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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, 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.
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.
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.
Alloza E, Al-Shahrour F, Cigudosa JC, Dopazo J. A large scale survey reveals that chromosomal copy-number alterations significantly affect gene modules involved in cancer initiation and progression. BMC Medical Genomics. 2011;4:37. doi:10.1186/1755-8794-4-37.
Alemán A, Garcia-Garcia F, Medina I, Dopazo J. A web tool for the design and management of panels of genes for targeted enrichment and massive sequencing for clinical applications. Nucleic acids research. 2014;42:W83-W87. doi:10.1093/nar/gku472.
Alemán A, Garcia-Garcia F, Salavert F, Medina I, Dopazo J. A web-based interactive framework to assist in the prioritization of disease candidate genes in whole-exome sequencing studies. Nucleic acids research. 2014;42:W88-W93. doi:10.1093/nar/gku407.
Al-Shahrour F, Minguez P, Tarraga J, et al. FatiGO +: a functional profiling tool for genomic data. Integration of functional annotation, regulatory motifs and interaction data with microarray experiments. Nucleic Acids Res. 2007;35:W91-6. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17478504.
Al-Shahrour F, Dopazo J. Ontologies and functional genomics. In: Data analysis and visualisation in genomics and proteomics. Data analysis and visualisation in genomics and proteomics. Wiley, F. Azuaje and J. Dopazo; 2005:99-102.
Al-Shahrour F, Minguez P, Vaquerizas JM, Conde L, Dopazo J. BABELOMICS: a suite of web tools for functional annotation and analysis of groups of genes in high-throughput experiments. Nucleic Acids Res. 2005;33:W460-4. Available at: http://nar.oxfordjournals.org/content/33/suppl_2/W460.long.
Al-Shahrour F, Herrero J, Mateos A, Santoyo J, Díaz-Uriarte R, Dopazo J. Using Gene Ontology on genome-scale studies to find significant associations of biologically relevant terms to group of genes. In: Neural Networks for Signal Processing XIII. Neural Networks for Signal Processing XIII. New York, USA: IEEE Press; 2003:43-52.