Francisco Gómez-Vela

Pablo de Olavide University | UPO · Polytechnic School

In recent years, gene networks have become one of the most useful tools for modeling biological processes. Many inference gene network algorithms have been developed as techniques for extracting knowledge from gene expression data. Ensuring the reliability of the inferred gene relationships is a crucial task in any study in order to prove that the...

Gene networks (GNs) have become one of the most important approaches for modelling gene-gene relationships in Bioinformatics (Hecker et al, 2009). These networks allow us to carry out studies of different biological processes in a visual way. Many GN inference algorithms have been developed as techniques for extracting biological knowledge (Ponzoni...

In this paper, we propose a greedy clustering algorithm to identify groups of related genes and a new measure to improve the results of this algorithm. 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. In order to...

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...

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 networks represent, in a graph data structure, genes or gene products and the functional relationships betwee...

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...

BioScience is an advanced Python library designed to satisfy the growing data analysis needs in the field of bioinformatics by leveraging High-Performance Computing (HPC). This library encompasses a vast multitude of functionalities, from loading specialized gene expression datasets (microarrays, RNA-Seq, etc.) to preprocessing techniques and data...

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...

The focus of biomedical research has shifted from single-omics data analysis to the concurrent use of multi-omics datasets in order to obtain accurate results and a better understanding of complex diseases, which frequently display perturbations in multiple omics layers. Although omics data can be examined individually and the resulting findings ma...

Type II DNA topoisomerases relax topological stress by transiently gating DNA passage in a controlled cut-and-reseal mechanism that affects both DNA strands. Therefore, they are essential to overcome topological problems associated with DNA metabolism. Their aberrant activity results in the generation of DNA double-strand breaks, which can seriousl...

Correctly defining and grouping electrical feeders is of great importance for electrical system operators. In this paper, we compare two different clustering techniques, K-means and hierarchical agglomerative clustering, applied to real data from the east region of Paraguay. The raw data were pre-processed, resulting in four data sets, namely, (i)...

Global energy consumption is growing due to multiple reasons, such as the COVID-19 pandemic. In order to improve the efficiency of energy consumption and thus contribute to the protection of the environment, governments are implementing new energy efficiency policies. Prediction of energy consumption is one of the most important objectives in this...

This paper presents a data set with information on meteorological data and electricity consumption in the department of Alto Paraná, Paraguay. The meteorological data were registered every three hours at the Aeropuerto Guarani, Department of Alto Paraná, which belongs to the Dirección Nacional de Aeronáutica Civil of Paraguay. The final data consis...

In feature selection, redundancy is one of the major concerns since the removal of redundancy in data is connected with dimensionality reduction. Despite the evidence of such a connection, few works present theoretical studies regarding redundancy. In this work, we analyze the effect of redundant features on the performance of classification models...

The discovery and description of patterns in electric energy consumption time series is fundamental for timely management of the system. A bicluster describes a subset of observation points in a time period in which a consumption pattern occurs as abrupt changes or instabilities homogeneously. Nevertheless, the pattern detection complexity increase...

Within the area of stock market prediction, forecasting price values or movements is one of the most challenging issue. Because of this, the use of machine learning techniques in combination with technical analysis indicators is receiving more and more attention. In order to tackle this problem, in this paper we propose a hybrid approach to generat...

The use of data collectors in energy systems is growing more and more [...]

DNA topoisomerase II-β (TOP2B) is fundamental to remove topological problems linked to DNA metabolism and 3D chromatin architecture, but its cut-and-reseal catalytic mechanism can accidentally cause DNA double-strand breaks (DSBs) that can seriously compromise genome integrity. Understanding the factors that determine the genome-wide distribution o...

In education, the overall performance of every student is an important issue when assessing the quality of teaching. However, in the traditional educational system not all students have the same opportunity to develop their academic skills in an efficient way. Different teaching techniques have been proposed to adapt the learning process to the stu...

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...

Today, new technologies, such as microarrays or high-performance sequencing, are producing more and more genomic data [...]

The role of three-dimensional genome organization as a critical regulator of gene expression has become increasingly clear over the last decade. Most of our understanding of this association comes from the study of long range chromatin interaction maps provided by Chromatin Conformation Capture-based techniques, which have greatly improved in recen...

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...

The role of three-dimensional genome organization as a critical regulator of gene expression has become increasingly clear over the last decade. Most of our understanding of this association comes from the study of long range chromatin interaction maps provided by Chromatin Conformation Capture-based techniques, which have greatly improved in recen...

DNA topoisomerase II- β (TOP2B) is fundamental to remove topological problems linked to DNA metabolism and 3D chromatin architecture, but its cut-and-reseal catalytic mechanism can accidentally cause DNA double-strand breaks (DSBs) that can seriously compromise genome integrity. Understanding the factors that determine the genome-wide distribution...

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...

Educational Data Mining (EDM) is an emerging discipline of increasing interest due to several factors, such as the adoption of learning management systems in education environment. In this work we analyze the predictive power of continuous evaluation activities with respect the overall student performance in physics course at Universidad Loyola And...

Gene Networks (GN), have emerged as an useful tool in recent years for the analysis of different diseases in the field of biomedicine. In particular, GNs have been widely applied for the study and analysis of different types of cancer. In this context, Lung carcinoma is among the most common cancer types and its short life expectancy is partly due...

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 our world, increasing amounts of data are produced everyday. These data come from everywhere: sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and cell phone GPS signals, are just a few examples. These data include big data. This trend also affects biology and med...

Smart buildings are equipped with sensors that allow monitoring a range of building systems including heating and air conditioning, lighting and the general electric energy consumption. Thees data can then be stored and analyzed. The ability to use historical data regarding electric energy consumption could allow improving the energy efficiency of...

Nowadays, smart buildings can collect data regarding the electric energy consumption, which can then be analyzed to gain insights or to predict or identify abnormal energy consumption. Numerous models are applied to face this problem but they are based on a global point of view and cannot detect local patterns of abnormal consumption. This work lie...

In the recent years, the vast amount of genetic information generated by new-generation approaches, have led to the need of new data handling methods. The integrative analysis of diverse-nature gene information could provide a much-sought overview to study complex biological systems and processes. In this sense, Gene Regulatory Networks (GRN) arise...

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...

The ability to predict short-term electric energy demand would provide several benefits, both at the economic and environmental level. For example, it would allow for an efficient use of resources in order to face the actual demand, reducing the costs associated to the production as well as the emission of CO 2 . To this aim, in this paper we propo...

Topoisomerases are proteins that regulate the topology of DNA by introducing transient breaks to relax supercoiling. In this paper we focus our attention on Topoisomerases 2 (TOP2), which generate double-strand DNA breaks that, if inefficiently repaired, can seriously compromise genomic stability. It is then important to gain insights on the molecu...

Motivation: Gene networks are currently considered a powerful tool to model biological processes in the Bioinformatics field. A number of approaches to infer gene networks and various software tools to handle them in a visual simplified way have been developed recently. However, there is still a need to assess the inferred networks in order to pro...

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...

Since the popularization of biological network inference methods, it has become crucial to create methods to validate the resulting models. Here we present GFD-Net, the first methodology that applies the concept of semantic similarity to gene network analysis. GFD-Net combines the concept of semantic similarity with the use of gene network topology...

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...

Gene association networks have become one of the most important approaches to modelling of biological processes by means of gene expression data. According to the literature, co-expression-based methods are the main approaches to identification of gene association networks because such methods can identify gene expression patterns in a dataset and...

In recent years, advances in technology have led to increasingly high-dimensional datasets. This increase of dimensionality along with the presence of irrelevant and redundant features make the feature selection process challenging with respect to efficiency and effectiveness. In this context, approximate algorithms are typically applied since they...

In classification tasks, as the dimensionality increases, the performance of the classifier improves until an optimal number of features is reached. Further increases of the dimensionality without increasing the number of training samples results in a degradation in classifier performance. This fact, called the curse of dimensionality, has become m...

Gene networks (GNs) have become one of the most important approaches for modeling biological processes. They are very useful to understand the different complex biological processes that may occur in living organisms. Currently, one of the biggest challenge in any study related with GN is to assure the quality of these GNs. In this sense, recent wo...

Con la llegada del Espacio Europeo de Educación Superior (EEES), las estrategias didácticas deben cambiar para centrarse en el aprendizaje del estudiante, convirtiendo al alumno en un elemento activo dentro de su aprendizaje, incentivando su participación, de tal manera que se sienta parte activa del proceso de aprendizaje. En la asignatura de ISG2...

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...