Reengineering chimeric antigen receptor T cells for targeted therapy of autoimmune disease

512 indexed citations

Abstract

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About

This paper, published in 2016, received 512 indexed citations. Written by Christoph T. Ellebrecht, Vijay Bhoj, Arben Nace, Eun Jung Choi, Xuming Mao, Michael Jeffrey Cho, Giovanni Di Zenzo, Antonio Lanzavecchia, John T. Seykora and George Cotsarelis covering the research area of Oncology, Biotechnology and Biomedical Engineering. It is primarily cited by scholars working on Oncology (282 citations), Immunology (205 citations) and Pathology and Forensic Medicine (115 citations). Published in Science.

Countries where authors are citing Reengineering chimeric antigen receptor T cells for targeted therapy of autoimmune disease

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This map shows the geographic impact of Reengineering chimeric antigen receptor T cells for targeted therapy of autoimmune disease. 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 Reengineering chimeric antigen receptor T cells for targeted therapy of autoimmune disease with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Reengineering chimeric antigen receptor T cells for targeted therapy of autoimmune disease more than expected).

Fields of papers citing Reengineering chimeric antigen receptor T cells for targeted therapy of autoimmune disease

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Reengineering chimeric antigen receptor T cells for targeted therapy of autoimmune disease. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Reengineering chimeric antigen receptor T cells for targeted therapy of autoimmune disease.

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/10.1126/science.aaf6756.

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