Publications

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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.
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.
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.
Dopazo J. On the Use of Functional Module Definitions in the Analysis of Genomic Experiments. Molecular and Cellular Toxicology. 2009;5:47-47.
Díaz-Uriarte R, Al-Shahrour F, Dopazo J. Use of GO Terms to Understand the Biological Significance of Microarray Differential Gene Expression Data. In: Microarray data analysis III. Microarray data analysis III. Kluwer Academic, K. F. Johnson and S. M. Lin; 2003:233-247.
Iverson GM, Reddel S, Victoria EJ, et al. Use of single point mutations in domain I of beta 2-glycoprotein I to determine fine antigenic specificity of antiphospholipid autoantibodies. J Immunol. 2002;169:7097-103. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12471146.
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.
Al-Shahrour F, Herrero J, Mateos A, Santoyo J, Díaz-Uriarte R, Dopazo J. Using Gene Ontology on genome-scale studies to find significant associations of biologically relevant terms to group of genes. In: Neural Networks for Signal Processing XIII. Neural Networks for Signal Processing XIII. New York, USA: IEEE Press; 2003:43-52.
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.
Torres JS, Espert IB, Dominguez AT, 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. 2012;9(4):1245 - 1256. doi:10.1109/TCBB.2012.49.
Torres JSalavert, Espert IBlanquer, Domínguez ATomás, et al. Using GPUs for the exact alignment of short-read genetic sequences by means of the Burrows-Wheeler transform. IEEE/ACM Trans Comput Biol Bioinform. 2012;9(4):1245-56. doi:10.1109/TCBB.2012.49.
Peña-Chilet M, Esteban-Medina M, Falco MM, et al. Using mechanistic models for the clinical interpretation of complex genomic variation. Scientific Reports. 2019;9(1). doi:10.1038/s41598-019-55454-7.
Mateos A, Herrero J, Dopazo J. Using perceptrons for supervised classification of DNA microarray samples: obtaining the optimal level of information and finding differentially expressed genes. In: ICANN 2002, LNCS 2415. ICANN 2002, LNCS 2415. J.R. Dorronsoro; 2002:577-582.