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Chacón-Solano E, León C, Díaz F, et al. Fibroblast activation and abnormal extracellular matrix remodelling as common hallmarks in three cancer-prone genodermatoses. Br J Dermatol. 2019;181(3):512-522. doi:10.1111/bjd.17698.
Peña A, Teeling H, Huerta-Cepas J, et al. Fine-scale evolution: genomic, phenotypic and ecological differentiation in two coexisting Salinibacter ruber strains. The ISME journal. 2010.
Peña A, Teeling H, Huerta-Cepas J, et al. Fine-scale evolution: genomic, phenotypic and ecological differentiation in two coexisting Salinibacter ruber strains. The ISME journal. 2010.
Hernáez JRodríguez, Cucchi MEsperanza, Cravero S, et al. The first complete genomic structure of Butyrivibrio fibrisolvens and its chromid. Microb Genom. 2018;4(10). doi:10.1099/mgen.0.000216.
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.
Dopazo J. Formulating and testing hypotheses in functional genomics. Artif Intell Med. 2009;45:97-107. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18789659.
Dopazo J. Formulating and testing hypotheses in functional genomics. Artif Intell Med. 2009;45(2-3):97-107. doi:10.1016/j.artmed.2008.08.003.
Khalaf AA, Gmitter FG, Conesa A, Dopazo J, Moore GA. Fortunella margarita Transcriptional Reprogramming Triggered by Xanthomonas citri subsp. citri. BMC plant biology. 2011;11:159.
Fernández RMa, Bleda M, Núñez-Torres R, et al. Four new loci associations discovered by pathway-based and network analyses of the genome-wide variability profile of Hirschsprung's disease. Orphanet J Rare Dis. 2012;7:103. doi:10.1186/1750-1172-7-103.
Fernández RMa, Bleda M, Núñez-Torres R, et al. Four new loci associations discovered by pathway-based and network analyses of the genome-wide variability profile of Hirschsprung’s disease. Orphanet journal of rare diseases. 2012;7:103. doi:10.1186/1750-1172-7-103.
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.
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.
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 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 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 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 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.
Dopazo J, Al-Shahrour F. Functional annotation of microarray experiments. In: Microarray Technology Through Applications. Microarray Technology Through Applications. New York, USA: Taylor & Francis, F. Falciani; 2007.
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.
Minguez P, Dopazo J. Functional genomics and networks: new approaches in the extraction of complex gene modules. Expert Rev Proteomics. 2010;7(1):55-63. doi:10.1586/epr.09.103.
Galan A, Montaner D, M Póo E, et al. Functional genomics of 5- to 8-cell stage human embryos by blastomere single-cell cDNA analysis. PLoS One. 2010;5(10):e13615. doi:10.1371/journal.pone.0013615.
Dopazo J. Functional interpretation of microarray experiments. OMICS. 2006;10:398-410. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17069516.
Conde L, Montaner D, Burguet-Castell J, Tárraga J, Al-Shahrour F, Dopazo J. Functional profiling and gene expression analysis of chromosomal copy number alterations. Bioinformation. 2007;1(10):432-5. doi:10.6026/97320630001432.