GENECI: A novel evolutionary machine learning consensus-based approach for the inference of gene regulatory networks. - Adrián Segura-Ortiz; José García-Nieto; José Francisco Aldana Montes; Ismael Navas-Delgado (Comput. Biol. Medicine, 2023)

Exploiting Medical-Expert Knowledge Via a Novel Memetic Algorithm for the Inference of Gene Regulatory Networks. - Adrián Segura-Ortiz; José García-Nieto; José Francisco Aldana Montes (ICCS (4), 2024)

Multi-objective context-guided consensus of a massive array of techniques for the inference of Gene Regulatory Networks. - Adrián Segura-Ortiz; José García-Nieto; José Francisco Aldana Montes; Ismael Navas-Delgado (Comput. Biol. Medicine, 2024)

Multifaceted evolution focused on maximal exploitation of domain knowledge for the consensus inference of Gene Regulatory Networks. - Adrián Segura-Ortiz; Karen Giménez-Orenga; José García-Nieto; Elisa Oltra; José Francisco Aldana Montes (Comput. Biol. Medicine, 2025)

Exhaustive biclustering driven by self-learning evolutionary approach for biomedical data. - Adrián Segura-Ortiz; Adán José García; Laetitia Jourdan; José García-Nieto (Comput. Methods Programs Biomed., 2025)