Experimental Diabetes Research

274 papers and 11.2k indexed citations i.

About

The 274 papers published in Experimental Diabetes Research in the last decades have received a total of 11.2k indexed citations. Papers published in Experimental Diabetes Research usually cover Molecular Biology (100 papers), Endocrinology, Diabetes and Metabolism (87 papers) and Physiology (67 papers) specifically the topics of Pancreatic Islet Dysfunction and Regeneration (53 papers), Metabolism, Diabetes, and Cancer (35 papers) and Adipose Tissue and Metabolism (29 papers). The most active scholars publishing in Experimental Diabetes Research are Hirofumi Noguchi, Mikako Obika, Kabirou Moutaïrou, Akadiri Yessoufou, Rebecca Hutcheson, Petra Ročić, Michael D. Williams, Geraldine M. Mitchell, Lu Cai and Zhongmin Alex.

In The Last Decade

Fields of papers published in Experimental Diabetes Research

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Experimental Diabetes Research. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Experimental Diabetes Research.

Countries where authors publish in Experimental Diabetes Research

Since Specialization
Citations

This map shows the geographic impact of research published in Experimental Diabetes 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 papers published in Experimental Diabetes Research with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Experimental Diabetes Research 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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