Genomic Detection Using Sparsity-inspired Tools

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dc.contributor.advisorBaraniuk, Richard G.
dc.creatorSheikh, Mona A.
dc.date.accessioned2013-03-08T00:38:51Z
dc.date.available2013-03-08T00:38:51Z
dc.date.issued2011
dc.description.abstractGenome-based detection methods provide the most conclusive means for establishing the presence of microbial species. A prime example of their use is in the detection of bacterial species, many of which are naturally vital or dangerous to human health, or can be genetically engineered to be so. However, current genomic detection methods are cost-prohibitive and inevitably use unique sensors that are specific to each species to be detected. In this thesis we advocate the use of combinatorial and non-specific identifiers for detection, made possible by exploiting the sparsity inherent in the species detection problem in a clinical or environmental sample. By modifying the sensor design process, we have developed new molecular biology tools with advantages that were not possible in their previous incarnations. Chief among these advantages are a universal species detection platform, the ability to discover unknown species, and the elimination of PCR, an expensive and laborious amplification step prerequisite in every molecular biology detection technique. Finally, we introduce a sparsity-based model for analyzing the millions of raw sequencing reads generated during whole genome sequencing for species detection, and achieve significant reductions in computational speed and high accuracy.
dc.format.extent108 p.en_US
dc.format.mimetypeapplication/pdf
dc.identifier.callnoTHESIS E.E. 2011 SHEIKH
dc.identifier.citationSheikh, Mona A.. "Genomic Detection Using Sparsity-inspired Tools." (2011) Diss., Rice University. <a href="https://hdl.handle.net/1911/70441">https://hdl.handle.net/1911/70441</a>.
dc.identifier.digitalSheikhMen_US
dc.identifier.urihttps://hdl.handle.net/1911/70441
dc.language.isoeng
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.
dc.subjectApplied sciences
dc.subjectBiological sciences
dc.subjectGenomic detection
dc.subjectWhole genome sequencing
dc.subjectBacterial detection
dc.subjectMolecular biology
dc.subjectElectrical engineering
dc.subjectBioinformatics
dc.titleGenomic Detection Using Sparsity-inspired Tools
dc.typeThesis
dc.type.materialText
thesis.degree.departmentElectrical Engineering
thesis.degree.disciplineEngineering
thesis.degree.grantorRice University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy
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