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Journal Article
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.
Montaner D, Dopazo J. Multidimensional gene set analysis of genomic data. PLoS One. 2010;5(4):e10348. doi:10.1371/journal.pone.0010348.
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.
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.
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.
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.
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.
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.
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.
Rian K, Esteban-Medina M, Hidalgo MR, et al. Mechanistic modeling of the SARS-CoV-2 disease map. BioData Min. 2021;14(1):5. doi:10.1186/s13040-021-00234-1.
Esteban-Medina M, Loucera C, Rian K, et al. The mechanistic functional landscape of retinitis pigmentosa: a machine learning-driven approach to therapeutic target discovery. J Transl Med. 2024;22(1):139. doi:10.1186/s12967-024-04911-7.
Carbonell J, Alloza E, Arce P, et al. A map of human microRNA variation uncovers unexpectedly high levels of variability. Genome medicine. 2012;4:62. doi:10.1186/gm363.
Iglesias JManuel, Beloqui I, Garcia-Garcia F, et al. Mammosphere formation in breast carcinoma cell lines depends upon expression of E-cadherin. PLoS One. 2013;8(10):e77281. doi:10.1371/journal.pone.0077281.
Iglesias JManuel, Beloqui I, Garcia-Garcia F, et al. Mammosphere Formation in Breast Carcinoma Cell Lines Depends upon Expression of E-cadherin. PLoS ONE. 2013;8:e77281 -. Available at: http://dx.doi.org/10.1371%2Fjournal.pone.0077281.
Yung S, Ledran M, Moreno-Gimeno I, et al. Large-scale transcriptional profiling and functional assays reveal important roles for Rho-GTPase signalling and SCL during haematopoietic differentiation of human embryonic stem cells. Hum Mol Genet. 2011;20(24):4932-46. doi:10.1093/hmg/ddr431.
Reumers J, Conde L, Medina I, et al. Joint annotation of coding and non-coding single nucleotide polymorphisms and mutations in the SNPeffect and PupaSuite databases. Nucleic Acids Res. 2008;36(Database issue):D825-9. doi:10.1093/nar/gkm979.
Conde L, Montaner D, Burguet-Castell J, et al. ISACGH: a web-based environment for the analysis of Array CGH and gene expression which includes functional profiling. Nucleic Acids Res. 2007;35(Web Server issue):W81-5. doi:10.1093/nar/gkm257.
Terol J, Ibañez V, Carbonell J, et al. Involvement of a citrus meiotic recombination TTC-repeat motif in the formation of gross deletions generated by ionizing radiation and MULE activation. BMC Genomics. 2015;16:69. doi:10.1186/s12864-015-1280-3.
González-Tendero A, Torre I, García-Cañadilla P, et al. Intrauterine growth restriction is associated with cardiac ultrastructural and gene expression changes related to the energetic metabolism in a rabbit model. Am J Physiol Heart Circ Physiol. 2013;305(12):H1752-60. doi:10.1152/ajpheart.00514.2013.
Wilkinson MD, Senger M, Kawas E, et al. Interoperability with Moby 1.0--it's better than sharing your toothbrush!. Brief Bioinform. 2008;9(3):220-31. doi:10.1093/bib/bbn003.
Moschen S, Di Rienzo JA, Higgins J, et al. Integration of transcriptomic and metabolic data reveals hub transcription factors involved in drought stress response in sunflower (Helianthus annuus L.). Plant Mol Biol. 2017;94(4-5):549-564. doi:10.1007/s11103-017-0625-5.
Moschen S, Luoni SBengoa, Di Rienzo JA, et al. Integrating transcriptomic and metabolomic analysis to understand natural leaf senescence in sunflower. Plant Biotechnol J. 2016;14(2):719-34. doi:10.1111/pbi.12422.
Gundogdu P, Loucera C, Alamo-Alvarez I, Dopazo J, Nepomuceno I. Integrating pathway knowledge with deep neural networks to reduce the dimensionality in single-cell RNA-seq data. BioData Min. 2022;15(1):1. doi:10.1186/s13040-021-00285-4.
Garcia-Garcia F, Panadero J, Dopazo J, Montaner D. Integrated gene set analysis for microRNA studies. Bioinformatics. 2016;32(18):2809-16. doi:10.1093/bioinformatics/btw334.
Németh A, Conesa A, Santoyo-López J, et al. Initial genomics of the human nucleolus. PLoS genetics. 2010;6:e1000889. doi:10.1371/journal.pgen.1000889.