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Whole genome alignment using suffix trees
Klouba, Lukáš ; Sedlář, Karel (referee) ; Maděránková, Denisa (advisor)
The aim of this thesis is to create an algorithm that allows the alignment of the genome of two organisms by means of suffix structures and to implement it into the programming language environment R. The thesis deals with the description of the construction of the suffix structures and the methods of whole genome alignment. The result of the thesis is a functional algorithm for whole genome alignment by means of suffix structures implemented in the software environment R and its comparison with similar programs for the whole genome alignment.
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Prediction of Transposons in DNA
Černohub, Jan ; Vogel, Ivan (referee) ; Martínek, Tomáš (advisor)
Cílem práce je seznámení se s problematikou uchovávání informace v DNA, provést rešerši na téma transpozony, bioinformatické nástroje a algoritmy, které jsou používány k jejich detekci v nasekvenovaných genomech a vytvořit tak stručný úvod do obsáhle problematiky, včetně jejího zasazení do kontextu současně probíhajícího výzkumu v dané oblasti. Na základě přehledu stávajících algoritmů a nástrojů pro detekci transpozonů je navržen a implementován nástroj pro hledání tzv. LTR transpozonů.
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Suffix Arrays Construction and Their Use in Bioinformatics
Hlávka, Ondřej ; Čermák, Martin (referee) ; Martínek, Tomáš (advisor)
This work describes perspective data structure called suffix array. This data structure is described in more detail and this paper also contains taxonomy of suffix array construction algorithms. A few algorithms are described more precisely and most space is devoted to algorithm called qsufsort. Finally we will show how can be suffix array used in practice. This work shows usage of suffix array in exact (binary search) and approximate (QUASAR) string matching in DNA sequences.
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Approximate Palindrome Detection in DNA Sequences
Divila, Jaroslav ; Lexa, Matej (referee) ; Martínek, Tomáš (advisor)
This work deals with conception and implemetation of tools for finding approximate palindromes in DNA sequences. The work focuses on the description of DNA structure, and on the function of palindromes in DNA sequences, and on the description of methods for finding approximate palindromes. Main part of thesis is focused on conclusion and description of implementation approximate palidromes finding tool.
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Rich Features in Phrase-Based Machine Translation
Kos, Kamil ; Bojar, Ondřej (advisor) ; Žabokrtský, Zdeněk (referee)
In this thesis we investigate several methods how to improve the quality of statistical machine translation (MT) by using linguistically rich information. First, we describe SemPOS, a metric that uses shallow semantic representation of sentences to evaluate the translation quality. We show that even though this metric has high correlation with human assessment of translation quality it is not directly suitable for system parameter optimization. Second, we extend the log-linear model used in statistical MT by additional source-context model that helps to better distinguish among possible translation options and select the most promising translation for a given context.
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Rich Features in Phrase-Based Machine Translation
Kos, Kamil ; Žabokrtský, Zdeněk (referee)
Title: Rich Features in Phrase-Based Machine Translation Author: Kamil Kos Department: Institute of Formal and Applied Linguistics Supervisor: RNDr. Ondřej Bojar, Ph.D. Supervisor's e-mail address: bojar@ufal.mff.cuni.cz Keywords: machine translation, quality evaluation, source-context model, suffix array Abstract: In this thesis we investigate several methods how to improve the quality of statistical machine translation (MT) by using linguistically rich information. First, we describe SemPOS, a metric that uses shallow semantic representation of sentences to evaluate the translation quality. We show that even though this metric has high correlation with human assessment of translation quality it is not directly suitable for system parameter optimization. Second, we extend the log-linear model used in statistical MT by addi- tional source-context model that helps to better distinguish among possible translation options and select the most promising translation for a given context.
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Whole genome alignment using suffix trees
Klouba, Lukáš ; Sedlář, Karel (referee) ; Maděránková, Denisa (advisor)
The aim of this thesis is to create an algorithm that allows the alignment of the genome of two organisms by means of suffix structures and to implement it into the programming language environment R. The thesis deals with the description of the construction of the suffix structures and the methods of whole genome alignment. The result of the thesis is a functional algorithm for whole genome alignment by means of suffix structures implemented in the software environment R and its comparison with similar programs for the whole genome alignment.
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Rich Features in Phrase-Based Machine Translation
Kos, Kamil ; Žabokrtský, Zdeněk (referee)
Title: Rich Features in Phrase-Based Machine Translation Author: Kamil Kos Department: Institute of Formal and Applied Linguistics Supervisor: RNDr. Ondřej Bojar, Ph.D. Supervisor's e-mail address: bojar@ufal.mff.cuni.cz Keywords: machine translation, quality evaluation, source-context model, suffix array Abstract: In this thesis we investigate several methods how to improve the quality of statistical machine translation (MT) by using linguistically rich information. First, we describe SemPOS, a metric that uses shallow semantic representation of sentences to evaluate the translation quality. We show that even though this metric has high correlation with human assessment of translation quality it is not directly suitable for system parameter optimization. Second, we extend the log-linear model used in statistical MT by addi- tional source-context model that helps to better distinguish among possible translation options and select the most promising translation for a given context.
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Rich Features in Phrase-Based Machine Translation
Kos, Kamil ; Bojar, Ondřej (advisor) ; Žabokrtský, Zdeněk (referee)
In this thesis we investigate several methods how to improve the quality of statistical machine translation (MT) by using linguistically rich information. First, we describe SemPOS, a metric that uses shallow semantic representation of sentences to evaluate the translation quality. We show that even though this metric has high correlation with human assessment of translation quality it is not directly suitable for system parameter optimization. Second, we extend the log-linear model used in statistical MT by additional source-context model that helps to better distinguish among possible translation options and select the most promising translation for a given context.
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Suffix Arrays Construction and Their Use in Bioinformatics
Hlávka, Ondřej ; Čermák, Martin (referee) ; Martínek, Tomáš (advisor)
This work describes perspective data structure called suffix array. This data structure is described in more detail and this paper also contains taxonomy of suffix array construction algorithms. A few algorithms are described more precisely and most space is devoted to algorithm called qsufsort. Finally we will show how can be suffix array used in practice. This work shows usage of suffix array in exact (binary search) and approximate (QUASAR) string matching in DNA sequences.
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