Maya Kudo

12 papers and 307 indexed citations i.

About

Maya Kudo is a scholar working on Physiology, Epidemiology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Maya Kudo has authored 12 papers receiving a total of 307 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Physiology, 4 papers in Epidemiology and 3 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Maya Kudo’s work include Adipose Tissue and Metabolism (5 papers), Adipokines, Inflammation, and Metabolic Diseases (2 papers) and Pancreatic Islet Dysfunction and Regeneration (2 papers). Maya Kudo is often cited by papers focused on Adipose Tissue and Metabolism (5 papers), Adipokines, Inflammation, and Metabolic Diseases (2 papers) and Pancreatic Islet Dysfunction and Regeneration (2 papers). Maya Kudo collaborates with scholars based in Japan and China. Maya Kudo's co-authors include Ming Gao, Tonghua Liu, Misa Hayashi, Lingling Qin, Li Wu, You Wu, Chengfei Zhang, Harumi Takahashi, Susumu Seino and Kohtaro Minami and has published in prestigious journals such as PLoS ONE, Frontiers in Pharmacology and Frontiers in Endocrinology.

In The Last Decade

Co-authorship network of co-authors of Maya Kudo i

Fields of papers citing papers by Maya Kudo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Maya Kudo

Since Specialization
Citations

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