Aging Cell

3.0k papers and 155.1k indexed citations i.

About

The 3.0k papers published in Aging Cell in the last decades have received a total of 155.1k indexed citations. Papers published in Aging Cell usually cover Molecular Biology (1.5k papers), Physiology (1.2k papers) and Aging (768 papers) specifically the topics of Genetics, Aging, and Longevity in Model Organisms (768 papers), Telomeres, Telomerase, and Senescence (376 papers) and Mitochondrial Function and Pathology (280 papers). The most active scholars publishing in Aging Cell are Mark P. Mattson, Richard A. Miller, Thomas von Zglinicki, Gordon J. Lithgow, Anne Brunet, Linda Partridge, David G. Nicholls, Marc Tatar, Valter D. Longo and Judith Campisi.

In The Last Decade

Fields of papers published in Aging Cell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Aging Cell. 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 Aging Cell.

Countries where authors publish in Aging Cell

Since Specialization
Citations

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