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Effective Dynamic Programming in Bioinformatics
Franěk, Jaromír ; Hynek, Jiří (referee) ; Burgetová, Ivana (advisor)
Purpose of this thesis is to study principle of effective algorithms, that are using dynamic programming. Using this knowledge to create application demonstrating principle of effective algorithm of dynamic programming in bioinformatics and write a report summarizing results. Algorithms used in this thesis are solving DNA sequence alignment or RNA secondary structure prediction. These algorithms are compared between themselves based on different input values. For DNA sequence alignment are used algorithms such as Needleman-Wunch and X-drop. For prediction of secondary RNA structure is used Zuker algorithm, that should remove some of Nussin algorithm weaknesses and Nussin algorithm itself. Recursion is showed by recursion trees. Dynamic programming is showed by score matrix. User also have ability to compare speed of both approaches for given sequences. It is programmed as web application, that run on client's side. This ensure easy availability.
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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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Robot path planning by means of dynamic programming
Stárek, Ivo ; Krček, Petr (referee) ; Dvořák, Jiří (advisor)
This work is dedicated to robot path planning with using principles of dynamic programing in discrete state space. Theoretical part is dedicated to actual situation in this field and to principle of applying Markov decission process to path planning. Practical part is dedicated to implementation of two algorithms based on MDP principles.
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Effective Dynamic Programming in Bioinformatics
Franěk, Jaromír ; Hynek, Jiří (referee) ; Burgetová, Ivana (advisor)
Purpose of this thesis is to study principle of effective algorithms, that are using dynamic programming. Using this knowledge to create application demonstrating principle of effective algorithm of dynamic programming in bioinformatics and write a report summarizing results. Algorithms used in this thesis are solving DNA sequence alignment or RNA secondary structure prediction. These algorithms are compared between themselves based on different input values. For DNA sequence alignment are used algorithms such as Needleman-Wunch and X-drop. For prediction of secondary RNA structure is used Zuker algorithm, that should remove some of Nussin algorithm weaknesses and Nussin algorithm itself. Recursion is showed by recursion trees. Dynamic programming is showed by score matrix. User also have ability to compare speed of both approaches for given sequences. It is programmed as web application, that run on client's side. This ensure easy availability.
|
|
|
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.
|
|
|
Robot path planning by means of dynamic programming
Stárek, Ivo ; Krček, Petr (referee) ; Dvořák, Jiří (advisor)
This work is dedicated to robot path planning with using principles of dynamic programing in discrete state space. Theoretical part is dedicated to actual situation in this field and to principle of applying Markov decission process to path planning. Practical part is dedicated to implementation of two algorithms based on MDP principles.
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