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Prediction of Secondary Structure of Proteins Using Cellular Automata
Brigant, Vladimír ; Drahošová, Michaela (referee) ; Bendl, Jaroslav (advisor)
This work describes a method of the secondary structure prediction of proteins based on cellular automaton (CA) model - CASSP. Optimal model and CA transition rule parameters are acquired by evolutionary algorithm. Prediction model uses only statistical characteristics of amino acids, so its prediction is fast. Achieved results was compared with results of other tools for this purpose. Prediction cooperation with a existing tool PSIPRED was also tested. It didn't succeed to beat this existing tool, but partial improvement was achieved in prediction of only alpha-helix secondary structure motif, what can be helful if we need the best prediction of alpha-helices. It was developed also a web interface of designed system.
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Prediction of the Effect of Amino Acid Substitutions on the Secondary Structure of Proteins
Kadlec, Miroslav ; Vogel, Ivan (referee) ; Bendl, Jaroslav (advisor)
This thesis is focused on amino acid substitutions and their impact on protein secondary structure. The main aim is to prove, that although the protein sequence is frequently mutated during the evolution, protein secondary structure is more robust against changes. In this case, the elements of protein secondary structure stay almost unchanged although a significant number of substitutions is observed. The proof of this hypothesis was obtained by developed simulator of evolution which employs two well-estabilished predicting tools: PSIPRED for prediction of protein secondary structure and PhD-SNP for prediction of the effect of amino acid substitution on protein function. The results of the experiments are provided as graphs and their meainings is discussed.
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Prediction of the Effect of Amino Acid Substitutions on Secondary Structure of Proteins
Hyrš, Martin ; Vogel, Ivan (referee) ; Bendl, Jaroslav (advisor)
In this thesis I investigate the effect of amino acid substitutions on secondary structure of proteins. I found that the secondary structure is relatively resistant to mutations, some regions hold the same secondary structure, even though their sequences are very different. Since this effect was observed also for random sequences, I conclude that it is a general property of the amino acid sequence. The particular elements of secondary structures are differentially sensitive to the changes caused by mutations. Protein's sensitivity to mutations depends on the composition of its secondary structure. Some methods of secondary structure prediction are described in the introductory section.
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Modern methods for protein secondary structure prediction and their comparison
Kraus, Ondřej ; Novotný, Marian (advisor) ; Pleskot, Roman (referee)
Today, there are several protein secondary structure predictors; most of them use algorithms such as hidden Markov models or artificial neural networks. Therefore I will introduce them to a reader in my thesis. I will explain their principles, as well as their advantages and disadvantages. The majority of contemporary predictors have accuracy 70%-80% for prediction of three types of protein secondary structure. However these results are only approximate, due to different testing methodology. Therefore the user should get familiar with the method and its testing methodology in detail at first. Key-words: protein structure prediction, hidden Markov model, artificial neural network, nearest neighbour, protein secondary structure
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Modern methods for protein secondary structure prediction and their comparison
Kraus, Ondřej ; Novotný, Marian (advisor) ; Pleskot, Roman (referee)
Today, there are several protein secondary structure predictors; most of them use algorithms such as hidden Markov models or artificial neural networks. Therefore I will introduce them to a reader in my thesis. I will explain their principles, as well as their advantages and disadvantages. The majority of contemporary predictors have accuracy 70%-80% for prediction of three types of protein secondary structure. However these results are only approximate, due to different testing methodology. Therefore the user should get familiar with the method and its testing methodology in detail at first. Key-words: protein structure prediction, hidden Markov model, artificial neural network, nearest neighbour, protein secondary structure
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Prediction of the Effect of Amino Acid Substitutions on Secondary Structure of Proteins
Hyrš, Martin ; Vogel, Ivan (referee) ; Bendl, Jaroslav (advisor)
In this thesis I investigate the effect of amino acid substitutions on secondary structure of proteins. I found that the secondary structure is relatively resistant to mutations, some regions hold the same secondary structure, even though their sequences are very different. Since this effect was observed also for random sequences, I conclude that it is a general property of the amino acid sequence. The particular elements of secondary structures are differentially sensitive to the changes caused by mutations. Protein's sensitivity to mutations depends on the composition of its secondary structure. Some methods of secondary structure prediction are described in the introductory section.
|
|
|
Prediction of Secondary Structure of Proteins Using Cellular Automata
Brigant, Vladimír ; Drahošová, Michaela (referee) ; Bendl, Jaroslav (advisor)
This work describes a method of the secondary structure prediction of proteins based on cellular automaton (CA) model - CASSP. Optimal model and CA transition rule parameters are acquired by evolutionary algorithm. Prediction model uses only statistical characteristics of amino acids, so its prediction is fast. Achieved results was compared with results of other tools for this purpose. Prediction cooperation with a existing tool PSIPRED was also tested. It didn't succeed to beat this existing tool, but partial improvement was achieved in prediction of only alpha-helix secondary structure motif, what can be helful if we need the best prediction of alpha-helices. It was developed also a web interface of designed system.
|
|
|
Prediction of the Effect of Amino Acid Substitutions on the Secondary Structure of Proteins
Kadlec, Miroslav ; Vogel, Ivan (referee) ; Bendl, Jaroslav (advisor)
This thesis is focused on amino acid substitutions and their impact on protein secondary structure. The main aim is to prove, that although the protein sequence is frequently mutated during the evolution, protein secondary structure is more robust against changes. In this case, the elements of protein secondary structure stay almost unchanged although a significant number of substitutions is observed. The proof of this hypothesis was obtained by developed simulator of evolution which employs two well-estabilished predicting tools: PSIPRED for prediction of protein secondary structure and PhD-SNP for prediction of the effect of amino acid substitution on protein function. The results of the experiments are provided as graphs and their meainings is discussed.
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