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Assessment of protein inclusions in cultured cells using automated image analysis
Proteinaceous inclusions are associated with neurodegenerative diseases and cell models are often used to determine genetic and chemical modifiers of their formation. This protocol involves the usage of automated microscopy and machine learning-based image analysis to accurately quantify the levels...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9535320/ https://www.ncbi.nlm.nih.gov/pubmed/36201320 http://dx.doi.org/10.1016/j.xpro.2022.101748 |
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author | McAlary, Luke Shephard, Victoria K. Sher, Mine Rice, Lauren J. Yerbury, Justin J. Cashman, Neil R. Plotkin, Steven S. |
author_facet | McAlary, Luke Shephard, Victoria K. Sher, Mine Rice, Lauren J. Yerbury, Justin J. Cashman, Neil R. Plotkin, Steven S. |
author_sort | McAlary, Luke |
collection | PubMed |
description | Proteinaceous inclusions are associated with neurodegenerative diseases and cell models are often used to determine genetic and chemical modifiers of their formation. This protocol involves the usage of automated microscopy and machine learning-based image analysis to accurately quantify the levels of protein inclusion formation in cultured cells from fluorescence microscopy images. This protocol is highly scalable and can be applied to a few images or large datasets. For complete details on the use and execution of this protocol, please refer to McAlary et al. (2022). |
format | Online Article Text |
id | pubmed-9535320 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-95353202022-10-07 Assessment of protein inclusions in cultured cells using automated image analysis McAlary, Luke Shephard, Victoria K. Sher, Mine Rice, Lauren J. Yerbury, Justin J. Cashman, Neil R. Plotkin, Steven S. STAR Protoc Protocol Proteinaceous inclusions are associated with neurodegenerative diseases and cell models are often used to determine genetic and chemical modifiers of their formation. This protocol involves the usage of automated microscopy and machine learning-based image analysis to accurately quantify the levels of protein inclusion formation in cultured cells from fluorescence microscopy images. This protocol is highly scalable and can be applied to a few images or large datasets. For complete details on the use and execution of this protocol, please refer to McAlary et al. (2022). Elsevier 2022-10-04 /pmc/articles/PMC9535320/ /pubmed/36201320 http://dx.doi.org/10.1016/j.xpro.2022.101748 Text en © 2022 The Authors. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Protocol McAlary, Luke Shephard, Victoria K. Sher, Mine Rice, Lauren J. Yerbury, Justin J. Cashman, Neil R. Plotkin, Steven S. Assessment of protein inclusions in cultured cells using automated image analysis |
title | Assessment of protein inclusions in cultured cells using automated image analysis |
title_full | Assessment of protein inclusions in cultured cells using automated image analysis |
title_fullStr | Assessment of protein inclusions in cultured cells using automated image analysis |
title_full_unstemmed | Assessment of protein inclusions in cultured cells using automated image analysis |
title_short | Assessment of protein inclusions in cultured cells using automated image analysis |
title_sort | assessment of protein inclusions in cultured cells using automated image analysis |
topic | Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9535320/ https://www.ncbi.nlm.nih.gov/pubmed/36201320 http://dx.doi.org/10.1016/j.xpro.2022.101748 |
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