Domingo Savio Rodríguez Baena

• Doctor of Engineering
• Pablo de Olavide University

Gene co-expression networks are valuable tools for discovering biologically relevant information within gene expression data. However, analysing large datasets presents challenges due to the identification of nonlinear gene–gene associations and the need to process an ever-growing number of gene pairs and their potential network connections. These...

Gene networks have become a powerful tool for the comprehensive examination of gene expression patterns. Thanks to these networks generated by means of inference algorithms, it is possible to study different biological processes and even identify new biomarkers for such diseases. These biomarkers are essential for the discovery of new treatments fo...

The construction of gene co-expression networks is an essential tool in Bioinformatics for discovering useful biological knowledge. There are a multitude of methodologies related to the construction of this type of network, and one of them is EnGNet, which carries out a joint and greedy approach to the reconstruction of large gene coexpression netw...

Automatic determination of abnormal animal activities can be helpful for the timely detection of signs of health and welfare problems. Usually, this problem is addressed as a classification problem, which typically requires manual annotation of behaviors. This manual annotation can introduce noise into the data and may not always be possible. This...

This article proposes, and justifies, the use of the Document-oriented databases as a flexible, easy to use, and powerful digital tool in the field of historical research. First, the reasons that have made relational databases the predominant instrument among historians are studied, while detailing the problems involved in their use. Next, the way...

We introduce a type of database that historians will find particularly useful for world-historical information. The paper compares the Relational database model (RDB, such as MS ACCESS) with that of a non-SQL (NoSQL) database model known as a document-oriented database. We explain the concept of “document” as it applies to a database and the differ...

Graphics Processing Units technology (GPU) and CUDA architecture are one of the most used options to adapt machine learning techniques to the huge amounts of complex data that are currently generated. Biclustering techniques are useful for discovering local patterns in datasets. Those of them that have been implemented to use GPU resources in paral...

Nowadays, Biclustering is one of the most widely used machine learning techniques to discover local patterns in datasets from different areas such as energy consumption, marketing, social networks or bioinformatics, among them. Particularly in bioinformatics, Biclustering techniques have become extremely time-consuming, also being huge the number o...

Gene networks have arisen as a promising tool in the comprehensive modeling and analysis of complex diseases. Particularly in viral infections, the understanding of the host-pathogen mechanisms, and the immune response to these, is considered a major goal for the rational design of appropriate therapies. For this reason, the use of gene networks ma...

BIGO es una potente herramienta software diseñada para mejorar la validación de los resultados generados por las herramientas de análisis de enriquecimiento de genes existentes, proporcionando una nueva información que ayuda a obtener nuevas conclusiones de los grupos de genes extraídos, a partir de los datos de expresión genética. More info: http...

In large livestock farming it would be beneficial to be able to automatically detect behaviors in animals. In fact, this would allow to estimate the health status of individuals, providing valuable insight to stock raisers. Traditionally this process has been carried out manually, relying only on the experience of the breeders. Such an approach is...

Gene networks have become a powerful tool in the comprehensive analysis of gene expression. Due to the increasing amount of available data, computational methods for networks generation must deal with the so-called curse of dimensionality in the quest for the reliability of the obtained results. In this context, ensemble strategies have significant...

In the last few years, gene networks have become one of most important tools to model biological processes. Among other utilities, these networks visually show biological relationships between genes. However, due to the large amount of the currently generated genetic data, their size has grown to the point of being unmanageable. To solve this probl...

Recently, the rising of the Big Data paradigm has had a great impact in several fields. Bioformatics is one such field. In fact, Bioinfomatics had to evolve in order to adapt to this phenomenon. The exponential increase of the biological information available, forced the researchers to find new solutions to handle these new challenges. In this pape...

Over the last few years, a lot of computational methods have been developed to analyze massive gene expression datasets in order to extract useful knowledge. Most of these methods are based on Clustering or Biclustering techniques, which main objective is to generate groups of genes with some properties in common. The gene enrichment analysis valid...

During the last years, a lot of methods have been developed to analyze massive data derived from the measurements of hundreds or thousands of genes. These genes are grouped into collections of genes sharing some functionally relevant characteristic. The gene enrichment analysis allows the validating of genes collections, by means of previous biolo...

This work proposes a novel algorithm to extract biclusters from binary datasets: the Bit-Pattern Biclustering Algorithm BiBit. The selective search performed by BiBit, based on a very fast bits words processing technique, provides very satisfactory results in quality and computational cost. Besides, a new software tool, named CarGene Characterizati...

RESUMEN El objetivo de este artículo es el de presentar tres casos prácticos, en el ámbito de tres asignaturas de la Titulación en Ingeniería Técnica en Informática de Gestión de la Universidad Pablo de Olavide, en los que el trabajo autónomo del alumno ha sido la herramienta utilizada para solventar la problemática provocada por la reducción de ho...

Knowledge extraction from gene expression data has been one of the main challenges in the bioinformatics field during the last few years. In this context, a particular kind of data, data retrieved in a temporal basis (also known as time series), provide information about the way a gene can be expressed during time. This work presents an exhaustive...

The great amount of biological information provides scientists with an incomparable framework for testing the results of new algorithms. Several tools have been developed for analysing gene-enrichment and most of them are Gene Ontology-based tools. We developed a Kyoto Encyclopedia of Genes and Genomes (Kegg)-based tool that provides a friendly gra...

Binary datasets represent a compact and simple way to store data about the relationships between a group of objects and their possible properties. In the last few years, different biclustering algorithms have been specially developed to be applied to binary datasets. Several approaches based on matrix factorization, suffix trees or divide-and-conqu...

In the last few years, DNA microarray technology has attained a very important role in biological and biomedical research. It enables analyzing the relations among thousands of genes simultaneously, generating huge amounts of data. The gene regulatory networks represent, in a graph data structure, genes or gene products and the functional relations...

Establishing an association between variables is always of interest in genomic studies. Generation of DNA microarray gene expression data introduces a variety of data analysis issues not encountered in traditional molecular biology or medicine. Frequent pattern mining (FPM) has been applied successfully in business and scientific data for discoveri...

The great amount of biological information stored in public databases provides scientists with an incomparable framework for testing the re- sults of new algorithms. Several tools have been developed for analysing gene-enrichment in terms and most of them are Gene Ontology-based tools. We developed a Kyoto Encyclopedia of Genes and Genomes (Kegg)-b...

Microarray experiments help researches to construct the structure of gene regulatory networks, i.e., networks representing relationships among different genes. Filter and knowledge extraction processes are necessary in order to handle the huge amount of data produced by microarray technologies. We propose regression trees techniques as a method to...

The biclustering techniques have the purpose of finding subsets of genes that show similar activity patterns under a subset of conditions. In this paper we characterize a specific type of pattern, that we have called α–pattern, and present an approach that consists in a new biclustering algorithm specifically designed to find α–patterns, in which t...

In this work, we propose a new greedy clustering algorithm to identify groups of related genes. Clustering algorithms analyze genes in order to group those with similar behavior. Instead, our approach groups pairs of genes that present similar positive and/or negative interactions. Our approach presents some interesting properties. For instance, th...

Résumé. L'analyse des données d'expression de génes dans les fragments d'ADN est un outil important utilisé dans la recherche genomique dont les objectifs prin-cipaux s'étendent de l'étude du caractére fonctionnel des génes spécifiques et leur participation dans les processus biologiques à la reconstruction de condi-tions des maladies et leur prono...

One of the most influential factors in the quality of the so- lutions found by an evolutionary algorithm is the appropriateness of the fitness function. Specifically in data mining, in where the extrac- tion of useful information is a main task, when databases have a great amount of examples, fitness functions are very time consuming. In this sense...

E-mail is one of the most common ways to communicate, assuming, in some cases, up to 75% of a company's communication, in which every employee spends about 90 minutes a day in e-mail tasks such as filing and deleting. This paper deals with the generation of clus- ters of relevant words from E-mail texts. Our approach consists of the application of...

Many of the supervised learning algorithms only work with spaces of dis-crete attributes. Some of the methods proposed in the bibliography focus on the dis-cretization towards the generation of decision rules. This work provides a new dis-cretization algorithm called USD (Unparametrized Supervised Discretization), which transforms the infinite spac...