Targeting cellular senescence prevents age-related bone loss in mice

819 indexed citations

Abstract

loading...

About

This paper, published in 2017, received 819 indexed citations. Written by Joshua N. Farr, Ming Xu, Megan Weivoda, David G. Monroe, Daniel G. Fraser, Jennifer L Onken, Jad Sfeir, Mikołaj Ogrodnik, Christine Hachfeld and Nathan K. LeBrasseur covering the research area of Cancer Research, Physiology and Immunology. It is primarily cited by scholars working on Physiology (423 citations), Molecular Biology (408 citations) and Immunology (165 citations). Published in Nature Medicine.

In The Last Decade

doi.org/10.1038/nm.4385 →

Countries where authors are citing Targeting cellular senescence prevents age-related bone loss in mice

Specialization
Citations

This map shows the geographic impact of Targeting cellular senescence prevents age-related bone loss in mice. 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 Targeting cellular senescence prevents age-related bone loss in mice with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Targeting cellular senescence prevents age-related bone loss in mice more than expected).

Fields of papers citing Targeting cellular senescence prevents age-related bone loss in mice

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Targeting cellular senescence prevents age-related bone loss in mice. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Targeting cellular senescence prevents age-related bone loss in mice.

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.4385.

Explore hit-papers with similar magnitude of impact

Rankless by CCL
2026