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Mateos A, Herrero J, Dopazo J. Using perceptrons for supervised classification of DNA microarray samples: obtaining the optimal level of information and finding differentially expressed genes. In: ICANN 2002, LNCS 2415. ICANN 2002, LNCS 2415. J.R. Dorronsoro; 2002:577-582.
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.
Díaz-Uriarte R, Al-Shahrour F, Dopazo J. Use of GO Terms to Understand the Biological Significance of Microarray Differential Gene Expression Data. In: Microarray data analysis III. Microarray data analysis III. Kluwer Academic, K. F. Johnson and S. M. Lin; 2003:233-247.
Capriotti E, Arbiza L, Casadio R, Dopazo J, Dopazo H, Marti-Renom MA. Use of estimated evolutionary strength at the codon level improves the prediction of disease-related protein mutations in humans. Hum Mutat. 2008;29:198-204. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17935148.
Conde L, Mateos A, Herrero J, Dopazo J. Unsupervised reduction of the dimensionality followed by supervised learning with a perceptron improves the classification of conditions in DNA microarray gene expression data. In: Neural Networks for Signal Processing XII. 2002 IEEE Signal Processing Society WorkshopProceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing. Neural Networks for Signal Processing XII. 2002 IEEE Signal Processing Society WorkshopProceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing. Martigny, Switzerland: IEEE; 2002. doi:10.1109/NNSP.2002.1030019.
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Mateos A, Dopazo J, Jansen R, Tu Y, Gerstein M, Stolovitzky G. Systematic learning of gene functional classes from DNA array expression data by using multilayer perceptrons. Genome Res. 2002;12:1703-15. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12421757.
Mateos A, Herrero J, Tamames J, Dopazo J. Supervised Neural Networks For Clustering Conditions In DNA Array Data After Reducing Noise By Clustering Gene Expression Profiles. In: Microarray data analysis II. Microarray data analysis II. Kluwer Academic; 2002:91-103.
Saar K, Beck A, Bihoreau MT, et al. SNP and haplotype mapping for genetic analysis in the rat. Nat Genet. 2008;40:560-6. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18443594.
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.
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.
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Conde L, Vaquerizas JM, Ferrer-Costa C, de la Cruz X, Orozco M, Dopazo J. PupasView: a visual tool for selecting suitable SNPs, with putative pathological effect in genes, for genotyping purposes. Nucleic Acids Res. 2005;33:W501-5. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15980522.
Conde L, Vaquerizas JM, Dopazo H, et al. PupaSuite: finding functional single nucleotide polymorphisms for large-scale genotyping purposes. Nucleic Acids Res. 2006;34:W621-5. Available at: http://nar.oxfordjournals.org/cgi/content/full/34/suppl_2/W621.
Conde L, Vaquerizas JM, Santoyo J, et al. PupaSNP Finder: a web tool for finding SNPs with putative effect at transcriptional level. Nucleic Acids Res. 2004;32:W242-8. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15215388.
Minguez P, Dopazo J. Protein Interactions for Functional Genomics. In: Li X-L, Ng S-K, eds. Biological Data Mining in Protein Interaction Networks. Biological Data Mining in Protein Interaction Networks. Hershey, USA: Idea Group Inc (IGI); 2009:223-238. Available at: http://books.google.es/books?id=pNyCy5GsqtkC.
Medina I, Montaner D, Tarraga J, Dopazo J. Prophet, a web-based tool for class prediction using microarray data. Bioinformatics. 2007;23:390-1. Available at: http://bioinformatics.oxfordjournals.org/cgi/content/full/23/3/390?view=long&pmid=17138587.
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.
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.
Huerta-Cepas J, Bueno A, Dopazo J, Gabaldón T. PhylomeDB: a database for genome-wide collections of gene phylogenies. Nucleic Acids Res. 2008;36:D491-6. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17962297.
Dopazo H, Santoyo J, Dopazo J. Phylogenomics and the number of characters required for obtaining an accurate phylogeny of eukaryote model species. Bioinformatics. 2004;20 Suppl 1:i116-21. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15262789.
Elena SF, Dopazo J, de la Pena M, Flores R, Diener TO, Moya A. Phylogenetic analysis of viroid and viroid-like satellite RNAs from plants: a reassessment. J Mol Evol. 2001;53:155-9. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=11479686.
Tarraga J, Medina I, Arbiza L, et al. Phylemon: a suite of web tools for molecular evolution, phylogenetics and phylogenomics. Nucleic Acids Res. 2007;35:W38-42. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17452346.
Palacios J, Honrado E, Osorio A, et al. Phenotypic characterization of BRCA1 and BRCA2 tumors based in a tissue microarray study with 37 immunohistochemical markers. Breast Cancer Res Treat. 2005;90:5-14. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15770521.
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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.
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.
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Calpena E, Martínez-Rubio D, Arpa J, et al. A novel locus for a hereditary recurrent neuropathy on chromosome 21q21. Neuromuscular disorders : NMD. 2014;24:660-5. doi:10.1016/j.nmd.2014.04.004.