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Functional non-parametric mixed effects models for cytotoxicity assessment and clustering
A multitude of natural and synthetic chemicals are present in our environment.Through the study of a compound’s cytotoxicity, researchers can carefully set regulations regarding how much of a certain chemical in the ambient environment is tolerable. In the past, research has focused on point measure...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10008646/ https://www.ncbi.nlm.nih.gov/pubmed/36906619 http://dx.doi.org/10.1038/s41598-023-31011-1 |
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author | Ma, Tiantian Richard, Dan Yang, Yongqing Betty Kashlak, Adam B Anton, Cristina |
author_facet | Ma, Tiantian Richard, Dan Yang, Yongqing Betty Kashlak, Adam B Anton, Cristina |
author_sort | Ma, Tiantian |
collection | PubMed |
description | A multitude of natural and synthetic chemicals are present in our environment.Through the study of a compound’s cytotoxicity, researchers can carefully set regulations regarding how much of a certain chemical in the ambient environment is tolerable. In the past, research has focused on point measurements such as the LD50. Instead, we consider entire time-dependent cellular response curves through the application of functional mixed effects models. We identify differences in such curves corresponding to the chemical’s mode of action—i.e. how the compound attacks human cells. Through such analysis, we identify curve features to be used for cluster analysis via application of both k-means and self organizing maps. The data is analyzed by making use of functional principal components as a data driven basis and separately by considering B-splines for identifying local-time features. Our analysis can be used to drastically speed up future cytotoxicity research. |
format | Online Article Text |
id | pubmed-10008646 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-100086462023-03-13 Functional non-parametric mixed effects models for cytotoxicity assessment and clustering Ma, Tiantian Richard, Dan Yang, Yongqing Betty Kashlak, Adam B Anton, Cristina Sci Rep Article A multitude of natural and synthetic chemicals are present in our environment.Through the study of a compound’s cytotoxicity, researchers can carefully set regulations regarding how much of a certain chemical in the ambient environment is tolerable. In the past, research has focused on point measurements such as the LD50. Instead, we consider entire time-dependent cellular response curves through the application of functional mixed effects models. We identify differences in such curves corresponding to the chemical’s mode of action—i.e. how the compound attacks human cells. Through such analysis, we identify curve features to be used for cluster analysis via application of both k-means and self organizing maps. The data is analyzed by making use of functional principal components as a data driven basis and separately by considering B-splines for identifying local-time features. Our analysis can be used to drastically speed up future cytotoxicity research. Nature Publishing Group UK 2023-03-11 /pmc/articles/PMC10008646/ /pubmed/36906619 http://dx.doi.org/10.1038/s41598-023-31011-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Ma, Tiantian Richard, Dan Yang, Yongqing Betty Kashlak, Adam B Anton, Cristina Functional non-parametric mixed effects models for cytotoxicity assessment and clustering |
title | Functional non-parametric mixed effects models for cytotoxicity assessment and clustering |
title_full | Functional non-parametric mixed effects models for cytotoxicity assessment and clustering |
title_fullStr | Functional non-parametric mixed effects models for cytotoxicity assessment and clustering |
title_full_unstemmed | Functional non-parametric mixed effects models for cytotoxicity assessment and clustering |
title_short | Functional non-parametric mixed effects models for cytotoxicity assessment and clustering |
title_sort | functional non-parametric mixed effects models for cytotoxicity assessment and clustering |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10008646/ https://www.ncbi.nlm.nih.gov/pubmed/36906619 http://dx.doi.org/10.1038/s41598-023-31011-1 |
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