DV-Curve Representation of Protein Sequences and Its Application

Based on the detailed hydrophobic-hydrophilic(HP) model of amino acids, we propose dual-vector curve (DV-curve) representation of protein sequences, which uses two vectors to represent one alphabet of protein sequences. This graphical representation not only avoids degeneracy, but also has good visualization no matter how long these sequences are, and can reflect the length of protein sequence. Then we transform the 2D-graphical representation into a numerical characterization that can facilitate quantitative comparison of protein sequences. The utility of this approach is illustrated by two examples: one is similarity/dissimilarity comparison among different ND6 protein sequences based on their DV-curve figures the other is the phylogenetic analysis among coronaviruses based on their spike proteins

Numerical representations of protein sequences for classification

S rozmachem bioinformatiky vyvstala možnost analyzovat a~srovnávat i~rozsáhlé soubory nejen genomických, ale i~proteomických sekvencí. Byla tedy nutnost zavést numerické reprezentace sekvencí pro jejich počítačové zpracování. Reprezentace proteinových sekvencí má svá specifika a~často vyšší výpočetní náročnost, než reprezentace genomických sekvencí. V~práci je představeno několik různých metod přístupu k~numerickým reprezentacím proteinů. Vybrané metody jsou poté testovány na setu mitochondriálně kódovaných proteinů a srovnány se standardní taxonomií a s běžně používanou symbolickou reprezentací.Todays we have the opportunity to analyze huge sets of genomics and proteomics data. In my bachaleor thesis I introduce a few numerical alternatives to represent proteins. The usage of numerical representations opened the way to analyze proteomics data as digital signals, which bring us quantity of new possibilities how to process the protein. In my thesis I compare a few numerical representation with standard taxonomy and with symbolic representation too.