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A
Al-Shahrour F, Minguez P, Tárraga J, et al. FatiGO +: a functional profiling tool for genomic data. Integration of functional annotation, regulatory motifs and interaction data with microarray experiments. Nucleic Acids Res. 2007;35(Web Server issue):W91-6. doi:10.1093/nar/gkm260.
Azuaje F, Al-Shahrour F, Dopazo J. Ontology-driven approaches to analyzing data in functional genomics. Methods Mol Biol. 2006;316:67-86. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16671401.
B
Wilkinson MD, Senger M, Kawas E, et al. Interoperability with Moby 1.0--it's better than sharing your toothbrush!. Brief Bioinform. 2008;9(3):220-31. doi:10.1093/bib/bbn003.
C
Capriotti E, Arbiza L, Casadio R, Dopazo J, Dopazo H, Marti-Renom MA. Use of estimated evolutionary strength at the codon level improves the prediction of disease-related protein mutations in humans. Hum Mutat. 2008;29(1):198-204. doi:10.1002/humu.20628.
Casimiro-Soriguer CS, Rigual MM, Brokate-Llanos AM, et al. Using AnABlast for intergenic sORF prediction in the Caenorhabditis elegans genome. Bioinformatics. 2020;36(19):4827-4832. doi:10.1093/bioinformatics/btaa608.
Conde L, Montaner D, Burguet-Castell J, et al. ISACGH: a web-based environment for the analysis of Array CGH and gene expression which includes functional profiling. Nucleic Acids Res. 2007;35(Web Server issue):W81-5. doi:10.1093/nar/gkm257.
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.
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.
D
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.
Dopazo J, Al-Shahrour F. Expression and microarrays. Methods Mol Biol. 2008;453:245-55. doi:10.1007/978-1-60327-429-6_12.
G
Galvez JM, Castillo-Secilla D, Herrera LJ, et al. Towards Improving Skin Cancer Diagnosis by Integrating Microarray and RNA-Seq Datasets. IEEE J Biomed Health Inform. 2020;24(7):2119-2130. doi:10.1109/JBHI.2019.2953978.
Garcia-Garcia F, Panadero J, Dopazo J, Montaner D. Integrated gene set analysis for microRNA studies. Bioinformatics. 2016;32(18):2809-16. doi:10.1093/bioinformatics/btw334.
Garrido-Rodriguez M, López-López D, Ortuno FM, et al. A versatile workflow to integrate RNA-seq genomic and transcriptomic data into mechanistic models of signaling pathways. PLoS Comput Biol. 2021;17(2):e1008748. doi:10.1371/journal.pcbi.1008748.
Gómez-López G, Dopazo J, Cigudosa JC, Valencia A, Al-Shahrour F. Precision medicine needs pioneering clinical bioinformaticians. Brief Bioinform. 2019;20(3):752-766. doi:10.1093/bib/bbx144.
Götz S, García-Gómez JMiguel, Terol J, et al. High-throughput functional annotation and data mining with the Blast2GO suite. Nucleic Acids Res. 2008;36(10):3420-35. doi:10.1093/nar/gkn176.
H
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.
Hidalgo MR, Amadoz A, Cubuk C, Carbonell-Caballero J, Dopazo J. Models of cell signaling uncover molecular mechanisms of high-risk neuroblastoma and predict disease outcome. Biol Direct. 2018;13(1):16. doi:10.1186/s13062-018-0219-4.
Huerta-Cepas J, Dopazo J, Gabaldón T. ETE: a python Environment for Tree Exploration. BMC Bioinformatics. 2010;11:24. doi:10.1186/1471-2105-11-24.
K
Koziol A, Gonzalo P, Mota A, et al. The protease MT1-MMP drives a combinatorial proteolytic program in activated endothelial cells. FASEB J. 2012;26(11):4481-94. doi:10.1096/fj.12-205906.
M
Marti-Renom MA, Pieper U, Madhusudhan MS, et al. DBAli tools: mining the protein structure space. Nucleic Acids Res. 2007;35(Web Server issue):W393-7. doi:10.1093/nar/gkm236.
Martorell-Marugán J, López-Domínguez R, García-Moreno A, et al. A comprehensive database for integrated analysis of omics data in autoimmune diseases. BMC Bioinformatics. 2021;22(1):343. doi:10.1186/s12859-021-04268-4.
Menden MP, Wang D, Mason MJ, et al. Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen. Nat Commun. 2019;10(1):2674. doi:10.1038/s41467-019-09799-2.
Méndez-Salazar EOrlando, Vázquez-Mellado J, Casimiro-Soriguer CS, et al. Taxonomic variations in the gut microbiome of gout patients with and without tophi might have a functional impact on urate metabolism. Mol Med. 2021;27(1):50. doi:10.1186/s10020-021-00311-5.
Mirzayi C, Renson A, Zohra F, et al. Reporting guidelines for human microbiome research: the STORMS checklist. Nat Med. 2021;27(11):1885-1892. doi:10.1038/s41591-021-01552-x.
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.