@article {920,
	title = {A map of human microRNA variation uncovers unexpectedly high levels of variability.},
	journal = {Genome medicine},
	volume = {4},
	year = {2012},
	month = {2012 Aug 20},
	pages = {62},
	abstract = {ABSTRACT: BACKGROUND: MicroRNAs (miRNAs) are key components of the gene regulatory network in many species. During the past few years, these regulatory elements have been shown to be involved in an increasing number and range of diseases. Consequently, the compilation of a comprehensive map of natural variability in healthy population seems an obvious requirement for future research on miRNA-related pathologies. METHODS: Data on 14 populations from the 1000 Genomes Project were analysed, along with new data extracted from 60 exomes of healthy individuals from a southern Spain population, sequenced in the context of the Medical Genome Project, to derive an accurate map of miRNA variability. RESULTS: Despite the common belief that miRNAs are highly conserved elements, analysis of the sequences of the 1,152 individuals indicated that the observed level of variability is double what was expected. A total of 527 variants were found. Among these, 45 variants affected the recognition region of the corresponding miRNA and were found in 43 different miRNAs, 26 of which are known to be involved in 57 diseases. Different parts of the mature structure of the miRNA were affected to different degrees by variants, which suggests the existence of a selective pressure related to the relative functional impact of the change. Moreover, 41 variants showed a significant deviation from the Hardy-Weinberg equilibrium, which supports the existence of a selective process against some alleles. The average number of variants per individual in miRNAs was 28. CONCLUSIONS: Despite an expectation that miRNAs would be highly conserved genomic elements, our study reports a level of variability comparable to that observed for coding genes.},
	keywords = {NGS},
	issn = {1756-994X},
	doi = {10.1186/gm363},
	url = {http://genomemedicine.com/content/4/8/62/abstract},
	author = {Carbonell, Jos{\'e} and Alloza, Eva and Arce, Pablo and Borrego, Salud and Santoyo, Javier and Ruiz-Ferrer, Macarena and Medina, Ignacio and Jim{\'e}nez-Almaz{\'a}n, Jorge and M{\'e}ndez-Vidal, Cristina and Gonz{\'a}lez-del Pozo, Mar{\'\i}a and Vela, Alicia and Bhattacharya, Shomi S and Anti{\v n}olo, Guillermo and Dopazo, Joaquin}
}
@article {593,
	title = {GEPAS, a web-based tool for microarray data analysis and interpretation.},
	journal = {Nucleic Acids Res},
	volume = {36},
	year = {2008},
	month = {2008 Jul 01},
	pages = {W308-14},
	abstract = {<p>Gene Expression Profile Analysis Suite (GEPAS) is one of the most complete and extensively used web-based packages for microarray data analysis. During its more than 5 years of activity it has continuously been updated to keep pace with the state-of-the-art in the changing microarray data analysis arena. GEPAS offers diverse analysis options that include well established as well as novel algorithms for normalization, gene selection, class prediction, clustering and functional profiling of the experiment. New options for time-course (or dose-response) experiments, microarray-based class prediction, new clustering methods and new tests for differential expression have been included. The new pipeliner module allows automating the execution of sequential analysis steps by means of a simple but powerful graphic interface. An extensive re-engineering of GEPAS has been carried out which includes the use of web services and Web 2.0 technology features, a new user interface with persistent sessions and a new extended database of gene identifiers. GEPAS is nowadays the most quoted web tool in its field and it is extensively used by researchers of many countries and its records indicate an average usage rate of 500 experiments per day. GEPAS, is available at http://www.gepas.org.</p>},
	keywords = {Computer Graphics, Dose-Response Relationship, Drug, Gene Expression Profiling, Internet, Kinetics, Oligonucleotide Array Sequence Analysis, Software},
	issn = {1362-4962},
	doi = {10.1093/nar/gkn303},
	author = {T{\'a}rraga, Joaqu{\'\i}n and Medina, Ignacio and Carbonell, Jos{\'e} and Huerta-Cepas, Jaime and Minguez, Pablo and Alloza, Eva and Al-Shahrour, F{\'a}tima and Vegas-Azc{\'a}rate, Susana and Goetz, Stefan and Escobar, Pablo and Garcia-Garcia, Francisco and Conesa, Ana and Montaner, David and Dopazo, Joaquin}
}
@article {605,
	title = {FatiGO +: a functional profiling tool for genomic data. Integration of functional annotation, regulatory motifs and interaction data with microarray experiments.},
	journal = {Nucleic Acids Res},
	volume = {35},
	year = {2007},
	month = {2007 Jul},
	pages = {W91-6},
	abstract = {<p>The ultimate goal of any genome-scale experiment is to provide a functional interpretation of the data, relating the available information with the hypotheses that originated the experiment. Thus, functional profiling methods have become essential in diverse scenarios such as microarray experiments, proteomics, etc. We present the FatiGO+, a web-based tool for the functional profiling of genome-scale experiments, specially oriented to the interpretation of microarray experiments. In addition to different functional annotations (gene ontology, KEGG pathways, Interpro motifs, Swissprot keywords and text-mining based bioentities related to diseases and chemical compounds) FatiGO+ includes, as a novelty, regulatory and structural information. The regulatory information used includes predictions of targets for distinct regulatory elements (obtained from the Transfac and CisRed databases). Additionally FatiGO+ uses predictions of target motifs of miRNA to infer which of these can be activated or deactivated in the sample of genes studied. Finally, properties of gene products related to their relative location and connections in the interactome have also been used. Also, enrichment of any of these functional terms can be directly analysed on chromosomal coordinates. FatiGO+ can be found at: http://www.fatigoplus.org and within the Babelomics environment http://www.babelomics.org.</p>},
	keywords = {Amino Acid Motifs, Animals, Binding Sites, Computational Biology, Gene Expression Profiling, Genes, Genomics, Humans, Internet, Oligonucleotide Array Sequence Analysis, Programming Languages, Software, Systems Integration, Transcription Factors},
	issn = {1362-4962},
	doi = {10.1093/nar/gkm260},
	author = {Al-Shahrour, F{\'a}tima and Minguez, Pablo and T{\'a}rraga, Joaqu{\'\i}n and Medina, Ignacio and Alloza, Eva and Montaner, David and Dopazo, Joaquin}
}
