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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.
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.
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 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.
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.
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.
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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.
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.
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.
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.
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.
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.
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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.
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.
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.
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.
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.