Publications

Export 504 results:
Author Title [ Type(Asc)] Year
Journal Article
Heyn H, Vidal E, Sayols S, et al. Whole-genome bisulfite DNA sequencing of a DNMT3B mutant patient. Epigenetics. 2012;7(6):542-50. doi:10.4161/epi.20523.
Avila-Fernandez A, Perez-Carro R, Corton M, et al. Whole-exome sequencing reveals ZNF408 as a new gene associated with autosomal recessive retinitis pigmentosa with vitreal alterations. Hum Mol Genet. 2015;24(14):4037-48. doi:10.1093/hmg/ddv140.
Méndez-Vidal C, del Pozo MGonzález-, Vela-Boza A, et al. Whole-exome sequencing identifies novel compound heterozygous mutations in USH2A in Spanish patients with autosomal recessive retinitis pigmentosa. Molecular vision. 2013;19:2187-95. Available at: http://www.molvis.org/molvis/v19/2187/.
Avila-Fernandez A, Perez-Carro R, Corton M, et al. Whole Exome Sequencing Reveals ZNF408 as a New Gene Associated With Autosomal Recessive Retinitis Pigmentosa with Vitreal Alterations. Human molecular genetics. 2015;24:4037-4048. doi:10.1093/hmg/ddv140.
Lucariello M, Vidal E, Vidal S, et al. Whole exome sequencing of Rett syndrome-like patients reveals the mutational diversity of the clinical phenotype. Hum Genet. 2016;135(12):1343-1354. doi:10.1007/s00439-016-1721-3.
Gui H, Schriemer D, Cheng WW, et al. Whole exome sequencing coupled with unbiased functional analysis reveals new Hirschsprung disease genes. Genome Biology. 2017;18(1). doi:10.1186/s13059-017-1174-6.
Gui H, Schriemer D, Cheng WW, et al. Whole exome sequencing coupled with unbiased functional analysis reveals new Hirschsprung disease genes. Genome biology. 2017;18:48. doi:10.1186/s13059-017-1174-6.
Salavert F, García-Alonso L, Sánchez R, et al. Web-based network analysis and visualization using CellMaps. Bioinformatics. 2016;32(19):3041-3. doi:10.1093/bioinformatics/btw332.
Alemán A, Garcia-Garcia F, Salavert F, Medina I, Dopazo J. A web-based interactive framework to assist in the prioritization of disease candidate genes in whole-exome sequencing studies. Nucleic acids research. 2014;42:W88-W93. doi:10.1093/nar/gku407.
Alemán A, Garcia-Garcia F, Medina I, Dopazo J. A web tool for the design and management of panels of genes for targeted enrichment and massive sequencing for clinical applications. Nucleic acids research. 2014;42:W83-W87. doi:10.1093/nar/gku472.
Gawron P, Hoksza D, Piñero J, et al. Visualization of automatically combined disease maps and pathway diagrams for rare diseases. Front Bioinform. 2023;3:1101505. doi:10.3389/fbinf.2023.1101505.
Juanes JM, Gallego A, Tárraga J, et al. VISMapper: ultra-fast exhaustive cartography of viral insertion sites for gene therapy. BMC Bioinformatics. 2017;18(1):421. doi:10.1186/s12859-017-1837-z.
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.
Huynen MA, Gabaldón T, Snel B. Variation and evolution of biomolecular systems: searching for functional relevance. FEBS Lett. 2005;579:1839-45. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15763561.
Medina I, De Maria A, Bleda M, et al. VARIANT: Command Line, Web service and Web interface for fast and accurate functional characterization of variants found by Next-Generation Sequencing. Nucleic Acids Res. 2012;40(Web Server issue):W54-8. doi:10.1093/nar/gks572.
Madhusudhan MS, Marti-Renom MA, Sanchez R, Sali A. Variable gap penalty for protein sequence-structure alignment. Protein Eng Des Sel. 2006;19:129-33. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16423846.
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.
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.
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.
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.
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.
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.