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Určování genetické odlišnosti biologických sekvencí DNA / Determination of genetic differences of biological DNA sequencesSliž, Ladislav Unknown Date (has links)
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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In Vivo RNAi Rescue in Drosophila melanogaster with Genomic Transgenes from Drosophila pseudoobscuraSchnorrer, Frank, Tomancak, Pavel, Schönbauer, Cornelia, Ejsmont, Radoslaw K., Langer, Christoph C. H. 10 December 2015 (has links)
Background
Systematic, large-scale RNA interference (RNAi) approaches are very valuable to systematically investigate biological processes in cell culture or in tissues of organisms such as Drosophila. A notorious pitfall of all RNAi technologies are potential false positives caused by unspecific knock-down of genes other than the intended target gene. The ultimate proof for RNAi specificity is a rescue by a construct immune to RNAi, typically originating from a related species.
Methodology/Principal Findings
We show that primary sequence divergence in areas targeted by Drosophila melanogaster RNAi hairpins in five non-melanogaster species is sufficient to identify orthologs for 81% of the genes that are predicted to be RNAi refractory. We use clones from a genomic fosmid library of Drosophila pseudoobscura to demonstrate the rescue of RNAi phenotypes in Drosophila melanogaster muscles. Four out of five fosmid clones we tested harbour cross-species functionality for the gene assayed, and three out of the four rescue a RNAi phenotype in Drosophila melanogaster.
Conclusions/Significance
The Drosophila pseudoobscura fosmid library is designed for seamless cross-species transgenesis and can be readily used to demonstrate specificity of RNAi phenotypes in a systematic manner.
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Predikce škodlivosti aminokyselinových mutací s využitím metody MAPP / Predicting the Effect of Amino Acid Substitutions on Protein Function Using MAPP MethodPelikán, Ondřej January 2014 (has links)
This thesis discusses the issue of predicting the effect of amino acid substitutions on protein function using MAPP method. This method requires the multiple sequence alignment and phylogenetic tree constructed by third-party tools. Main goal of this thesis is to find the combination of suitable tools and their parameters to generate the inputs of MAPP method on the basis of analysis on one massively mutated protein. Then, the MAPP method is tested with chosen combination of parameters and tools on two large independent datasets and consequently is compared with the other tools focused on prediction of the effect of mutations. Apart from this the web interface for the MAPP method was created. This interface simplifies the use of the method since the user need not to install any tools or set any parameters.
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Detekce genomových variací / Detection of Genome VariationsBeluský, Tomáš January 2013 (has links)
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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Vyhodnocení příbuznosti organismů pomocí číslicového zpracování genomických dat / Evaluation of Organisms Relationship by Genomic Signal ProcessingŠkutková, Helena January 2016 (has links)
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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On dysgraphia diagnosis support via the automation of the BVSCO test scoring : Leveraging deep learning techniques to support medical diagnosis of dysgraphia / Om dysgrafi diagnosstöd via automatisering av BVSCO-testpoäng : Utnyttja tekniker för djupinlärning för att stödja medicinsk diagnos av dysgrafiSommaruga, Riccardo January 2022 (has links)
Dysgraphia is a rather widespread learning disorder in the current society. It is well established that an early diagnosis of this writing disorder can lead to improvement in writing skills. However, as of today, although there is no comprehensive standard process for the evaluation of dysgraphia, most of the tests used for this purpose must be done at a physician’s office. On the other hand, the pandemic triggered by COVID-19 has forced people to stay at home and opened the door to the development of online medical consultations. The present study therefore aims to propose an automated pipeline to provide pre-clinical diagnosis of dysgraphia. In particular, it investigates the possibility of applying deep learning techniques to the most widely used test for assessing writing difficulties in Italy, the BVSCO-2. This test consists of several writing exercises to be performed by the child on paper under the supervision of a doctor. To test the hypothesis that it is possible to enable children to have their writing impairment recognized even at a distance, an innovative system has been developed. It leverages an already developed customized tablet application that captures the graphemes produced by the child and an artificial neural network that processes the images and recognizes the handwritten text. The experimental results were analyzed using different methods and were compared with the actual diagnosis that a doctor would have provided if the test had been carried out normally. It turned out that, despite a slight fixed bias introduced by the machine for some specific exercises, these results seemed very promising in terms of both handwritten text recognition and diagnosis of children with dysgraphia, thus giving a satisfactory answer to the proposed research question. / Dysgrafi är en ganska utbredd inlärningsstörning i dagens samhälle. Det är väl etablerat att en tidig diagnos av denna skrivstörning kan leda till en förbättring av skrivförmågan. Även om det i dag inte finns någon omfattande standardprocess för utvärdering av dysgrafi måste dock de flesta av de tester som används för detta ändamål göras på en läkarmottagning. Å andra sidan har den pandemi som utlöstes av COVID-19 tvingat människor att stanna hemma och öppnat dörren för utvecklingen av medicinska konsultationer online. Syftet med denna studie är därför att föreslå en automatiserad pipeline för att ge preklinisk diagnos av dysgrafi. I synnerhet undersöks möjligheten att tillämpa djupinlärningstekniker på det mest använda testet för att bedöma skrivsvårigheter i Italien, BVSCO-2. Testet består av flera skrivövningar som barnet ska utföra på papper under överinseende av en läkare. För att testa hypotesen att det är möjligt att göra det möjligt för barn att få sina skrivsvårigheter erkända även på distans har ett innovativt system utvecklats. Det utnyttjar en redan utvecklad skräddarsydd applikation för surfplattor som fångar de grafem som barnet producerar och ett artificiellt neuralt nätverk som bearbetar bilderna och känner igen den handskrivna texten. De experimentella resultaten analyserades med hjälp av olika metoder och jämfördes med den faktiska diagnos som en läkare skulle ha ställt om testet hade utförts normalt. Det visade sig att, trots en liten fast bias som maskinen införde för vissa specifika övningar, verkade dessa resultat mycket lovande när det gäller både igenkänning av handskriven text och diagnos av barn med dysgrafi, vilket gav ett tillfredsställande svar på den föreslagna forskningsfrågan.
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Multiple sequence analysis in the presence of alignment uncertaintyHerman, Joseph L. January 2014 (has links)
Sequence alignment is one of the most intensely studied problems in bioinformatics, and is an important step in a wide range of analyses. An issue that has gained much attention in recent years is the fact that downstream analyses are often highly sensitive to the specific choice of alignment. One way to address this is to jointly sample alignments along with other parameters of interest. In order to extend the range of applicability of this approach, the first chapter of this thesis introduces a probabilistic evolutionary model for protein structures on a phylogenetic tree; since protein structures typically diverge much more slowly than sequences, this allows for more reliable detection of remote homologies, improving the accuracy of the resulting alignments and trees, and reducing sensitivity of the results to the choice of dataset. In order to carry out inference under such a model, a number of new Markov chain Monte Carlo approaches are developed, allowing for more efficient convergence and mixing on the high-dimensional parameter space. The second part of the thesis presents a directed acyclic graph (DAG)-based approach for representing a collection of sampled alignments. This DAG representation allows the initial collection of samples to be used to generate a larger set of alignments under the same approximate distribution, enabling posterior alignment probabilities to be estimated reliably from a reasonable number of samples. If desired, summary alignments can then be generated as maximum-weight paths through the DAG, under various types of loss or scoring functions. The acyclic nature of the graph also permits various other types of algorithms to be easily adapted to operate on the entire set of alignments in the DAG. In the final part of this work, methodology is introduced for alignment-DAG-based sequence annotation using hidden Markov models, and RNA secondary structure prediction using stochastic context-free grammars. Results on test datasets indicate that the additional information contained within the DAG allows for improved predictions, resulting in substantial gains over simply analysing a set of alignments one by one.
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Molecular epidemiology of epidemic severe malaria caused by Plasmodium vivax in the state of Amazonas, Brazil /Santos-Ciminera, Patricia Dantas. Ciminera, Patricia Dantas Santos. Santos, Patricia. January 2005 (has links) (PDF)
Thesis (Ph. D.)--Uniformed Services University of the Health Sciences, 2005. / Typescript (photocopy).
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Analyse visuelle et cérébrale de l’état cognitif d’un apprenantBen Khedher, Asma 02 1900 (has links)
No description available.
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Electrostaticanalisys the Ras active siteKhan, Abdul Kareem 05 March 2009 (has links)
La preorganització electrostàtica del centre actiu s'ha postulat com el mecanisme genèric de l'acció dels enzims. Així, alguns residus "estratègics" es disposarien per catalitzar reaccions interaccionant en una forma més forta amb l'estat de transició, baixant d'aquesta manera el valor de l'energia dactivació g cat. S'ha proposat que aquesta preorientació electrostática s'hauria de poder mostrar analitzant l'estabilitat electrostàtica de residus individuals en el centre actiu.Ras es una proteïna essencial de senyalització i actúa com un interruptor cel.lular. Les característiques estructurals de Ras en el seu estat actiu (ON) són diferents de les que té a l'estat inactiu (OFF). En aquesta tesi es duu a terme una anàlisi exhaustiva de l'estabilitat dels residus del centre actiu deRas en l'estat actiu i inactiu. / The electrostatic preorganization of the active site has been put forward as the general framework of action of enzymes. Thus, enzymes would position "strategic" residues in such a way to be prepared to catalyze reactions byinteracting in a stronger way with the transition state, in this way decreasing the activation energy g cat for the catalytic process. It has been proposed thatsuch electrostatic preorientation should be shown by analyzing the electrostatic stability of individual residues in the active site.Ras protein is an essential signaling molecule and functions as a switch in thecell. The structural features of the Ras protein in its active state (ON state) are different than those in its inactive state (OFF state). In this thesis, an exhaustive analysis of the stability of residues in the active and inactive Ras active site is performed.
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