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C
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.
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.
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.
Martorell-Marugán J, López-Domínguez R, García-Moreno A, et al. A comprehensive database for integrated analysis of omics data in autoimmune diseases. BMC Bioinformatics. 2021;22(1):343. doi:10.1186/s12859-021-04268-4.
Martorell-Marugán J, López-Domínguez R, García-Moreno A, et al. A comprehensive database for integrated analysis of omics data in autoimmune diseases. BMC Bioinformatics. 2021;22(1):343. doi:10.1186/s12859-021-04268-4.
Martorell-Marugán J, López-Domínguez R, García-Moreno A, et al. A comprehensive database for integrated analysis of omics data in autoimmune diseases. BMC Bioinformatics. 2021;22(1):343. doi:10.1186/s12859-021-04268-4.
Núñez-Torres R, Pita G, Peña-Chilet M, et al. A Comprehensive Analysis of 21 Actionable Pharmacogenes in the Spanish Population: From Genetic Characterisation to Clinical Impact. Pharmaceutics. 2023;15(4). doi:10.3390/pharmaceutics15041286.
Gabaldón T. Comparative genomics-based prediction of protein function. In: Methods in Molecular Biology.Vol 439. Methods in Molecular Biology. M. Starkey and R. Elaswarapu, Humana press; 2008. Available at: http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-188-8_26.
Menden MP, Wang D, Mason MJ, et al. Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen. Nat Commun. 2019;10(1):2674. doi:10.1038/s41467-019-09799-2.
Menden MP, Wang D, Mason MJ, et al. Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen. Nat Commun. 2019;10(1):2674. doi:10.1038/s41467-019-09799-2.
Menden MP, Wang D, Mason MJ, et al. Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen. Nat Commun. 2019;10(1):2674. doi:10.1038/s41467-019-09799-2.
Menden MP, Wang D, Mason MJ, et al. Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen. Nat Commun. 2019;10(1):2674. doi:10.1038/s41467-019-09799-2.
Yang M, Petralia F, Li Z, et al. Community Assessment of the Predictability of Cancer Protein and Phosphoprotein Levels from Genomics and Transcriptomics. Cell Syst. 2020;11(2):186-195.e9. doi:10.1016/j.cels.2020.06.013.
Ewing AD, Houlahan KE, Hu Y, et al. Combining tumor genome simulation with crowdsourcing to benchmark somatic single-nucleotide-variant detection. participants ICGC-TCGADREAMSoma, Xi L, Dewal N, et al., eds. Nature methods. 2015. doi:10.1038/nmeth.3407.
Huynen MA, Spronk CA, Gabaldón T, Snel B. Combining data from genomes, Y2H and 3D structure indicates that BolA is a reductase interacting with a glutaredoxin. FEBS Lett. 2005;579:591-6. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15670813.
de Castro-Miró M, Pomares E, Lorés-Motta L, et al. Combined genetic and high-throughput strategies for molecular diagnosis of inherited retinal dystrophies. PloS one. 2014;9:e88410. doi:10.1371/journal.pone.0088410.
Valls J, Grau M, Sole X, et al. CLEAR-test: combining inference for differential expression and variability in microarray data analysis. J Biomed Inform. 2008;41:33-45. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17597009.
Luque J, Mendes I, Gómez B, et al. CIBERER: Spanish National Network for Research on Rare Diseases: a highly productive collaborative initiative. Clin Genet. 2022. doi:10.1111/cge.14113.
Luque J, Mendes I, Gómez B, et al. CIBERER: Spanish National Network for Research on Rare Diseases: a highly productive collaborative initiative. Clin Genet. 2022. doi:10.1111/cge.14113.
Gundogdu P, Payá-Milans M, Alamo-Alvarez I, Nepomuceno-Chamorro IA, Dopazo J, Loucera C. Cell-Level Pathway Scoring Comparison with a Biologically Constrained Variational Autoencoder. Cham: Springer Nature Switzerland; 2023:62 - 77. doi:10.1007/978-3-031-42697-110.1007/978-3-031-42697-1_5.
Bleda M, Tárraga J, De Maria A, et al. CellBase, a comprehensive collection of RESTful web services for retrieving relevant biological information from heterogeneous sources. Nucleic acids research. 2012;40:W609-14. doi:10.1093/nar/gks575.
Puig-Butille JAnton, Escamez MJosé, Garcia-Garcia F, et al. Capturing the biological impact of CDKN2A and MC1R genes as an early predisposing event in melanoma and non melanoma skin cancer. Oncotarget. 2013. Available at: http://www.impactjournals.com/oncotarget/index.php?journal=oncotarget&page=article&op=view&path%5B%5D=1444&path%5B%5D=1824.
B
Romero A, Garcia-Garcia F, López-Perolio I, et al. BRCA1 Alternative splicing landscape in breast tissue samples. BMC cancer. 2015;15:219. doi:10.1186/s12885-015-1145-9.
Romero A, Garcia-Garcia F, López-Perolio I, et al. BRCA1 Alternative splicing landscape in breast tissue samples. BMC cancer. 2015;15:219. doi:10.1186/s12885-015-1145-9.
Romero A, Garcia-Garcia F, López-Perolio I, et al. BRCA1 Alternative splicing landscape in breast tissue samples. BMC cancer. 2015;15:219. doi:10.1186/s12885-015-1145-9.