Classification of Symbol Sequences over Their Frequency Dictionaries: Towards the Connection between Structure and Natural Taxonomy

Abstract

The classifications of bacterial 16S RNA sequences developed over the real and transformed frequency dictionaries have been studied. Two sequences are considered to be close, when their frequency dictionaries are close in Euclidean metrics. A procedure to transform a dictionary is proposed that makes clear some features of the information pattern of a symbol sequence. A comparative study of classifications developed over real frequency dictionaries vs. the transformed ones has been carried out. A correlation between information patterns of nucleotide sequences and taxonomy of the bearer of the sequence was found. The sites with high information value are found to be the main factors of the difference between the classes in a classification. The classification of nucleotide sequences developed over real frequency dictionaries of thickness 3 reveals the best correlation to a gender of bacteria. A set of sequences of the same gender is included entirely into one class, as a rule, and exclusions occur rarely. A hierarchical classification yields one or two taxonomy groups on each level of classification. An unexpectedly often, or unexpectedly rare occurrence of some sites within a sequence makes a basic difference between the structure patterns of the classes yielded; a number of those sites is not to large. Further investigations are necessary in order to campare the sites revealed with those determined due to other methodology.