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Models for pattern formation in biological systems

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TitleInfo
Title
Models for pattern formation in biological systems
Name (type = personal)
NamePart (type = family)
Pouradier Duteil
NamePart (type = given)
Nastassia
NamePart (type = date)
1990-
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Nastassia Pouradier Duteil
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author
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Piccoli
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Benedetto
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Benedetto Piccoli
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Advisory Committee
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chair
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Yakoby
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Nir
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Nir Yakoby
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Advisory Committee
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internal member
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Fu
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Siqi
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Siqi Fu
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Advisory Committee
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internal member
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Trelat
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Emmanuel
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Emmanuel Trelat
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Advisory Committee
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outside member
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Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
Camden Graduate School
Role
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school
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Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (qualifier = exact)
2017
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2017-05
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2017
Place
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xx
Language
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eng
Abstract (type = abstract)
This thesis presents models for two different kinds of pattern formation in biological systems. Developmental patterning refers to pattern formation by cell differentiation during an organism's development. Cell differentiation is controlled by morphogens, signaling molecules that diffuse in a growing organism. We focus on the specific case of the activation of the epidermal growth factor receptor pathway, a highly-conserved signaling pathway across animals, that controls both the posterior-anterior and the dorso-ventral axes during Drosophila oogenesis. Not only can the diffusion of morphogens control the growth of an organism, but the diffusion itself is influenced by the changing geometry of the domain. We develop a mathematical framework enabling this double coupling of the diffusion of a signal on a time-evolving Riemannian manifold and the evolution of the manifold via a vector field depending on the diffusing signal: "Developmental Partial Differential Equations". The second kind of pattern formation, behavioral patterning, arises from local interactions between individuals that lead to a global group behavior. We focus on several of these models, also referred to as Social Dynamics systems. We examine how to control the dynamics to guide the system to a target configuration. In particular, we study the optimal control of a collective migration model to guide the system to consensus at a target velocity, as well as the controllability away from consensus of an opinion dynamics system. We analyze the influence of the state space on the dynamics by designing a general opinion dynamics model on Riemannian manifolds. Lastly, we investigate the role of the interaction network on the periodicity of the dynamics, specifically in creating a "social choreography".
Subject (authority = RUETD)
Topic
Computational and Integrative Biology
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_8174
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (vii, 164 p. : ill.)
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Subject (authority = ETD-LCSH)
Topic
Biological systems
Note (type = statement of responsibility)
by Nastassia Pouradier Duteil
RelatedItem (type = host)
TitleInfo
Title
Camden Graduate School Electronic Theses and Dissertations
Identifier (type = local)
rucore10005600001
Location
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NjNbRU
Identifier (type = doi)
doi:10.7282/T3FT8PS1
Genre (authority = ExL-Esploro)
ETD doctoral
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Rights

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The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Pouradier Duteil
GivenName
Nastassia
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2017-05-01 22:48:02
AssociatedEntity
Name
Nastassia Pouradier Duteil
Role
Copyright holder
Affiliation
Rutgers University. Camden Graduate School
AssociatedObject
Type
License
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Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical

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2017-05-04T11:43:07
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