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Georgia Tech

1. Rosen, Gail L. Signal processing for biologically-inspired gradient source localization and DNA sequence analysis.

Degree: PhD, Electrical and Computer Engineering, 2006, Georgia Tech

Biological signal processing can help us gain knowledge about biological complexity, as well as using this knowledge to engineer better systems. Three areas are identified as critical to understanding biology: 1) understanding DNA, 2) examining the overall biological function and 3) evaluating these systems in environmental (ie: turbulent) conditions. DNA is investigated for coding structure and redundancy, and a new tandem repeat region, an indicator of a neurodegenerative disease, is discovered. The linear algebraic framework can be used for further analysis and techniques. The work illustrates how signal processing is a tool to reverse engineer biological systems, and how our better understanding of biology can improve engineering designs. Then, the way a single-cell mobilizes in response to a chemical gradient, known as chemotaxis, is examined. Inspiration from receptor clustering in chemotaxis combined with a Hebbian learning method is shown to improve a gradient-source (chemical/thermal) localization algorithm. The algorithm is implemented, and its performance is evaluated in diffusive and turbulent environments. We then show that sensor cross-correlation can be used in solving chemical localization in difficult turbulent scenarios. This leads into future techniques which can be designed for gradient source tracking. These techniques pave the way for use of biologically-inspired sensor networks in chemical localization. Advisors/Committee Members: Paul Hasler (Committee Chair), David Anderson (Committee Member), James H. McClellan (Committee Member), Mark T. Smith (Committee Member), Oliver Brand (Committee Member).

Subjects/Keywords: DNA analysis; Ficks second law; Hebbian learning; Biased random walk; Sensor cross-correlation; Delay-and-Sum beamforming; Turbulent plumes; Electronic nose; Tandem repeats; Gradient sensing; Bacterial chemotaxis navigation; Chemotaxis; Sensor networks; Signal processing; Biologically-inspired computing; Chemotaxis; Nervous system Degeneration; Nucleotide sequence

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Rosen, G. L. (2006). Signal processing for biologically-inspired gradient source localization and DNA sequence analysis. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/11628

Chicago Manual of Style (16th Edition):

Rosen, Gail L. “Signal processing for biologically-inspired gradient source localization and DNA sequence analysis.” 2006. Doctoral Dissertation, Georgia Tech. Accessed October 20, 2020. http://hdl.handle.net/1853/11628.

MLA Handbook (7th Edition):

Rosen, Gail L. “Signal processing for biologically-inspired gradient source localization and DNA sequence analysis.” 2006. Web. 20 Oct 2020.

Vancouver:

Rosen GL. Signal processing for biologically-inspired gradient source localization and DNA sequence analysis. [Internet] [Doctoral dissertation]. Georgia Tech; 2006. [cited 2020 Oct 20]. Available from: http://hdl.handle.net/1853/11628.

Council of Science Editors:

Rosen GL. Signal processing for biologically-inspired gradient source localization and DNA sequence analysis. [Doctoral Dissertation]. Georgia Tech; 2006. Available from: http://hdl.handle.net/1853/11628

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