nanite: using machine learning to assess the quality of atomic force microscopy-enabled nano-indentation data
Abstract Background Atomic force microscopy (AFM) allows the mechanical characterization of single cells and live tissue by quantifying force-distance (FD) data in nano-indentation experiments. One of the main problems when dealing with biological tissue is the fact that the measured FD curves can b...
Main Authors: | Paul Müller, Shada Abuhattum, Stephanie Möllmert, Elke Ulbricht, Anna V. Taubenberger, Jochen Guck |
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Format: | Article |
Language: | English |
Published: |
BMC
2019-09-01
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Series: | BMC Bioinformatics |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1186/s12859-019-3010-3 |
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