NEPOMUCENO CHAMORRO , Juan Antonio

In this paper we present a software tool to represent P systems modelling signalling networks of biochemical reactions using SBML (Systems Biology Markup Language), a machine-readable format for describing qualitative and quantitative models of biochemical networks. CLIPS (C Language Integrated Production System), a tool which provides a...

In this paper, a new algorithm Database Reduction Simulta neously by Ordered Projections (RESOP) is introduced. This algorithm reduces databases in two directions: editing examples and feature se lection simultaneously. Ordered projections techniques have been used to design RESOP taking advantage of symmetrical ideas for two dif ferent task....

Gene expression data analysis is based on the assumption that co-expressed genes imply co-regulated genes. This assumption is being reformulated because the co-expression of a group of genes may be the result of an independent activation with respect to the same experimental condition and not due to the same regulatory regime. For this reason,...

Background: Biclustering algorithms search for groups of genes that share the same behavior under a subset of samples in gene expression data. Nowadays, the biological knowledge available in public repositories can be used to drive these algorithms to find biclusters composed of groups of genes functionally coherent. On the other hand, a...

El marco del Espacio Europeo de Educación Supe rior (EEES) y la implantación del Sistema de Crédito Europeo (ECTS) han motivado un cambio en el mo delo educativo. De un modelo basado en clases ma gistrales se ha evolucionado hacia un modelo basado en el aprendizaje por competencias del alumnado. Esto implica un cambio en el sistema de...

En este trabajo se propone el uso de conocimiento a priori como heurística en métodos de inferencia de redes de genes a partir de datos de expresión obtenidos con tecnología de Microarray. Utilizamos Gene Ontology [15] como fuente de conocimiento a priori. Este repositorio se nutre de la información de anotaciones de relaciones en el material...

In this paper we study a measure, named weakness of an example, which allows us to establish the importance of an example to find representative patterns for the data set editing problem. Our ap proach consists in reducing the database size without losing information, using algorithm patterns by ordered projections. The idea is to relax...

Biclustering is an unsupervised machine learning technique that simultaneously clusters genes and conditions in gene expression data. Gene Ontology (GO) is usually used in this context to validate the biological relevance of the results. However, although the integration of biological information from different sources is one of the...

Sepsis is a life-threatening condition whose early recognition is key to improving outcomes for patients in intensive care units (ICUs). Artificial intelligence can play a crucial role in mining and exploiting health data for sepsis prediction. However, progress in this field has been impeded by a lack of comparability across studies. Some...

Traditional computational techniques are recently being improved with the use of prior biological knowledge from open access repositories in the area of gene expression data analysis. In this work, we propose the use of prior knowledge as heuristic in an inference method of gene-gene associations from gene expression profiles. In this paper, we...

Los datos de expresión génica, y su particular naturaleza e importancia, motivan no sólo el desarrollo de nuevas técnicas sino la formulación de nuevos problemas como el problema del biclustering. El biclustering es una técnica de aprendizaje no supervisado que agrupa tanto genes como condiciones. Este doble agrupamiento lo diferencia del...

Background and objective: The major difficulty of the analysis of the input gene expression data in a microarray-based approach for an automated diagnosis of can cer is the large number of genes (high dimensionality) with many irrelevant genes (noise) compared to the very small number of samples. This research study tackles the dimensionality...

In this paper a hybrid metaheuristic for biclustering based on Scatter Search and Genetic Algorithms is pre sented. A general scheme of Scatter Search has been used to obtain high–quality biclusters, but a way of generating the initial population and a method of combination based on Genetic Algorithms have been chosen. Moreover, in the own...

A new measure to evaluate the quality of a bicluster is proposed in this paper. This measure is based on correlations among genes. Moreover, a new evolutionary metaheuristic based on Scatter Search, which uses this measure as the fitness function, is presented to obtain biclusters that contain groups de highly-correlated genes. Later, an...