@article {12695324,
	title = {Comparing bacterial genomes through conservation profiles},
	journal = {Genome Res},
	volume = {13},
	number = {5},
	year = {2003},
	note = {Martin, Maria J Herrero, Javier Mateos, Alvaro Dopazo, Joaquin Comparative Study United States Genome research Genome Res. 2003 May;13(5):991-8. Epub 2003 Apr 14.},
	pages = {991-8},
	abstract = {We constructed two-dimensional representations of profiles of gene conservation across different genomes using the genome of Escherichia coli as a model. These profiles permit both the visualization at the genome level of different traits in the organism studied and, at the same time, reveal features related to the genomes analyzed (such as defective genomes or genomes that lack a particular system). Conserved genes are not uniformly distributed along the E. coli genome but tend to cluster together. The study of gene distribution patterns across genomes is important for the understanding of how sets of genes seem to be dependent on each other, probably having some functional link. This provides additional evidence that can be used for the elucidation of the function of unannotated genes. Clustering these patterns produces families of genes which can be arranged in a hierarchy of closeness. In this way, functions can be defined at different levels of generality depending on the level of the hierarchy that is studied. The combined study of conservation and phenotypic traits opens up the possibility of defining phenotype/genotype associations, and ultimately inferring the gene or genes responsible for a particular trait.},
	keywords = {Bacterial Genotype Models, Bacterial/genetics Cluster Analysis Conserved Sequence/*genetics DNA, Bacterial/genetics Escherichia coli/classification/*genetics Evolution, Bacterial/genetics Gene Order/genetics Genes, Bacterial/genetics/physiology *Genome, Chromosome Mapping/methods Chromosomes, Genetic Phenotype Phylogeny Sequence Homology, Molecular Gene Expression Profiling/methods Gene Expression Regulation, Nucleic Acid Species Specificity Terminology as Topic},
	url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=12695324},
	author = {Martin, M. J. and Herrero, J. and A. Mateos and Dopazo, J.}
}
@article {12645919,
	title = {Combining hierarchical clustering and self-organizing maps for exploratory analysis of gene expression patterns},
	journal = {J Proteome Res},
	volume = {1},
	number = {5},
	year = {2002},
	note = {Herrero, Javier Dopazo, Joaquin Research Support, Non-U.S. Gov{\textquoteright}t United States Journal of proteome research J Proteome Res. 2002 Sep-Oct;1(5):467-70.},
	pages = {467-70},
	abstract = {Self-organizing maps (SOM) constitute an alternative to classical clustering methods because of its linear run times and superior performance to deal with noisy data. Nevertheless, the clustering obtained with SOM is dependent on the relative sizes of the clusters. Here, we show how the combination of SOM with hierarchical clustering methods constitutes an excellent tool for exploratory analysis of massive data like DNA microarray expression patterns.},
	keywords = {Cluster Analysis Computational Biology/methods *Gene Expression Genes, Fungal/genetics *Genome Oligonucleotide Array Sequence Analysis/*methods Statistics as Topic/*methods Time Factors},
	url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=12645919},
	author = {Herrero, J. and Dopazo, J.}
}
