On DNA numerical representations for genomic similarity computation

Genomic signal processing (GSP) refers to the use of signal processing for the analysis of genomic data. GSP methods require the transformation or mapping of the genomic data to a numeric representation. To date, several DNA numeric representations (DNR) have been proposed; however, it is not clear...

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Bibliographic Details
Published in:PloS one 2017-03, Vol.12 (3), p.e0173288-e0173288
Main Authors: Mendizabal-Ruiz, Gerardo, Román-Godínez, Israel, Torres-Ramos, Sulema, Salido-Ruiz, Ricardo A, Morales, J Alejandro
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Animals
Biology and Life Sciences
Computer Simulation
Cyclooxygenase 1 - genetics
Data processing
Databases, Genetic
Deoxyribonucleic acid
DNA
DNA sequencing
Ecology and Environmental Sciences
Encyclopedias
Evolution
Fourier transforms
Gene mapping
Gene sequencing
Genomics
Humans
Molecular biology
Nucleotide sequence
Phylogenetics
Proteins
Representations
Research and analysis methods
Ribosomal Proteins - genetics
Sequence Analysis, DNA - methods
Sequence Homology
Signal processing
Signal Processing, Computer-Assisted
Similarity
Transformation
Transformations (mathematics)
Values
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Summary:Genomic signal processing (GSP) refers to the use of signal processing for the analysis of genomic data. GSP methods require the transformation or mapping of the genomic data to a numeric representation. To date, several DNA numeric representations (DNR) have been proposed; however, it is not clear what the properties of each DNR are and how the selection of one will affect the results when using a signal processing technique to analyze them. In this paper, we present an experimental study of the characteristics of nine of the most frequently-used DNR. The objective of this paper is to evaluate the behavior of each representation when used to measure the similarity of a given pair of DNA sequences.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0173288