Bancos de dados biológicos utilizados para comparação e alinhamento local de sequências tem crescido de forma exponencial. Isso popularizou programas que realizam buscas nesses bancos. As implementações dos algoritmos de alinhamento de sequências Smith- Waterman e distância Levenshtein demonstraram ser computacionalmente intensivas e, portanto, propícias para aceleração em hardware. Este trabalho descreve arquiteturas em hardware dedicado prototipadas para FPGA e ASIC para acelerar os algoritmos Smith- Waterman e distância Levenshtein mantendo os mesmos resultados obtidos por softwares. Descrevemos uma nova e eficiente unidade de processamento para o cálculo do Smith- Waterman utilizando affine gap. Também projetamos uma arquitetura que permite particionar as sequências de entrada para a distância Levenshtein em um array sistólico de tamanho fixo. Nossa implementação em FPGA para o Smith-Waterman acelera de 275 a 494 vezes o algoritmo em relação a um computador com processador de propósito geral. Ainda é 52 a 113% mais rápida em relação, segundo nosso conhecimento, as mais rápidas arquiteturas recentemente publicadas. / Bioinformatics databases used for sequence comparison and local sequence alignment are growing exponentially. This has popularized programs that carry out database searches. Current implementations of sequence alignment methods based on Smith- Waterman and Levenshtein distance have proven to be computationally intensive and, hence, amenable for hardware acceleration. This Msc. Thesis describes an FPGA and ASIC based hardware implementation designed to accelerate the Smith-Waterman and Levenshtein distance maintaining the same results yielded by general softwares. We describe an new efficient Smith-Waterman affine gap process element and a new architecture to partitioning and maping the Levenshtein distance into fixed size systolic arrays. Our FPGA Smith-Waterman implementation delivers 275 to 494-fold speed-up over a standard desktop computer and is also about 52 to 113% faster, to the best of our knowledge, than the fastest implementation in a most recent family of accelerators.

This thesis deals with detection of dynamic network applications. It describes some of the existing protocols and methods of their identification from IP flow and packet contents. It constitues a design of a detection system based on the automatic creation of regular expressions and describes its implementation. It presents the created regular expressions for BitTorrent and eDonkey protocol. It compares their quality with the solution of L7-filter.

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.

This graduation theses describes walk, cyclist, ski-ing and waterman{\crq}s tourist roads and educational trails in the Novohradské Mountains, its highlands and in part of the Třeboňská basin {--} in the territory demarked by tourist map {\clqq}Novohradské Mountains``, from edition Club of czech tourists, in ratio scale 1:50 000. Particular roads are described in text and in general tables, whereby is possible easy reproach the character of mentioned tourist roads. Methodology of work, which was taken over from D. Bobrová (2002) and description of particular tourist roads, is a substantial part of graduation theses. Introductory chapters specify the respective area from physical-geographic and social-geographic point of view. The appendix is formed by gazetteer, which processed D. Bobrová (2002) and by graphic part, formed by photographies.

This paper describes sequence alignment algorithms of nucleotide sequences. There are described pairwise alignment algorithms using database search or dynamic programming. Then in the paper is description of dynamic programming for multiple sequences and algorithm that builds phylogenetic trees. At the end of the first part of the paper is the description of technology FPGA. In the second part that is more practical is described implemntation of the choosen one algorithm. This part includes also examples of some multiple alignments.

Methods for aproximate string matching of various sequences used in bioinformatics are crucial part of development in this branch. Tasks are of very large time complexity and therefore we want create a hardware platform for acceleration of these computations. Goal of this work is to design a generalized architecture based on FPGA technology, which can work with various types of sequences. Designed acceleration card will use especially dynamic algorithms like Needleman-Wunsch and Smith-Waterman.