Acoustic generator for evoked potentials stimulation

Evokované potenciály jsou elektrickou odpovědí mozku na vnější stimul. Jsou důležitou diagnostickou neobrazovou metodou v neurologii. Pro jejich vybuzení se využívá různých druhů stimulace, nejčastěji: zrakové, sluchové, somatosenzorické, čichové a chuťové. Evokované potenciály objektivně měří smyslové vnímání. V této diplomové práci se zaměřuji převážně na zvukové evokované potenciály a návrhem akustického generátoru pro jejich stimulaci. Zvukové evokované potenciály jsou nejčastěji využívány pro objektivní měření sluchu, ale mají i další využití. Předně je aplikace zaměřena na zdravotnictví. Cílem této diplomové práce je skloubit stanovené lékařské požadavky s dostupnými technickými prostředky.Evoked potentials are electric brain response to external stimulus. They are important diagnostic no visual method in neurology. For their excitation use of different of kinds stimulation, most often: visual, auditory, somatosenzory, olfactory and gustatory. Evoked potentials are objective method for measurement sense perception. This master’s thesis is specialized to auditory evoked potentials and design acoustic generator for their stimulation. Auditory evoked potentials are primary used for objective audiometry, but they have another usage. In the first place, application is specialized on health sector. The aim of this master’s thesis is compact specified medical requirements with available technical resources.

Evaluation of Organisms Relationship by Genomic Signal Processing

Tato dizertační práce se zabývá alternativními přístupy k analýze genetické informace organismů. V teoretické části práce jsou představeny dva odlišné přístupy vyhodnocení příbuznosti organismů na základě podobnosti jejich genetické informace obsažené v sekvenci DNA. Jedním z nich je dnes standardizovaný postup fylogenetické analýzy znakového zápisu sekvencí DNA. Přestože je tento postup poměrně výpočetně náročný kvůli potřebě mnohonásobného zarovnání DNA sekvencí, umožňuje stanovit podobnost jak globálně celých sekvencí DNA, tak lokalizovat jen konkrétní homologie v nich. Druhým přístupem jsou alternativní techniky klasifikace sekvencí DNA ve formě numerického vektoru reprezentujícího charakteristický rys obsažené genetické informace. Tyto metody označované jako „alignment-free“ umožňují velmi rychlé vyhodnocení globální podobnosti sekvencí DNA, numerickou konverzí však ztrácejí možnost vyhodnotit lokální změny v sekvencích. V praktické části je pak představena nová metoda klasifikace numerických reprezentací DNA kombinující výhody obou uvedených přístupů. Z numerických reprezentací DNA jsou zvoleny jen reprezentace mající 1D signálu podobný charakter, tzn. obsahující specifický trend vyvíjející se podél osy x. Hlavním předpokladem je taxonomická specifičnost těchto genomických signálů. Praktická část práce se zabývá vytvořením vhodných nástrojů pro číslicové zpracování genomických signálů umožňující vyhodnocení vzájemné podobnosti taxonomicky specifických trendů. Na základě vyhodnocené vzájemné podobnosti genomických signálů je provedena klasifikace formou dendrogramu, jež je obdobou fylogenetických stromů využívaných ve standardní fylogenetice.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.

Bipartite Graphs for Visualization Analysis of Microbiome Data

Visualization analysis plays an important role in metagenomics research. Proper and clear visualization can help researchers get their first insights into data and by selecting different features, also revealing and highlighting hidden relationships and drawing conclusions. To prevent the resulting presentations from becoming chaotic, visualization techniques have to properly tackle the high dimensionality of microbiome data. Although a number of different methods based on dimensionality reduction, correlations, Venn diagrams, and network representations have already been published, there is still room for further improvement, especially in the techniques that allow visual comparison of several environments or developmental stages in one environment. In this article, we represent microbiome data by bipartite graphs, where one partition stands for taxa and the other stands for samples. We demonstrated that community detection is independent of taxonomical level. Moreover, focusing on higher taxonomical levels and the appropriate merging of samples greatly helps improving graph organization and makes our presentations clearer than other graph and network visualizations. Capturing labels in the vertices also brings the possibility of clearly comparing two or more microbial communities by showing their common and unique parts

Word entropy-based approach to detect highly variable genetic markers for bacterial genotyping

Genotyping methods are used to distinguish bacterial strains from one species. Thus, distinguishing bacterial strains on a global scale, between countries or local districts in one country is possible. However, the highly selected bacterial populations (e.g. local populations in hospital) are typically closely related and low diversified. Therefore, currently used typing methods are not able to distinguish individual strains from each other. Here, we present a novel pipeline to detect highly variable genetic segments for genotyping a closely related bacterial population. The method is based on a degree of disorder in analyzed sequences that can be represented by sequence entropy. With the identified variable sequences, it is possible to find out transmission routes and sources of highly virulent and multiresistant strains. The proposed method can be used for any bacterial population, and due to its whole genome range, also noncoding regions are examined

First Complete Genome of the Thermophilic Polyhydroxyalkanoates Producing Bacterium Schlegelella thermodepolymerans DSM 15344

Schlegelella thermodepolymerans is a moderately thermophilic bacterium capable of producing polyhydroxyalkanoates (PHA) – biodegradable polymers representing an alternative to conventional plastics. Here, we present the first complete genome of the type strain S. thermodepolymerans DSM 15344 that was assembled by hybrid approach using both, long (Oxford Nanopore) and short (Illumina) reads. The genome consists of a single 3,858,501bp long circular chromosome with GC content of 70.3%. Genome annotation identified 3,650 genes in total while 3,598 open reading frames belonged to protein coding genes. Functional annotation of the genome and division of genes into clusters of orthologous groups (COG) revealed a relatively high number of 1,013 genes with unknown function or unknown COG, which reflects the fact that only a little is known about thermophilic PHA producing bacteria on a genome level. On the other hand, 270 genes involved in energy conversion and production were detected. This group covers genes involved in catabolic processes which suggests capability of S. thermodepolymerans DSM 15344 to utilize and biotechnologically convert various substrates such as lignocellulose-based saccharides, glycerol, or lipids. Based on the knowledge of its genome, it can be stated that S. thermodepolymerans DSM 15344 is a very interesting, metabolically versatile bacterium with great biotechnological potential

Soubor pravidel pro podvzorkování genomických signálů

Comparison and classification of organisms based on molecular data is an important task of computational biology, since at least parts of DNA sequences for many organisms are available. Unfortunately, methods for comparison are computationally very demanding, suitable only for short sequences. In this paper, we focus on the redundancy of genetic information stored in DNA sequences. We proposed rules for downsampling of DNA signals of cumulated phase. According to the length of an original sequence, we are able to significantly reduce the amount of data with only slight loss of original information. Dyadic wavelet transform was chosen for fast downsampling with minimum influence on signal shape carrying the biological information. We proved the usability of such new short signals by measuring percentage deviation of pairs of original and downsampled signals while maintaining spectral power of signals. Minimal loss of biological information was proved by measuring the Robinson-Foulds distance between pairs of phylogenetic trees reconstructed from the original and downsampled signals. The preservation of inter-species and intra-species information makes these signals suitable for fast sequence identification as well as for more detailed phylogeny reconstruction.Porovnání a klasifikace organismů založená na molekulárních datech je důležitá část výpočetní biologie. V tomto článku jsme se zaměřili na redundanci genetické informace v DNA sekvencích

Progrsivní zarovnání genomických signálů pomocí dynamického borcení časové osy

This paper presents the utilization of progressive alignment principle for positional adjustment of a set of genomic signals with different lengths. The new method of multiple alignment of signals based on dynamic time warping is tested for the purpose of evaluating the similarity of different length genes in phylogenetic studies. Two sets of phylogenetic markers were used to demonstrate the effectiveness of the evaluation of intraspecies and interspecies genetic variability. The part of the proposed method is modification of pairwise alignment of two signals by dynamic time warping with using correlation in a sliding window. The correlation based dynamic time warping allows more accurate alignment dependent on local homologies in sequences without the need of scoring matrix or evolutionary models, because mutual similarities of residues are included in the numerical code of signals.Článek se zabývý progresivním principem zarovnání setu různě dlouhých genomických signálů. Metoda je založená na dynamickém borcení časové osy. Výsledné genomické signály s přízpůsobenou délkou jsou použity pro fylogenetickou analýzu

Using deep learning for gene detection and classification in raw nanopore signals

Recently, nanopore sequencing has come to the fore as library preparation is rapid and simple, sequencing can be done almost anywhere, and longer reads are obtained than with next-generation sequencing. The main bottleneck still lies in data postprocessing which consists of basecalling, genome assembly, and localizing significant sequences, which is time consuming and computationally demanding, thus prolonging delivery of crucial results for clinical practice. Here, we present a neural network-based method capable of detecting and classifying specific genomic regions already in raw nanopore signals—squiggles. Therefore, the basecalling process can be omitted entirely as the raw signals of significant genes, or intergenic regions can be directly analyzed, or if the nucleotide sequences are required, the identified squiggles can be basecalled, preferably to others. The proposed neural network could be included directly in the sequencing run, allowing real-time squiggle processing

Diversity and Evolution of Clostridium beijerinckii and Complete Genome of the Type Strain DSM 791T

Clostridium beijerinckii is a relatively widely studied, yet non-model, bacterium. While 246 genome assemblies of its various strains are available currently, the diversity of the whole species has not been studied, and it has only been analyzed in part for a missing genome of the type strain. Here, we sequenced and assembled the complete genome of the type strain Clostridium beijerinckii DSM 791T, composed of a circular chromosome and a circular megaplasmid, and used it for a comparison with other genomes to evaluate diversity and capture the evolution of the whole species. We found that strains WB53 and HUN142 were misidentified and did not belong to the Clostridium beijerinckii species. Additionally, we filtered possibly misassembled genomes, and we used the remaining 237 high-quality genomes to define the pangenome of the whole species. By its functional annotation, we showed that the core genome contains genes responsible for basic metabolism, while the accessory genome has genes affecting final phenotype that may vary among different strains. We used the core genome to reconstruct the phylogeny of the species and showed its great diversity, which complicates the identification of particular strains, yet hides possibilities to reveal hitherto unreported phenotypic features and processes utilizable in biotechnology

Rapid high-resolution melting genotyping scheme for Escherichia coli based on MLST derived single nucleotide polymorphisms

Routinely used typing methods including MLST, rep-PCR and whole genome sequencing (WGS) are time-consuming, costly, and often low throughput. Here, we describe a novel mini-MLST scheme for Eschericha coli as an alternative method for rapid genotyping. Using the proposed mini-MLST scheme, 10,946 existing STs were converted into 1,038 Melting Types (MelTs). To validate the new mini-MLST scheme, in silico analysis was performed on 73,704 strains retrieved from EnteroBase resulting in discriminatory power D = 0.9465 (CI 95% 0.9726-0.9736) for mini-MLST and D = 0.9731 (CI 95% 0.9726-0.9736) for MLST. Moreover, validation on clinical isolates was conducted with a significant concordance between MLST, rep-PCR and WGS. To conclude, the great portability, efficient processing, cost-effectiveness, and high throughput of mini-MLST represents immense benefits, even when accompanied with a slightly lower discriminatory power than other typing methods. This study proved mini-MLST is an ideal method to screen and subgroup large sets of isolates and/or quick strain typing during outbreaks. In addition, our results clearly showed its suitability for prospective surveillance monitoring of emergent and high-risk E. coli clones'