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I
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.
Palomero L, Galván-Femenía I, de Cid R, et al. Immune Cell Associations with Cancer Risk. iScience. 2020;23(7):101296. doi:10.1016/j.isci.2020.101296.
Palomero L, Galván-Femenía I, de Cid R, et al. Immune Cell Associations with Cancer Risk. iScience. 2020;23(7):101296. doi:10.1016/j.isci.2020.101296.
Jaime MDLA, Lopez-Llorca LVicente, Conesa A, et al. Identification of yeast genes that confer resistance to chitosan oligosaccharide (COS) using chemogenomics. BMC genomics. 2012;13:267. doi:10.1186/1471-2164-13-267.
Tracey L, Villuendas R, Ortiz P, et al. Identification of genes involved in resistance to interferon-alpha in cutaneous T-cell lymphoma. Am J Pathol. 2002;161:1825-37. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12414529.
Tracey L, Villuendas R, Ortiz P, et al. Identification of genes involved in resistance to interferon-alpha in cutaneous T-cell lymphoma. Am J Pathol. 2002;161:1825-37. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12414529.
H
Huerta-Cepas J, Dopazo H, Dopazo J, Gabaldón T. The human phylome. Genome Biol. 2007;8:R109. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17567924.
Sanchez-Mut JV, Heyn H, Vidal E, et al. Human DNA methylomes of neurodegenerative diseases show common epigenomic patterns. Transl Psychiatry. 2016;6:e718. doi:10.1038/tp.2015.214.
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, 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.
Medina I, Tárraga J, Martínez H, et al. Highly sensitive and ultrafast read mapping for RNA-seq analysis. DNA Res. 2016;23(2):93-100. doi:10.1093/dnares/dsv039.
Hidalgo MR, Cubuk C, Amadoz A, Salavert F, Carbonell-Caballero J, Dopazo J. High throughput estimation of functional cell activities reveals disease mechanisms and predicts relevant clinical outcomes. Oncotarget. 2017;8(3):5160-5178. doi:10.18632/oncotarget.14107.
Herrero J, Valencia A, Dopazo J. A hierarchical unsupervised growing neural network for clustering gene expression patterns. Bioinformatics. 2001;17:126-36. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=11238068.
Lopez J, Coll J, Haimel M, et al. HGVA: the Human Genome Variation Archive. Nucleic Acids Res. 2017;45(W1):W189-W194. doi:10.1093/nar/gkx445.
Hoffmann R, Dopazo J, Cigudosa JC, Valencia A. HCAD, closing the gap between breakpoints and genes. Nucleic Acids Res. 2005;33:D511-3. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15608250.
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Vaquerizas JM, Conde L, Yankilevich P, et al. GEPAS, an experiment-oriented pipeline for the analysis of microarray gene expression data. Nucleic Acids Res. 2005;33:W616-20. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15980548.
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.
Tarraga J, Medina I, Carbonell J, et al. GEPAS, a web-based tool for microarray data analysis and interpretation. Nucleic Acids Res. 2008;36:W308-14. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18508806.
Herrero J, Al-Shahrour F, Diaz-Uriarte R, et al. GEPAS: A web-based resource for microarray gene expression data analysis. Nucleic Acids Res. 2003;31:3461-7. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12824345.
Rian K, Hidalgo MR, Cubuk C, et al. Genome-scale mechanistic modeling of signaling pathways made easy: A bioconductor/cytoscape/web server framework for the analysis of omic data. Computational and Structural Biotechnology Journal. 2021;19:2968 - 2978. doi:10.1016/j.csbj.2021.05.022.
Cubuk C, Hidalgo MR, Amadoz A, et al. Gene Expression Integration into Pathway Modules Reveals a Pan-Cancer Metabolic Landscape. Cancer Res. 2018;78(21):6059-6072. doi:10.1158/0008-5472.CAN-17-2705.
Cubuk C, Hidalgo MR, Amadoz A, et al. Gene Expression Integration into Pathway Modules Reveals a Pan-Cancer Metabolic Landscape. Cancer Res. 2018;78(21):6059-6072. doi:10.1158/0008-5472.CAN-17-2705.
Herrero J, Diaz-Uriarte R, Dopazo J. Gene expression data preprocessing. Bioinformatics. 2003;19:655-6. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12651726.
F
Al-Shahrour F, Arbiza L, Dopazo H, et al. From genes to functional classes in the study of biological systems. BMC Bioinformatics. 2007;8:114. doi:10.1186/1471-2105-8-114.
Al-Shahrour F, Arbiza L, Dopazo H, et al. From genes to functional classes in the study of biological systems. BMC Bioinformatics. 2007;8:114. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17407596.