Genomic Detection Using Sparsity-inspired Tools

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dc.contributor.advisorBaraniuk, Richard G.en_US
dc.creatorSheikh, Mona A.en_US
dc.date.accessioned2013-03-08T00:38:51Zen_US
dc.date.available2013-03-08T00:38:51Zen_US
dc.date.issued2011en_US
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.en_US
dc.format.extent108 p.en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.callnoTHESIS E.E. 2011 SHEIKHen_US
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>.en_US
dc.identifier.digitalSheikhMen_US
dc.identifier.urihttps://hdl.handle.net/1911/70441en_US
dc.language.isoengen_US
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.en_US
dc.subjectApplied sciencesen_US
dc.subjectBiological sciencesen_US
dc.subjectGenomic detectionen_US
dc.subjectWhole genome sequencingen_US
dc.subjectBacterial detectionen_US
dc.subjectMolecular biologyen_US
dc.subjectElectrical engineeringen_US
dc.subjectBioinformaticsen_US
dc.titleGenomic Detection Using Sparsity-inspired Toolsen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentElectrical Engineeringen_US
thesis.degree.disciplineEngineeringen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelDoctoralen_US
thesis.degree.nameDoctor of Philosophyen_US
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