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Birmingham A, Selfors LM, Forster T, et al. Statistical methods for analysis of high-throughput RNA interference screens. Nature Methods. 2009;6:569 - 575. Available at: http://dx.doi.org/10.1038/nmeth.1351.
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.
Bediaga NG, Acha-Sagredo A, Guerra I, et al. DNA methylation epigenotypes in breast cancer molecular subtypes. Breast Cancer Res. 2010;12(5):R77. doi:10.1186/bcr2721.
Baù D, Sanyal A, Lajoie BR, et al. The three-dimensional folding of the α-globin gene domain reveals formation of chromatin globules. Nature structural & molecular biology. 2011;18:107-14.
Baù D, Marti-Renom MA. Structure determination of genomic domains by satisfaction of spatial restraints. Chromosome research : an international journal on the molecular, supramolecular and evolutionary aspects of chromosome biology. 2011;19:25-35.
Barragán I, Borrego S, Pieras JIgnacio, et al. Mutation spectrum of EYS in Spanish patients with autosomal recessive retinitis pigmentosa. Hum Mutat. 2010;31(11):E1772-800. doi:10.1002/humu.21334.
Bañó-Polo M, Baldin F, Tamborero S, Marti-Renom MA, Mingarro I. N-glycosylation efficiency is determined by the distance to the C-terminus and the amino acid preceding an Asn-Ser-Thr sequon. Protein science : a publication of the Protein Society. 2011;20:179-86.
A
Azuaje F, Dopazo J. Data analysis and visualisation in genomics and proteomics. In: Wiley, F. Azuaje and J. Dopazo; 2005.
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.
Azuaje F, Dopazo J, Wang H. Data and Predictive Model Integration: an Overview of Key Concepts, Problems and Solutions. In: Data analysis and visualisation in genomics and proteomics. Data analysis and visualisation in genomics and proteomics. Wiley, F. Azuaje and J. Dopazo; 2005.
Azuaje F, Al-Shahrour F, Dopazo J. Ontology-driven approaches to analyzing data in functional genomics. Methods Mol Biol. 2006;316:67-86. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16671401.
Avila-Fernandez A, Perez-Carro R, Corton M, et al. Whole-exome sequencing reveals ZNF408 as a new gene associated with autosomal recessive retinitis pigmentosa with vitreal alterations. Hum Mol Genet. 2015;24(14):4037-48. doi:10.1093/hmg/ddv140.
Avila-Fernandez A, Perez-Carro R, Corton M, et al. Whole Exome Sequencing Reveals ZNF408 as a New Gene Associated With Autosomal Recessive Retinitis Pigmentosa with Vitreal Alterations. Human molecular genetics. 2015;24:4037-4048. doi:10.1093/hmg/ddv140.
Ariño J, Casamayor A, Pérez JPerez, et al. Assessing Differential Expression Measurements by Highly Parallel Pyrosequencing and DNA Microarrays: A Comparative Study. Omics : a journal of integrative biology. 2013. doi:10.1089/omi.2011.0065.
Arbiza L, Patricio M, Dopazo H, Posada D. Genome-wide heterogeneity of nucleotide substitution model fit. Genome biology and evolution. 2011;3:896-908.
Arbiza L, Dopazo J, Dopazo H. Positive selection, relaxation, and acceleration in the evolution of the human and chimp genome. PLoS Comput Biol. 2006;2:e38. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16683019.
Arbiza L, Duchi S, Montaner D, et al. Selective pressures at a codon-level predict deleterious mutations in human disease genes. J Mol Biol. 2006;358:1390-404. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16584746.
Aragues R, Sali A, Bonet J, Marti-Renom MA, Oliva B. Characterization of protein hubs by inferring interacting motifs from protein interactions. PLoS Comput Biol. 2007;3:1761-71. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17941705.
Aparicio G, Gotz S, Conesa A, et al. Blast2GO goes grid: developing a grid-enabled prototype for functional genomics analysis. Stud Health Technol Inform. 2006;120:194-204. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16823138.
Antón J, Peña A, Valens M, et al. Salinibacter ruber: genomics and biogeography. In: Adaptation to life in high salt concentrations in Archaea, Bacteria and Eukarya.Vol 9. Adaptation to life in high salt concentrations in Archaea, Bacteria and Eukarya. Dordrecht, Netherlands: Nina Gunde-Cimerman, Ana Plemenitas, and Aharon Oren. Kluwer Academic Publishers; 2005:257-266.
Amadoz A, Hidalgo MR, Cubuk C, Carbonell-Caballero J, Dopazo J. A comparison of mechanistic signaling pathway activity analysis methods. Brief Bioinform. 2019;20(5):1655-1668. doi:10.1093/bib/bby040.
Amadoz A, Sebastián-Leon P, Vidal E, Salavert F, Dopazo J. Using activation status of signaling pathways as mechanism-based biomarkers to predict drug sensitivity. Sci Rep. 2015;5:18494. doi:10.1038/srep18494.
Alvarez-Mora MI, Rodriguez-Revenga L, Madrigal I, et al. Deregulation of key signaling pathways involved in oocyte maturation in FMR1 premutation carriers with Fragile X-associated primary ovarian insufficiency. Gene. 2015;571(1):52-7. doi:10.1016/j.gene.2015.06.039.
Alvarez S, Diaz-Uriarte R, Osorio A, et al. A predictor based on the somatic genomic changes of the BRCA1/BRCA2 breast cancer tumors identifies the non-BRCA1/BRCA2 tumors with BRCA1 promoter hypermethylation. Clin Cancer Res. 2005;11:1146-53. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15709182.
Alonso R, Salavert F, Garcia-Garcia F, et al. Babelomics 5.0: functional interpretation for new generations of genomic data. Nucleic acids research. 2015;43:W117-W121. doi:10.1093/nar/gkv384.