A new method for identifying bivariate differential expression in high dimensional microarray data using quadratic discriminant analysis

<p>Abstract</p> <p>Background</p> <p>One of the drawbacks we face up when analyzing gene to phenotype associations in genomic data is the ugly performance of the designed classifier due to the small sample-high dimensional data structures (<it>n</it> ≪ <it>p</it>) at hand. This is known as the peaking phenomenon, a common situation in the analysis of gene expression data. Highly predictive bivariate gene interactions whose marginals are useless for discrimination are also affected by such phenomenon, so they are commonly discarded by state of the art sequential search algorithms. Such patterns are known as weak/marginal strong bivariate interactions. This paper addresses the problem of uncovering them in high dimensional settings.</p> <p>Results</p> <p>We propose a new approach which uses the quadratic discriminant analysis (QDA) as a search engine in order to detect such signals. The choice of QDA is justified by a simulation study for a benchmark of classifiers which reveals its appealing properties. The procedure rests on an exhaustive search which explores the feature space in a blockwise manner by dividing it in blocks and by assessing the accuracy of the QDA for the predictors within each pair of blocks; the block size is determined by the resistance of the QDA to peaking. This search highlights chunks of features which are expected to contain the type of subtle interactions we are concerned with; a closer look at this smaller subset of features by means of an exhaustive search guided by the QDA error rate for all the pairwise input combinations within this subset will enable their final detection. The proposed method is applied both to synthetic data and to a public domain microarray data. When applied to gene expression data, it leads to pairs of genes which are not univariate differentially expressed but exhibit subtle patterns of bivariate differential expression.</p> <p>Conclusions</p> <p>We have proposed a novel approach for identifying weak marginal/strong bivariate interactions. Unlike standard approaches as the top scoring pair (TSP) and the CorScor, our procedure does not assume a specified shape of phenotype separation and may enrich the type of bivariate differential expression patterns that can be uncovered in high dimensional data.</p

Un Juego de ordenador para el aprendizaje de la configuración de los componentes de red

Los equipos de red avanzados son relativamente caros y el acceso a ellos está generalmente limitado a las sesiones planificadas en los laboratorios disponibles de la universidad. Por ello, es importante sacar el máximo partido del tiempo asignado y reducir la dedicación de los estudiantes a actividades que pueden realizar fuera de las sesiones de laboratorio. La familiarización con el conjunto de comandos de configuración básicos es una de estas actividades. Con este objetivo, hemos desarrollado un juego de ordenador que permite a los estudiantes practicar y aprender éstas en un entorno motivador y agradable. El juego se ha diseñado con reglas sencillas de aprender y se han combinado situaciones de aprendizaje cooperativas y competitivas.Peer Reviewe

Class discovery from semi-structured EEG data for affective computing and personalisation

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Many approaches to recognising emotions from metrical data such as EEG signals rely on identifying a very small number of classes and to train a classifier. The interpretation of these classes varies from a single emotion such as stress [24] to features of emotional model such as valence-arousal [4]. There are two major issues here. First classification approach limits the analysis of the data within the selected classes and is also highly dependent on training data/cycles, all of which limits generalisation. Second issue is that it does not explore the inter-relationships between the data collected missing out on any correlations that could tell us interesting facts beyond emotional recognition. This second issue would be of particular interest to psychologists and medical professions. In this paper, we investigate the use of Self-Organizing Maps (SOM) in identifying clusters from EEG signals that could then be translated into classes. We start by training varying sizes of SOM with the EEG data provided in a public dataset (DEAP). The produced graphs showing Neighbour Distance, Sample Hits, Weight Position are analysed holistically to identify patterns in the structure. Following that, we have considered the ground- truth label provided in DEAP, in order to identify correlations between the label and the clustering produced by the SOM. The results show the potential of SOM for class discovery in this particular context. We conclude with a discussion on the implications of this work and the difficulties in evaluating the outcome

A spatial algorithm to reduce phase wraps from two dimensional signals in fringe projection profilometry

© 2015 Elsevier Ltd. All rights reserved. In this paper, we present a novel algorithm to reduce the number of phase wraps in two dimensional signals in fringe projection profilometry. The technique operates in the spatial domain, and achieves a significant computational saving with regard to existing methods based on frequency shifting. The method works by estimating the modes of the first differences distribution in each axial direction. These are used to generate a tilted plane, which is subtracted from the entire phase map. Finally, the result is re-wrapped to obtain a phase map with fewer wraps. The method may be able to completely eliminate the phase wraps in many cases, or can achieve a significant phase wrap reduction that helps the subsequent unwrapping of the signal. The algorithm has been exhaustively tested across a large number of real and simulated signals, showing similar results compared to approaches operating in the frequency domain, but at significantly lower running times

Fast fringe pattern phase demodulation using FIR Hilbert transformers

This paper suggests the use of FIR Hilbert transformers to extract the phase of fringe patterns. This method is computationally faster than any known spatial method that produces wrapped phase maps. Also, the algorithm does not require any parameters to be adjusted which are dependent upon the specific fringe pattern that is being processed, or upon the particular setup of the optical fringe projection system that is being used. It is therefore particularly suitable for full algorithmic automation. The accuracy and validity of the suggested method has been tested using both computer-generated and real fringe patterns. This novel algorithm has been proposed for its advantages in terms of computational processing speed as it is the fastest available method to extract the wrapped phase information from a fringe pattern

Estudio empírico sobre la influencia de recursos heurísticos en la resolución de problemas de probabilidad condicionada L0 y L2

Se ha constatado la dificultad de los estudiantes a la hora de resolver problemas de probabilidad condicionada (Cañadas et al., 2011). En general, la complejidad de estos problemas es debida a varios factores: el formato y el orden en el que se presentan los datos, el contexto en el que se plantea el problema, el lenguaje utilizado para expresar los datos condicionales o las herramientas utilizadas en el proceso de resolución. En nuestro estudio nos centraremos en el uso y la influencia de recursos heurísticos, como tablas de contingencia o diagramas de árbol, durante la resolución de un problema de probabilidad condicionada

Modelado de estudiante en resolución de problemas a través de la dinámica de sistemas

Nuestra intención es utilizar un sistema tutorial inteligente (Arnau, Arevalillo-Herráez, González-Calero, 2014) para realizar la recogida de datos ligados a la destreza inicial del estudiante como resolutor de problemas aritméticos y poder construir un modelo de estudiante siguiendo la Teoría General de Sistemas. Esta teoría propone el uso de metodologías de carácter transdisciplinar que permitan construir modelos matemáticos con los que resolver problemas en el ámbito de los sistemas dinámicos complejos

Shifting of wrapped phase maps in the frequency domain using a rational number

The number of phase wraps in an image can be either reduced, or completely eliminated, by transforming the image into the frequency domain using a Fourier transform, and then shifting the spectrum towards the origin. After this, the spectrum is transformed back to the spatial domain using the inverse Fourier transform and finally the phase is extracted using the arctangent function. However, it is a common concern that the spectrum can be shifted only by an integer number, meaning that the phase wrap reduction is often not optimal. In this paper we propose an algorithm than enables the spectrum to be frequency shifted by a rational number. The principle of the proposed method is confirmed both by using an initial computer simulation and is subsequently validated experimentally on real fringe patterns. The technique may offer in some cases the prospects of removing the necessity for a phase unwrapping process altogether and/or speeding up the phase unwrapping process. This may be beneficial in terms of potential increases in signal recovery robustness and also for use in time-critical applications

A software system to teach economics to secondary school and first year engineering students

[EN] In this paper, we present a graphical user interface which has been devised to teach the basic concepts of economics in secondary schools and first year engineering courses. The application allows students to vary certain parameters and visually observe the effect on the supply and demand curves. The system has been developed in Matlab and employed in a secondary school in Spain. The first results are presented.[ES] Presentamos una interfaz gráfica desarrollada mediante Matlab diseñada para complementar el aprendizaje de los conceptos básicos de economía en Bachillerato, grado superior de ciclos formativos y cursos universitarios de introducción a la economía. La aplicación informática permite que los estudiantes varíen los parámetros de los que dependen las curvas de oferta y demanda, y visualicen el efecto sobre el equilibrio de mercado de estas variaciones. Se presentan los resultados de una primera experiencia de aplicación del programa en enseñanza secundaria en España.García-March, M.; Zacarés, M.; Isidro, J.; Monreal, L.; López-Javier, C.; Arevalillo-Herráez, M. (2009). A software system to teach economics to secondary school and first year engineering students. Modelling in Science Education and Learning. 2:105-113. doi:10.4995/msel.2009.3126SWORD105113