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.

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.

Robledo M, González-Neira A, Dopazo J. f single nucleotide polymorphism arrays: Design, tools and applications. In:  Microarray Technology Through Applications. Microarray Technology Through Applications. New York, USA: Taylor & Francis, F. Falciani; 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.

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.

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.

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.

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.

Wang H, Azuaje F, Bodenreider O, Dopazo J. Gene expression Correlation and Gene Ontology-Based Similarity: An Assessment of Quantitative Relationship. In:  IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology.; 2004:25-31.

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.

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.

Dopazo J. Microarray Data Processing And Analysis. In:  Microarray data analysis II. Microarray data analysis II. Kluwer Academic; 2002:43-63.

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.