Mayu Ukai

45 papers and 586 indexed citations i.

About

Mayu Ukai is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Obstetrics and Gynecology. According to data from OpenAlex, Mayu Ukai has authored 45 papers receiving a total of 586 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Cellular and Molecular Neuroscience, 17 papers in Molecular Biology and 9 papers in Obstetrics and Gynecology. Recurrent topics in Mayu Ukai’s work include Neuropeptides and Animal Physiology (18 papers), Receptor Mechanisms and Signaling (15 papers) and Neurotransmitter Receptor Influence on Behavior (8 papers). Mayu Ukai is often cited by papers focused on Neuropeptides and Animal Physiology (18 papers), Receptor Mechanisms and Signaling (15 papers) and Neurotransmitter Receptor Influence on Behavior (8 papers). Mayu Ukai collaborates with scholars based in Japan, United States and Switzerland. Mayu Ukai's co-authors include Tsutomu Kameyama, S G Holtzman, T Kameyama, Jiro Itoh, Takayoshi Mamiya, Masato Yoshihara, Sho Tano, Michinori Mayama, Hidenori Oguchi and Yasuyuki Kishigami and has published in prestigious journals such as Annals of the New York Academy of Sciences, American Journal of Obstetrics and Gynecology and Journal of Pharmacology and Experimental Therapeutics.

In The Last Decade

Co-authorship network of co-authors of Mayu Ukai i

Fields of papers citing papers by Mayu Ukai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Mayu Ukai

Since Specialization
Citations

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

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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2025