Investigating Power and Limitations of Ensemble Motif Finders Using Metapredictor CE3

Ensemble methods represent a relatively new approach to motif discovery that combines the results returned by "third-party" finders with the aim of achieving a better accuracy than that obtained by the single tools. Besides the choice of the external finders, another crucial element for the success of an ensemble method is the particular strategy adopted to combine the finders' results, a.k.a. learning function. Results appeared in the literature seem to suggest that ensemble methods can provide noticeable improvements over the quality of the most popular tools available for motif discovery. With the goal of better understanding potentials and limitations of ensemble methods, we developed a general software architecture whose major feature is the flexibility with respect to the crucial aspects of ensemble methods mentioned above. The architecture provides facilities for the easy addition of virtually any third-party tool for motif discovery whose code is publicly available, and for the definition of new learning functions. We present a prototype implementation of our architecture, called CE3 (Customizable and Easily Extensible Ensemble). Using CE3, and available ensemble methods, we performed experiments with three well-known datasets. The results presented here are varied. On the one hand, they confirm that ensemble methods cannot be just considered as the universal remedy for "in-silico" motif discovery. On the other hand, we found some encouraging regularities that may help to find a general set up for CE3 (and other ensemble methods as well) able to guarantee substantial improvements over single finders in a systematic way

Sistema inteligente de recolha, armazenamento e visualização de informação proveniente do twitter

As redes sociais têm ganho bastante popularidade para a partilha de informação sobre os mais diversos tópicos desde a política, desporto ou mesmo aspetos do quotidiano. As mensagens partilhadas no Twitter1 (tweets) são essencialmente públicas constituindo uma fonte de informação que por ser difundida em tempo real pode revelar-se útil em domínios como o turismo, marketing, saúde ou segurança. Este artigo descreve o desenvolvimento de um Sistema de Informação envolvendo a criação de um repositório de tweets (corpus) escritos em Português Europeu e publicados em Portugal. O sistema envolve também uma REST API que permite o acesso à informação armazenada e um Dashboard Web para análise e visualização de indicadores sobre os dados.info:eu-repo/semantics/acceptedVersio

Generic data processing & analysis architecture of a personal health system to manage daily interactive sessions in patients with major depression

[EN] The World Health Organization (WHO) considers Major Unipolar Depression as a significant cause of disability worldwide (globally, more than 350 million people of all ages suffer from depression). This common mental disorder spends many economic and clinical resources and it is sometimes responsible for patient suicides. The work presented in this Master Thesis document describes the design and implementation of a generic Data Processing & Analysis module which has been included within the Personal Health System developed in the Help4Mood Research European Project [FP7 ICT-248765]. The aim of Help4Mood is to develop a computational distributed system to support the treatment of people with Major Depression in the community. It is focused on reducing depressive symptoms, improving functioning, and preventing the recurrence of symptoms in the future. The developed Data Processing & Analysis module is the mechanism responsible of: i) The analysis of the objective and subjective inputs received from the user; ii) The inference of clinical concepts and the production of a set of activities to be suggested by the system during the treatment of depression; iii) The planning of the most appropriate interactive sessions based on the inferred activities; iv) The generation of adequate emotional responses represented in the Help4Mood¿s Virtual Agent to better engages the patient with the use of the system and to facilitate a better adherence to the treatment process; and v) The summarization of the relevant clinical information about the progress of the patient every week. The results of this work suggests that the generic Data Processing & Analysis module is useful for managing flexible and personalised sessions in the treatment of the depression, and it is able to be adapted to other clinical domains. It provides a systematic framework for data collection, processing and analysis which improves the continuous monitoring and treatment of the patients. Additionally, our module improves the communication between patients and clinicians by facilitating the joint reflexion about the evolution and improvements in wellbeing at the different stages of the treatment[ES] La Organización Mundial de la Salud (OMS) considera la Depresión Mayor Unipolar como una causa significativa de discapacidad mundial (más de 350 millones de personas de todas las edades padecen depresión). Esta común enfermedad mental consume muchos recursos económicos y clínicos y en ocasiones es responsable de suicidios de pacientes. El trabajo presentado en esta Tesina de Máster describe el diseño y la implementación de un módulo genérico de Procesado y Análisis de Datos, el cual ha sido incluido en el Sistema Personal de Salud desarrollado en el proyecto de investigación Europeo Help4Mood [FP7 ICT-248765]. El propósito de Help4Mood es el desarrollo de un sistema computacional distribuido que de soporte al tratamiento de personas con Depresión Mayor. Se centra en la reducir los síntomas de la depresión, mejorar el funcionamiento, y en prevenir la futura reaparición de los síntomas. El módulo de Procesado y Análisis de Datos desarrollado es el responsable de: i) El análisis de los datos objetivos y subjetivos recibidos por parte del usuario del sistema; ii) La inferencia de conceptos clínicos y la producción de un conjunto de actividades que serán propuestas por el sistema durante el tratamiento de la depresión; iii) La planificación de la sesión interactiva más apropiada basada en las actividades inferidas; iv) La generación de una respuesta emocional adecuada que el Agente Virtual de Help4Mood muestre para lograr una mayor participación de los usuarios en el uso del sistema y una mejor adherencia al proceso del tratamiento; y v) El resumen de la información clínica relevante sobre el progreso semanal del paciente. Los resultados de este trabajo sugieren que el módulo genérico de Procesado y Análisis de Datos es útil para la gestión flexible y personalizada de sesiones diarias para el tratamiento de la Depresión, además podría ser adaptada a otros dominios clínicos. Este módulo proporciona un marco sistemático para la recopilación, procesamiento y análisis que permite mejorar el control continuo y el tratamiento de los pacientes. Adicionalmente, nuestro módulo mejora la comunicación entre los pacientes y los médicos, facilitando la reflexión conjunta sobre la evolución y las mejoras en el bienestar en las diferentes etapas del tratamiento.Bresó Guardado, A. (2013). Generic data processing & analysis architecture of a personal health system to manage daily interactive sessions in patients with major depression. http://hdl.handle.net/10251/39155Archivo delegad

Structural and statistical aspects in joint modelling of artesunate pharmacometrics and malarial parasite lifecycle

Malaria is a parasite with a complex lifecycle, and commonly used antimalarial agents from the artemisinin family have varied effectiveness over different stages of this lifecycle. The pharmacokinetic profile of the artemisinins is also strongly influenced by the parasite burden and lifecycle stage. This work introduces a new pharmacokinetic and pharmacodynamic model incorporating these interdependent drug and lifecycle features, for orally administered artesunate and its principal metabolite dihydroartemisinin. This model, like the underlying system whose features it attempts to capture, is quite complex and cannot be solved analytically like standard linear first-order compartmental models previously used for pharmacokinetic modelling of these drugs. Therefore, understanding, inference and validity are explored through use of the modern statistical technique of a Sequential Monte Carlo sampler. Structural, numerical and practical identifiability are important concepts for all models, the latter two especially so in this case as the model structure does not admit an algebraic structural identifiability analysis. Motivated by this, the above identifiability concepts are also investigated in connection with the Sequential Monte Carlo technique. Sequential Monte Carlo is demonstrated to be a useful tool for gaining insight into models whose structural identifiability is not known, just as it is also shown to have significant advantages in parameter inference over the classical approach. The coupled parasite lifecycle and artemisinin-derivative model is built in stages, starting with an in vitro submodel capturing the dynamics of uptake of artemisinins into parasitised and non-parasitised red blood cells. Next, the parasite lifecycle, or ‘ageing’ model, is introduced, which uses a new concept of shadow compartments to achieve its aims of describing ageing in continuous time and to exhibit sufficient control over the parasite population. Finally, these models are integrated together into the full coupled pharmacokinetic and pharmacodynamic model. More work is needed to fully assess the resultant model on clinical datasets, but the building blocks upon which it was constructed appear to fulfil their aims reasonably well

Optimización de la Entrada Salida mediante librerías y lenguajes paralelos

Uno de los grandes retos de la HPC (High Performance Computing) consiste en optimizar el subsistema de Entrada/Salida, (E/S), o I/O (Input/Output). Ken Batcher resume este hecho en la siguiente frase: "Un supercomputador es un dispositivo que convierte los problemas limitados por la potencia de cálculo en problemas limitados por la E/S" ("A Supercomputer is a device for turning compute-bound problems into I/O-bound problems") . En otras palabras, el cuello de botella ya no reside tanto en el procesamiento de los datos como en la disponibilidad de los mismos. Además, este problema se exacerbará con la llegada del Exascale y la popularización de las aplicaciones Big Data. En este contexto, esta tesis contribuye a mejorar el rendimiento y la facilidad de uso del subsistema de E/S de los sistemas de supercomputación. Principalmente se proponen dos contribuciones al respecto: i) una interfaz de E/S desarrollada para el lenguaje Chapel que mejora la productividad del programador a la hora de codificar las operaciones de E/S; y ii) una implementación optimizada del almacenamiento de datos de secuencias genéticas. Con más detalle, la primera contribución estudia y analiza distintas optimizaciones de la E/S en Chapel, al tiempo que provee a los usuarios de una interfaz simple para el acceso paralelo y distribuido a los datos contenidos en ficheros. Por tanto, contribuimos tanto a aumentar la productividad de los desarrolladores, como a que la implementación sea lo más óptima posible. La segunda contribución también se enmarca dentro de los problemas de E/S, pero en este caso se centra en mejorar el almacenamiento de los datos de secuencias genéticas, incluyendo su compresión, y en permitir un uso eficiente de esos datos por parte de las aplicaciones existentes, permitiendo una recuperación eficiente tanto de forma secuencial como aleatoria. Adicionalmente, proponemos una implementación paralela basada en Chapel

Modelling and evaluation of interventions to support overactive bladder issues in spinal cord injury subjects

This thesis uses mathematical modelling to improve understanding and address the challenges associated with a neurogenic bladder in patients with spinal cord injuries (SCIs), focusing on an overactive bladder (OAB) and detrusor sphincter dyssynergia (DSD). OAB refers to the occurrence of unwanted and uncontrolled contractions during the bladder’s filling stage, while DSD involves simultaneous contractions of the detrusor and urethral sphincters [1]. Traditionally, OAB symptoms have been treated with anticholinergic drugs, particularly oxybutynin (OXY). However, due to the typical occurrence of adverse effects, a novel drug called mirabegron (MBG) has been developed with the aim of minimising these unwanted effects [2]. Botulinum toxin type A (BoNT/A) injections are also administered as a second-line treatment, every 6 to 9 months, depending on the reappearance of involuntary contractions [3]. Furthermore, clean intermittent catheterisation is typically performed for DSD every 4 to 6 hours [4], [5]. This thesis represents the initial phase of a larger project that aims to develop a “smart” catheter to assist SCI patients with OAB and DSD symptoms. The primary objective of this device is to estimate unwanted bladder contractions associated with OAB, facilitating patient monitoring by the clinician. The thesis specifically focuses on characterising the associated fluid dynamics and the development of structurally identifiable pharmacometrics models for the three different treatments (BoNT/A, OXY and MBG) targeting OAB, using the limited literature data available in these areas. In this thesis population pharmacokinetic (PK) models have been developed for OXY and MBG using mean human data from the literature. Covariate assessment methods have been employed to explore their potential influence on the PK, aiming to identify factors contributing to observed variability in plasma versus time profiles of OXY and MBG. BoNT/A has been characterised through a preliminary target-mediated drug disposition (TMDD) kinetic/pharmacodynamic (K-PD) model, based on limited contractility versus time data. This model is the first study that attempts to mathematically characterise the long-term effects of BoNT/A on the detrusor of SCI patients. The duration of the effects of BoNT/A is medically significant, considering the limited knowledge available on its long-term application, and the timing of re-treatment is of significant importance to SCI sufferers. Thus, once fully validated, this model could potentially determine the appropriate timing for rescheduling of BoNT/A treatment for each individual patient, based on minimal and appropriate effect versus time data. Additionally, a comprehensive investigation into the differences between males and females regarding estimation of urodynamic variables at the outlet of intermittent catheters has been conducted employing mathematical modelling methodologies and in vitro experimental techniques to support model validation. The thesis examines current data limitations in these fields, outlines subsequent steps in the longer-term project and establishes methodological foundations for PK/PD model development across the current drug treatments, to account for contractility effects in the detrusor of SCI patients. The findings from this study contribute to potential improvements in strategies and provide a basis for future research in this field