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Compression of biological sequences
Šurín, Tomáš ; Mráz, František (advisor) ; Dvořák, Tomáš (referee)
Volumes of data obtained from the next generation sequencing platforms is growing faster than the available capacity of storage media. Sequencers mainly produce short reads of DNA. However, output of the sequencing machines also contains other information, for example information about read reliability/quality. This data must be archived even after successful complete genome assembly. Standard file format used for this type of data is format SAM (Sequence Alignment/Mapping Format) and its binary compressed version BAM. In this thesis we describe the construction of a better lossless compression scheme for compression of files in the SAM/BAM format. This compression scheme provides better compression ratios than the BAM format. In addition, random access to data in the compressed file is retained. Implementation of this compression scheme is platform independent and allows simple configuration of the compression process. Implementation also offers easy extensibility. Thanks to this, we will be able to respond to changes in current sequencing platforms as well as to changes in the SAM format.
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Searching for similar secondary structures in RNA
Vojtek, Daniel ; Mráz, František (advisor) ; Hoffmann, Petr (referee)
In contrast to DNA, the RNA strings fold into complicated secondary structures, which are highly important for their function. Main goal of this work was to create an application, which allows designing a detailed pattern of RNA secondary structure and then finding similar ones in the given set of RNA. The application has also direct access to GenBank database, from which it can download RNA sequences according to the user-defined query. Sequences without secondary structure are folded using a function from Vienna RNA Package. A part of the application is a graphic user interface, which provides comfortable way to design a pattern and allows the browsing found similar secondary structures. The work also presents basic principles of searching of similar RNA secondary structures and its usage in building phylogenetic trees. Description of all used algorithms is present too.
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Machine learning of formal languages
Klonfar, Matěj ; Mráz, František (advisor) ; Bednárek, David (referee)
In the present work I study the task of machine learning of formal languages. The task of the work is to design and implement the program with anyone will be able to study the progress and results of algorithms for learning languages. With this program is possible to run algorithms for learning from examples. Examples could be sets of positive and negative examples of the result languages or sets expressed by teacher who knows the result language. The main task is to design easily extensible application with a view to inserting add-ins without no limits of used representation of learned languages or language complexity.
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Recognition of picture languages
Barták, Jakub ; Mráz, František (advisor) ; Plátek, Martin (referee)
We present a transformation of one-dimensional shrinking restarting automaton concept into two-dimensions. The resulting automaton (called Two-dimensional Restarting Automaton - 2RA) proved to have an interesting closure properties as well as close relation to the class or recognizable languages (REC) which qualify it as a notable member of two-dimensional language hierarchy.
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Machine learning of formal languages
Klonfar, Matěj ; Mráz, František (advisor) ; Plátek, Martin (referee)
In the present work I study the task of machine learning of formal languages. The task of the work is to design and implement the program with anyone will be able to study the progress and results of algorithms for learning languages. With this program is possible to run algorithms for learning from examples. Examples could be sets of positive and negative examples of the result languages or sets expressed by teacher who knows the result language. The main task is to design easily extensible application with a view to inserting add-ins without no limits of used representation of learned languages or language complexity.
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Grammatical evolution
Nohejl, Adam ; Mráz, František (advisor) ; Iša, Jiří (referee)
Grammatical evolution (GE) is a recent grammar-based approach to genetic programming that allows development of solutions in an arbitrary programming language. Its existing implementations lack documentation and do not provide reproducible results suitable for further analysis. This thesis summarises the methods of GE and the standard methods used in evolutionary algorithms, and reviews the existing implementations, foremost the only actively developed one, GEVA. A new comprehensive software framework for GE is designed and implemented based on this review. It is modular, well-documented, portable, and gives reproducible results. It has been tested in two benchmark applications, in which it showed competitive results and outperformed GEVA 10 to 29 times in computational time. It is also shown how to further improve the performance and results by using techniques unsupported by GEVA, including new modications to the previously published methods of bit-level mutation and "sensible" initialisation. The thesis and the software together form a solid foundation for further experiments and research.
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A database for RNA secondary structures
Tattermusch, Jan ; Mráz, František (advisor) ; Hoffmann, Petr (referee)
In the presented work we study RNA primary and secondary structures and we select suitable models for their computational representation. Next, we state criteria for primary and secondary structure comparison. Based on this criteria, we select tree alignment as a suitable method for implementation of structural search. We also mention some speci cs of structural search task and propose some possible modi cations that can speed-up the search. An important part of this work is web application "RNA Secondary Structure Database", which implements structural and sequence-structural search.
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Parallel evolutionary algorithms for multiobjective optimization
Pilát, Martin ; Neruda, Roman (advisor) ; Mráz, František (referee)
In the present work we study the options for parallelization of evolutionary algorithms for multiobjective optimization (MOGA). We provide the overview of existing sequential and parallel MOGAs and we propose three other methods: FCMOGA - MOGA with fuzzy constraints, HIMOGA - heterogeneous island MOGA, and MOGASOLS - MOGA with single objective local search. We test these algorithms on a set of benchmark problems and compare them with existing MOGAs.
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L-systems online
Fišer, Marek ; Pelikán, Josef (advisor) ; Mráz, František (referee)
An L-system in its simplest form is a variant of a context-free grammar. Originally, L-systems were developed and are still mainly used for modeling plant growth, though with L-systems it is possible to create general fractals, models of towns or even music. However, anyone interested in L-systems and wanting to experiment with them may have difficulty finding an appropriate application. The goal of this work was to create an online system, suitable for a wide range of users, for working and experimenting with L-systems. The resulting solution consists of two parts. The first part is a universal, easily-expandable library for processing L-sys- tems. Expandability is achieved thanks to its modularity. All input is processed through interconnected components that are specialized in particular activities. The specialization of the components also contributes to the clarity and reliability of the whole processing system. The library is independent and multiplatform and can thus be readily used in other applications. The second part consists of a modern web interface designed to be under- standable for beginners and yet also capable of providing advanced features for more advanced users. Part of the site is a gallery of L-systems to which each user can contribute and which thus helps to create a user-community. The...
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Evolution of algorithm for artificial creatures
Kohout, Jan ; Holan, Tomáš (advisor) ; Mráz, František (referee)
The task of this work is to create an application which allows performing of experiments with evolution of artificial creatures. Behavior of each creature is managed by its algorithm. The algorithm is able to use creature's memory cells (which represent logical variables) and is the genome of the creature. By the crossing-over and mutation, the algorithm evolves. The second aim of this work is to make some tests with the application and describe their results.
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