Serotonin regulates pancreatic beta cell mass during pregnancy
- Journal
- Nature Medicine
In The Last Decade
doi.org/10.1038/nm.2173 →Countries where authors are citing Serotonin regulates pancreatic beta cell mass during pregnancy
This map shows the geographic impact of Serotonin regulates pancreatic beta cell mass during pregnancy. 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 Serotonin regulates pancreatic beta cell mass during pregnancy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Serotonin regulates pancreatic beta cell mass during pregnancy more than expected).
Fields of papers citing Serotonin regulates pancreatic beta cell mass during pregnancy
This network shows the impact of Serotonin regulates pancreatic beta cell mass during pregnancy. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Serotonin regulates pancreatic beta cell mass during pregnancy.
About Serotonin regulates pancreatic beta cell mass during pregnancy
This paper, published in 2010, received 455 indexed citations . Written by Hail Kim, Yukiko Toyofuku, Francis C. Lynn, Eric Chak, Toyoyoshi Uchida, Hiroki Mizukami, Yoshio Fujitani, Ryuzo Kawamori, Takeshi Miyatsuka and Yasuhiro Kosaka covering the research area of Genetics, Surgery and Endocrinology, Diabetes and Metabolism. It is primarily cited by scholars working on Surgery (286 citations), Genetics (166 citations), Endocrinology, Diabetes and Metabolism (158 citations), Molecular Biology (131 citations) and Pediatrics, Perinatology and Child Health (92 citations). Published in Nature Medicine.
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.
This paper is also available at doi.org/10.1038/nm.2173.