Abstract
Tools that effectively analyze and compare sequences are of great importance in various areas of applied computational research, especially in the framework of molecular biology. In the present paper, we introduce simple geometric criteria based on the notion of string linearity and use them to compare DNA sequences of various organisms, as well as to distinguish them from random sequences. Our experiments reveal a significant difference between biosequences and random sequences the former having much higher deviation from linearity than the latter as well as a general trend of increasing deviation from linearity between primitive and biologically complex organisms. The proposed approach is potentially applicable to the construction of dendograms representing the evolutionary relationships among species.
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Brimkov, B., Brimkov, V.E. (2014). Geometric Approach to Biosequence Analysis. In: Saez-Rodriguez, J., Rocha, M., Fdez-Riverola, F., De Paz Santana, J. (eds) 8th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB 2014). Advances in Intelligent Systems and Computing, vol 294. Springer, Cham. https://doi.org/10.1007/978-3-319-07581-5_12
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DOI: https://doi.org/10.1007/978-3-319-07581-5_12
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07580-8
Online ISBN: 978-3-319-07581-5
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