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The Application of the Expectation-Maximization Algorithm to the Identification of Biological Models

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dc.contributor.authorChen, Shuoen
dc.contributor.committeechairBaumann, William T.en
dc.contributor.committeememberXuan, Jianhua Jasonen
dc.contributor.committeememberWang, Joseph C.en
dc.contributor.departmentElectrical and Computer Engineeringen
dc.date.accessioned2014-03-14T20:49:37Zen
dc.date.adate2007-03-09en
dc.date.available2014-03-14T20:49:37Zen
dc.date.issued2006-12-11en
dc.date.rdate2007-03-09en
dc.date.sdate2006-12-15en
dc.description.abstractWith the onset of large-scale gene expression profiling, many researchers have turned their attention toward biological process modeling and system identification. The abundance of data available, while inspiring, is also daunting to interpret. Following the initial work of Rangel et al., we propose a linear model for identifying the biological model behind the data and utilize a modification of the Expectation-Maximization algorithm for training it. With our model, we explore some commonly accepted assumptions concerning sampling, discretization, and state transformations. Also, we illuminate the model complexities and interpretation difficulties caused by unknown state transformations and propose some solutions for resolving these problems. Finally, we elucidate the advantages and limitations of our linear state-space model with simulated data from several nonlinear networks.en
dc.description.degreeMaster of Scienceen
dc.identifier.otheretd-12152006-132023en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-12152006-132023/en
dc.identifier.urihttp://hdl.handle.net/10919/36160en
dc.language.isoenen
dc.publisherVirginia Techen
dc.relation.haspartFinal_Thesis.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectGene Regulatory Networksen
dc.subjectEM Algorithmen
dc.titleThe Application of the Expectation-Maximization Algorithm to the Identification of Biological Modelsen
dc.typeThesisen
thesis.degree.disciplineElectrical and Computer Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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