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Computational Methods for Estimation of Cell Cycle Phase Distributions of Yeast Cells

Two computational methods for estimating the cell cycle phase distribution of a budding yeast (Saccharomyces cerevisiae) cell population are presented. The first one is a nonparametric method that is based on the analysis of DNA content in the individual cells of the population. The DNA content is m...

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Autores principales: Niemistö, Antti, Nykter, Matti, Aho, Tommi, Jalovaara, Henna, Marjanen, Kalle, Ahdesmäki, Miika, Ruusuvuori, Pekka, Tiainen, Mikko, Linne, Marja-Leena, Yli-Harja, Olli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3171340/
https://www.ncbi.nlm.nih.gov/pubmed/18354733
http://dx.doi.org/10.1155/2007/46150
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author Niemistö, Antti
Nykter, Matti
Aho, Tommi
Jalovaara, Henna
Marjanen, Kalle
Ahdesmäki, Miika
Ruusuvuori, Pekka
Tiainen, Mikko
Linne, Marja-Leena
Yli-Harja, Olli
author_facet Niemistö, Antti
Nykter, Matti
Aho, Tommi
Jalovaara, Henna
Marjanen, Kalle
Ahdesmäki, Miika
Ruusuvuori, Pekka
Tiainen, Mikko
Linne, Marja-Leena
Yli-Harja, Olli
author_sort Niemistö, Antti
collection PubMed
description Two computational methods for estimating the cell cycle phase distribution of a budding yeast (Saccharomyces cerevisiae) cell population are presented. The first one is a nonparametric method that is based on the analysis of DNA content in the individual cells of the population. The DNA content is measured with a fluorescence-activated cell sorter (FACS). The second method is based on budding index analysis. An automated image analysis method is presented for the task of detecting the cells and buds. The proposed methods can be used to obtain quantitative information on the cell cycle phase distribution of a budding yeast S. cerevisiae population. They therefore provide a solid basis for obtaining the complementary information needed in deconvolution of gene expression data. As a case study, both methods are tested with data that were obtained in a time series experiment with S. cerevisiae. The details of the time series experiment as well as the image and FACS data obtained in the experiment can be found in the online additional material at http://www.cs.tut.fi/sgn/csb/yeastdistrib/.
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spelling pubmed-31713402011-09-13 Computational Methods for Estimation of Cell Cycle Phase Distributions of Yeast Cells Niemistö, Antti Nykter, Matti Aho, Tommi Jalovaara, Henna Marjanen, Kalle Ahdesmäki, Miika Ruusuvuori, Pekka Tiainen, Mikko Linne, Marja-Leena Yli-Harja, Olli EURASIP J Bioinform Syst Biol Research Article Two computational methods for estimating the cell cycle phase distribution of a budding yeast (Saccharomyces cerevisiae) cell population are presented. The first one is a nonparametric method that is based on the analysis of DNA content in the individual cells of the population. The DNA content is measured with a fluorescence-activated cell sorter (FACS). The second method is based on budding index analysis. An automated image analysis method is presented for the task of detecting the cells and buds. The proposed methods can be used to obtain quantitative information on the cell cycle phase distribution of a budding yeast S. cerevisiae population. They therefore provide a solid basis for obtaining the complementary information needed in deconvolution of gene expression data. As a case study, both methods are tested with data that were obtained in a time series experiment with S. cerevisiae. The details of the time series experiment as well as the image and FACS data obtained in the experiment can be found in the online additional material at http://www.cs.tut.fi/sgn/csb/yeastdistrib/. Springer 2007-08-19 /pmc/articles/PMC3171340/ /pubmed/18354733 http://dx.doi.org/10.1155/2007/46150 Text en Copyright © 2007 Antti Niemistö et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Niemistö, Antti
Nykter, Matti
Aho, Tommi
Jalovaara, Henna
Marjanen, Kalle
Ahdesmäki, Miika
Ruusuvuori, Pekka
Tiainen, Mikko
Linne, Marja-Leena
Yli-Harja, Olli
Computational Methods for Estimation of Cell Cycle Phase Distributions of Yeast Cells
title Computational Methods for Estimation of Cell Cycle Phase Distributions of Yeast Cells
title_full Computational Methods for Estimation of Cell Cycle Phase Distributions of Yeast Cells
title_fullStr Computational Methods for Estimation of Cell Cycle Phase Distributions of Yeast Cells
title_full_unstemmed Computational Methods for Estimation of Cell Cycle Phase Distributions of Yeast Cells
title_short Computational Methods for Estimation of Cell Cycle Phase Distributions of Yeast Cells
title_sort computational methods for estimation of cell cycle phase distributions of yeast cells
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3171340/
https://www.ncbi.nlm.nih.gov/pubmed/18354733
http://dx.doi.org/10.1155/2007/46150
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