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Clustering of Protein Sequences Based on Primary Structure of Proteins
Jurásek, Petr ; Stryka, Lukáš (referee) ; Burgetová, Ivana (advisor)
This master's thesis consider clustering of protein sequences based on primary structure of proteins. Studies the protein sequences from they primary structure. Describes methods for similarities in the amino acid sequences of proteins, cluster analysis and clustering algorithms. This thesis presents concept of distance function based on similarity of protein sequences and implements clustering algorithms ANGES, k-means, k-medoids in Python programming language.
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Techniques for Comparing Biological Sequences
Sladký, Roman ; Křivka, Zbyněk (referee) ; Burgetová, Ivana (advisor)
This work presents the building up of basic biological units DNA, RNA and proteins as well as their function. Provided data are kept in biological databases which are connected worldwide to supply preferable communication along with all kinds of available information to be used in the scientific research. The secret of alive is hidden in genes coded in sequences of nucleotides. Genes enable the creation of proteins which are made of sequences of amino-acids. The wide-spread methods of comparing these sequences are FASTA and BLAST algorithms. Their base is used for the PSProt program which is described in this work. PSProt program is the tool for comparing the sequences of proteins. First it is necessary to synthesise the protein from the DNA oligonucleotide because it codes the surveyed protein. The most similar proteins are searched out by heuristic of hitpoints, then their final score that is essential for aligning is modified by semiglobal alignment algorithm.
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