Listar por autor "Segura Ortiz, Adrián"
Mostrando ítems 1-5 de 5
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Diseño de un flujo de trabajo para el análisis de datos procedentes de secuenciación masiva
(2021)Actualmente, la secuenciación masiva ha sido integrada en numerosos laboratorios clínicos a causa de ser la herramienta más potente para llevar a cabo la identificación de alteraciones moleculares sobre muestras de pacientes. ... -
Exhaustive biclustering driven by self-learning evolutionary approach for biomedical data
Segura Ortiz, Adrián; José-García, Adán; Jourdan, Laetitia; García-Nieto, José Manuel
(Elsevier, 2025-05-29)
Background and Objective: Biclustering is a key data analysis technique that identifies submatrices with coherent patterns, widely applied in biomedical fields such as gene co-expression analysis. Despite its importance, ... -
Exploiting medical-expert knowledge via a novel memetic algorithm for the inference of gene regulatory networks.
This study introduces an innovative memetic algorithm for optimizing the consensus of well-adapted techniques for the inference of gene regulation networks. Building on the methodology of a previous proposal (GENECI), this ... -
GENECI: A novel evolutionary machine learning consensus-based approach for the inference of gene regulatory networks
Segura Ortiz, Adrián; García-Nieto, José Manuel; Aldana-Montes, José Francisco; Navas-Delgado, Ismael (Elsevier, 2023)
Gene regulatory networks define the interactions between DNA products and other substances in cells. Increasing knowledge of these networks improves the level of detail with which the processes that trigger different ... -
Multi-objective context-guided consensus of a massive array oftechniques for the inference of Gene Regulatory Networks
Segura Ortiz, Adrián; García-Nieto, José Manuel; Aldana-Montes, José Francisco; Navas-Delgado, Ismael (Elsevier, 2024-07-15)
Background and Objective: Gene Regulatory Network (GRN) inference is a fundamental task in biology and medicine, as it enables a deeper understanding of the intricate mechanisms of gene expression present in organisms. ...