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Montaner D, Minguez P, Al-Shahrour F, Dopazo J. Gene set internal coherence in the context of functional profiling. BMC Genomics. 2009;10:197. doi:10.1186/1471-2164-10-197.
Montero-Conde C, Martín-Campos JM, Lerma E, et al. Molecular profiling related to poor prognosis in thyroid carcinoma. Combining gene expression data and biological information. Oncogene. 2008;27(11):1554-61. doi:10.1038/sj.onc.1210792.
Montero-Conde C, Martin-Campos JM, Lerma E, et al. Molecular profiling related to poor prognosis in thyroid carcinoma. Combining gene expression data and biological information. Oncogene. 2008;27:1554-61. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17873908.
Moreno-Manzano V, Rodríguez-Jiménez FJ, Aceña-Bonilla JL, et al. FM19G11, a new hypoxia-inducible factor (HIF) modulator, affects stem cell differentiation status. The Journal of biological chemistry. 2010;285:1333-42.
Moschen S, Luoni SBengoa, Di Rienzo JA, et al. Integrating transcriptomic and metabolomic analysis to understand natural leaf senescence in sunflower. Plant Biotechnol J. 2016;14(2):719-34. doi:10.1111/pbi.12422.
Moschen S, Di Rienzo JA, Higgins J, et al. Integration of transcriptomic and metabolic data reveals hub transcription factors involved in drought stress response in sunflower (Helianthus annuus L.). Plant Mol Biol. 2017;94(4-5):549-564. doi:10.1007/s11103-017-0625-5.
Moura DS, Mondaza-Hernandez JL, Sanchez-Bustos P, et al. HMGA1 regulates trabectedin sensitivity in advanced soft-tissue sarcoma (STS): A Spanish Group for Research on Sarcomas (GEIS) study. Cell Mol Life Sci. 2024;81(1):219. doi:10.1007/s00018-024-05250-y.
Moura DS, Peña-Chilet M, Varela JAntonio Co, et al. A DNA damage repair gene-associated signature predicts responses of patients with advanced soft-tissue sarcoma to treatment with trabectedin. Mol Oncol. 2021;15(12):3691-3705. doi:10.1002/1878-0261.12996.
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.
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Negredo A, Palacios G, Vázquez-Morón S, et al. Discovery of an ebolavirus-like filovirus in europe. PLoS pathogens. 2011;7:e1002304.
Németh A, Conesa A, Santoyo-López J, et al. Initial genomics of the human nucleolus. PLoS genetics. 2010;6:e1000889. doi:10.1371/journal.pgen.1000889.
Niarakis A, Ostaszewski M, Mazein A, et al. Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches. Front Immunol. 2024;14:1282859. doi:10.3389/fimmu.2023.1282859.
Nobre LS, Al-Shahrour F, Dopazo J, Saraiva LM. Exploring the antimicrobial action of a carbon monoxide-releasing compound through whole-genome transcription profiling of Escherichia coli. Microbiology. 2009;155:813-24. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=19246752.
Nobre LS, Al-Shahrour F, Dopazo J, Saraiva LM. Exploring the antimicrobial action of a carbon monoxide-releasing compound through whole-genome transcription profiling of Escherichia coli. Microbiology (Reading). 2009;155(Pt 3):813-824. doi:10.1099/mic.0.023911-0.
Nueda MJ, Conesa A, Westerhuis JA, et al. Discovering gene expression patterns in time course microarray experiments by ANOVA-SCA. Bioinformatics. 2007;23:1792-800. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17519250.
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.
Nueda MJosé, Carbonell J, Medina I, Dopazo J, Conesa A. Serial Expression Analysis: a web tool for the analysis of serial gene expression data. Nucleic Acids Res. 2010;38(Web Server issue):W239-45. doi:10.1093/nar/gkq488.
Nueda MJosé, Sebastián P, Tarazona S, et al. Functional assessment of time course microarray data. BMC Bioinformatics. 2009;10 Suppl 6:S9. doi:10.1186/1471-2105-10-S6-S9.
Nunez JI, Martin MJ, Piccone ME, et al. Identification of optimal regions for phylogenetic studies on VP1 gene of foot-and-mouth disease virus: analysis of types A and O Argentinean viruses. Vet Res. 2001;32:31-45. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=11254175.
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.
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Olanda R, Pérez M, Orduña JM, Tárraga J, Dopazo J. A new parallel pipeline for DNA methylation analysis of long reads datasets. BMC bioinformatics. 2017;18:161. doi:10.1186/s12859-017-1574-3.
Olivares-González L, Velasco S, Gallego I, et al. An SPM-Enriched Marine Oil Supplement Shifted Microglia Polarization toward M2, Ameliorating Retinal Degeneration in Mice. Antioxidants (Basel). 2022;12(1). doi:10.3390/antiox12010098.
Oppert B, Dowd SE, Bouffard P, et al. Transcriptome profiling of the intoxication response of Tenebrio molitor larvae to Bacillus thuringiensis Cry3Aa protoxin. PloS one. 2012;7:e34624. doi:10.1371/journal.pone.0034624.
Orti L, Carbajo RJ, Pieper U, et al. A kernel for open source drug discovery in tropical diseases. PLoS Negl Trop Dis. 2009;3:e418. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=19381286.
Orti L, Carbajo RJ, Pieper U, et al. A kernel for the Tropical Disease Initiative. Nat Biotechnol. 2009;27:320-1. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=19352362.