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dc.contributor.authorAhn, Tae-Hyuken_US
dc.date.accessioned2017-04-06T15:43:17Z
dc.date.available2017-04-06T15:43:17Z
dc.date.issued2016-09-27en_US
dc.identifier.otheretd-08172012-094352en_US
dc.identifier.urihttp://hdl.handle.net/10919/77162
dc.description.abstractAn accelerated pace of discovery in biological sciences is made possible by a new generation of computational biology and bioinformatics tools. In this dissertation we develop novel computational, analytical, and high performance simulation techniques for biological problems, with applications to the yeast cell division cycle, and to the RNA-Sequencing of the yellow fever mosquito. Cell cycle system evolves stochastic effects when there are a small number of molecules react each other. Consequently, the stochastic effects of the cell cycle are important, and the evolution of cells is best described statistically. Stochastic simulation algorithm (SSA), the standard stochastic method for chemical kinetics, is often slow because it accounts for every individual reaction event. This work develops a stochastic version of a deterministic cell cycle model, in order to capture the stochastic aspects of the evolution of the budding yeast wild-type and mutant strain cells. In order to efficiently run large ensembles to compute statistics of cell evolution, the dissertation investigates parallel simulation strategies, and presents a new probabilistic framework to analyze the performance of dynamic load balancing algorithms. This work also proposes new accelerated stochastic simulation algorithms based on a fully implicit approach and on stochastic Taylor expansions. Next Generation RNA-Sequencing, a high-throughput technology to sequence cDNA in order to get information about a sample's RNA content, is becoming an efficient genomic approach to uncover new genes and to study gene expression and alternative splicing. This dissertation develops efficient algorithms and strategies to find new genes in Aedes aegypti, which is the most important vector of dengue fever and yellow fever. We report the discovery of a large number of new gene transcripts, and the identification and characterization of genes that showed male-biased expression profiles. This basic information may open important avenues to control mosquito borne infectious diseases.en_US
dc.language.isoen_USen_US
dc.publisherVirginia Techen_US
dc.rightsI hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Virginia Tech or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.en_US
dc.subjectStochastic simulation algorithm (SSA)en_US
dc.subjectParallel load balancingen_US
dc.subjectCell cycleen_US
dc.subjectRNA-Sequencingen_US
dc.subjectStochastic differential equations (SDEs)en_US
dc.titleComputational Techniques for the Analysis of Large Scale Biological Systemsen_US
dc.typeDissertationen_US
dc.contributor.departmentComputer Scienceen_US
dc.description.degreePh. D.en_US
thesis.degree.namePh. D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineComputer Scienceen_US
dc.contributor.committeechairSandu, Adrianen_US
dc.contributor.committeememberZhang, Liqingen_US
dc.contributor.committeememberTu, Zhijian Jakeen_US
dc.contributor.committeememberBaumann, William T.en_US
dc.contributor.committeememberShaffer, Clifford A.en_US
dc.type.dcmitypeTexten_US
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-08172012-094352/en_US
dc.date.sdate2012-08-17en_US
dc.date.rdate2013-08-28
dc.date.adate2012-08-27en_US


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