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Author Title [ Type(Asc)] Year
Journal Article
Arbiza L, Patricio M, Dopazo H, Posada D. Genome-wide heterogeneity of nucleotide substitution model fit. Genome biology and evolution. 2011;3:896-908.
Villalba-Benito L, López-López D, Torroglosa A, et al. Genome-wide analysis of DNA methylation in Hirschsprung enteric precursor cells: unraveling the epigenetic landscape of enteric nervous system developmentAbstractBackgroundResultsConclusionsGraphic abstract. Clinical Epigenetics. 2021;13(1). doi:10.1186/s13148-021-01040-6.
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.
Dopazo H, Dopazo J. Genome-scale evidence of the nematode-arthropod clade. Genome Biol. 2005;6:R41. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15892869.
Medina I, Salavert F, Sánchez R, et al. Genome Maps, a new generation genome browser. Nucleic acids research. 2013;41:W41-W46. doi:10.1093/nar/gkt530.
Medina I, Montaner D, Bonifaci N, et al. Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies. Nucl. Acids Res. 2009;37:W340-344. doi:10.1093/nar/gkp481.
Medina I, Montaner D, Bonifaci N, et al. Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies. Nucleic Acids Res. 2009;37(Web Server issue):W340-4. doi:10.1093/nar/gkp481.
Montaner D, Minguez P, Al-Shahrour F, Dopazo J. Gene set internal coherence in the context of functional profiling. BMC Genomics. 2009;10:197. doi:10.1186/1471-2164-10-197.
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.
Melendez B, Diaz-Uriarte R, Cuadros M, et al. Gene expression analysis of chromosomal regions with gain or loss of genetic material detected by comparative genomic hybridization. Genes Chromosomes Cancer. 2004;41:353-65. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15382261.
Conesa A, Punt PJ, van den Hondel CA. Fungal peroxidases: molecular aspects and applications. J Biotechnol. 2002;93:143-58. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=11738721.
Minguez P, Al-Shahrour F, Dopazo J. A function-centric approach to the biological interpretation of microarray time-series. Genome Inform. 2006;17:57-66.
Aggarwal M, Sánchez-Beato M, Gómez-López G, et al. Functional signatures identified in B-cell non-Hodgkin lymphoma profiles. Leuk Lymphoma. 2009;50(10):1699-708. doi:10.1080/10428190903189035.
Minguez P, Al-Shahrour F, Montaner D, Dopazo J. Functional profiling of microarray experiments using text-mining derived bioentities. Bioinformatics. 2007;23(22):3098-9. doi:10.1093/bioinformatics/btm445.
Minguez P, Al-Shahrour F, Montaner D, Dopazo J. Functional profiling of microarray experiments using text-mining derived bioentities. Bioinformatics. 2007;23:3098-9. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17855415.
Conde L, Montaner D, Burguet-Castell J, Tarraga J, Al-Shahrour F, Dopazo J. Functional profiling and gene expression analysis of chromosomal copy number alterations. Bioinformation. 2007;1:432-5. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17597935.
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.
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.
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.
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.
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.
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.
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.