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Journal Article
Luzón-Toro B, Bleda M, Navarro E, et al. Identification of epistatic interactions through genome-wide association studies in sporadic medullary and juvenile papillary thyroid carcinomas. BMC medical genomics. 2015;8:83. doi:10.1186/s12920-015-0160-7.
Luzón-Toro B, Bleda M, Navarro E, et al. Identification of epistatic interactions through genome-wide association studies in sporadic medullary and juvenile papillary thyroid carcinomas. BMC Medical Genomics. 2015;8:83. doi:10.1186/s12920-015-0160-7.
Tracey L, Villuendas R, Ortiz P, et al. Identification of genes involved in resistance to interferon-alpha in cutaneous T-cell lymphoma. Am J Pathol. 2002;161:1825-37. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12414529.
Nunez JI, Martin MJ, Piccone ME, et al. Identification of optimal regions for phylogenetic studies on VP1 gene of foot-and-mouth disease virus: analysis of types A and O Argentinean viruses. Vet Res. 2001;32:31-45. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=11254175.
Largo C, Alvarez S, Saez B, et al. Identification of overexpressed genes in frequently gained/amplified chromosome regions in multiple myeloma. Haematologica. 2006;91:184-91. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16461302.
Corton M, Avila-Fernández A, Campello L, et al. Identification of the Photoreceptor Transcriptional Co-Repressor SAMD11 as Novel Cause of Autosomal Recessive Retinitis Pigmentosa. Sci Rep. 2016;6:35370. doi:10.1038/srep35370.
Jaime MDLA, Lopez-Llorca LVicente, Conesa A, et al. Identification of yeast genes that confer resistance to chitosan oligosaccharide (COS) using chemogenomics. BMC genomics. 2012;13:267. doi:10.1186/1471-2164-13-267.
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.
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.
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.
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.