Hybrid mathematical modeling decodes the complexity of sphingolipid pathway to predict chemosensitivity. - Jose Arturo Molina-Mora; M. Kop-Montero; Juan Luis Crespo-Mariño; Steve Quirós; Rodrigo Antonio Mora-Rodríguez (IWOBI, 2017)

Gene Expression Dynamics Induced by Ciprofloxacin and Loss of Lexa Function in Pseudomonas Aeruginosa PAO1 Using Data Mining and Network Analysis. - Jose Arturo Molina-Mora; Rebeca Campos-Sánchez; Fernando García (IWOBI, 2018)

Predicting Cancer Chemosensitivity Based on Intensity/Distribution Profiles of Cells Loaded with a Fluorescent Sphingolipid Analogue. - I. Quirós-Fernández; Jose Arturo Molina-Mora; M. Kop-Montero; E. Salas-Hidalgo; Rodrigo Antonio Mora-Rodríguez (IWOBI, 2018)

A hybrid mathematical modeling approach of the metabolic fate of a fluorescent sphingolipid analogue to predict cancer chemosensitivity. - Jose Arturo Molina-Mora; M. Kop-Montero; I. Quirós-Fernández; Steve Quirós; Juan Luis Crespo-Mariño; Rodrigo Antonio Mora-Rodríguez (Comput. Biol. Medicine, 2018)

A first perturbome of Pseudomonas aeruginosa: Identification of core genes related to multiple perturbations by a machine learning approach. - Jose Arturo Molina-Mora; Pablo Montero-Manso; Raquel García-Batán; Rebeca Campos-Sánchez; Jose Vilar-Fernández; Fernando García (Biosyst., 2021)

Set-theory based benchmarking of three different variant callers for targeted sequencing. - Jose Arturo Molina-Mora; Mariela Solano-Vargas (BMC Bioinform., 2021)