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Book Chapter
Conesa A, Forment J, Gadea J, van Dijk J. Microarray Technology in Agricultural Research. In: Microarray Technology Through Applications. Microarray Technology Through Applications. F. Falciani. Publisher: Taylor and Francis Group; 2007:173-209.
Journal Article
Dopazo J, Amadoz A, Bleda M, et al. 267 Spanish exomes reveal population-specific differences in disease-related genetic variation. Molecular biology and evolution. 2016. doi:10.1093/molbev/msw005.
Boxma B, de Graaf RM, van der Staay GW, et al. An anaerobic mitochondrion that produces hydrogen. Nature. 2005;434:74-9. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15744302.
E. Lewintre J, C. Martin R, Montaner D, et al. Analysis of chronic lymphotic leukemia transcriptomic profile: differences between molecular subgroups. Leuk Lymphoma. 2009;50:68-79. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=19127482.
Trevino V, Tadesse MG, Vannucci M, et al. Analysis of normal-tumour tissue interaction in tumours: prediction of prostate cancer features from the molecular profile of adjacent normal cells. PloS one. 2011;6:e16492.
Dopazo J, Mendoza A, Herrero J, et al. Annotated draft genomic sequence from a Streptococcus pneumoniae type 19F clinical isolate. Microb Drug Resist. 2001;7:99-125. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=11442348.
Dopazo J, Mendoza A, Herrero J, et al. Annotated draft genomic sequence from a Streptococcus pneumoniae type 19F clinical isolate. Microb Drug Resist. 2001;7:99-125. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=11442348.
Casimiro-Soriguer CS, Loucera C, Florido JPerez, López-López D, Dopazo J. Antibiotic resistance and metabolic profiles as functional biomarkers that accurately predict the geographic origin of city metagenomics samples. Biol Direct. 2019;14(1):15. doi:10.1186/s13062-019-0246-9.
Nueda MJ, Ferrer A, Conesa A. ARSyN: a method for the identification and removal of systematic noise in multifactorial time course microarray experiments. Biostatistics (Oxford, England). 2011.
Munro SA, Lund SP, P Pine S, et al. Assessing technical performance in differential gene expression experiments with external spike-in RNA control ratio mixtures. Nature communications. 2014;5:5125. doi:10.1038/ncomms6125.
Gonzalez S, Clavijo B, Rivarola M, et al. ATGC transcriptomics: a web-based application to integrate, explore and analyze de novo transcriptomic data. BMC Bioinformatics. 2017;18(1):121. doi:10.1186/s12859-017-1494-2.
Tamames J, Clark D, Herrero J, et al. Bioinformatics methods for the analysis of expression arrays: data clustering and information extraction. J Biotechnol. 2002;98:269-83. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12141992.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Ostaszewski M, Niarakis A, Mazein A, et al. COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms. Mol Syst Biol. 2021;17(10):e10387. doi:10.15252/msb.202110387.