Title

Biologically Inspired Wireless Sensor Networking

Presenter Information

Alec Bayliff

Department

Electrical and Computer Engineering

Major

Computer Engineering

Research Advisor

Das, Sajal K.

Advisor's Department

Computer Science

Funding Source

National Science Foundation

Abstract

Gene regulatory networks (GRNs) involve the interactions of proteins in collections of DNA segments. Understanding GRNs has many applications in both biological and computational sciences, ranging from a potential cure for cancer to solving problems incurred by maintaining large scale sensor networks. The study of the GRNs has boomed over the past several years, as DNA sequencing technology has progressed, unlocking the potential of understanding the GRN by analyzing the regulatory process more in-depth. The objective of this research is to analyze the graph representations of E. coli and yeast GRNs for the purpose of creating similar scale-free networks able to be used for robust, efficient wireless sensor networking.

Biography

Alec Bayliff is a senior in computer engineering at the Missouri University of Science and Technology. He is the robotic arm team lead for the Telemetry and Controls division of the Missouri S&T Mars Rover Design Team. Alec also participates as an officer of the Institute of Electrical and Electronics Engineers as well as Miners in Space. Alec recently completed an REU with CReWMaN labs in the computer science department at Missouri S&T.

Research Category

Sciences

Presentation Type

Poster Presentation

Document Type

Poster

Location

Upper Atrium/Hall

Presentation Date

15 Apr 2015, 9:00 am - 11:45 am

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Apr 15th, 9:00 AM Apr 15th, 11:45 AM

Biologically Inspired Wireless Sensor Networking

Upper Atrium/Hall

Gene regulatory networks (GRNs) involve the interactions of proteins in collections of DNA segments. Understanding GRNs has many applications in both biological and computational sciences, ranging from a potential cure for cancer to solving problems incurred by maintaining large scale sensor networks. The study of the GRNs has boomed over the past several years, as DNA sequencing technology has progressed, unlocking the potential of understanding the GRN by analyzing the regulatory process more in-depth. The objective of this research is to analyze the graph representations of E. coli and yeast GRNs for the purpose of creating similar scale-free networks able to be used for robust, efficient wireless sensor networking.