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A novel way to numerically characterize DNA sequences and its application.

Ying GuoYan-Fang WangSheng-Li Zhang
Published in: International journal of quantum chemistry (2010)
We presented a novel way to numerically characterize DNA sequences based on the graphical representation for the sequences comparison and analysis. Instead of calculating the leading eigenvalues of the matrix for graphical representation, we computed curvature and torsion of curves as the descriptor to numerically characterize DNA sequences. The new method was tested on three data sets: the coding sequences of β-globin gene, all of their exons, and 24 coronavirus geneomes from NCBI. The similarities/dissimilarities and phylogenetic tree of these species verify the validity of our method. © 2010 Wiley Periodicals, Inc. Int J Quantum Chem, 2011.
Keyphrases
  • circulating tumor
  • cell free
  • single molecule
  • genetic diversity
  • sars cov
  • big data
  • copy number
  • magnetic resonance
  • machine learning
  • dna methylation
  • neural network
  • genome wide identification