Beyond 2D cell cultures: how 3D models are changing the <i>in vitro</i> study of ovarian cancer and how to make the most of them
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Autores:
Marilisa Cortesi, Kristina Warton, Caroline E. Ford
Publicado en:
PeerJ, Edición 12, 2024, Página(s) e17603, ISSN 2167-8359
Editor:
PeerJ
DOI:
10.7717/peerj.17603
Author Correction: A comparative analysis of 2D and 3D experimental data for the identification of the parameters of computational models
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Autores:
Marilisa Cortesi, Dongli Liu, Christine Yee, Deborah J. Marsh, Caroline E. Ford
Publicado en:
Scientific Reports, Edición 14, 2024, ISSN 2045-2322
Editor:
Nature Publishing Group
DOI:
10.1038/s41598-023-50403-x
A comparative analysis of 2D and 3D experimental data for the identification of the parameters of computational models
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Autores:
Cortesi M., Liu D., Yee C., Marsh D., and Ford C
Publicado en:
Scientific Reports, 2023, ISSN 2045-2322
Editor:
Nature Publishing Group
DOI:
10.1038/s41598-023-42486-3
Driving cell response through deep learning, a study in simulated 3D cell cultures
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Autores:
Marilisa Cortesi, Emanuele Giordano
Publicado en:
Heliyon, Edición 10, 2024, Página(s) e29395, ISSN 2405-8440
Editor:
Cell Press
DOI:
10.1016/j.heliyon.2024.e29395
Accurate Identification of Cancer Cells in Complex Pre‐Clinical Models Using a Deep‐Learning Neural Network: A Transfection‐Free Approach
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Autores:
Marilisa Cortesi, Dongli Liu, Elyse Powell, Ellen Barlow, Kristina Warton, Caroline E. Ford
Publicado en:
Advanced Biology, 2024, ISSN 2701-0198
Editor:
Wiley
DOI:
10.1002/adbi.202400034
