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Graduate Defense: Shoshanna Llewellyn

November 18 @ 3:00 pm - 4:00 pm MST

Thesis Information

Title: Structure Aware Smart Encoding and Decoding of Information in DNA

Program: Master of Science in Computer Science

Advisor: Dr. Timothy Andersen, Computer Science

Committee Members: Dr. Will Hughes, Materials Science and Engineering, Dr. Edoardo Serra, Computer Science, and Dr. Reza Zadegan, Computer Science and Materials Science and Engineering

Abstract

Our increasingly information driven world is growing the demand for new storage technologies. By 2025 the total digital data will approach 175 zetabytes. DNA is an attractive technology due to its incredible density (several magnitudes higher than flash memory), almost negligable energy requirements, and data retention measured in centuries. DNA does come with many new challenges. It is an organic compound with complex internal interactions that complicates the design and synthesis of DNA sequences for the purpose of data storage. In this work we demonstrate a new encoding technique that can account for these challenges in encoding and decoding, including the secondary structure of the sequence, repeated nucleotides, unwanted subsequences, as well as the GC content, vital for ensuring stable sequences. This is done by using a graph representation of the possible encoding space combined with a search algorithm that accounts for these interactions. The decoding side of this algorithm, which functions on the same principle as the encoder, is also able to correct basic single point errors without the aid of error correction codes, something no current competing algorithm is capable of.