Jiménez Jiménez, Víctor

Quantitative Methods

PhD: Universidad Autónoma de Madrid

BIO

Víctor Jiménez holds a Ph.D. in Molecular Biosciences from Universidad Autónoma de Madrid (Summa Cum Laude, International Mention), a Bachelor in Biotechnology (University of Salamanca), a Bachelor Mathematics (UNED), and a Master in Teacher Training. He continued his education at the Technische Universität Dresden (Germany), earning a Master in Molecular Bioengineering and a Master in Nanobiophysics.

During his time at the National Center for Cardiovascular Research (CNIC), he specialized in biostatistics, omics data analysis, and machine learning, contributing to national and international projects and publishing in high-impact journals. He was granted recognition for a six-year research period (Sexenio de Investigación) by ANECA for 2016–2021.

From 2024 to 2025, he served as a Tenure-Track Assistant Professor at UCAV, teaching biostatistics and data analysis and conducting interdisciplinary research in preventive medicine and public health. His career reflects a multidisciplinary approach that integrates molecular biology, advanced statistics, and university-level teaching.

Researcher IDs:

ORCID: https://orcid.org/0000-0001-6698-7328

Scopus Author ID: 57193606455

WoS Researcher ID: H-1462-2016

Google Scholar ID: QAfA2dQAAAAJ

Education

PhD in Molecular Biosciences, Universidad Autónoma de Madrid (2023)

Master in Molecular Bioengineering, Technische Universität Dresden (2015), Master in Nanobiophysics, Technische Universität Dresden (2016) and Master in Teacher Training, Universidad Nacional de Educación a Distancia (2024)

Bachelor in Biotechnology, Universidad de Salamanca (2013) and Bachelor in Mathematics, Universidad Nacional de Educación a Distancia (2021)

Publications in Scientific Journals

Aboy-Pardal, María C.M.; Guadamillas, Marta C.; Guerrero, Carlos R.; Català-Montoro, Mauro; Toledano-Donado, Mónica; Terrés-Domínguez, Sara; Pavón, Dácil M.; Jiménez-Jiménez, Víctor; Jimenez-Carretero, Daniel; Zamai, Moreno; Folgueira, Cintia; Cerezo, Ana; Lolo, Fidel Nicolás; Nogueiras, Rubén; Sabio, Guadalupe; Sánchez-Álvarez, Miguel; Echarri, Asier; Garcia, Ricardo; Del Pozo, Miguel A.: “Plasma membrane remodeling determines adipocyte expansion and mechanical adaptability”, Nature communications, 15(1), 10102, 2024.

Aboy-Pardal, María C.M.; Jimenez-Carretero, Daniel., Terrés-Domínguez, Sara; Pavón, Dacil M.; Sotodosos-Alonso, Laura; Jiménez-Jiménez, Víctor; Sánchez-Cabo, Fátima; Del Pozo, Miguel A.:“A deep learning-based tool for the automated detection and analysis of caveolae in transmission electron microscopy images”, Computational and Structural Biotechnology Journal, 21, 224-237, 2022.

Bueno, Héctor; Bernal, José L.; Jiménez-Jiménez, Víctor, Martín-Sánchez, Francisco Javier; Rossello, Xavier; Moreno, Guillermo; Goñi, Clara; Gil, Víctor; Llorens, Pere; Naranjo, Nerea; Jacob, Javier; Herrero-Puente, Pablo; Garrote, Sergio; Silla-Castro, Juan Carlos; Pocock, Stuart J.; Miró, Óscar: “El modelo Clinical outcomes, healthcare resource utilization, and related costs (COHERENT). Aplicación en pacientes con insuficiencia cardiaca”, Revista Española de Cardiología, 75(7), 585-594, 2021.

Strippoli, Raffaele; Sandoval, Pilar; Moreno-Vicente, Roberto; Rossi, Lucia; Battistelli, Cecilia; Terri, Michela; Pascual-Antón, Lucía; Loureiro, Marta; Matteini, Francesca; Calvo, Enrique; Jiménez-Heffernan, José Antonio; Gómez, Manuel José; Jiménez-Jiménez, Víctor; Sánchez-Cabo, Fátima; Vázquez, Jesús; Tripodi, Marco; López-Cabrera, Manuel; Del Pozo, Miguel Angel: “Caveolin1 and YAP drive mechanically induced mesothelial to mesenchymal transition and fibrosis”, Cell Death & Disease, 11, 647, 2020.

Ciucci, Sara; Ge, Yan; Durán, Claudio; Palladini, Alessandra; Jiménez-Jiménez, Víctor; Martínez-Sánchez, Luisa María; Wang, Yuting; Sales, Susanne; Shevchenko, Andrej; Poser, Steven W.; Herbig, Maik; Otto, Oliver; Androutsellis-Theotokis, Andreas; Guck, Jochen; Gerl, Mathias J; Cannistraci, Carlo Vittorio: “Enlightening discriminative network functional modules behind Principal Component Analysis separation in differential-omic science studies”, Scientific Reports, 7, 43946, 2017.