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dc.contributor.advisorIqbal, Samir M.
dc.creatorMansur, Nuzhat
dc.date.accessioned2017-10-06T20:31:33Z
dc.date.available2017-10-06T20:31:33Z
dc.date.created2017-08
dc.date.issued2017-10-06
dc.date.submittedAugust 2017
dc.identifier.urihttp://hdl.handle.net/10106/27011
dc.description.abstractMetastasis is the leading cause of cancer related deaths. Early detection of cancer cells can enable early disease diagnosis and stage specific therapeutics. Metastatic cancer cells have abnormal expression of certain proteins. One such protein is Epidermal Growth Factor Receptor (EGFR). Anti-EGFR aptamers have emerged as more effective probe molecules for selectively binding with EGFR compared to antibodies. Capturing cancer cells with aptamer is an emerging and developing technique for cancer cell isolation. Nanotextured substrates inspired by naturally occurring basement membranes are promising platform for triggering unique cell behavior. Along with the biochemical and physical techniques to probe cancer cell behavior, mathematical analysis using high performing computers is proving to be highly efficient for accurate and fast inference. This work is presented with the anticipation of presenting a novel and exciting approach based on computational analysis of cellular behavior on physically and biochemically modified substrates to detect metastatic cancer cells at early stage. This research focuses on two major areas. One is observing, understanding and modifying cellular behavior on functionalized substrates. The other focus is utilizing the developed platform for cancer detection similar to a clinical setting and ultimately pave the path for a future point of care device.
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.subjectMetastatic cancer
dc.subjectEarly detection
dc.subjectBreast cancer
dc.subjectBladder cancer
dc.subjectNanotextured substrate
dc.subjectFunctionalization
dc.subjectDistance matrix
dc.titleEARLY DETECTION OF METASTATIC CANCER USING COMPUTATIONAL ANALYSIS
dc.typeThesis
dc.date.updated2017-10-06T20:31:34Z
thesis.degree.departmentElectrical Engineering
thesis.degree.grantorThe University of Texas at Arlington
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy in Electrical Engineering
dc.type.materialtext


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