Tanifuji, Ryoma Kamikawa, Yasukazu Nakamura	6
9	Large-scale epidemiological study on feline autosomal dominant polycystic kidney disease and identification of novel PKD1 gene variants 2023 ·Journal of Feline Medicine and Surgery ·(unknown), (unknown), (unknown), Yuki Matsumoto, Mika Sakamoto, Yasuhiro Tanizawa, Yasukazu Nakamura, Tomohiro Yonezawa, Yasuyuki Momoi, Shingo Maeda	2
10	A highly contiguous genome assembly of red perilla ( Perilla frutescens ) domesticated in Japan 2022 ·DNA Research ·Keita Tamura, Mika Sakamoto, Yasuhiro Tanizawa, Takako Mochizuki, (unknown), (unknown), (unknown), (unknown), Yasukazu Nakamura, Hidemasa Bono	11
11	MarpolBase Expression: A Web-Based, Comprehensive Platform for Visualization and Analysis of Transcriptomes in the Liverwort Marchantia polymorpha 2022 ·Plant and Cell Physiology ·Shogo Kawamura, Facundo Romani, Masaru Yagura, Takako Mochizuki, Mika Sakamoto, Shohei Yamaoka, Ryuichi Nishihama, Yasukazu Nakamura, Katsuyuki T. Yamato, John L. Bowman, Takayuki Kohchi, Yasuhiro Tanizawa	34
12	Abnormal heart rate variability during non-REM sleep and postictal generalized EEG suppression in focal epilepsy 2022 ·Clinical Neurophysiology ·Mika Sakamoto, Kazutaka Jin, (unknown), (unknown), Nobukazu Nakasato	1
13	Determination of language areas in patients with epilepsy using the super-selective Wada test 2022 ·IBRO Neuroscience Reports ·(unknown), (unknown), Hiroaki Hosokawa, (unknown), (unknown), (unknown), (unknown), (unknown), Kazutaka Jin, Mákoto Ishida, Takafumi Sato, Mika Sakamoto, Kuniyasu Niizuma, Teiji Tominaga, Nobukazu Nakasato, Kyoko Suzuki	6
14	Robust classification of cell cycle phase and biological feature extraction by image-based deep learning 2020 ·Molecular Biology of the Cell ·(unknown), Mika Sakamoto, Takumi Chinen, Yasushi Okada, Daisuke Takao	25
15	Relationship between conformation shift and disease related variation sites in ATP-binding cassette transporter proteins 2019 ·Biophysics and Physicobiology ·Mika Sakamoto, Hirofumi Suzuki, Kei Yura	4
16	Passive cigarette smoking changes the circadian rhythm of clock genes in rat intervertebral discs 2015 ·Journal of Orthopaedic Research® ·(unknown), Mariko Esumi, Mika Sakamoto, Michiko Endo, (unknown), (unknown), Akio Yoshida, Yasuaki Tokuhashi	32
17	Multiple γ-glutamylation: A novel type of post-translational modification in a diapausing Artemia cyst protein 2010 ·Biochemical and Biophysical Research Communications ·M. Hasegawa, Yuka Ikeda, (unknown), Mika Sakamoto, (unknown), Susumu Tsunasawa, Toshio Uchiumi, Shoji Odani	3

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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