3D tumor spheroids as in vitro models to mimic in vivo human solid tumors resistance to therapeutic drugs

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This paper, published in 1950, received 527 indexed citations. Written by Andreia S. Barros, Elisabete C. Costa, André F. Moreira and Ilídio J. Correia covering the research area of Oncology, Cancer Research and Biomedical Engineering. It is primarily cited by scholars working on Biomedical Engineering (287 citations), Oncology (236 citations) and Molecular Biology (154 citations). Published in Biotechnology and Bioengineering.

Countries where authors are citing 3D tumor spheroids as in vitro models to mimic in vivo human solid tumors resistance to therapeutic drugs

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This map shows the geographic impact of 3D tumor spheroids as in vitro models to mimic in vivo human solid tumors resistance to therapeutic drugs. 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 3D tumor spheroids as in vitro models to mimic in vivo human solid tumors resistance to therapeutic drugs with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites 3D tumor spheroids as in vitro models to mimic in vivo human solid tumors resistance to therapeutic drugs more than expected).

Fields of papers citing 3D tumor spheroids as in vitro models to mimic in vivo human solid tumors resistance to therapeutic drugs

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of 3D tumor spheroids as in vitro models to mimic in vivo human solid tumors resistance to therapeutic drugs. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the 3D tumor spheroids as in vitro models to mimic in vivo human solid tumors resistance to therapeutic drugs.

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/10.1002/bit.26845.

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