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Cubuk C, Hidalgo MR, Amadoz A, et al. Gene Expression Integration into Pathway Modules Reveals a Pan-Cancer Metabolic Landscape. Cancer Res. 2018;78(21):6059-6072. doi:10.1158/0008-5472.CAN-17-2705.
Montaner D, Minguez P, Al-Shahrour F, Dopazo J. Gene set internal coherence in the context of functional profiling. BMC Genomics. 2009;10:197. doi:10.1186/1471-2164-10-197.
Medina I, Montaner D, Bonifaci N, et al. Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies. Nucl. Acids Res. 2009;37:W340-344. doi:10.1093/nar/gkp481.
Medina I, Montaner D, Bonifaci N, et al. Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies. Nucleic Acids Res. 2009;37(Web Server issue):W340-4. doi:10.1093/nar/gkp481.
Medina I, Salavert F, Sánchez R, et al. Genome Maps, a new generation genome browser. Nucleic acids research. 2013;41:W41-W46. doi:10.1093/nar/gkt530.
Rian K, Hidalgo MR, Cubuk C, et al. Genome-scale mechanistic modeling of signaling pathways made easy: A bioconductor/cytoscape/web server framework for the analysis of omic data. Computational and Structural Biotechnology Journal. 2021;19:2968 - 2978. doi:10.1016/j.csbj.2021.05.022.
Villalba-Benito L, López-López D, Torroglosa A, et al. Genome-wide analysis of DNA methylation in Hirschsprung enteric precursor cells: unraveling the epigenetic landscape of enteric nervous system developmentAbstractBackgroundResultsConclusionsGraphic abstract. Clinical Epigenetics. 2021;13(1). doi:10.1186/s13148-021-01040-6.
Arbiza L, Patricio M, Dopazo H, Posada D. Genome-wide heterogeneity of nucleotide substitution model fit. Genome biology and evolution. 2011;3:896-908.
Serra F, Arbiza L, Dopazo H. Genómica Comparativa y Selección Natural. Aplicaciones en el Genoma Humano. Capítulo 1.6. In: Dopazo H, Navarro A, eds. Evolución y Adaptacón. 150 años después del Origen de las Especies. Evolución y Adaptacón. 150 años después del Origen de las Especies. Valencia: Obrapropia.; 2009:51-59.
Wu GAlbert, Terol J, Ibañez V, et al. Genomics of the origin and evolution of Citrus. Nature. 2018;554(7692):311-316. doi:10.1038/nature25447.
Herrero J, Al-Shahrour F, Diaz-Uriarte R, et al. GEPAS: A web-based resource for microarray gene expression data analysis. Nucleic Acids Res. 2003;31:3461-7. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12824345.
Tarraga J, Medina I, Carbonell J, et al. GEPAS, a web-based tool for microarray data analysis and interpretation. Nucleic Acids Res. 2008;36:W308-14. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18508806.
Tarraga J, Medina I, Carbonell J, et al. GEPAS, a web-based tool for microarray data analysis and interpretation. Nucleic Acids Res. 2008;36:W308-14. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18508806.
Tárraga J, Medina I, Carbonell J, et al. GEPAS, a web-based tool for microarray data analysis and interpretation. Nucleic Acids Res. 2008;36(Web Server issue):W308-14. doi:10.1093/nar/gkn303.
Tárraga J, Medina I, Carbonell J, et al. GEPAS, a web-based tool for microarray data analysis and interpretation. Nucleic Acids Res. 2008;36(Web Server issue):W308-14. doi:10.1093/nar/gkn303.
Vaquerizas JM, Conde L, Yankilevich P, et al. GEPAS, an experiment-oriented pipeline for the analysis of microarray gene expression data. Nucleic Acids Res. 2005;33:W616-20. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15980548.
Roca-Ayats N, Balcells S, Garcia-Giralt N, et al. GGPS1 Mutation and Atypical Femoral Fractures with Bisphosphonates. N Engl J Med. 2017;376(18):1794-1795. doi:10.1056/NEJMc1612804.PDF icon Roca-Ayats-2017NEJM - GGPS1 Mutation and Atypical Femoral Fractures with Bisphosphonates.pdf (214.03 KB)
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Hidalgo MR, Cubuk C, Amadoz A, Salavert F, Carbonell-Caballero J, Dopazo J. High throughput estimation of functional cell activities reveals disease mechanisms and predicts relevant clinical outcomes. Oncotarget. 2017;8(3):5160-5178. doi:10.18632/oncotarget.14107.
Moura DS, Mondaza-Hernandez JL, Sanchez-Bustos P, et al. HMGA1 regulates trabectedin sensitivity in advanced soft-tissue sarcoma (STS): A Spanish Group for Research on Sarcomas (GEIS) study. Cell Mol Life Sci. 2024;81(1):219. doi:10.1007/s00018-024-05250-y.
Moura DS, Mondaza-Hernandez JL, Sanchez-Bustos P, et al. HMGA1 regulates trabectedin sensitivity in advanced soft-tissue sarcoma (STS): A Spanish Group for Research on Sarcomas (GEIS) study. Cell Mol Life Sci. 2024;81(1):219. doi:10.1007/s00018-024-05250-y.
Moura DS, Mondaza-Hernandez JL, Sanchez-Bustos P, et al. HMGA1 regulates trabectedin sensitivity in advanced soft-tissue sarcoma (STS): A Spanish Group for Research on Sarcomas (GEIS) study. Cell Mol Life Sci. 2024;81(1):219. doi:10.1007/s00018-024-05250-y.
Tárraga J, Gallego A, Arnau V, Medina I, Dopazo J. HPG pore: an efficient and scalable framework for nanopore sequencing data. BMC bioinformatics. 2016;17:107. doi:10.1186/s12859-016-0966-0.
Tárraga J, Gallego A, Arnau V, Medina I, Dopazo J. HPG pore: an efficient and scalable framework for nanopore sequencing data. BMC Bioinformatics. 2016;17(1). doi:10.1186/s12859-016-0966-0.
Sanchez-Mut JV, Heyn H, Vidal E, et al. Human DNA methylomes of neurodegenerative diseases show common epigenomic patterns. Transl Psychiatry. 2016;6:e718. doi:10.1038/tp.2015.214.
Sanchez-Mut JV, Heyn H, Vidal E, et al. Human DNA methylomes of neurodegenerative diseases show common epigenomic patterns. Transl Psychiatry. 2016;6:e718. doi:10.1038/tp.2015.214.