A machine learning approach to predict cellular mechanical stresses in response to chemical perturbation-Reference-Cited by-同舟云学术

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A machine learning approach to predict cellular mechanical stresses in response to chemical perturbation

Published:2023-09 Issue:17 Volume:122 Page:3413-3424
ISSN:0006-3495
Container-title:Biophysical Journal
language:en
Short-container-title:Biophysical Journal

Author:

SubramanianBalachandar VigneshAravind,Islam Md. Mydul,Steward R.L.

Funder

National Heart Lung and Blood Institute Division of Intramural Research

National Science Foundation

National Institutes of Health

National Heart, Lung, and Blood Institute

Publisher

Elsevier BV

Subject

Biophysics

Reference52 articles.

1. Dissipation of contractile forces: the missing piece in cell mechanics;Kurzawa;Mol. Biol. Cell,2017

2. Mechanical signaling in a pulmonary microvascular endothelial cell monolayer;Patel;Biochem. Biophys. Res. Commun.,2019

3. Cell traction force and measurement methods;Wang;Biomech. Model. Mechanobiol.,2007

4. Quantifying cellular traction forces in three dimensions;Maskarinec;Proc. Natl. Acad. Sci. USA,2009

5. FRET measurements of cell-traction forces and nano-scale clustering of adhesion ligands varied by substrate stiffness;Kong;Proc. Natl. Acad. Sci. USA.,2005

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