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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.
Santoyo J, Vaquerizas JM, Dopazo J. Highly specific and accurate selection of siRNAs for high-throughput functional assays. Bioinformatics. 2005;21:1376-82. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15591357.
Schluter A, Fourcade S, Domenech-Estevez E, et al. PeroxisomeDB: a database for the peroxisomal proteome, functional genomics and disease. Nucleic Acids Res. 2007;35:D815-22. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17135190.
Sebastián-Leon P, Vidal E, Minguez P, et al. Understanding disease mechanisms with models of signaling pathway activities. BMC systems biology. 2014;8:121. doi:10.1186/s12918-014-0121-3.
Sebastián-Leon P, Vidal E, Minguez P, et al. Understanding disease mechanisms with models of signaling pathway activities. BMC systems biology. 2014;8:121. doi:10.1186/s12918-014-0121-3.
Sebastián-Leon P, Carbonell J, Salavert F, Sánchez R, Medina I, Dopazo J. Inferring the functional effect of gene expression changes in signaling pathways. Nucleic Acids Res. 2013;41(Web Server issue):W213-7. doi:10.1093/nar/gkt451.
Serra F, Arbiza L, Dopazo J, Dopazo H. Natural selection on functional modules, a genome-wide analysis. PLoS Comput Biol. 2011;7(3):e1001093. doi:10.1371/journal.pcbi.1001093.
Sevilla T, Lupo V, Martínez-Rubio D, et al. Mutations in the MORC2 gene cause axonal Charcot-Marie-Tooth disease. Brain. 2016;139(Pt 1):62-72. doi:10.1093/brain/awv311.
Sevilla T, Sivera R, Martínez-Rubio D, et al. The EGR2 gene is involved in axonal Charcot-Marie-Tooth disease. Eur J Neurol. 2015;22(12):1548-55. doi:10.1111/ene.12782.
Shi W, Bessarabova M, Dosymbekov D, et al. Functional analysis of multiple genomic signatures demonstrates that classification algorithms choose phenotype-related genes. Pharmacogenomics J. 2010;10(4):310-23. doi:10.1038/tpj.2010.35.
Shi L, Campbell G, Jones WD, et al. The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models. Nature biotechnology. 2010;28:827-38. Available at: http://www.nature.com/nbt/journal/v28/n8/full/nbt.1665.html.
Silbiger VN, Luchessi AD, Hirata RDC, et al. Novel genes detected by transcriptional profiling from whole-blood cells in patients with early onset of acute coronary syndrome. Clin Chim Acta. 2013;421:184-90. doi:10.1016/j.cca.2013.03.011.
Silbiger VN, Luchessi AD, Hirata RDC, et al. Novel genes detected by transcriptional profiling from whole-blood cells in patients with early onset of acute coronary syndrome: Transcriptional profiling of acute coronary syndrome. Clinica chimica acta; international journal of clinical chemistry. 2013. doi:10.1016/j.cca.2013.03.011.
Sola-García A, Cáliz-Molina MÁngeles, Espadas I, et al. Metabolic reprogramming by Acly inhibition using SB-204990 alters glucoregulation and modulates molecular mechanisms associated with aging. Commun Biol. 2023;6(1):250. doi:10.1038/s42003-023-04625-4.
Stanley WA, Fodor K, Marti-Renom MA, Schliebs W, Wilmanns M. Protein translocation into peroxisomes by ring-shaped import receptors. FEBS Lett. 2007;581:4795-802. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17884042.
Saar K, Beck A, Bihoreau M-T, et al. SNP and haplotype mapping for genetic analysis in the rat. Nat Genet. 2008;40(5):560-6. doi:10.1038/ng.124.
Stierum R, Conesa A, Heijne W, et al. Transcriptome analysis provides new insights into liver changes induced in the rat upon dietary administration of the food additives butylated hydroxytoluene, curcumin, propyl gallate and thiabendazole. Food Chem Toxicol. 2008;46:2616-28. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18539377.
Stojkovic M, Guzmán FManuel Ort, Han D, Stojkovic P, Dopazo J, Stankovic KM. Polystyrene nanoplastics affect transcriptomic and epigenomic signatures of human fibroblasts and derived induced pluripotent stem cells: Implications for human health. Environ Pollut. 2023:120849. doi:10.1016/j.envpol.2022.120849.
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.
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.
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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.
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.
Tárraga J, Medina I, Carbonell J, et al. GEPAS, a web-based tool for microarray data analysis and interpretation. Nucleic Acids Res. 2008;36(Web Server issue):W308-14. doi:10.1093/nar/gkn303.
Tárraga J, Pérez M, Orduña JM, Duato J, Medina I, Dopazo J. A Parallel and Sensitive Software Tool for Methylation Analysis on Multicore Platforms. Bioinformatics (Oxford, England). 2015;31:3130-3138. doi:10.1093/bioinformatics/btv357.
Tárraga J, Gallego A, Arnau V, Medina I, Dopazo J. HPG pore: an efficient and scalable framework for nanopore sequencing data. BMC Bioinformatics. 2016;17(1). doi:10.1186/s12859-016-0966-0.