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Journal Article
Torres JSalavert, Espert IBlanquer, Dominguez ATomas, et al. Using GPUs for the Exact Alignment of Short-read Genetic Sequences by Means of the Burrows–Wheeler Transform. IEEE/ACM transactions on computational biology and bioinformatics / IEEE, ACM. 2012;9:1245-1256. doi:10.1109/TCBB.2012.49.
Amadoz A, Sebastián-Leon P, Vidal E, Salavert F, Dopazo J. Using activation status of signaling pathways as mechanism-based biomarkers to predict drug sensitivity. Sci Rep. 2015;5:18494. doi:10.1038/srep18494.
Dopazo J. On the Use of Functional Module Definitions in the Analysis of Genomic Experiments. Molecular and Cellular Toxicology. 2009;5:47-47.
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.
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;29:198-204. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17935148.
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.
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;29:198-204. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17935148.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Razzoli M, Frontini A, Gurney A, et al. Stress-induced activation of brown adipose tissue prevents obesity in conditions of low adaptive thermogenesis. Mol Metab. 2016;5(1):19-33. doi:10.1016/j.molmet.2015.10.005.
Birmingham A, Selfors LM, Forster T, et al. Statistical methods for analysis of high-throughput RNA interference screens. Nature Methods. 2009;6:569 - 575. Available at: http://dx.doi.org/10.1038/nmeth.1351.