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Computations of DSGRN
Descriptive
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Title
Computations of DSGRN
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Zhang
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Lun
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Lun Zhang
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author
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Mischaikow
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Konstantin
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Konstantin Mischaikow
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chair
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Saks
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Michael
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Michael Saks
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internal member
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Cakoni
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internal member
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Gedeon
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Tomas
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Tomas Gedeon
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Rutgers University
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School of Graduate Studies
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theses
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ETD doctoral
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2020
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2020-10
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2020
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English
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The study of this thesis is mainly motivated by the computational problems that arised from paper [7] where authors designed a new dynamic system model called Dynamic Signatures Generated by Regulatory Networks (DSGRN) to simulate gene regulatory networks. An essential property of DSGRN model is that the phase transition graph is invariant over a family of subvariety which is defined by a set of simple polynomials over parameter space. One of the work in DSGRN is to study the family of subvariety over parameter space and two basic problem arises: realizability and topology. As to reailizability, we are concerned with constructing the whole family of subvariety. For topology, we want to compute the homology group of a set of subvariety for a given phenotype. This thesis has two main contributions. First, we develop a new algorithm that greatly extends the computational ability of DSGRN to wider class of regulatory network. Second, we design a computational framework for the homology computation of subvariety over the parameter space.
Subject
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Mathematics
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Rutgers University Electronic Theses and Dissertations
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1 online resource (vi, 93 pages) : illustrations
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Ph.D.
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Includes bibliographical references
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School of Graduate Studies Electronic Theses and Dissertations
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rucore10001600001
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Identifier
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doi:10.7282/t3-xc52-yt51
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Rights
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The author owns the copyright to this work.
RightsHolder
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Name
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Zhang
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Lun
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Permission or license
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2020-09-03 05:05:46
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Lun Zhang
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Rutgers University. School of Graduate Studies
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Author Agreement License
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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
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Copyright protected
Availability
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Open
Reason
Permission or license
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