{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/29445"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/29445","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Modeling and analysis of gene expression arrays","abstract":"Gene expression arrays are a technology used to measure quantities of messenger ribonucleic acid (mRNA). Application of the technology involves a variety of physical processes beginning with the acquisition of mRNA samples and ending with the fluorescence imaging of a gene expression array. This thesis examines these physical processes, develops a mechanistic model, and derives the analysis procedure based on the model. Chief advantages of this approach are that it accounts for certain previously unexplained array phenomena and is based in a clear way on physical knowledge allowing non-arbitrary determination of both the probability that any given gene has altered expression ratio relative to a control as well as the magnitude of this induction or repression. We demonstrate its use on simulated and real array data, and show that a considerable amount of previously unrecognized information concerning gene expression differences is inherent in the array measurements.","abstract_html":"Gene expression arrays are a technology used to measure quantities of messenger ribonucleic acid (mRNA). Application of the technology involves a variety of physical processes beginning with the acquisition of mRNA samples and ending with the fluorescence imaging of a gene expression array. This thesis examines these physical processes, develops a mechanistic model, and derives the analysis procedure based on the model. Chief advantages of this approach are that it accounts for certain previously unexplained array phenomena and is based in a clear way on physical knowledge allowing non-arbitrary determination of both the probability that any given gene has altered expression ratio relative to a control as well as the magnitude of this induction or repression. We demonstrate its use on simulated and real array data, and show that a considerable amount of previously unrecognized information concerning gene expression differences is inherent in the array measurements.","abstract_has_math":false,"creators":["Duggar, Keith Howard, 1976-"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Dept. of Chemical Engineering.","school":null,"contributors":[],"advisors":["Douglas A. Lauffenburger and Peter K. 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