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D
Tarazona S, García-Alcalde F, Dopazo J, Ferrer A, Conesa A. Differential expression in RNA-seq: a matter of depth. Genome Res. 2011;21(12):2213-23. doi:10.1101/gr.124321.111.
Carretero M, Guerrero-Aspizua S, Illera N, et al. Differential Features Between Chronic Skin Inflammatory Diseases Revealed in Skin-Humanized Psoriasis and Atopic Dermatitis Mouse Models. J Invest Dermatol. 2015. doi:10.1038/jid.2015.362.
Aguerri M, Calzada D, Montaner D, et al. Differential gene-expression analysis defines a molecular pattern related to olive pollen allergy. J Biol Regul Homeost Agents. 2013;27(2):337-50.
Prieur X, Mok CYL, Velagapudi VR, et al. Differential Lipid Partitioning Between Adipocytes and Tissue Macrophages Modulates Macrophage Lipotoxicity and M2/M1 Polarization in Obese Mice. Diabetes. 2011;60:797-809.
Cubuk C, Hidalgo MR, Amadoz A, et al. Differential metabolic activity and discovery of therapeutic targets using summarized metabolic pathway models. NPJ Syst Biol Appl. 2019;5:7. doi:10.1038/s41540-019-0087-2.
Conesa A, Bro R, Garcia-Garcia F, et al. Direct functional assessment of the composite phenotype through multivariate projection strategies. Genomics. 2008;92:373-83. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18652888.
Conesa A, Bro R, Garcia-Garcia F, et al. Direct functional assessment of the composite phenotype through multivariate projection strategies. Genomics. 2008;92(6):373-83. doi:10.1016/j.ygeno.2008.05.015.
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.
Al-Shahrour F, Diaz-Uriarte R, Dopazo J. Discovering molecular functions significantly related to phenotypes by combining gene expression data and biological information. Bioinformatics. 2005;21:2988-93. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15840702.
López-Sánchez M, Loucera C, Peña-Chilet M, Dopazo J. Discovering potential interactions between rare diseases and COVID-19 by combining mechanistic models of viral infection with statistical modeling. Hum Mol Genet. 2022. doi:10.1093/hmg/ddac007.
García-Alonso L, Alonso R, Vidal E, et al. Discovering the hidden sub-network component in a ranked list of genes or proteins derived from genomic experiments. Nucleic Acids Res. 2012;40(20):e158. doi:10.1093/nar/gks699.
Dopazo J, Aloy P. Discovery and hypothesis generation through bioinformatics. Genome Biol. 2006;7:307. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16522224.
Negredo A, Palacios G, Vázquez-Morón S, et al. Discovery of an ebolavirus-like filovirus in europe. PLoS pathogens. 2011;7:e1002304.
Sundaram AYM, Kiron V, Dopazo J, Fernandes JMO. Diversification of the expanded teleost-specific toll-like receptor family in Atlantic cod, Gadus morhua. BMC Evol Biol. 2012;12:256. doi:10.1186/1471-2148-12-256.
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.
Bediaga NG, Acha-Sagredo A, Guerra I, et al. DNA methylation epigenotypes in breast cancer molecular subtypes. Breast Cancer Res. 2010;12(5):R77. doi:10.1186/bcr2721.
Vaquerizas JM, Dopazo J, Diaz-Uriarte R. DNMAD: web-based diagnosis and normalization for microarray data. Bioinformatics. 2004;20:3656-8. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15247094.
Garcia-Garcia F, Montaner D. Docencia en Estadística: Experiencias de Innovación. In: III Jornadas de Intercambio de Experiencias de Innovación Educativa en Estadística.Vol 1. III Jornadas de Intercambio de Experiencias de Innovación Educativa en Estadística.; 2013:201-210.
Gutiérrez J, González-Pérez S, Garcia-Garcia F, Lorenzo O, Arellano JB. Does singlet oxygen activate cell death in Arabidopsis cell suspension cultures? Analysis of the early transcriptional defence responses to high light stress. Plant signaling & behavior. 2011;6.
Walsh I, Fishman D, Garcia-Gasulla D, et al. DOME: recommendations for supervised machine learning validation in biology. Nat Methods. 2021;18(10):1122-1127. doi:10.1038/s41592-021-01205-4.
Esteban-Medina M, Roque VManuel de, Herráiz-Gil S, Peña-Chilet M, Dopazo J, Loucera C. drexml: A command line tool and Python package for drug repurposing. Comput Struct Biotechnol J. 2024;23:1129-1143. doi:10.1016/j.csbj.2024.02.027.
Loucera C, Esteban-Medina M, Rian K, Falco MM, Dopazo J, Peña-Chilet M. Drug repurposing for COVID-19 using machine learning and mechanistic models of signal transduction circuits related to SARS-CoV-2 infection. Signal Transduct Target Ther. 2020;5(1):290. doi:10.1038/s41392-020-00417-y.
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.
Prieto J, León M, Ponsoda X, et al. Dysfunctional mitochondrial fission impairs cell reprogramming. Cell Cycle. 2016;15(23):3240-3250. doi:10.1080/15384101.2016.1241930.
E
Vivas Y, Martinez-Garcia C, Izquierdo A, et al. Early peroxisome proliferator-activated receptor gamma regulated genes involved in expansion of pancreatic beta cell mass. BMC Med Genomics. 2011;4:86. doi:10.1186/1755-8794-4-86.