Numerical representation of DNA sequences

Kwan, Hon Keung; Arniker, Swarna Bai

doi:10.1109/eit.2009.5189632

Cited by 69 publications

(57 citation statements)

References 22 publications

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“…In FM techniques, the nucleotides of DNA data are transformed into a series of arbitrary numerical sequences [5]. These techniques are represented by two choices [6].…”

Section: Fixed Mapping Of Dna Sequencementioning

confidence: 99%

“…The second choice is based on the geometric representations where meaningful real or complex numbers are assigned to the four characters A, T, G, and C. In this way a single numerical sequence representing the entire character string is obtained. In general FM techniques [5] include the Voss [7], the tetrahedron [2], the complex [8]- [11], the integer [9], the real [12], and the quaternion [13] - [14] representations. Each of the DNA numerical representations offers different properties as will be show in details in the following sections.…”

Section: Fixed Mapping Of Dna Sequencementioning

confidence: 99%

“…The computational complexity can be reduced either at mapping process or at implementation time. In recent years [4]- [5], a number of schemes have been introduced to map DNA nucleotides into numerical values. Some possible desirable properties of a DNA numerical representation include:…”

Section: Introductionmentioning

confidence: 99%

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Genomic Analysis and Classification of Exon and Intron Sequences Using DNA Numerical Mapping Techniques

Abo‐Zahhad¹,

Ahmed²,

Abd-Elrahman³

2012

IJITCS

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Abstract-Using digital signal processing in genomic field is a key of solving most problems in this area such as prediction of gene locations in a genomic sequence and identifying the defect regions in DNA sequence. It is found that, using DSP is possible only if the symbol sequences are mapped into numbers. In literature many techniques have been developed for numerical representation of DNA sequences. They can be classified into two types, Fixed Mapping (FM) and Physico Chemical Property Based Mapping (PCPBM ( . The open question is that, which one of these numerical representation techniques is to be used? The answer to this question needs understanding these numerical representations considering the fact that each mapping depends on a particular application. This paper explains this answer and introduces comparison between these techniques in terms of their precision in exon and intron classification. Simulations are carried out using short sequences of the human genome (GRch37/hg19). The final results indicate that the classification performance is a function of the numerical representation method.

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“…In FM techniques, the nucleotides of DNA data are transformed into a series of arbitrary numerical sequences [5]. These techniques are represented by two choices [6].…”

Section: Fixed Mapping Of Dna Sequencementioning

confidence: 99%

Section: Fixed Mapping Of Dna Sequencementioning

confidence: 99%

See 1 more Smart Citation

Genomic Analysis and Classification of Exon and Intron Sequences Using DNA Numerical Mapping Techniques

Abo‐Zahhad¹,

Ahmed²,

Abd-Elrahman³

2012

IJITCS

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show abstract

“…Other representations include the quaternion approach [15], the electron-ion interaction potential method [20], real-number representation [21], complex number mapping [22], etc. The most commonly used method in spectrum analysis is the discrete Fourier transform (DFT) [23], as shown in Eq.…”

Section: Fourier Transform and Digital Signal Processingmentioning

confidence: 99%

A Comprehensive Review of Emerging Computational Methods for Gene Identification

2016

J Inf Process Syst

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Gene identification is at the center of genomic studies. Although the first phase of the Encyclopedia of DNA Elements (ENCODE) project has been claimed to be complete, the annotation of the functional elements is far from being so. Computational methods in gene identification continue to play important roles in this area and other relevant issues. So far, a lot of work has been performed on this area, and a plethora of computational methods and avenues have been developed. Many review papers have summarized these methods and other related work. However, most of them focus on the methodologies from a particular aspect or perspective. Different from these existing bodies of research, this paper aims to comprehensively summarize the mainstream computational methods in gene identification and tries to provide a short but concise technical reference for future studies. Moreover, this review sheds light on the emerging trends and cutting-edge techniques that are believed to be capable of leading the research on this field in the future.

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“…Such a mapping is called numerical representation and its choice affects how well the biological properties of a nucleotide sequence can be revealed in numerical domain. A nucleotide sequence can be numerically represented in the form of R-sequence, a survey on mappings with R ≥ 1 is given in [3,4]. 1-sequence numerical representation (with R = 1) is the most compact form of mapping in which one nucleotide is mapped to one fixed numerical value to form a single sequence.…”

Section: Introductionmentioning

confidence: 99%

Novel methodologies for spectral classification of exon and intron sequences

Kwan

2012

EURASIP J. Adv. Signal Process.

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Digital processing of a nucleotide sequence requires it to be mapped to a numerical sequence in which the choice of nucleotide to numeric mapping affects how well its biological properties can be preserved and reflected from nucleotide domain to numerical domain. Digital spectral analysis of nucleotide sequences unfolds a period-3 power spectral value which is more prominent in an exon sequence as compared to that of an intron sequence. The success of a period-3 based exon and intron classification depends on the choice of a threshold value. The main purposes of this article are to introduce novel codes for 1-sequence numerical representations for spectral analysis and compare them to existing codes to determine appropriate representation, and to introduce novel thresholding methods for more accurate period-3 based exon and intron classification of an unknown sequence. The main findings of this study are summarized as follows: Among sixteen 1-sequence numerical representations, the K-Quaternary Code I offers an attractive performance. A windowed 1-sequence numerical representation (with window length of 9, 15, and 24 bases) offers a possible speed gain over non-windowed 4-sequence Voss representation which increases as sequence length increases. A winner threshold value (chosen from the best among two defined threshold values and one other threshold value) offers a top precision for classifying an unknown sequence of specified fixed lengths. An interpolated winner threshold value applicable to an unknown and arbitrary length sequence can be estimated from the winner threshold values of fixed length sequences with a comparable performance. In general, precision increases as sequence length increases. The study contributes an effective spectral analysis of nucleotide sequences to better reveal embedded properties, and has potential applications in improved genome annotation.

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Numerical representation of DNA sequences

Cited by 69 publications

References 22 publications

Genomic Analysis and Classification of Exon and Intron Sequences Using DNA Numerical Mapping Techniques

Genomic Analysis and Classification of Exon and Intron Sequences Using DNA Numerical Mapping Techniques

A Comprehensive Review of Emerging Computational Methods for Gene Identification

Novel methodologies for spectral classification of exon and intron sequences

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