Publications

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A
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.
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.
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.
Azuaje F, Dopazo J. Data analysis and visualisation in genomics and proteomics. In: Wiley, F. Azuaje and J. Dopazo; 2005.
Azuaje F, Dopazo J, Wang H. Data and Predictive Model Integration: an Overview of Key Concepts, Problems and Solutions. In: Data analysis and visualisation in genomics and proteomics. Data analysis and visualisation in genomics and proteomics. Wiley, F. Azuaje and J. Dopazo; 2005.
Azuaje F, Dopazo J. Integrative Data Analysis and Visualization: Introduction to Critical Problems, Goals and Challenges. In: Data analysis and visualisation in genomics and proteomics. Data analysis and visualisation in genomics and proteomics. Wiley, F. Azuaje and J. Dopazo; 2005:3-9.
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Capriotti E, Marti-Renom MA. Assessment of protein structure predictions. In: Computational Structural Biology. Computational Structural Biology. New Jersey, USA: World Scientific Publishing Company; 2008. Available at: http://www.amazon.com/dp/9812778772/.
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.
D
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.
Dopazo H. La clasificación de los organismos. In: Invitación a la Biología. Invitación a la Biología. Buenos Aires: Curtis, Barnes, Schnek & Flores. 2da, Editorial Medica Panamericana; 2006.
Dopazo J. Microarray Data Processing And Analysis. In: Microarray data analysis II. Microarray data analysis II. Kluwer Academic; 2002:43-63.
Dopazo J. Functional profiling methods in cancer. In: Grützmann R, Pilarsky C, eds. Methods in molecular biology (Clifton, N.J.).Vol 576. Methods in molecular biology (Clifton, N.J.).; 2010:363-74.
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.
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 J. Clustering - Class discovery in the post-genomic era. In: Fundamentals of data mining in genomics and proteomics. Fundamentals of data mining in genomics and proteomics. New York, USA: Springer-Verlag, W. Dubitzky, M. Granzow and D.P. Berrar; 2007.
Dopazo J, Al-Shahrour F. Functional annotation of microarray experiments. In: Microarray Technology Through Applications. Microarray Technology Through Applications. New York, USA: Taylor & Francis, F. Falciani; 2007.
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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.
Gabaldón T. Comparative genomics-based prediction of protein function. In: Methods in Molecular Biology.Vol 439. Methods in Molecular Biology. M. Starkey and R. Elaswarapu, Humana press; 2008. Available at: http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-188-8_26.
Gabaldón T, Gil R, Peretó J, Latorre A, Moya A. The core of a minimal gene set: insights from natural reduced genomes. In: Protocells: Bridging nonliving and living matter. Protocells: Bridging nonliving and living matter. USA: The MIT Press; 2008:347-366.
Garcia-Garcia F, Montaner D. Docencia en Estadística: Experiencias de Innovación. In: III Jornadas de Intercambio de Experiencias de Innovación Educativa en Estadística.Vol 1. III Jornadas de Intercambio de Experiencias de Innovación Educativa en Estadística.; 2013:201-210.
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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.
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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/.
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.
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.
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.