Computational Models of the Mammalian Cell Cycle

Computational Models of the Mammalian Cell Cycle

Bibliographic Details
Main Author: Weis, Michael Christian
Language:English
Published: Case Western Reserve University School of Graduate Studies / OhioLINK 2011
Subjects:
Applied Mathematics
Bioinformatics
Biology
Engineering
Molecular Biology
Systems Science
systems biology
computational biology
mathematical biology
cell cycle
molecular biology
Online Access:http://rave.ohiolink.edu/etdc/view?acc_num=case1323278159
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spelling ndltd-OhioLink-oai-etd.ohiolink.edu-case13232781592021-08-03T05:34:26Z Computational Models of the Mammalian Cell Cycle Weis, Michael Christian Applied Mathematics Bioinformatics Biology Engineering Molecular Biology Systems Science systems biology computational biology mathematical biology cell cycle molecular biology Systems biology has sometimes been defined as the application of systems science and engineering concepts to biological problems. This dissertation illustrates the usefulness of this approach in understanding the regulation of the mammalian cell cycle. Cell growth and division are fundamental properties of life, and the dysregulation of cell cycle control is central to the development of cancer. Understandably then, the cell cycle has historically been a popular subject for mathematical modeling efforts and we review 154 models developed over the past 80 years. Beyond mathematics however, understanding systems requires the evaluation of models against data. The work presented herein illustrates an approach for estimating the median dynamic expression profiles of cell cycle regulatory molecules from a flow cytometric snapshot of an asynchronous population, and applies this data to the modification and calibration of a computational model of mammalian cell cycle control. This contribution illustrates the value of the systems biology approach in integrating existing evidence, interpreting data, and driving new hypotheses regarding the organizing principles of biological systems. Having used single cell data to model the median trajectory of a population, we then investigate approaches to simulate cell-cell variation and reproduce the distribution of cells originally measured with flow cytometry. This comprehensive methodology also establishes an approach to studying proliferative diseases, such as hematopoietic cancers, which can be easily sampled and measured using flow cytometry. As only one static measurement is needed to define the underlying expression profile, this may provide an entry point to applying computational models and systems engineering methodologies to the treatment of individual patients. 2011 English text Case Western Reserve University School of Graduate Studies / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=case1323278159 http://rave.ohiolink.edu/etdc/view?acc_num=case1323278159 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.
collection NDLTD
language English
sources NDLTD
topic Applied Mathematics
Bioinformatics
Biology
Engineering
Molecular Biology
Systems Science
systems biology
computational biology
mathematical biology
cell cycle
molecular biology
spellingShingle Applied Mathematics
Bioinformatics
Biology
Engineering
Molecular Biology
Systems Science
systems biology
computational biology
mathematical biology
cell cycle
molecular biology
Weis, Michael Christian
Computational Models of the Mammalian Cell Cycle
author Weis, Michael Christian
author_facet Weis, Michael Christian
author_sort Weis, Michael Christian
title Computational Models of the Mammalian Cell Cycle
title_short Computational Models of the Mammalian Cell Cycle
title_full Computational Models of the Mammalian Cell Cycle
title_fullStr Computational Models of the Mammalian Cell Cycle
title_full_unstemmed Computational Models of the Mammalian Cell Cycle
title_sort computational models of the mammalian cell cycle
publisher Case Western Reserve University School of Graduate Studies / OhioLINK
publishDate 2011
url http://rave.ohiolink.edu/etdc/view?acc_num=case1323278159
work_keys_str_mv AT weismichaelchristian computationalmodelsofthemammaliancellcycle
_version_ 1719421899356766208

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