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1. Verfasser: Boquet-Pujadas, Aleix
Format: Preprint
Veröffentlicht: 2024
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Online-Zugang:https://arxiv.org/abs/2412.18406
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author Boquet-Pujadas, Aleix
author_facet Boquet-Pujadas, Aleix
contents Mechanobiology is gaining more and more traction as the fundamental role of physical forces in biological function becomes clearer. Forces at the microscale are often measured indirectly using inverse problems such as Traction Force Microscopy because biological experiments are hard to access with physical probes. In contrast with the experimental nature of biology and physics, these measurements do not come with error bars, confidence regions, or p-values. The aim of this manuscript is to publicize this issue and to propose a first step towards a remedy therefor in the form of a general reconstruction framework. We also show that this opens the door to hypothesis testing of seemingly abstract experimental questions.
format Preprint
id arxiv_https___arxiv_org_abs_2412_18406
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle How accurate is mechanobiology? A statistical test of cell force
Boquet-Pujadas, Aleix
Biological Physics
Computer Vision and Pattern Recognition
Computational Physics
Mechanobiology is gaining more and more traction as the fundamental role of physical forces in biological function becomes clearer. Forces at the microscale are often measured indirectly using inverse problems such as Traction Force Microscopy because biological experiments are hard to access with physical probes. In contrast with the experimental nature of biology and physics, these measurements do not come with error bars, confidence regions, or p-values. The aim of this manuscript is to publicize this issue and to propose a first step towards a remedy therefor in the form of a general reconstruction framework. We also show that this opens the door to hypothesis testing of seemingly abstract experimental questions.
title How accurate is mechanobiology? A statistical test of cell force
topic Biological Physics
Computer Vision and Pattern Recognition
Computational Physics
url https://arxiv.org/abs/2412.18406