No description available.

Data profiling is the process of analyzing data and producing an output with statistical summaries. The size of data rapidly increases and it is more difficult to process all data in a reasonable time. All data can not be stored in RAM memory, so it is not possible to run exact single-pass algorithms without using slower computer storage. The diploma thesis focuses on the implementation, comparison, and selection of suitable algorithms for data profiling of large input data. Usage of approximate algorithms brings a possibility to limit mem- ory for computation, do the whole process in RAM memory and the duration of data profiling should be reduced. The tool can compute frequency analysis, cardinality, quantiles, histograms, and other single-column statistics in a short time with a relative error lower than one percent.

No description available.

No description available.

[ES] Uno de los aspectos más apasionantes de la transcripción es la plasticidad transcriptómica y proteómica mediada por los procesos de regulación post-transcripcional (PTR). Los mecanismos PTR como el splicing alternativo (AS) y la poliadenilación alternativa (APA) han emergido como procesos estrechamente regulados que juegan un papel clave en la generación de la complejidad transcriptómica y están asociados con la coordinación de la diferenciación celular o el desarrollo de tejidos. Sin embargo nuestro conocimiento sobre cómo estos mecanismos regulan las propiedades de los productos resultantes para definir el fenotipo es aún muy reducido. La cantidad de variantes existentes y el amplio rango de posibles consecuencias funcionales, hacen su validación funcional una tarea impracticable si se realiza caso por caso. Además, la falta de herramientas para la evaluación funcional orientada a isoformas ha provocado que gran parte del trabajo computacional haya empleado pipelines ad-hoc aplicadas a sistemas biológicos específicos o simplemente hayan confiado en análisis de enriquecimiento GO, los cuales no son informativos del impacto en las propiedades de las isoformas que hay detrás de la regulación PTR. De hecho, a pesar de las más de sesenta mil publicaciones relativas al AS, muy pocas isoformas se han asociado con propiedades específicas, mientras que el número de nuevas variantes AS/APA con function desconocida crece exponencialmente debido a las técnicas de secuenciación de segunda generación (NGS). Además, y debido a limitaciones técnicas de las NGS para reconstruir la estructura de los transcritos, las tecnologías de secuenciación de tercera generación (TGS) están definiendo una nueva era en la que, por primera vez, es posible conocer la secuencia de elementos estructurales y funcionales en los mRNAs. En esta tesis se han abordado tres propósitos principales para poder avanzar en el estudio funcional de las isoformas. En primer lugar, con las TGS siendo cada vez más utilizadas, la evaluación de la calidad de los transcriptomas \textit{de novo} es esencial para asegurar la fiabilidad de la diversidad transcriptómica encontrada. La falta de análisis de calidad orientados a secuencias largas ha motivado el desarrollo de SQANTI, una pipeline automatizado para la exhaustiva evaluación de TGS transcriptomas. En segundo lugar, la información a nivel de gen de la mayoría de bases de datos funcionales sigue siendo el principal escollo para el estudio de la variabilidad entre isoformas, especialmente en el caso de las isoformas nuevas, en las que las bases de datos estáticas impiden su caracterización. Así, hemos diseñado IsoAnnot, que construye una base de datos de anotaciones funcionales con resolución a nivel de isoformas integrando información diseminada por múltiples bases de datos y métodos de predicción. Finalmente, la indisponibilidad de métodos para estudiar el impacto funcional de la regulación de isoformas, nos ha motivado a desarrollar tappAS, una herramienta dinámica, flexible y diseñada para facilitar el abordaje de este tipo de estudios. Por lo tanto, durante esta tesis hemos desarrollado una infraestructura que resuelve los retos principales del análisis funcional de isoformas, proporcionando un conjunto de nuevos métodos y herramientas que ofrecen una oportunidad única para explorar cómo el fenotipo se especifica post-transcripcionalmente, mediante la alteración de las propiedades funcionales de las isoformas expresadas. La aplicación de nuestro análisis a un doble sistema de diferenciación neuronal en ratón definió el efecto de la regulación de isoformas entre la diferenciación de motoneuronas y oligodendrocitos para múltiples elementos funcionales. Entre ellos, hemos descubierto regiones transmembrana que son diferencialmente incluidas en las isoformas expresadas entre ambos tipos celulares y cuya regulación podría estar contribuyendo al control de / [CA] Un dels aspectes més emocionants de la biologia del transcriptoma és l'adaptabilitat contextual de transcriptomes i proteomes eucariotes mitjançant la regulació post-transcripcional (PTR). Els mecanismes PTR, com el splicing alternatiu (AS) i la poliadenilació alternativa (APA), s'han convertit en processos molt regulats que juguen un paper clau en la generació de la complexitat del transcriptoma i en la coordinació de la diferenciació cel·lular o del desenvolupament de teixits. No obstant això, el nostre coneixement de com aquests mecanismes imprimeixen característiques funcionals diferents al conjunt resultant d'isoformes per definir el fenotip observat és encara escàs. El nombre de variants de PTR i les seues conseqüències potencialment funcionals fa que la validació funcional sigui una tasca poc pràctica si es fa cas per cas. A més, la manca d'enfocaments funcionals orientats a isoformes ha fet que gran part del treballs computacionals per esbrinar qüestions funcionals a nivell de transcriptoma siguen estratègies computacionals ad hoc aplicades a sistemes biològics específics o bé basats en un simple anàlisi d'enriquiment GO, que no aporten informació sobre l'impacte de la PTR sobre les propietats de les isoformes. Així, malgrat les més de 60.000 publicacions existents sobre AS, poques de les isoformes existents s'han associat a propietats específiques, mentre que el nombre de noves variants AS/APA amb funcions desconegudes i fins i tot inexplorades augmenta de manera exponencial gràcies a la seqüenciació de nova generació (NGS). A causa de les limitacions tècniques del NGS per reconstruir l'estructura dels transcrits, la seqüenciació d'alt rendiment de transcrits de longitud completa mitjançant tecnologies de tercera generació (TGS) obre una nova era en la transcriptòmica, ja que millora la definició dels models genètics i, per primera vegada, permet associar amb precisió esdeveniments funcionals dins de la molècula d'ARN. Aquesta tesi aborda tres grans reptes per a progressar en l'estudi de la funció de les isoformes. En primer lloc, amb l'aparició i la popularitat creixent del TGS, la definició precisa i la caracterització completa dels transcriptomes de novo són essencials per garantir la qualitat de qualsevol conclusió sobre la diversitat del transcriptoma. La manca d'anàlisis de qualitat orientats a lectures llargues va motivar el desenvolupament de SQANTI (https://bitbucket.org/ ConesaLab / sqanti), una estratègia computacional automatitzada per a la caracterització estructural i l'avaluació de la qualitat dels transcriptomes de longitud completa. En segon lloc, els recursos funcionals existents centrats en el gen suposen una gran limitació per a l'estudi extensiu de la variabilitat funcional de les isoformes, especialment en les noves isoformes, que no es poden caracteritzar per bases de dades estàtiques. Per tant, vam dissenyar IsoAnnot, que construeix dinàmicament una base de dades amb anotacions funcionals a nivell d'isoforma, que utilitza com a informació d'entrada les seqüències dels transcrits i integra informació de diverses bases de dades i mètodes de predicció. Finalment, com no hi havia cap mètode per interrogar l'impacte funcional del PTR, vam desenvolupar nous enfocaments i eines fàcils d'utilitzar, com ara tappAS (http://tappas.org/), dissenyada per facilitar als investigadors els estudis funcionals de transcriptoma complet i de regulació d'isoformes en contexts específics. Per tant, aquesta tesi descriu el desenvolupament d'un marc d'anàlisi que aborda els reptes fonamentals de l'anàlisi funcional d'isoformes. Aplicada a un sistema de diferenciació neuronal murina, vam descobrir regions transmembrana específiques d'isoformes, la modulació de les quals per PTR podria contribuir a controlar la dinàmica mitocondrial específica del tipus cel·lular durant la determinació del destí neuronal. / [EN] One of the most exciting aspects of transcriptome biology is the contextual adaptability of eukaryotic transcriptomes and proteomes by post-transcriptional regulation (PTR). PTR mechanisms such as alternative splicing (AS) and alternative polyadenylation (APA) have emerged as tightly regulated processes playing a key role in generating transcriptome complexity and coordinating cell differentiation or tissue development. However, how these mechanisms imprint distinct functional characteristics on the resulting set of isoforms to define the observed phenotype remains poorly understood. The number of PTR variants and their resulting range of potentially functional consequences makes their functional validation an impractical task if done on a case-by-case basis. Besides, the lack of isoform-oriented functional profiling approaches has made that much of the computational work done to elucidate transcriptome-wide functional questions has either involved ad hoc computational pipelines applied to specific biological systems or has relied on simple GO-enrichment analysis that are not informative about the PTR impact on isoform properties. Thus, even though more than 60,000 publications on AS, a few number of existing isoforms have been associated with specific properties while the number of novel AS/APA variants with unknown and even unexplored functions is exponentially increasing thanks to the use of next-generation sequencing (NGS). Due to the technical limitations of NGS to reconstruct the transcript structure, high-throughput sequencing of full-length transcripts using third-generation technologies (TGS) is opening up a new transcriptomics era that enhances the definition of gene models and, for the first time, enables to precisely associate functional events within the RNA molecule. This thesis addresses three major challenges to the progression of the study of isoform function. First, with the emergence and increasing popularity of TGS, the accurate definition and comprehensive characterisation of de novo transcriptomes is essential to ensure the quality of any conclusions on transcriptome diversity drawn from these data. The lack of long-read oriented quality aware analysis motivated the development of SQANTI \url{(https://bitbucket.org/ConesaLab/sqanti)}, an automated pipeline for the structural characterization and quality assessment of full-length transcriptomes. Secondly, the gene-centric nature of functional resources remained the major limitation to the extended study of functional isoform variability, especially for novel isoforms, which cannot be characterised by static databases. Thus, we designed IsoAnnot, which dynamically constructs an isoform-resolved rich database of functional annotations by using as input transcript sequences and integrating information disseminated across several databases and prediction methods. Finally, because no methods to interrogate the functional impact of PTR were available, we developed novel approaches and user-friendly tools such as tappAS \url{(http://tappas.org/)}, designed to facilitate researchers the transcriptome-wide functional study of context-specific isoform regulation. Thereby, this thesis describes the development of an analysis framework that tackles the fundamental challenges of the isoform functional analysis by providing a set of novel methods and tools that offer an unique opportunity to explore how the phenotype is specified by altering the functional characteristics of expressed isoforms. Applied to a murine neural differentiation system, our pipeline profiled the effect of isoform regulation on the inclusion of several functional elements within transcripts between motor-neuron and oligodendrocyte differentiation systems and specifically, we discovered isoform-specific transmembrane regions whose modulation by PTR might contribute to control cell type-specific mitochondrial dynamics during neural fate determination. / This work was funded by the following grants: From 2014 to 2018. FPU: Training programme for Academic Staff. Spanish Ministry of Education, FPU2013/02348. From 2016 to 2019. NOVELSEQ: Novel methods for new challenges in the analysis of high-throughput sequencing data. MINECO, BIO2015-1658-R. From 2014 to 2017. DEANN: Developing a European American NGS Network. EU Marie Curie IRSES, GA-612583. / Fuente Lorente, LDL. (2019). Development of a bioinformatics approach for the functional analysis of alternative splicing [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/124974 / TESIS

No description available.

Pyrogenic ecosystems are maintained by fires which vary in frequency, seasonality, and intensity. Florida oak-saw palmetto scrub ecosystem is characterized by fires occurring at intervals of 10-20 years. Diverse factors as private land acquisition and development has created a patchy distribution of scrub ecosystems and also interrupted the natural fire cycle. The effects of fire over plant regeneration and fauna habitat utilization of the scrub have been well characterized in previous research. In the present paper the objective is to characterize the short- and long-term fire effects on the soil microbial community. Fire effects were studied in a chronosequence, comprising a recently burned scrub during a winter-prescribed fire to scrub where fire did not occur for 40 years. The number of culturable cells was reduced by two orders of magnitude by indirect fire effects and environmental factors, principally hydric stress. However, the duration of fire effects was very short since the microbial community returned to pre-fire numbers and activity by day 47 after fire. Microbial community activity was distinctively related to inoculum density in the soil and litter samples. Soil and litter microbial communities showed differences in metabolic activity. There was no difference in substrate utilization pattern, but there was significant seasonal variation related to the decrease in water content during the month of May. Substrate utilization by litter microbial communities was higher during the month of January compared to soil microbial communities and this relationship was inversed during the month of May probably associated to the more stringent conditions, low water availability, on the litter layer. Seasonal effects outweighed fire effects in this study as this environmental constraint determined the microbial community structure and activity.

Stroke is an acute neurological deficit that results from abnormal blood flow to the brain. The term stroke encompasses two primary subgroups: hemorrhagic stroke that is due to extravasation of blood and ischemic stroke that is due to vessel obstruction. Determining stroke type and underlying etiology is a crucial step in patient management as it influences treatment strategies. Currently diagnosis of stroke relies on clinical examination and neuroimaging, but there is a lack of rapid diagnostic and prognostic testing. Using microarray technology we identified a novel association between elevated peripheral blood expression of MCEMP1 and stroke. We have also shown that MCEMP1 discriminates between primary stroke types and predicts one-month post-stroke prognosis. Since genetic mechanisms underlying stroke remain incompletely understood we next conducted a global gene network analysis. Network analysis identified four large groups of co-expressed genes associated with ischemic stroke. NLRC4, CKLF, and HS.546375 were the most interconnected genes within unique modules and each was also independently associated with ischemic stroke. We show that multi-gene models have greater discriminative capacity for stroke and stroke prognosis, than single gene models. In addition to stroke biomarkers we also identified biomarkers of atrial fibrillation (AF), a known risk factor of stroke. Currently our understanding of the molecular mechanisms underlying AF remains incompletely understood. Thus we conducted whole blood expression profiling in patients with persistent AF before and after successful electrical cardioversion, a procedure that aims to restore sinus rhythm to the heart. We identified elevated expression of SLC25A20 and PDK4 during AF as compared with sinus rhythm. Furthermore we show that SLC25A20, PDK4 and NT-proBNP have incremental utility to discriminate AF from sinus rhythm. Taken together, the thesis implicates new genes with stroke and AF, and also indicates that whole blood RNA biomarkers may have clinical utility. / Thesis / Doctor of Philosophy (PhD)

Sediment deposited in back-arc basins preserves a record of the extensional, volcanic and tectonic history of the arc-backarc systems. Back-arc sedimentation is of particular interest as seafloor massive sulfide deposits may be preserved in back-arc basin sediments. The study of back-arc sedimentation using acoustic data, such as high-resolution sub-bottom profiling data (Parasound) and seismic reflection data, can be a much more cost effective approach than analysis of sediments recovered from drill cores. In this study, we use these two acoustic datasets to build a facies model of sedimentation in the northeast Lau Basin, an actively opening back-arc basin in the southwest Pacific Ocean. Using 830 km of Parasound and 730 km of seismic lines along 4 transects of the Lau Basin, we constructed one of the most detailed models of sedimentation in a back-arc basin to date. Parasound data show distinct echoes with sub-bottom reflections indicative of a high proportion of hemipelagic sediment, whereas the indistinct echoes with few to no sub-bottom reflections indicate a higher proportion of coarse, bedded, volcaniclastic turbidites. Hyperbolic echoes are associated with regions of rugged or uneven terrain characterized by exposed, rough basement or deposits formed by contour currents, turbidity currents, slumps or slides. These relationships form the basis of an echo-facies legend developed for typical back-arc basin sediments. The echo-facies observed in the Parasound, and confirmed by deeper-penetrating seismic reflection data, provide important insights into the sedimentary processes involved in back-arc sedimentation. We observed mass transport deposits (MTDs) in all of the sub-basins and slope deposits within and on the flanks of active rifts (e.g., the Fonualei Rift and Spreading Centre, FRSC), suggesting a direct correlation between MTDs and zones of active rifting. We observed an overall increase in sediment thickness toward the Tofua Arc which suggests it is the main sediment source, but local variations in sediment thickness suggest significant input from local intrabasinal seamounts. The uppermost echo-facies in over 60% of the sub-basins in the study area is dominated by hemipelagic material, which suggests an abrupt transition in the dominant sediment source from volcaniclastic to hemipelagic at around 0.3 Ma, when a period of volcanic quiescence from the Tofua Arc began. The study shows that a near complete record of basin evolution can be constructed using geophysical and acoustic methods and that this work may help to locate future drill sites where in situ data can be collected.

Driving Behavior Analysis (DBA) plays a pivotal role in designing intelligent transportation systems, enhancing road safety, and advancing Autonomous Vehicles (AVs). Driver identification, as a key aspect of DBA, has the potential to provide unprecedented opportunities for enhanced security and driver profiling. However, the current solutions for driver identification suffer from demanding extensive data collection, limited scalability, and inadequate generalization. Furthermore, DBA is also essential for training AVs, addressing the main challenges they face: accurately perceiving their surroundings to make informed decisions and to navigate safely, and effectively handling unforeseen scenarios. In the first part of this thesis, we concentrate on behavior analysis for driver identification and verification and design two novel schemes aiming to reduce data dependency and enhance the generalization ability of existing approaches. First, we propose a novel driver identification model, called DriverRep, which reduces data dependency by presenting a fully unsupervised triplet loss training. DriverRep is the first model that extracts the latent representations associated with each driver, called driver embeddings, in an unsupervised manner. In addition, we develop a novel model to tackle driver verification and impostor detection tasks based on DBA and extracted driver embeddings. In the second part, we focus on behavior prediction for AVs and their surrounding agents. First, we tackle behavior prediction in dynamic and complex scenarios by introducing three novel prediction models for forecasting drivers intentions and behaviors at unsignalized intersections. We then address social reasoning by proposing a novel prediction model that analyzes agent interactions using graph neural networks, making the scene understanding process more informative for AVs. Our proposed prediction model, called STAG, explicitly activates social modeling with a directed graph representation while considering spatial and temporal inter-agent correlations. We further design a novel prediction system, namely CAPHA, which conditions the future behavior of agents on grid-based plans modeled as a Markov decision process and solves the prediction task via inverse reinforcement learning to produce scene compliant behaviors. Moreover, we introduce a novel goal-based prediction model, called GMP, which encodes interactions between agents and dynamic and static context information to estimate the distribution of target goals, efficiently considering the inherent uncertainty in agents behavior. Extensive quantitative and qualitative comparisons have been conducted between the developed solutions and related benchmark schemes using various scenarios and environments. The obtained results demonstrate the potential of these solutions for the understudy tasks of DBA and real-world applications.