Publications

Export 493 results:
Author Title [ Type(Asc)] Year
Journal Article
Marti-Renom MA, Madhusudhan MS, Sali A. Alignment of protein sequences by their profiles. Protein Sci. 2004;13:1071-87. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15044736.
Madhusudhan MS, Webb BM, Marti-Renom MA, Eswar N, Sali A. Alignment of multiple protein structures based on sequence and structure features. Protein engineering, design & selection : PEDS. 2009;22:569-74.
Iglesias JManuel, Leis O, Ruiz EPérez, et al. The Activation of the Sox2 RR2 Pluripotency Transcriptional Reporter in Human Breast Cancer Cell Lines is Dynamic and Labels Cells with Higher Tumorigenic Potential. Front Oncol. 2014;4:308. doi:10.3389/fonc.2014.00308.
Salavert F, Hidago MR, Amadoz A, et al. Actionable pathways: interactive discovery of therapeutic targets using signaling pathway models. Nucleic acids research. 2016. doi:10.1093/nar/gkw369.
Melo F, Marti-Renom MA. Accuracy of sequence alignment and fold assessment using reduced amino acid alphabets. Proteins. 2006;63:986-95. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16506243.
Tárraga J, Arnau V, Martinez H, et al. Acceleration of short and long DNA read mapping without loss of accuracy using suffix array. Bioinformatics (Oxford, England). 2014;30:3396-3398. doi:10.1093/bioinformatics/btu553.
Dopazo J, Amadoz A, Bleda M, et al. 267 Spanish exomes reveal population-specific differences in disease-related genetic variation. Molecular biology and evolution. 2016. doi:10.1093/molbev/msw005.
Golubnitschaja O, Topolcan O, Kucera R, Costigliola V. 10th Anniversary of the European Association for Predictive, Preventive and Personalised (3P) Medicine - EPMA World Congress Supplement 2020. EPMA J. 2020:1-133. doi:10.1007/s13167-020-00206-1.
Conference Paper
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.
Silbiger V, Luchessi A, Hirata R, et al. Peripheral blood cells transcriptome to study new biomarkers for myocardial infarction follow up. In: ; 2009.
Gonzalez CY, Bleda M, Salavert F, Sánchez R, Dopazo J, Medina I. Multicore and Cloud-based Solutions for Genomic Variant Analysis. In: Proceedings of the 18th International Conference on Parallel Processing Workshops. Proceedings of the 18th International Conference on Parallel Processing Workshops. Berlin, Heidelberg: Springer-Verlag; 2013. doi:10.1007/978-3-642-36949-0_30.
Book Chapter
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.
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.
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.
Mateos A, Herrero J, Tamames J, Dopazo J. Supervised Neural Networks For Clustering Conditions In DNA Array Data After Reducing Noise By Clustering Gene Expression Profiles. In: Microarray data analysis II. Microarray data analysis II. Kluwer Academic; 2002:91-103.
Marti-Renom MA, Capriotti E, Shindyalov I, Bourne P. Structural Comparison and Alignment. In: Structural Bioinformatics. 2ndnd ed. Structural Bioinformatics. New Jersey. USA: Wiley-Blackwell; 2009. Available at: http://www.amazon.com/gp/product/0470181052/.
Dopazo H. Selective Constraints on Human Disease Mutations and Polymorphisms. In: Handbook of Human Molecular Evolution. Handbook of Human Molecular Evolution. UK: Hildegard Kehrer-Sawatzki & David N. Cooper. John Wiley & Sons, Ltd; 2008. Available at: http://eu.wiley.com/WileyCDA/WileyTitle/productCd-0470517468,descCd-description.html.
Dopazo H. Selective Constraints and Human Disease Genes: Evolutionary and Bioinformatic Approaches. In: Encyclopedia of Life Science. Encyclopedia of Life Science. UK: John Wiley & Sons, Ltd.; 2008. doi:10.1002/9780470015902.a0020762.
Antón J, Peña A, Valens M, et al. Salinibacter ruber: genomics and biogeography. In: Adaptation to life in high salt concentrations in Archaea, Bacteria and Eukarya.Vol 9. Adaptation to life in high salt concentrations in Archaea, Bacteria and Eukarya. Dordrecht, Netherlands: Nina Gunde-Cimerman, Ana Plemenitas, and Aharon Oren. Kluwer Academic Publishers; 2005:257-266.
Huynen MA, Snel B, T G. Reliable and specific protein function prediction by combining homology with genomic(s) context. In: Discovery of biomolecular mechanisms with theoretical data analyses. Discovery of biomolecular mechanisms with theoretical data analyses. F. Eisenhaber, Landes Bioscience; 2006. Available at: http://www.landesbioscience.com/iu/output.php?id=479.
Gabaldón T, Huynen MA. Reconstruction of ancestral proteomes. In: Ancestral Sequence Reconstruction. Ancestral Sequence Reconstruction. Oxford: D. Liberles; 2007. Available at: http://www.us.oup.com/us/catalog/general/subject/LifeSciences/EvolutionaryBiology/?view=usa&ci=9780199299188.
Minguez P, Dopazo J. Protein Interactions for Functional Genomics. In: Li X-L, Ng S-K, eds. Biological Data Mining in Protein Interaction Networks. Biological Data Mining in Protein Interaction Networks. Hershey, USA: Idea Group Inc (IGI); 2009:223-238. Available at: http://books.google.es/books?id=pNyCy5GsqtkC.
Al-Shahrour F, Dopazo J. Ontologies and functional genomics. In: Data analysis and visualisation in genomics and proteomics. Data analysis and visualisation in genomics and proteomics. Wiley, F. Azuaje and J. Dopazo; 2005:99-102.
Montaner D, Al-Shahrour F, Dopazo J. New Trends in the Analysis of Functional Genomic Data. In: Progress in Industrial Mathematics at ECMI 2006.Vol 12. Progress in Industrial Mathematics at ECMI 2006. Berlin: Springer; 2007:576-580. doi:10.1007/978-3-540-71992-2_94.
Conesa A, Forment J, Gadea J, van Dijk J. Microarray Technology in Agricultural Research. In: Microarray Technology Through Applications. Microarray Technology Through Applications. F. Falciani. Publisher: Taylor and Francis Group; 2007:173-209.