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Methods to Visualize, Dissect and Simulate Complex Cellular Behaviors- [electronic resource]
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Methods to Visualize, Dissect and Simulate Complex Cellular Behaviors- [electronic resource]
자료유형  
 학위논문
Control Number  
0016931937
International Standard Book Number  
9798379653361
Dewey Decimal Classification Number  
574
Main Entry-Personal Name  
DeFelice, Mialy Murie.
Publication, Distribution, etc. (Imprint  
[S.l.] : Stanford University., 2021
Publication, Distribution, etc. (Imprint  
Ann Arbor : ProQuest Dissertations & Theses, 2021
Physical Description  
1 online resource(122 p.)
General Note  
Source: Dissertations Abstracts International, Volume: 84-12, Section: B.
General Note  
Advisor: Bryant, Zev David;Lin, Michael Z.;Covert, Markus.
Dissertation Note  
Thesis (Ph.D.)--Stanford University, 2021.
Restrictions on Access Note  
This item must not be sold to any third party vendors.
Summary, Etc.  
요약When we consider a problem, like a disease, our instinct is to find the source of the issue and fix it. For some diseases we encounter this is possible because we can identify a single trackable cause of the issue. For example, in the mid-1800's surgeons realized that they could prevent bacterial infections and death in patients by simply washing their hands and wearing gloves during surgery. But for other diseases, like diabetes or schizophrenia the 'cause' is not so evident, and work over time has taught us that these diseases are systemic. It's only through fully understanding the underlying system that we can tackle the disease.Systems large and small have been found to underlie all of biology, not just complex diseases. It's not enough to understand how proteins or pathways or cells work in isolation. If we really want to understand them, we need to piece together how they work as a whole - as a system.My thesis work is a story of systems on different scales: from a pathway, to a cell, to a population of cells. I will first discuss work we did to understand how increasing stimulus into a pathway is able to produce non-monotonic outputs. Next, I report efforts to experimentally validate a central prediction that arose out of our lab's recent Escherichia coli whole-cell modeling project: sub-generational gene expression. I will then discuss how revelations from this work led to my most recent work, adding operon structure into the whole-cell model. And finally, I will discuss plans we have to experimentally determine the import of this architecture in ensuring population survival, and perspectives on the future of model-driven discovery. Although these systems all seem different, they connect through common themes including the presence of emergent phenomena and the need for methods to visualize, dissect and simulate these complex cellular behaviors.
Subject Added Entry-Topical Term  
RNA polymerase.
Subject Added Entry-Topical Term  
Gene expression.
Subject Added Entry-Topical Term  
E coli.
Subject Added Entry-Topical Term  
Cell cycle.
Subject Added Entry-Topical Term  
Parameter estimation.
Subject Added Entry-Topical Term  
Biochemistry.
Subject Added Entry-Topical Term  
Bioinformatics.
Subject Added Entry-Topical Term  
Cellular biology.
Subject Added Entry-Topical Term  
Genetics.
Added Entry-Corporate Name  
Stanford University.
Host Item Entry  
Dissertations Abstracts International. 84-12B.
Host Item Entry  
Dissertation Abstract International
Electronic Location and Access  
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Control Number  
joongbu:643211
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