The role of the symbolic-to-numerical mapping in the detection of DNA periodicities

Rushdi, Ahmad; Tuqan, J.

doi:10.1109/gensips.2008.4555680

Cited by 5 publications

(2 citation statements)

References 18 publications

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“…Notice that the latter shows the complementary property, in the same way as in the complex assignment (19). Rushdi and Tuqan [17] proposed a generic matrix based framework that comprises most of the mappings reported in the literature as special cases and can allow a number of potential new mappings.…”

Section: Numerical Representation Of Genomic Sequencesmentioning

confidence: 99%

Digital Signal Processing in the Analysis of Genomic Sequences

Lorenzo-Ginori

Rodriguez-Fuentes

Abalo

et al. 2009

CBIO

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Digital Signal Processing (DSP) applications in Bioinformatics have received great attention in recent years, where new effective methods for genomic sequence analysis, such as the detection of coding regions, have been developed. The use of DSP principles to analyze genomic sequences requires defining an adequate representation of the nucleotide bases by numerical values, converting the nucleotide sequences into time series. Once this has been done, all the mathematical tools usually employed in DSP are used in solving tasks such as identification of protein coding DNA regions, identification of reading frames, and others. In this article we present an overview of the most relevant applications of DSP algorithms in the analysis of genomic sequences, showing the main results obtained by using these techniques, analyzing their relative advantages and drawbacks, and providing relevant examples. We finally analyze some perspectives of DSP in Bioinformatics, considering recent research results on algebraic structures of the genetic code, which suggest other new DSP applications in this field, as well as the new field of Genomic Signal Processing.

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Section: Numerical Representation Of Genomic Sequencesmentioning

confidence: 99%

Digital Signal Processing in the Analysis of Genomic Sequences

Lorenzo-Ginori

Rodriguez-Fuentes

Abalo

et al. 2009

CBIO

View full text Add to dashboard Cite

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“…One approach to answer this question was presented in [27], where a novel framework for the analysis of the equivalence of the mappings used for numerical representation of symbolic data based on signal correlation was presented, along with strong and weak equivalence properties. In [28], we attempted to answer the same question starting at the aforementioned DSP model for a limited set of mappings. Our main goal in this study is to de-embed the symbolic to numerical mapping process from the DNA spectrum computation process.…”

Section: Introductionmentioning

confidence: 99%

Map-invariant spectral analysis for the identification of DNA periodicities

Rushdi

Tuqan

Strohmer

2012

J Bioinform Sys Biology

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Many signal processing based methods for finding hidden periodicities in DNA sequences have primarily focused on assigning numerical values to the symbolic DNA sequence and then applying spectral analysis tools such as the short-time discrete Fourier transform (ST-DFT) to locate these repeats. The key results pertaining to this approach are however obtained using a very specific symbolic to numerical map, namely the so-called Voss representation. An important research problem is to therefore quantify the sensitivity of these results to the choice of the symbolic to numerical map. In this article, a novel algebraic approach to the periodicity detection problem is presented and provides a natural framework for studying the role of the symbolic to numerical map in finding these repeats. More specifically, we derive a new matrix-based expression of the DNA spectrum that comprises most of the widely used mappings in the literature as special cases, shows that the DNA spectrum is in fact invariable under all these mappings, and generates a necessary and sufficient condition for the invariance of the DNA spectrum to the symbolic to numerical map. Furthermore, the new algebraic framework decomposes the periodicity detection problem into several fundamental building blocks that are totally independent of each other. Sophisticated digital filters and/or alternate fast data transforms such as the discrete cosine and sine transforms can therefore be always incorporated in the periodicity detection scheme regardless of the choice of the symbolic to numerical map. Although the newly proposed framework is matrix based, identification of these periodicities can be achieved at a low computational cost.

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A DSP Approach for Finding the Codon Bias in DNA Sequences

Tuqan

Rushdi

2008

IEEE J. Sel. Top. Signal Process.

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The role of the symbolic-to-numerical mapping in the detection of DNA periodicities

Cited by 5 publications

References 18 publications

Digital Signal Processing in the Analysis of Genomic Sequences

Digital Signal Processing in the Analysis of Genomic Sequences

Map-invariant spectral analysis for the identification of DNA periodicities

A DSP Approach for Finding the Codon Bias in DNA Sequences

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