Computational Systems Biology of Saccharomyces cerevisiae Cell Growth and Division
<p>Cell division and growth are complex processes fundamental to all living organisms. In the budding yeast, <italic>Saccharomyces cerevisiae</italic>, these two processes are known to be coordinated with one another as a cell's mass must roughly double before division. Moreov...
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ndltd-DUKE-oai-dukespace.lib.duke.edu-10161-90892015-02-24T03:32:23ZComputational Systems Biology of Saccharomyces cerevisiae Cell Growth and DivisionMayhew, Michael BenjaminBioinformaticsStatisticsCellular biologyBayesian statisticscell cyclecell growthimage analysissystems biology<p>Cell division and growth are complex processes fundamental to all living organisms. In the budding yeast, <italic>Saccharomyces cerevisiae</italic>, these two processes are known to be coordinated with one another as a cell's mass must roughly double before division. Moreover, cell-cycle progression is dependent on cell size with smaller cells at birth generally taking more time in the cell cycle. This dependence is a signature of size control. Systems biology is an emerging field that emphasizes connections or dependencies between biological entities and processes over the characteristics of individual entities. Statistical models provide a quantitative framework for describing and analyzing these dependencies. In this dissertation, I take a statistical systems biology approach to study cell division and growth and the dependencies within and between these two processes, drawing on observations from richly informative microscope images and time-lapse movies. I review the current state of knowledge on these processes, highlighting key results and open questions from the biological literature. I then discuss my development of machine learning and statistical approaches to extract cell-cycle information from microscope images and to better characterize the cell-cycle progression of populations of cells. In addition, I analyze single cells to uncover correlation in cell-cycle progression, evaluate potential models of dependence between growth and division, and revisit classical assertions about budding yeast size control. This dissertation presents a unique perspective and approach towards comprehensive characterization of the coordination between growth and division.</p>DissertationHartemink, Alexander JHaase, Steven B2014Dissertationhttp://hdl.handle.net/10161/9089 |
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Bioinformatics Statistics Cellular biology Bayesian statistics cell cycle cell growth image analysis systems biology |
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Bioinformatics Statistics Cellular biology Bayesian statistics cell cycle cell growth image analysis systems biology Mayhew, Michael Benjamin Computational Systems Biology of Saccharomyces cerevisiae Cell Growth and Division |
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<p>Cell division and growth are complex processes fundamental to all living organisms. In the budding yeast, <italic>Saccharomyces cerevisiae</italic>, these two processes are known to be coordinated with one another as a cell's mass must roughly double before division. Moreover, cell-cycle progression is dependent on cell size with smaller cells at birth generally taking more time in the cell cycle. This dependence is a signature of size control. Systems biology is an emerging field that emphasizes connections or dependencies between biological entities and processes over the characteristics of individual entities. Statistical models provide a quantitative framework for describing and analyzing these dependencies. In this dissertation, I take a statistical systems biology approach to study cell division and growth and the dependencies within and between these two processes, drawing on observations from richly informative microscope images and time-lapse movies. I review the current state of knowledge on these processes, highlighting key results and open questions from the biological literature. I then discuss my development of machine learning and statistical approaches to extract cell-cycle information from microscope images and to better characterize the cell-cycle progression of populations of cells. In addition, I analyze single cells to uncover correlation in cell-cycle progression, evaluate potential models of dependence between growth and division, and revisit classical assertions about budding yeast size control. This dissertation presents a unique perspective and approach towards comprehensive characterization of the coordination between growth and division.</p> === Dissertation |
author2 |
Hartemink, Alexander J |
author_facet |
Hartemink, Alexander J Mayhew, Michael Benjamin |
author |
Mayhew, Michael Benjamin |
author_sort |
Mayhew, Michael Benjamin |
title |
Computational Systems Biology of Saccharomyces cerevisiae Cell Growth and Division |
title_short |
Computational Systems Biology of Saccharomyces cerevisiae Cell Growth and Division |
title_full |
Computational Systems Biology of Saccharomyces cerevisiae Cell Growth and Division |
title_fullStr |
Computational Systems Biology of Saccharomyces cerevisiae Cell Growth and Division |
title_full_unstemmed |
Computational Systems Biology of Saccharomyces cerevisiae Cell Growth and Division |
title_sort |
computational systems biology of saccharomyces cerevisiae cell growth and division |
publishDate |
2014 |
url |
http://hdl.handle.net/10161/9089 |
work_keys_str_mv |
AT mayhewmichaelbenjamin computationalsystemsbiologyofsaccharomycescerevisiaecellgrowthanddivision |
_version_ |
1716730981476466688 |