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I
Palomero L, Galván-Femenía I, de Cid R, et al. Immune Cell Associations with Cancer Risk. iScience. 2020;23(7):101296. doi:10.1016/j.isci.2020.101296.
Brozos-Vázquez EMaría, Díaz-Peña R, García-González J, et al. Immunotherapy in nonsmall-cell lung cancer: current status and future prospects for liquid biopsy. Cancer Immunol Immunother. 2021;70(5):1177-1188. doi:10.1007/s00262-020-02752-z.
García-León FJavier, Villegas-Portero R, Goicoechea-Salazar JAntonio, Muñoyerro-Muñiz D, Dopazo J. [Impact assessment on data protection in research projects]. Gac Sanit. 2020;34(5):521-523. doi:10.1016/j.gaceta.2019.10.006.
Dopazo J, Maya-Miles D, García F, et al. Implementing Personalized Medicine in COVID-19 in Andalusia: An Opportunity to Transform the Healthcare System. J Pers Med. 2021;11(6). doi:10.3390/jpm11060475.
Bravo-Gil N, Méndez-Vidal C, Romero-Pérez L, et al. Improving the management of Inherited Retinal Dystrophies by targeted sequencing of a population-specific gene panel. Sci Rep. 2016;6:23910. doi:10.1038/srep23910.
Torrent-Vernetta A, Gaboli M, Castillo-Corullón S, et al. Incidence and Prevalence of Children's Diffuse Lung Disease in Spain. Arch Bronconeumol. 2022;58(1):22-29. doi:10.1016/j.arbres.2021.06.001.
Sebastián-Leon P, Carbonell J, Salavert F, Sánchez R, Medina I, Dopazo J. Inferring the functional effect of gene expression changes in signaling pathways. Nucleic Acids Res. 2013;41(Web Server issue):W213-7. doi:10.1093/nar/gkt451.
Bleda M, Medina I, Alonso R, De Maria A, Salavert F, Dopazo J. Inferring the regulatory network behind a gene expression experiment. Nucleic Acids Res. 2012;40(Web Server issue):W168-72. doi:10.1093/nar/gks573.
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.
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.
Casimiro-Soriguer CS, Perez-Florido J, Robles EA, et al. The integrated genomic surveillance system of Andalusia (SIEGA) provides a One Health regional resource connected with the clinic. Sci Rep. 2024;14(1):19200. doi:10.1038/s41598-024-70107-0.
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.
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.
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.
Azuaje F, Dopazo J. Integrative Data Analysis and Visualization: Introduction to Critical Problems, Goals and Challenges. In: Data analysis and visualisation in genomics and proteomics. Data analysis and visualisation in genomics and proteomics. Wiley, F. Azuaje and J. Dopazo; 2005:3-9.
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.
Wilkinson MD, Senger M, Kawas E, et al. Interoperability with Moby 1.0–it’s better than sharing your toothbrush!. Brief Bioinform. 2008;9:220-31. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18238804.
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.
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.
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.
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:W81-5. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17468499.
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.
J
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.
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:D825-9. Available at: http://nar.oxfordjournals.org/cgi/content/full/36/suppl_1/D825.
K
Orti L, Carbajo RJ, Pieper U, et al. A kernel for open source drug discovery in tropical diseases. PLoS Negl Trop Dis. 2009;3:e418. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=19381286.