Research of Calculation Methods of Word Entropy Function and its Application to Clustering of Plant Genomes

Student: Pestova Anastasiia

Supervisor: Mikhail Ulyanov

Educational Programme: Software Engineering (Bachelor)

Year of Graduation: 2017

An approach to the information analysis is considered for the case when the information is presented by words of finite length over a finite alphabet. A method of generating a measure of symbolic diverseness of words based on peak characteristics of a shift entropy function is proposed. The shift entropy function is formally defined using a unit translation operator and the entropy of discrete distributions. A model example is presented together with some results of application of the proposed measure in the clustering of families of plants using the analysis of genome of their representatives. The paper contains 37 pages, 3 chapters, 11 illustrations, 5 tables, 23 bibliography items, 5 appendices. Key words: shift entropy, measure of symbolic diverseness, clustering of plant genomes.

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