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dc.contributor.advisorArup K. Chakraborty.en_US
dc.contributor.authorArtomov, Maksymen_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Chemistry.en_US
dc.date.accessioned2010-08-31T14:32:24Z
dc.date.available2010-08-31T14:32:24Z
dc.date.copyright2009en_US
dc.date.issued2010en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/57773
dc.descriptionThesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemistry, February 2010.en_US
dc.descriptionCataloged from PDF version of thesis. Vita.en_US
dc.descriptionIncludes bibliographical references.en_US
dc.description.abstractMajority of biological processes can not be described deterministically. Multple levels of regulation contribute to the noise in the observable properties of the cells: fluctuations are ubiquitous in biological networks and in their spatial organization. In this thesis we consider several examples from three broad categories. Firstly, we study two problems that highlight connection between network topologies and manifestations of stochastic fluctuation in networks of chemical reactions that are meant to represent biological networks in the coarse-grained way. We show that specific network structure can have profound consequences on the steady-state probability distribution function of corresponding chemical system. Secondly, we study effects of spatial organization of the proteins on the membrane surface of T-cells on the initialization of signal propagation. We show that coordinated diffusion of proteins is critical for signal-enhancing properties of co-receptors CD4 and CD8. In third part of the thesis we attempt to reconstruct network topology based on incomplete information about specific interactions between the network nodes and some information about "macroscopic" behavior of the system governed by the network in question. The matter of the Part III, however, is one scale larger than the corresponding objects considered in Part II and I. Specifically, we consider transformations of cells between different cell types and molecular origins that underlie cell transformations (such as differentiation/de-differentiation). Our model suggests specific structure of the master-regulatory network of genes and makes testable predictions.en_US
dc.description.statementofresponsibilityby Maksym Artomov.en_US
dc.format.extent221 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.subjectChemistry.en_US
dc.titleStochastic processes in biological systems : selected problemsen_US
dc.typeThesisen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Chemistry
dc.identifier.oclc630688440en_US


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