Automated Bio-AFM Generation of Large Mechanome Data Set and Their Analysis by Machine Learning to Classify Cancerous Cell Lines-Reference-Cited by-同舟云学术

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Automated Bio-AFM Generation of Large Mechanome Data Set and Their Analysis by Machine Learning to Classify Cancerous Cell Lines

Published:2024-08-20 Issue:34 Volume:16 Page:44504-44517
ISSN:1944-8244
Container-title:ACS Applied Materials & Interfaces
language:en
Short-container-title:ACS Appl. Mater. Interfaces

Author:

Thomas - - Chemin Ophélie¹,Séverac Childérick¹²,Moumen Abderazzak¹,Martinez-Rivas Adrian³,Vieu Christophe¹,Le Lann Marie-Véronique¹,Trevisiol Emmanuelle¹⁴^ORCID,Dague Etienne¹^ORCID

Affiliation:

1. LAAS-CNRS, Université de Toulouse, CNRS, 31031 Toulouse, France

2. RESTORE Research Center, Université de Toulouse, INSERM, CNRS, EFS, ENVT, Université P. Sabatier, 31100 Toulouse, France

3. CIC, Instituto Politécnico Nacional (IPN), 07738 Mexico City, Mexico

4. TBI, Université de Toulouse, CNRS, INRAE, INSA, 31400 Toulouse, France

Funder

Agence Nationale de la Recherche

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acsami.4c09218

Reference63 articles.

1. Atomic Force Microscopy and pharmacology: From microbiology to cancerology

2. Past, present and future of atomic force microscopy in life sciences and medicine

3. Application of atomic force microscopy in cancer research

4. AFM: A Nanotool in Membrane Biology

5. Elasticity, Adhesion, and Tether Extrusion on Breast Cancer Cells Provide a Signature of Their Invasive Potential

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