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Evolutionary ordering of the mitochondrion-encoded proteins

Kozarzewski B.

Journal of Applied Computer Science

2016

Vol. 24, nr 1

37--49

The parsing of a symbolic sequence into a set of short substrings called words invented by the author is used for a new definition of the distance between sequences. No sequence alignment is necessary. The most frequent among spectra of multiprotein sequences are selected and considered as a reference spectrum of the sequences. The distance between the reference spectrum and protein sequences is considered as the estimation of the evolutionary distance of the protein. As an application, amino acid sequences of the several mitochondria-encoded proteins of mammal species are ordered according to their evolutionary distance. Statistical distribution of the distances between exhibits some structures related to the evolutionary rate in the past.

Numerical Representation of Symbolic Data

Kozarzewski B.

Computational Methods in Science and Technology

2015

Vol. 21, No. 4

241--249

A method of direct numerical representation of symbolic data is proposed. The method starts with parsing a sequence into an ordered set (spectrum) of distinct, non-overlapping short strings of symbols (words). Next, the words spectrum is mapped onto a vector of binary components in a high dimensional, linear space. The numerical representation allows for some arithmetical operations on symbolic data. Among them is a meaningful average spectrum of two sequences. As a test, the new numerical representation is used to build centroid vectors for the k-means clustering algorithm. It significantly enhanced the clustering quality. The advantage over the conventional approach is a high score of correct clustering several real character sequences like novel, DNA and protein.