About
18
Publications
1,903
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
28
Citations
Introduction
Aurelio López Fernández is an Assistant Professor at the University of Seville. He is also a researcher in the Intelligent Data Analysis (DATAi) research group. He received his PhD in Computer Engineering from the Pablo de Olavide University.
His lines of research are based on the application of High-Performance Computing (HPC) to AI algorithms for the exploration and extraction of useful biological knowledge from massive data sources.
Current institution
Additional affiliations
September 2019 - September 2024
December 2015 - January 2021
Position
- Senior Researcher
Description
- European Research Council Consolidator Grant (Horizon 2020): An ARTery of EMPIRE. Conquest, Commerce, Crisis, Culture and the Panamanian Junction (ERC CoG 648535).
October 2015 - December 2015
Position
- Senior Researcher
Description
- Ministry of Economy and Competitiveness Research Project: Comercio, conflicto y cultura en el Istmo de Panama. Una arteria del Imperio y la crisis global (HAR2014- 52260-P).
Education
October 2019 - July 2022
September 2016 - June 2017
Field of study
- Teaching secondary education, Post-Compulsory secondary education, vocational training and languages
November 2015 - June 2017
Publications
Publications (18)
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...
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...
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...
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...
This work introduces an innovative teaching methodology based on microcompetences applied in a higher education context. The intervention involved creating a repository of practical case studies in the form of quizzes and integrating microcompetences into each course activity. The digital tool Sapiens was used to identify learning deficiencies and...
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...
This article presents a relational database capable of integrating data from a variety of types of written sources as well as material remains. In response to historical research questions, information from such diverse sources as documentary, bioanthropo-logical, isotopic, and DNA analyses has been assessed, homogenized, and situated in time and s...
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...
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...
