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Deciphering the genetic regulatory code using an inverse error control coding framework.

Description: We have found that developing a computational framework for reconstructing error control codes for engineered data and ultimately for deciphering genetic regulatory coding sequences is a challenging and uncharted area that will require advances in computational technology for exact solutions. Although exact solutions are desired, computational approaches that yield plausible solutions would be considered sufficient as a proof of concept to the feasibility of reverse engineering error control codes and the possibility of developing a quantitative model for understanding and engineering genetic regulation. Such evidence would help move the idea of reconstructing error control codes for engineered and biological systems from the high risk high payoff realm into the highly probable high payoff domain. Additionally this work will impact biological sensor development and the ability to model and ultimately develop defense mechanisms against bioagents that can be engineered to cause catastrophic damage. Understanding how biological organisms are able to communicate their genetic message efficiently in the presence of noise can improve our current communication protocols, a continuing research interest. Towards this end, project goals include: (1) Develop parameter estimation methods for n for block codes and for n, k, and m for convolutional codes. Use methods to determine error control (EC) code parameters for gene regulatory sequence. (2) Develop an evolutionary computing computational framework for near-optimal solutions to the algebraic code reconstruction problem. Method will be tested on engineered and biological sequences.
Date: March 1, 2005
Creator: Rintoul, Mark Daniel; May, Elebeoba Eni; Brown, William Michael; Johnston, Anna Marie & Watson, Jean-Paul
Partner: UNT Libraries Government Documents Department

Detection and reconstruction of error control codes for engineered and biological regulatory systems.

Description: A fundamental challenge for all communication systems, engineered or living, is the problem of achieving efficient, secure, and error-free communication over noisy channels. Information theoretic principals have been used to develop effective coding theory algorithms to successfully transmit information in engineering systems. Living systems also successfully transmit biological information through genetic processes such as replication, transcription, and translation, where the genome of an organism is the contents of the transmission. Decoding of received bit streams is fairly straightforward when the channel encoding algorithms are efficient and known. If the encoding scheme is unknown or part of the data is missing or intercepted, how would one design a viable decoder for the received transmission? For such systems blind reconstruction of the encoding/decoding system would be a vital step in recovering the original message. Communication engineers may not frequently encounter this situation, but for computational biologists and biotechnologist this is an immediate challenge. The goal of this work is to develop methods for detecting and reconstructing the encoder/decoder system for engineered and biological data. Building on Sandia's strengths in discrete mathematics, algorithms, and communication theory, we use linear programming and will use evolutionary computing techniques to construct efficient algorithms for modeling the coding system for minimally errored engineered data stream and genomic regulatory DNA and RNA sequences. The objective for the initial phase of this project is to construct solid parallels between biological literature and fundamental elements of communication theory. In this light, the milestones for FY2003 were focused on defining genetic channel characteristics and providing an initial approximation for key parameters, including coding rate, memory length, and minimum distance values. A secondary objective addressed the question of determining similar parameters for a received, noisy, error-control encoded data set. In addition to these goals, we initiated exploration of algorithmic approaches to determine ...
Date: October 1, 2003
Creator: May, Elebeoba Eni; Rintoul, Mark Daniel; Johnston, Anna Marie; Pryor, Richard J.; Hart, William Eugene & Watson, Jean-Paul
Partner: UNT Libraries Government Documents Department

Unique Signal mathematical analysis task group FY03 status report.

Description: The Unique Signal is a key constituent of Enhanced Nuclear Detonation Safety (ENDS). Although the Unique Signal approach is well prescribed and mathematically assured, there are numerous unsolved mathematical problems that could help assess the risk of deviations from the ideal approach. Some of the mathematics-based results shown in this report are: 1. The risk that two patterns with poor characteristics (easily generated by inadvertent processes) could be combined through exclusive-or mixing to generate an actual Unique Signal pattern has been investigated and found to be minimal (not significant when compared to the incompatibility metric of actual Unique Signal patterns used in nuclear weapons). 2. The risk of generating actual Unique Signal patterns with linear feedback shift registers is minimal, but the patterns in use are not as invulnerable to inadvertent generation by dependent processes as previously thought. 3. New methods of testing pair-wise incompatibility threats have resulted in no significant problems found for the set of Unique Signal patterns currently used. Any new patterns introduced would have to be carefully assessed for compatibility with existing patterns, since some new patterns under consideration were found to be deficient when associated with other patterns in use. 4. Markov models were shown to correspond to some of the engineered properties of Unique Signal sequences. This gives new support for the original design objectives. 5. Potential dependence among events (caused by a variety of communication protocols) has been studied. New evidence has been derived of the risk associated with combined communication of multiple events, and of the improvement in abnormal-environment safety that can be achieved through separate-event communication.
Date: December 1, 2003
Creator: Baty, Roy Stuart (Los Alamos National Laboratory, Los Alamos, NM); Johnston, Anna Marie; Hart, Elizabeth (Utah State University, Logan, UT); White, Allan (NASA, Langley Research Center, Hampton, VA) & Cooper, James Arlin
Partner: UNT Libraries Government Documents Department