Koichi Murashita

643 total citations
38 papers, 355 citations indexed

About

Koichi Murashita is a scholar working on Physiology, Molecular Biology and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Koichi Murashita has authored 38 papers receiving a total of 355 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Physiology, 9 papers in Molecular Biology and 7 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Koichi Murashita's work include Gut microbiota and health (8 papers), Physical Activity and Health (5 papers) and Nutritional Studies and Diet (3 papers). Koichi Murashita is often cited by papers focused on Gut microbiota and health (8 papers), Physical Activity and Health (5 papers) and Nutritional Studies and Diet (3 papers). Koichi Murashita collaborates with scholars based in Japan, Italy and Ireland. Koichi Murashita's co-authors include Shigeyuki Nakaji, Kazushige Ihara, Seiya Imoto, Kaori Sawada, Masanori Kakuta, Itoyo Tokuda, Eiichiro Uchino, Shigeyuki Nakaji, Takanori Hasegawa and Yasushi Okuno and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Koichi Murashita

31 papers receiving 351 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Koichi Murashita Japan 11 147 138 66 53 27 38 355
Francisco J. Muñoz‐Torres Puerto Rico 10 129 0.9× 45 0.3× 185 2.8× 86 1.6× 4 0.1× 16 391
Rena Zelig United States 10 103 0.7× 12 0.1× 96 1.5× 44 0.8× 19 0.7× 38 315
Nicoletta Cerundolo Italy 11 270 1.8× 183 1.3× 6 0.1× 43 0.8× 15 0.6× 29 598
Denzil P. Mathew United States 6 269 1.8× 90 0.7× 14 0.2× 72 1.4× 30 1.1× 12 514
Małgorzata Godala Poland 9 87 0.6× 43 0.3× 54 0.8× 45 0.8× 29 1.1× 32 331
Misuzu Sato Japan 16 337 2.3× 31 0.2× 401 6.1× 86 1.6× 131 4.9× 33 713
Akane Miki Japan 9 280 1.9× 32 0.2× 4 0.1× 97 1.8× 26 1.0× 12 362
Kulapong Jayanama Thailand 10 368 2.5× 76 0.6× 10 0.2× 142 2.7× 4 0.1× 20 552
Deborah Carrera Italy 9 118 0.8× 53 0.4× 3 0.0× 99 1.9× 7 0.3× 17 306
Mohammad Ali Bayani Iran 9 65 0.4× 58 0.4× 39 0.6× 27 0.5× 1 0.0× 28 284

Countries citing papers authored by Koichi Murashita

Since Specialization
Citations

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

Fields of papers citing papers by Koichi Murashita

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Koichi Murashita

This figure shows the co-authorship network connecting the top 25 collaborators of Koichi Murashita. A scholar is included among the top collaborators of Koichi Murashita 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 Koichi Murashita. Koichi Murashita 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
2.
Sato, Satoshi, Daisuke Chinda, Katsuhiro Mikami, et al.. (2025). Four-Year Longitudinal Epidemiological Study on the Association Between a Multi-Item Saliva Testing System and Oral and Gut Microbiota. Microorganisms. 13(11). 2483–2483.
3.
Fujimoto, Kenji, Eiichiro Uchino, Ken Itoh, et al.. (2025). Network analysis reveals causal relationships among individual background risk factors leading to influenza susceptibility. Scientific Reports. 15(1). 30721–30721.
4.
Ozato, Naoki, Kenta Mori, Hiromitsu Kawada, et al.. (2025). Correction: Effect of visceral fat on onset of metabolic syndrome. Scientific Reports. 15(1). 34820–34820. 1 indexed citations
5.
Kinoshita, Keita, Naoki Ozato, Tohru Yamaguchi, et al.. (2025). Association of the gut microbiota with type 2 diabetes: Links to disease and remission in the Japanese population. Journal of Diabetes Investigation. 16(7). 1315–1324. 2 indexed citations
6.
Ozato, Naoki, Kenta Mori, Hiromitsu Kawada, et al.. (2025). Effect of visceral fat on onset of metabolic syndrome. Scientific Reports. 15(1). 19012–19012.
7.
Yamauchi, T., Hiroyuki Suganuma, Shigenori Suzuki, et al.. (2023). Definition of a Dietary Pattern Expressing the Intake of Vegetables and Fruits and Its Association with Intestinal Microbiota. Nutrients. 15(9). 2104–2104. 2 indexed citations
8.
Yang, Yichi, Kyi Mar Wai, Tao Jiang, et al.. (2023). The Association between Gut Microbiota and Depression in the Japanese Population. Microorganisms. 11(9). 2286–2286. 7 indexed citations
9.
Kinoshita, Keita, Naoki Ozato, Tohru Yamaguchi, et al.. (2023). Association of the COVID-19 pandemic with changes in objectively measured sedentary behaviour and adiposity. International Journal of Obesity. 47(5). 375–381. 12 indexed citations
10.
Nakamura, Kazuki, Eiichiro Uchino, Noriaki Sato, et al.. (2023). Individual health-disease phase diagrams for disease prevention based on machine learning. Journal of Biomedical Informatics. 144. 104448–104448. 5 indexed citations
12.
Hasegawa, Takanori, Masanori Kakuta, Rui Yamaguchi, et al.. (2022). Impact of salivary and pancreatic amylase gene copy numbers on diabetes, obesity, and functional profiles of microbiome in Northern Japanese population. Scientific Reports. 12(1). 7 indexed citations
13.
Kinoshita, Keita, Naoki Ozato, Tohru Yamaguchi, et al.. (2022). Association between visceral fat and influenza infection in Japanese adults: A population-based cross-sectional study. PLoS ONE. 17(7). e0272059–e0272059. 1 indexed citations
14.
Wai, Kyi Mar, Akira Kanda, Masataka Ando, et al.. (2021). Low Level of Serum Cadmium in Relation to Blood Pressures Among Japanese General Population. Biological Trace Element Research. 200(1). 67–75. 8 indexed citations
15.
Wai, Kyi Mar, Kaori Sawada, Ken Itoh, et al.. (2021). Telomere Length and Arterial Stiffness Reflected by Brachial–Ankle Pulse Wave Velocity: A Population-Based Cross-Sectional Study. Journal of Personalized Medicine. 11(12). 1278–1278. 4 indexed citations
16.
Hasegawa, Takanori, Rui Yamaguchi, Masanori Kakuta, et al.. (2021). Application of state-space model with skew-t measurement noise to blood test value prediction. Applied Mathematical Modelling. 100. 365–378. 1 indexed citations
17.
Nakamura, Kazuki, Ryosuke Kojima, Eiichiro Uchino, et al.. (2021). Health improvement framework for actionable treatment planning using a surrogate Bayesian model. Nature Communications. 12(1). 3088–3088. 8 indexed citations
18.
Wai, Kyi Mar, Kaori Sawada, Mika Kumagai, et al.. (2020). Relationship between Selected Trace Elements and Hematological Parameters among Japanese Community Dwellers. Nutrients. 12(6). 1615–1615. 13 indexed citations
19.
Kakuta, Masanori, Takanori Hasegawa, Rui Yamaguchi, et al.. (2020). Metagenomic analysis of bacterial species in tongue microbiome of current and never smokers. npj Biofilms and Microbiomes. 6(1). 39 indexed citations
20.
Kakuta, Masanori, Takanori Hasegawa, Rui Yamaguchi, et al.. (2020). Metagenomic profiling of gut microbiome in early chronic kidney disease. Nephrology Dialysis Transplantation. 36(9). 1675–1684. 44 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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