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

Abstract

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 themore » 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 if a data set could be approximated with an error-control code and performed initial investigations into optimization based methodologies for extracting the encoding algorithm given the coding rate of an encoded noise-free and noisy data stream.« less

Authors:
; ; ; ; ;
Publication Date:
Research Org.:
Sandia National Laboratories
Sponsoring Org.:
USDOE
OSTI Identifier:
918239
Report Number(s):
SAND2003-3963
TRN: US200818%%324
DOE Contract Number:
AC04-94AL85000
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; 99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; ALGORITHMS; APPROXIMATIONS; COMMUNICATIONS; DESIGN; DETECTION; DNA; ENGINEERS; EXPLORATION; GENETICS; LINEAR PROGRAMMING; OPTIMIZATION; RNA; TRANSCRIPTION

Citation Formats

May, Elebeoba Eni, Rintoul, Mark Daniel, Johnston, Anna Marie, Pryor, Richard J., Hart, William Eugene, and Watson, Jean-Paul. Detection and reconstruction of error control codes for engineered and biological regulatory systems.. United States: N. p., 2003. Web. doi:10.2172/918239.
May, Elebeoba Eni, Rintoul, Mark Daniel, Johnston, Anna Marie, Pryor, Richard J., Hart, William Eugene, & Watson, Jean-Paul. Detection and reconstruction of error control codes for engineered and biological regulatory systems.. United States. doi:10.2172/918239.
May, Elebeoba Eni, Rintoul, Mark Daniel, Johnston, Anna Marie, Pryor, Richard J., Hart, William Eugene, and Watson, Jean-Paul. Wed . "Detection and reconstruction of error control codes for engineered and biological regulatory systems.". United States. doi:10.2172/918239. https://www.osti.gov/servlets/purl/918239.
@article{osti_918239,
title = {Detection and reconstruction of error control codes for engineered and biological regulatory systems.},
author = {May, Elebeoba Eni and Rintoul, Mark Daniel and Johnston, Anna Marie and Pryor, Richard J. and Hart, William Eugene and Watson, Jean-Paul},
abstractNote = {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 if a data set could be approximated with an error-control code and performed initial investigations into optimization based methodologies for extracting the encoding algorithm given the coding rate of an encoded noise-free and noisy data stream.},
doi = {10.2172/918239},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Oct 01 00:00:00 EDT 2003},
month = {Wed Oct 01 00:00:00 EDT 2003}
}

Technical Report:

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