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Falco MM, Peña-Chilet M, Loucera C, Hidalgo MR, Dopazo J. Mechanistic models of signaling pathways deconvolute the glioblastoma single-cell functional landscapeAbstract. NAR Cancer. 2020;2(2). doi:10.1093/narcan/zcaa011.
Cubuk C, Can FE, Peña-Chilet M, Dopazo J. Mechanistic Models of Signaling Pathways Reveal the Drug Action Mechanisms behind Gender-Specific Gene Expression for Cancer Treatments. Cells. 2020;9(7). doi:10.3390/cells9071579.
Sola-García A, Cáliz-Molina MÁngeles, Espadas I, et al. Metabolic reprogramming by Acly inhibition using SB-204990 alters glucoregulation and modulates molecular mechanisms associated with aging. Commun Biol. 2023;6(1):250. doi:10.1038/s42003-023-04625-4.
Mateos A, Herrero J, Tamames J, Dopazo J. Methods of Microarray Data Analysis IISupervised Neural Networks for Clustering Conditions in DNA Array Data After Reducing Noise by Clustering Gene Expression Profiles. (Lin SM, Johnson KF, eds.). Boston: Kluwer Academic Publishers; 2002:91 - 103. doi:10.1007/b11298210.1007/0-306-47598-7_7.
Shi L, Campbell G, Jones WD, et al. The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models. Nature biotechnology. 2010;28:827-38. Available at: http://www.nature.com/nbt/journal/v28/n8/full/nbt.1665.html.
Corrales P, Martin-Taboada M, Vivas-García Y, et al. microRNAs-mediated regulation of insulin signaling in white adipose tissue during aging: Role of caloric restriction. Aging Cell. 2023:e13919. doi:10.1111/acel.13919.
Hidalgo MR, Amadoz A, Cubuk C, Carbonell-Caballero J, Dopazo J. Models of cell signaling uncover molecular mechanisms of high-risk neuroblastoma and predict disease outcome. Biol Direct. 2018;13(1):16. doi:10.1186/s13062-018-0219-4.
Ibáñez M, Carbonell-Caballero J, Such E, et al. The modular network structure of the mutational landscape of Acute Myeloid Leukemia. PLoS One. 2018;13(10):e0202926. doi:10.1371/journal.pone.0202926.
Gonzalez CY, Bleda M, Salavert F, Sánchez R, Dopazo J, Medina I. Multicore and Cloud-based Solutions for Genomic Variant Analysis. In: Proceedings of the 18th International Conference on Parallel Processing Workshops. Proceedings of the 18th International Conference on Parallel Processing Workshops. Berlin, Heidelberg: Springer-Verlag; 2013. doi:10.1007/978-3-642-36949-0_30.
Montaner D, Dopazo J. Multidimensional gene set analysis of genomic data. PLoS One. 2010;5(4):e10348. doi:10.1371/journal.pone.0010348.
del Pozo MGonzález-, Borrego S, Barragán I, et al. Mutation screening of multiple genes in Spanish patients with autosomal recessive retinitis pigmentosa by targeted resequencing. PLoS One. 2011;6(12):e27894. doi:10.1371/journal.pone.0027894.
Barragán I, Borrego S, Pieras JIgnacio, et al. Mutation spectrum of EYS in Spanish patients with autosomal recessive retinitis pigmentosa. Hum Mutat. 2010;31(11):E1772-800. doi:10.1002/humu.21334.
Millán-Esteban D, Peña-Chilet M, García-Casado Z, et al. Mutational Characterization of Cutaneous Melanoma Supports Divergent Pathways Model for Melanoma Development. Cancers (Basel). 2021;13(20). doi:10.3390/cancers13205219.
Ibáñez M, Carbonell-Caballero J, García-Alonso L, et al. The Mutational Landscape of Acute Promyelocytic Leukemia Reveals an Interacting Network of Co-Occurrences and Recurrent Mutations. PLoS One. 2016;11(2):e0148346. doi:10.1371/journal.pone.0148346.
Sevilla T, Lupo V, Martínez-Rubio D, et al. Mutations in the MORC2 gene cause axonal Charcot-Marie-Tooth disease. Brain. 2016;139(Pt 1):62-72. doi:10.1093/brain/awv311.
Matalonga L, Bravo M, Serra-Peinado C, et al. Mutations in TRAPPC11 are associated with a congenital disorder of glycosylation. Hum Mutat. 2017;38(2):148-151. doi:10.1002/humu.23145.
Jimenez RC, Salazar GA, Gel B, Dopazo J, Mulder N, Corpas M. myKaryoView: a light-weight client for visualization of genomic data. PLoS One. 2011;6(10):e26345. doi:10.1371/journal.pone.0026345.