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The Pseudo K-tuple nucleotide composition or PseKNC, was extended from Chou's Pseudo amino acid composition (PseAAC). [1] Both PseAAC and PseKNC are of vector descriptor, but the former represents protein or peptide sequences while the latter represents DNA or RNA sequences.
To avoid completely losing the sequence-order information for protein and peptide sequences, the PseAAC [1] was proposed by Kuo-Chen Chou. To address the problem of DNA and RNA sequences, the pseudo K-tuple nucleotide composition or PseKNC was proposed. [2] [3] [4] For the convenience scientific community, a freely available web server called PseKNC [2] and an open source package called PseKNC-General [3] were developed in 2013 and 2014, respectively, that could convert large-scale sequence datasets to pseudo nucleotide compositions with numerous choices of physicochemical property combinations. PseKNC-General can generate several modes of pseudo nucleotide compositions, including conventional k-tuple nucleotide compositions, Moreau–Broto autocorrelation coefficient, Moran autocorrelation coefficient, Geary autocorrelation coefficient, Type I PseKNC and Type II PseKNC.
Like PseAAC in computational proteomics and proteome analysis, PseKNC has also been increasingly used in computational genomics and performing various genome analyses.