Signal processing for biologically-inspired gradient source localization and DNA sequence analysis

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

Rosen, Gail L. ; Electrical and Computer Engineering

University:Georgia Institute of Technology

Department:Electrical and Computer Engineering

关键词: 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;   

Others  :  https://smartech.gatech.edu/bitstream/1853/11628/1/rosen_gail_l_200608_phd.pdf

美国|英语

来源: SMARTech Repository

【 摘 要 】

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.