Coding theory based models for protein translation initiation in prokaryotic organisms

May, Elebeoba; Vouk, Mladen A.; Bitzer, Donald L.; Rosnick, David

doi:10.1016/j.biosystems.2004.05.017

Cited by 27 publications

(19 citation statements)

References 40 publications

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“…Of the three block code models constructed, G 1 6~(~,~) represented prokaryotic translation initiation the best. The generator G16S(s,2) distinguished between valid and invalid leader regions within the Shine-Dalgarno region, a behavior consistent with the original block code model [17]. Although GOrjginal(s,z) and GOrjgDmjn(s,2) produced regions where there are differences between leader and non-leader sequence groups, the behavior of the leader sequences are the inverse of what is expected.…”

Section: Construction Of Optimal Generators For the Initiation Processsupporting

confidence: 52%

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

May¹,

Rintoul²,

Johnston³

et al. 2003

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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 or intercepted, how would one design a viable decoder for the received transmission? For such systems blind reconstruction of the encodingldecoding 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.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 The goal of this work is to develop methods for detecting and reconstructing the encoderldecoder 3 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 methodolgies for extracting the encoding algorithm given the coding rate of an encoded noise-free and noisy data stream.

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Section: Construction Of Optimal Generators For the Initiation Processsupporting

confidence: 52%

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

May¹,

Rintoul²,

Johnston³

et al. 2003

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“…The mean experimental in [23] and limiting distributions using both matrices P and PAM 250 are displayed in Table 2. The mean experimental and limiting distributions, for each class, are very close except for the class of amino acids corresponding to six codons obtained from the limiting distribution using the probability transition matrix P. The reason is that arginine, which is coded by six codons, appears with a much lower frequency than 6 61 . This has been ascribed to the rare appearance of the CG base doublet so that, in fact, in most observed proteins, arginine is coded only by AGA and AGG [4].…”

Section: Protein Communication Channelmentioning

confidence: 76%

“…That is the channel of the genetic communication system is the translation process. May [6], [9] and Rosen [8] consider the channel to be the replication and transcription processes whereas the translation process models the decoder of the system. However, both models are inconsistent with engineering communication systems, which model transmission and storage of the same messages at the source and destination (excluding errors due to channel degradation).…”

Section: Introductionmentioning

confidence: 99%

Protein Communication System: Evolution and Genomic Structure

Bouaynaya

Schonfeld

2007

Algorithmica

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Abstract.We develop a mathematical model of the genetic information storage and transmission system and investigate its properties. Breaking with tradition, whereas the genetic information storage and transmission apparatus is conventionally modelled as an engineering communication system with the DNA sequence as the input and the amino acid chain as the output, in this paper the genetic communication model is viewed as one between proteins. A connection in a series of protein communication systems is equivalent to a channel through time: the Channel of Evolution. We investigate the dynamics of the channel of evolution in both cases of a constant and time-variant point mutation rates. We prove that the distribution of amino acids converges geometrically to a specific distribution which matches nearly perfectly an estimate of the natural abundance of amino acids in Nature today. Moreover, based on the highly redundant structure of the encoded genetic message (i.e., DNA), we demonstrate that the role of introns in eukaryotic genomes is to maintain a fine balance between two competing yet complementary forces: stability and adaptability. The stability role is evaluated by showing that introns play the role of a decoy in absorbing mutations. We derive the optimal exon length distribution, which minimizes the probability of error in eukaryotic genomes. Furthermore, to understand how Nature can physically achieve such a distribution, we propose a diffusive random walk model for exon generation throughout evolution. This model results in an alpha stable distribution, which is asymptotically equivalent to the optimal distribution. Experimental results on various eukaryotic organisms spanning the phylogenetic tree from unicellular organisms to plants to vertebrates show that both distributions accurately fit the biological data.

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“…Particularly, by analyzing the gene expression process, various analogies with the field of digital data transmission can be clearly noticed. Principles from communications, coding, information theory, detection theory, and pattern recognition can be utilized to reveal further similarities between the latter fields [1]- [6].…”

Section: Introductionmentioning

confidence: 99%

Bayesian Classification of Ribosome Binding Sites in Prokaryotic Genome Sequences: A Communications Theory Approach

Bataineh¹,

Al-qudah²

2017

IJBBB

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Dramatic advances in genomics and computational biology have resulted in large amounts of data and have encouraged the development of computational algorithms for the identification and analysis of coding regions. This paper proposes a novel application of fundamental principles and concepts from communications theory for the identification of exact translation initiation sites in prokaryotic genomes. It employs several Bayesian classifiers to assess the performance of the ribosome binding sites detection algorithms investigated in this work. The proposed classification algorithms utilize well-known principles in communications theory such as cross correlation and Euclidean distance based metrics to make precise real-time decisions of weather a given open reading frame (ORF) is a valid protein coding region or not. The simulation results confirm that the proposed Bayesian classification algorithms can provide a efficient and accurate gene identification with sensitivity and specificity values comparable to the ones obtained by the well-known prokaryotic gene detection methods such as GLIMMER and GeneMark. This further confirms the significance of applying communications theory concepts to genomic sequence analysis.

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Coding theory based models for protein translation initiation in prokaryotic organisms

Cited by 27 publications

References 40 publications

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

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

Protein Communication System: Evolution and Genomic Structure

Bayesian Classification of Ribosome Binding Sites in Prokaryotic Genome Sequences: A Communications Theory Approach

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