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Mateos A, Herrero J, Tamames J, Dopazo J. Supervised Neural Networks For Clustering Conditions In DNA Array Data After Reducing Noise By Clustering Gene Expression Profiles. In: Microarray data analysis II. Microarray data analysis II. Kluwer Academic; 2002:91-103.
Cuenca-Bono B, García-Molinero V, Pascual-García P, et al. SUS1 introns are required for efficient mRNA nuclear export in yeast. Nucleic acids research. 2011;39:8599-611.
Mateos A, Dopazo J, Jansen R, Tu Y, Gerstein M, Stolovitzky G. Systematic learning of gene functional classes from DNA array expression data by using multilayer perceptrons. Genome Res. 2002;12:1703-15. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12421757.
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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.
Calzada D, Aguerri M, Baos S, et al. Therapeutic targets for olive pollen allergy defined by gene markers modulated by Ole e 1-derived peptides. Molecular immunology. 2015;64:252-61. doi:10.1016/j.molimm.2014.12.002.
Baù D, Sanyal A, Lajoie BR, et al. The three-dimensional folding of the α-globin gene domain reveals formation of chromatin globules. Nature structural & molecular biology. 2011;18:107-14.
Agudo M, Perez-Marin MC, Lonngren U, et al. Time course profiling of the retinal transcriptome after optic nerve transection and optic nerve crush. Mol Vis. 2008;14:1050-63. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18552980.
Eswar N, John B, Mirkovic N, et al. Tools for comparative protein structure modeling and analysis. Nucleic Acids Res. 2003;31:3375-80. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12824331.
Casimiro-Soriguer CS, Loucera C, Peña-Chilet M, Dopazo J. Towards a metagenomics machine learning interpretable model for understanding the transition from adenoma to colorectal cancer. Sci Rep. 2022;12(1):450. doi:10.1038/s41598-021-04182-y.
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.
Gabaldón T, Rainey D, Huynen MA. Tracing the evolution of a large protein complex in the eukaryotes, NADH:ubiquinone oxidoreductase (Complex I). J Mol Biol. 2005;348:857-70. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15843018.
Hoogerwerf WA, Sinha M, Conesa A, et al. Transcriptional profiling of mRNA expression in the mouse distal colon. Gastroenterology. 2008;135:2019-29. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18848557.
Gandia M, Conesa A, Ancillo G, et al. Transcriptional response of Citrus aurantifolia to infection by Citrus tristeza virus. Virology. 2007;367:298-306. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17617431.
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.
Oppert B, Dowd SE, Bouffard P, et al. Transcriptome profiling of the intoxication response of Tenebrio molitor larvae to Bacillus thuringiensis Cry3Aa protoxin. PloS one. 2012;7:e34624. doi:10.1371/journal.pone.0034624.
León C, Garcia-Garcia F, Llames S, et al. Transcriptomic Analysis of a Diabetic Skin-Humanized Mouse Model Dissects Molecular Pathways Underlying the Delayed Wound Healing Response. Genes (Basel). 2020;12(1). doi:10.3390/genes12010047.
Hillung J, Garcia-Garcia F, Dopazo J, Cuevas JM, Elena SF. The transcriptomics of an experimentally evolved plant-virus interaction. Sci Rep. 2016;6:24901. doi:10.1038/srep24901.
Carcel-Trullols J, Aguilar-Gallardo C, García-Alcalde F, et al. Transdifferentiation of MALME-3M and MCF-7 Cells toward Adipocyte-like Cells is Dependent on Clathrin-mediated Endocytosis. SpringerPlus. 2012;1:44. doi:10.1186/2193-1801-1-44.
Haibe-Kains B, Adam GAlexandru, Hosny A, et al. Transparency and reproducibility in artificial intelligence. Nature. 2020;586(7829):E14-E16. doi:10.1038/s41586-020-2766-y.
García-Cazorla A, Oyarzabal A, Fort J, et al. Two novel mutations in the BCKDK (branched-chain keto-acid dehydrogenase kinase) gene are responsible for a neurobehavioral deficit in two pediatric unrelated patients. Hum Mutat. 2014;35(4):470-7. doi:10.1002/humu.22513.
García-Cazorla A, Oyarzabal A, Fort J, et al. Two Novel Mutations in the BCKDK Gene (Branched-Chain Keto-Acid Dehydrogenase Kinase) are Responsible of a Neurobehavioral Deficit in two Pediatric Unrelated Patients. Human mutation. 2014;35:470-7. doi:10.1002/humu.22513.
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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.
Zhang Z, Hernandez K, Savage J, et al. Uniform genomic data analysis in the NCI Genomic Data CommonsAbstract. Nature Communications. 2021;12(1). doi:10.1038/s41467-021-21254-9.
Conde L, Mateos A, Herrero J, Dopazo J. Unsupervised reduction of the dimensionality followed by supervised learning with a perceptron improves the classification of conditions in DNA microarray gene expression data. In: Neural Networks for Signal Processing XII. 2002 IEEE Signal Processing Society WorkshopProceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing. Neural Networks for Signal Processing XII. 2002 IEEE Signal Processing Society WorkshopProceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing. Martigny, Switzerland: IEEE; 2002. doi:10.1109/NNSP.2002.1030019.