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Analysis and modeling of cells, cell behavior, and helical biological molecules

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dc.contributor.authorBenoit, Steven Richard, author
dc.contributor.authorPutkaradze, Vakhtang, advisor
dc.contributor.authorShipman, Patrick, committee member
dc.contributor.authorEstep, Don, committee member
dc.contributor.authorMarconi, Mario, committee member
dc.contributor.authorTobet, Stuart, committee member
dc.date.accessioned2007-01-03T05:15:51Z
dc.date.available2007-01-03T05:15:51Z
dc.date.issued2011
dc.description.abstractMathematical models of biological systems have evolved over time and through the introduction and growth of computer simulation and analysis. Models have increased in sophistication and power through the combination of multi-scale approaches, molecular and granular dynamics simulations, and advances in parallelization and processing speed. However, current cell models cannot accurately predict behaviors at the whole-cell scale, nor can molecular models predict accurately the complex shape assumed by large biological molecules including proteins, although significant progress is being made toward this goal. The present work introduces new models in three domains within biological systems modeling. We first discuss a phenomenological model of observed cell motions in developing tissue that characterizes cells according to a best-fit generalized diffusion model and combines this data with Voronoi diagrams to effectively visualize patterns of cell behavior in tissue. Next, we present a series of component models for cells and cell structure that support simulations involving tens to hundreds of cells in a way that captures behaviors ignored by existing models, including pseudopod formation, membrane mechanics, cytoskeletal polymerization / depolymerization, and chemical signal transduction. The resulting models exhibit many of the behaviors of real-world cells including polarization and chemotaxis. Finally, we present a method for analysis of biological molecules that form helical conformations that includes long-range electrostatic interactions as well as short-range interactions to prevent self-intersections. We consider the stability of molecules with repeating monomers that include off-axis charge concentrations and derive energy landscapes to identify stable conformations, then analyze helical stability using geometric methods.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.identifierBenoit_colostate_0053A_10343.pdf
dc.identifier.urihttp://hdl.handle.net/10217/47376
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof2000-2019
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectcell models
dc.subjecthelical molecules
dc.titleAnalysis and modeling of cells, cell behavior, and helical biological molecules
dc.typeText
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineMathematics
thesis.degree.grantorColorado State University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)

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