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

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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 ... continued below

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42 p.

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May, Elebeoba Eni; Rintoul, Mark Daniel; Johnston, Anna Marie; Pryor, Richard J.; Hart, William Eugene & Watson, Jean-Paul October 1, 2003.

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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 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.

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42 p.

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  • Report No.: SAND2003-3963
  • Grant Number: AC04-94AL85000
  • DOI: 10.2172/918239 | External Link
  • Office of Scientific & Technical Information Report Number: 918239
  • Archival Resource Key: ark:/67531/metadc889138

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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  • October 1, 2003

Added to The UNT Digital Library

  • Sept. 22, 2016, 2:13 a.m.

Description Last Updated

  • Dec. 7, 2016, 10:33 a.m.

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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., report, October 1, 2003; United States. (digital.library.unt.edu/ark:/67531/metadc889138/: accessed December 17, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.