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Author Title [ Type(Desc)] Year
Journal Article
Fernandez P, Soria M, Blesa D, et al. Development, Characterization and Experimental Validation of a Cultivated Sunflower (Helianthus annuus L.) Gene Expression Oligonucleotide Microarray. PloS one. 2012;7:e45899. doi:10.1371/journal.pone.0045899.
Forment J, Gadea J, Huerta L, et al. Development of a citrus genome-wide EST collection and cDNA microarray as resources for genomic studies. Plant Mol Biol. 2005;57:375-91. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15830128.
Williams TD, Diab AM, George SG, et al. Development of the GENIPOL European flounder (Platichthys flesus) microarray and determination of temporal transcriptional responses to cadmium at low dose. Environ Sci Technol. 2006;40:6479-88. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17120584.
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.
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.