Osteoimmunology: The Conceptual Framework Unifying the Immune and Skeletal Systems

411 indexed citations

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This paper, published in 2017, received 411 indexed citations. Written by Kazuo Okamoto, Tomoki Nakashima, Masahiro Shinohara, Takako Negishi‐Koga, Noriko Komatsu, Asuka Terashima, Shinichiro Sawa, Takeshi Nitta and Hiroshi Takayanagi covering the research area of Molecular Biology, Cancer Research and Oncology. It is primarily cited by scholars working on Molecular Biology (256 citations), Oncology (119 citations) and Immunology (108 citations). Published in Physiological Reviews.

Countries where authors are citing Osteoimmunology: The Conceptual Framework Unifying the Immune and Skeletal Systems

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This map shows the geographic impact of Osteoimmunology: The Conceptual Framework Unifying the Immune and Skeletal Systems. 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 Osteoimmunology: The Conceptual Framework Unifying the Immune and Skeletal Systems with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Osteoimmunology: The Conceptual Framework Unifying the Immune and Skeletal Systems more than expected).

Fields of papers citing Osteoimmunology: The Conceptual Framework Unifying the Immune and Skeletal Systems

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Osteoimmunology: The Conceptual Framework Unifying the Immune and Skeletal Systems. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Osteoimmunology: The Conceptual Framework Unifying the Immune and Skeletal Systems.

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/10.1152/physrev.00036.2016.

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