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Calpena E, Martínez-Rubio D, Arpa J, et al. A novel locus for a hereditary recurrent neuropathy on chromosome 21q21. Neuromuscular disorders : NMD. 2014;24:660-5. doi:10.1016/j.nmd.2014.04.004.
Calzada D, Aguerri M, Baos S, et al. Therapeutic targets for olive pollen allergy defined by gene markers modulated by Ole e 1-derived peptides. Molecular immunology. 2015;64:252-61. doi:10.1016/j.molimm.2014.12.002.
Capriotti E, Marti-Renom MA. RNA structure alignment by a unit-vector approach. Bioinformatics. 2008;24:i112-8. Available at:
Capriotti E, Marti-Renom MA. Assessment of protein structure predictions. In: Computational Structural Biology. Computational Structural Biology. New Jersey, USA: World Scientific Publishing Company; 2008. Available at:
Capriotti E, Arbiza L, Casadio R, Dopazo J, Dopazo H, Marti-Renom MA. Use of estimated evolutionary strength at the codon level improves the prediction of disease-related protein mutations in humans. Hum Mutat. 2008;29:198-204. Available at:
Capriotti E, Arbiza L, Casadio R, Dopazo J, Dopazo H, Marti-Renom MA. Use of estimated evolutionary strength at the codon level improves the prediction of disease-related protein mutations in humans. Hum Mutat. 2008;29(1):198-204. doi:10.1002/humu.20628.
Capriotti E, Marti-Renom MA. SARA: a server for function annotation of RNA structures. Nucl. Acids Res. 2009:gkp433. doi:10.1093/nar/gkp433.
Capriotti E, Marti-Renom MA. Quantifying the relationship between sequence and three-dimensional structure conservation in RNA. BMC bioinformatics. 2010;11:322.
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.
Carbonell-Caballero J, Alonso R, Ibañez V, Terol J, Talon M, Dopazo J. A phylogenetic analysis of 34 chloroplast genomes elucidates the relationships between wild and domestic species within the genus Citrus. Molecular biology and evolution. 2015;32:2015-2035. doi:10.1093/molbev/msv082.
Carbonell-Caballero J, López-Quílez A, Conesa D, Dopazo J. Deciphering Genomic Heterogeneity and the Internal Composition of Tumour Activities through a Hierarchical Factorisation Model. Mathematics. 2021;9(21):2833. doi:10.3390/math9212833.
Carbonell-Caballero J, Amadoz A, Alonso R, et al. Reference genome assessment from a population scale perspective: an accurate profile of variability and noise. Bioinformatics. 2017;33(22):3511-3517. doi:10.1093/bioinformatics/btx482.
Carcel-Trullols J, Aguilar-Gallardo C, García-Alcalde F, et al. Transdifferentiation of MALME-3M and MCF-7 Cells toward Adipocyte-like Cells is Dependent on Clathrin-mediated Endocytosis. SpringerPlus. 2012;1:44. doi:10.1186/2193-1801-1-44.
Cardona F, Sánchez-Mut JVicente, Dopazo H, Pérez-Tur J. Phylogenetic and in silico structural analysis of the Parkinson disease-related kinase PINK1. Human mutation. 2011;32:369-78. doi:10.1002/humu.21444.
F Carmona J, Davalos V, Vidal E, et al. A Comprehensive DNA Methylation Profile of Epithelial-to-Mesenchymal Transition. Cancer research. 2014;74:5608–19. doi:10.1158/0008-5472.CAN-13-3659.
Carrero R, Cerrada I, Lledó E, et al. IL1β induces mesenchymal stem cells migration and leucocyte chemotaxis through NF-κB. Stem Cell Rev Rep. 2012;8(3):905-16. doi:10.1007/s12015-012-9364-9.
Carretero M, Guerrero-Aspizua S, Illera N, et al. Differential Features Between Chronic Skin Inflammatory Diseases Revealed in Skin-Humanized Psoriasis and Atopic Dermatitis Mouse Models. J Invest Dermatol. 2015. doi:10.1038/jid.2015.362.
Cascon A, Ruiz-Llorente S, Rodriguez-Perales S, et al. A novel candidate region linked to development of both pheochromocytoma and head/neck paraganglioma. Genes Chromosomes Cancer. 2005;42:260-8. Available at:
Casimiro-Soriguer CS, Perez-Florido J, Fernandez-Rueda JL, et al. Phylogenetic Analysis of the 2020 West Nile Virus (WNV) Outbreak in Andalusia (Spain). Viruses. 2021;13(5):836. doi:10.3390/v13050836.
Casimiro-Soriguer CS, Loucera C, Florido JPerez, López-López D, Dopazo J. Antibiotic resistance and metabolic profiles as functional biomarkers that accurately predict the geographic origin of city metagenomics samples. Biol Direct. 2019;14(1):15. doi:10.1186/s13062-019-0246-9.
Casimiro-Soriguer CS, Loucera C, Peña-Chilet M, Dopazo J. Towards a metagenomics machine learning interpretable model for understanding the transition from adenoma to colorectal cancer. Sci Rep. 2022;12(1):450. doi:10.1038/s41598-021-04182-y.