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dc.contributor.advisorH. Harry Asada.en_US
dc.contributor.authorMayalu, Michaëlle Ntalaen_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Mechanical Engineering.en_US
dc.date.accessioned2012-11-19T19:19:16Z
dc.date.available2012-11-19T19:19:16Z
dc.date.copyright2012en_US
dc.date.issued2012en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/74929
dc.descriptionThesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2012.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 56-59).en_US
dc.description.abstractEffective control of cellular behaviors has serious implications in the study of biological processes and disease. However, phenotypic changes may be difficult to detect instantaneously and are usually associated with noticeable delay between input cue and output cellular response. Because of this, relying on detection of phenotypic behaviors for use in feedback control may lead to instability and decreased controller performance. In order to alleviate these issues, a new approach to regulating cell behaviors through control of intracellular signaling events is presented. Many cell behaviors are mediated by a network of intracellular protein activations that originate at the membrane in response to stimulation of cell surface receptors. Multiple protein signaling transductions occur concurrently through diverse pathways triggered by different extracellular cues. Cell behavior differs, depending on the chronological order of multiple signaling events. This thesis develops several modeling frameworks for an intracellular signaling network specific to endothelial cell migration in angiogenesis. Unlike previous works, the models developed in this thesis exploit the effect of signaling order on extracellular response. Our approach examines the transduction time associated with each pathway of a cascaded signaling network. Transduction times of multiple pathways are compared, and the probability that the multiple signaling events occur in a desired chronological order is evaluated. We begin our development with an input-output time-delay model derived from simulated data that is used to predict the optimal extracellular input intensity for a desired response. We then present a stochastic "pseudo-discrete" model of the signal transduction time. We conclude by presenting several control strategies for control of intracellular signaling events.en_US
dc.description.statementofresponsibilityby Michaëlle Ntala Mayalu.en_US
dc.format.extent59 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectMechanical Engineering.en_US
dc.titleStochastic modeling of intracellular signaling dynamics for the purpose of regulating endothelial cell migrationen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineering
dc.identifier.oclc815772536en_US


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