A New Numerical Method for DNA Sequence Analysis Based on 8-Dimensional Vector Representation

Abstract

Background: The multiple sequence alignment (MSA) algorithms are the traditional ways to compare and analyze DNA sequences. However, for large DNA sequences, these algorithms require a long time computationally. Objective: Here we will propose a new numerical method to characterize and compare DNA sequences quickly. Method: Based on a new 2-dimensional (2D) graphical representation of DNA sequences, we can obtain an 8-dimensional vector using two basic concepts of probability, the mean and the variance. Results: We perform similarity/dissimilarity analyses among two real DNA data sets, the coding sequences of the first exon of beta-globin gene of 11 species and 31 mammalian mitochondrial genomes, respectively. Conclusion: Our results are in agreement with the existing analyses in our literatures. We also compare our approach with other methods and find that ours is more effective. IntroductionWith the rapid growth in biological data, how to get more information from these big data is a challenge for scientists. For this purpose, an important problem is to find a suitable way to digitize these DNA sequences so that the sequence comparison can be applied. For computational time reason, beyond the traditional multiple sequence alignment (MSA), many alignment-free sequence comparison methods were introduced, for more details, please refer to [1] [2] [3] and the references therein.

Graphical Approach to Unveil Evolutionary Relationship from DNA Sequence Analysis

“…Each edge is given a weight based on the distance [20]. DN A sequence analysis by numerical characterization can be seen in [21][22][23].…”

The Effect of Numerical Mapping Techniques on Performance in Genomic Research

“…X=[AGCTACCGTG]𝑋 ̂ = [70, 78,58, 66, 70,58,58, 78, 66, 78] Atomic numbers are assigned to nucleotides.X=[AGCTACCGTG] 𝑋 ̂(ⅈ) = [62,62, 42, 42, 62, 42, 42, 62, 42, 62] Atomic numbers are assigned to paired nucleotides. X=[AGCTACCGTG] Propeller Twist 𝑋 ̂(ⅈ) = [-14.00, -11.08, -14.00, -11.85, -13.10, -8.10, -10.03, -13.10, -9.45] Bending Stiffness 𝑋 ̂(ⅈ) = [60, 85, 60, 20, 60, 130, 85, 60, 60] X=[AGCTACCGTG] 𝑋 ̂(ⅈ) = [7.8, 11.1, 7.8, 6.0, 6.5, 11.0, 11.9, 6.…”