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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.
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.
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(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.
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.
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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.
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.
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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.
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.
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.
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.
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.
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.
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.