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Detection of Genome Variations
Beluský, Tomáš ; Vogel, Ivan (referee) ; Martínek, Tomáš (advisor)
An influence of variations in human genome is perceptible at a first glance on human itself to see differences between the individuals and entire populations. Also, behavior or probability of certain diseases are influenced in large way by differences at genome's level. This work presents methods for detecting variations in the human genome that were developed after an arose of the second-generation sequencing technologies. A new tool that combines read pair and split read methods, with information about a depth of coverage was also designed and implemented. The tool was tested on simulated and real data and compared with a reference outputs.
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Techniques for Multiple Sequence Alignments
Hrazdil, Jiří ; Martínek, Tomáš (referee) ; Burgetová, Ivana (advisor)
This thesis summarizes ways of representation of biological sequences and file formats used for sequence exchange and storage. Next part deals with techniques used for sequence pairwise alignment, followed by extension of these techniques to the problem of multiple sequence alignment. Additional methods are introduced, that are suboptimal, but on the other hand are able to compute results in reasonable time. Practical part of this thesis consists of implementing multiple sequence alignment application in Java programming language.
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Recegnition of Repeating SMS Patterns
Kočalka, Jakub ; Češka, Milan (referee) ; Holík, Lukáš (advisor)
Vďaka pokroku v rozpoznávaní spamu v e-mailoch a zvyšovaní povedomia používateľov smerujú spameri k menej preskúmaným médiám. Jedným z nich je \emph{short messaging service} (SMS). Táto služba poskytuje užívateľom možnosť reagovať na správy v krátkom čase a v skoro ľubovolnom prostredí. Tieto vlastnosti sú atraktívne aj pre legitímne podniky, ktoré potrebujú svojim klinetom zasielať krátke hromadné správy. Aj keď sú tieto správy z pohladu koncového užívateľa vyžiadané, pre poskytovateľa služieb SMS môžu predstavovať stratu, pretože tieto podniky často zneužívajú neobmedzené SMS plány určené pre bežných zákazníkov, aby sa vyhli plateniu za pre nich určené, ale drahšie produkty. Je preto žiaduce vedieť rozpoznať nevyžiadané aj vyžiadané hromadné správy. Hromadné správy sa zvyčajne generujú zo šablóny. Cieľom tejto práce je navrhnúť zhlukovací algoritmus ktorý správy analyzuje ako sekvencie lexikálnych jednotiek (slov), a vyhodnotiť jeho efektivitu v porovnaní s \emph{locality sensitivity hashing} metódou ktorá správy analyzuje ako reťazce symbolov. Práca vyhodnocuje vhodnosť algoritmu Smith-Waterman pre túto úlohu. Práca popisuje, prečo je Smith-Waterman (a ďalšie lokálne zarovnávania) nevhodný, a ako je možné ho nahradiť algoritmom Needleman-Wunsch (globálnym zarovnávaním), aby sa dosiahli oveľa lepšie výsledky. Výsledný algoritmus dokáže uspokojivo zhlukovať skutočné správy do kampaní a funguje dobre aj v situáciách, kde \emph{locality sensitivity hashing} kampane fragmentuje.
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Evaluation of Organisms Relationship by Genomic Signal Processing
Škutková, Helena ; Tkacz, Ewaryst (referee) ; Schwarz,, Daniel (referee) ; Provazník, Ivo (advisor)
This dissertation deals with alternative techniques for analysis of genetic information of organisms. The theoretical part presents two different approaches for evaluation of relationship between organisms based on mutual similarity of genetic information contained in their DNA sequences. The first approach is currently standardized phylogenetics analysis of character based records of DNA sequences. Although this approach is computationally expensive due to the need of multiple sequence alignment, it allows evaluation of global and local similarity of DNA sequences. The second approach is represented by techniques for classification of DNA sequences in a form of numerical vectors representing characteristic features of their genetic information. These methods known as „alignment free“ allow fast evaluation of global similarity but cannot evaluate local changes. The new method presented in this dissertation combines the advantages of both approaches. It utilizes numerical representation similar to 1D digital signal, i.e. representation that contains specific trend along x-axis. The experimental part of dissertation deals with design of a set of appropriate tools for genomic signal processing to allow evaluation mutual similarity of taxonomically specific trends. On the basis of the mutual similarity of genomic signals, the classification in the form of dendrogram is applied. It corresponds to phylogenetic trees used in standard phylogenetics.
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Effects of hyperparameters in multiple sequence alignment for Align-RUDDER using Clustal
SAMWALD, Christian
Delayed rewards are detrimental to the learning of reinforcement learning agents.One approach to this problem is the usage of return decomposition and rewardredistribution. It was realised in the Align-RUDDER algorithm of Patilet al.[14].Their solution employed the multiple sequence alignment algorithm Clustal W. Iintegrated the sequence alignment Tool Clustal, Clustal W's successor, intoAlign RUDDER to increase efficiency. During the testing process, the usage ofClustal's EPA function and the effects of different sample sizes played a centralrole. The data set that was used came from the MineRL data set [6].
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Auto-Encoding Amino Acid Sequences with LSTM
PROMBERGER, Markus
In this thesis a sequence to sequence autoencoder for amino acid sequences is constructed. The latent representation of the autoencoder is then used to classify the amino acid sequences according to their animal kingdom. The data consists of sequences from three different kingdoms, mammals, fish and birds. The thesis includes the preprocessing necessary for the data, the construction of the sequence to sequence autoencoder and the process of classification in the latent space.
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Multiple sequence alignment using genetic algorithms
Pátek, Zdeněk ; Mráz, František (advisor) ; Pešková, Klára (referee)
Title: Multiple sequence alignment using genetic algorithms Author: Zdeněk Pátek Department: Department of Software and Computer Science Education Supervisor: RNDr. František Mráz, CSc. Abstract: The thesis adresses the problem of multiple sequence alignment (MSA). It contains the specication of the proposed method MSAMS that allows to find motifs in biological sequences, to split sequences to blocks using the motifs, to solve MSA on the blocks and nally to assemble the global alignment from the aligned blocks and motifs. Motif search and MSA are both solved using genetic algorithms. The thesis describes the implementation of the method, conguration of its settings, benchmarking on the BAliBASE database and comparison to the ClustalW program. Experimental results showed that MSAMS can discover better alignments than ClustalW. Keywords: multiple sequence alignment, motif nding, genetic algorithms, ClustalW
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Recegnition of Repeating SMS Patterns
Kočalka, Jakub ; Češka, Milan (referee) ; Holík, Lukáš (advisor)
Vďaka pokroku v rozpoznávaní spamu v e-mailoch a zvyšovaní povedomia používateľov smerujú spameri k menej preskúmaným médiám. Jedným z nich je \emph{short messaging service} (SMS). Táto služba poskytuje užívateľom možnosť reagovať na správy v krátkom čase a v skoro ľubovolnom prostredí. Tieto vlastnosti sú atraktívne aj pre legitímne podniky, ktoré potrebujú svojim klinetom zasielať krátke hromadné správy. Aj keď sú tieto správy z pohladu koncového užívateľa vyžiadané, pre poskytovateľa služieb SMS môžu predstavovať stratu, pretože tieto podniky často zneužívajú neobmedzené SMS plány určené pre bežných zákazníkov, aby sa vyhli plateniu za pre nich určené, ale drahšie produkty. Je preto žiaduce vedieť rozpoznať nevyžiadané aj vyžiadané hromadné správy. Hromadné správy sa zvyčajne generujú zo šablóny. Cieľom tejto práce je navrhnúť zhlukovací algoritmus ktorý správy analyzuje ako sekvencie lexikálnych jednotiek (slov), a vyhodnotiť jeho efektivitu v porovnaní s \emph{locality sensitivity hashing} metódou ktorá správy analyzuje ako reťazce symbolov. Práca vyhodnocuje vhodnosť algoritmu Smith-Waterman pre túto úlohu. Práca popisuje, prečo je Smith-Waterman (a ďalšie lokálne zarovnávania) nevhodný, a ako je možné ho nahradiť algoritmom Needleman-Wunsch (globálnym zarovnávaním), aby sa dosiahli oveľa lepšie výsledky. Výsledný algoritmus dokáže uspokojivo zhlukovať skutočné správy do kampaní a funguje dobre aj v situáciách, kde \emph{locality sensitivity hashing} kampane fragmentuje.
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Determination of genetic differences of biological DNA sequences
Sliž, Ladislav ; Škutková, Helena (referee) ; Provazník, Ivo (advisor)
Work on determining the genetic diversity of biological signal aligning DNA sequences, will address a brief description of the composition of DNA. Following is basic information on the bioinformatics analysis. Then the work will describe the possibility of aligning DNA sequences. Work will focus primarily on global Needleman-Wunsch algorithm and local Smit - Watermanovův algorithm. Furthermore, this work will focus on aligning DNA sequences using methods CGR and FCGR. At the end of the work will describe the practical application of identifying genetic differences by aligning the sequences.
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Multiple sequence alignment using genetic algorithms
Pátek, Zdeněk ; Mráz, František (advisor) ; Pešková, Klára (referee)
Title: Multiple sequence alignment using genetic algorithms Author: Zdeněk Pátek Department: Department of Software and Computer Science Education Supervisor: RNDr. František Mráz, CSc. Abstract: The thesis adresses the problem of multiple sequence alignment (MSA). It contains the specication of the proposed method MSAMS that allows to find motifs in biological sequences, to split sequences to blocks using the motifs, to solve MSA on the blocks and nally to assemble the global alignment from the aligned blocks and motifs. Motif search and MSA are both solved using genetic algorithms. The thesis describes the implementation of the method, conguration of its settings, benchmarking on the BAliBASE database and comparison to the ClustalW program. Experimental results showed that MSAMS can discover better alignments than ClustalW. Keywords: multiple sequence alignment, motif nding, genetic algorithms, ClustalW
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