Home

Publications

Export 597 results:
Author [ Title(Desc)] Type Year
Filters: First Letter Of Last Name is D  [Clear All Filters]
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
C
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.
Javierre BM, Fernandez AF, Richter J, et al. Changes in the pattern of DNA methylation associate with twin discordance in systemic lupus erythematosus. Genome research. 2010;20:170-9.
Sanghez V, Cubuk C, Sebastián-Leon P, et al. Chronic subordination stress selectively downregulates the insulin signaling pathway in liver and skeletal muscle but not in adipose tissue of male mice. Stress (Amsterdam, Netherlands). 2016:1-11. doi:10.3109/10253890.2016.1151491.
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.
Mas JM, Aloy P, Marti-Renom MA, et al. Classification of protein disulphide-bridge topologies. J Comput Aided Mol Des. 2001;15:477-87. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=11394740.
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.
Dopazo J. Clustering - Class discovery in the post-genomic era. In: Fundamentals of data mining in genomics and proteomics. Fundamentals of data mining in genomics and proteomics. New York, USA: Springer-Verlag, W. Dubitzky, M. Granzow and D.P. Berrar; 2007.
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.
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.
Herrero J, Dopazo J. Combining hierarchical clustering and self-organizing maps for exploratory analysis of gene expression patterns. J Proteome Res. 2002;1:467-70. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12645919.
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.
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.
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.
de la Rosa LRodríguez, Sánchez-Calderón H, Contreras J, et al. Comparative gene expression study of the vestibular organ of the Igf1 deficient mouse using whole-transcript arrays. Hearing research. 2015. doi:10.1016/j.heares.2015.08.016.
de la Rosa LRodríguez, Sánchez-Calderón H, Contreras J, et al. Comparative gene expression study of the vestibular organ of the Igf1 deficient mouse using whole-transcript arrays. Hearing research. 2015. doi:10.1016/j.heares.2015.08.016.
Martin MJ, Herrero J, Mateos A, Dopazo J. Comparing bacterial genomes through conservation profiles. Genome Res. 2003;13:991-8. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12695324.
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.
Eramian D, Shen MY, Devos D, Melo F, Sali A, Marti-Renom MA. A composite score for predicting errors in protein structure models. Protein Sci. 2006;15:1653-66. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16751606.
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.
Su Z, Labaj PP, , et al. A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium. Nature biotechnology. 2014;32:903–914. doi:10.1038/nbt.2957.
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.
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.
Martinez H, Tárraga J, Medina I, et al. Concurrent and Accurate Short Read Mapping on Multicore Processors. IEEE/ACM transactions on computational biology and bioinformatics / IEEE, ACM. 2015;12:995-1007. doi:10.1109/TCBB.2015.2392077.