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Herrero J, Diaz-Uriarte R, Dopazo J. An approach to inferring transcriptional regulation among genes from large-scale expression data. Comp Funct Genomics. 2003;4:148-54. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18629097.

Martin MJ, Herrero J, Mateos A, Dopazo J. Comparing bacterial genomes through conservation profiles. Genome Res. 2003;13:991-8. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12695324.

Herrero J, Diaz-Uriarte R, Dopazo J. Gene expression data preprocessing. Bioinformatics. 2003;19:655-6. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12651726.

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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.

Tamames J, Clark D, Herrero J, et al. Bioinformatics methods for the analysis of expression arrays: data clustering and information extraction. J Biotechnol. 2002;98:269-83. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12141992.

Herrero J, Dopazo J. Combining hierarchical clustering and self-organizing maps for exploratory analysis of gene expression patterns. J Proteome Res. 2002;1:467-70. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12645919.

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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.

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.

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.

Dopazo J, Mendoza A, Herrero J, et al. Annotated draft genomic sequence from a Streptococcus pneumoniae type 19F clinical isolate. Microb Drug Resist. 2001;7:99-125. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=11442348.

Herrero J, Valencia A, Dopazo J. A hierarchical unsupervised growing neural network for clustering gene expression patterns. Bioinformatics. 2001;17:126-36. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=11238068.