pyTFM: A tool for traction force and monolayer stress microscopy
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378050%3A_____%2F21%3A00554346" target="_blank" >RIV/68378050:_____/21:00554346 - isvavai.cz</a>
Result on the web
<a href="https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008364" target="_blank" >https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008364</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1371/journal.pcbi.1008364" target="_blank" >10.1371/journal.pcbi.1008364</a>
Alternative languages
Result language
angličtina
Original language name
pyTFM: A tool for traction force and monolayer stress microscopy
Original language description
Cellular force generation and force transmission are of fundamental importance for numerous biological processes and can be studied with the methods of Traction Force Microscopy (TFM) and Monolayer Stress Microscopy. Traction Force Microscopy and Monolayer Stress Microscopy solve the inverse problem of reconstructing cell-matrix tractions and inter- and intra-cellular stresses from the measured cell force-induced deformations of an adhesive substrate with known elasticity. Although several laboratories have developed software for Traction Force Microscopy and Monolayer Stress Microscopy computations, there is currently no software package available that allows non-expert users to perform a full evaluation of such experiments. Here we present pyTFM, a tool to perform Traction Force Microscopy and Monolayer Stress Microscopy on cell patches and cell layers grown in a 2dimensional environment. pyTFM was optimized for ease-of-use, it is open-source and well documented (hosted at https://pytfm.readthedocs.io/) including usage examples and explanations of the theoretical background. pyTFM can be used as a standalone Python package or as an add-on to the image annotation tool ClickPoints. In combination with the ClickPoints environment, pyTFM allows the user to set all necessary analysis parameters, select regions of interest, examine the input data and intermediary results, and calculate a wide range of parameters describing forces, stresses, and their distribution. In this work, we also thoroughly analyze the accuracy and performance of the Traction Force Microscopy and Monolayer Stress Microscopy algorithms of pyTFM using synthetic and experimental data from epithelial cell patches.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10608 - Biochemistry and molecular biology
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
PLoS Computational Biology
ISSN
1553-734X
e-ISSN
1553-7358
Volume of the periodical
17
Issue of the periodical within the volume
6
Country of publishing house
US - UNITED STATES
Number of pages
17
Pages from-to
e1008364
UT code for WoS article
000670609800001
EID of the result in the Scopus database
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