@article {1129,
	title = {Babelomics 5.0: functional interpretation for new generations of genomic data.},
	journal = {Nucleic acids research},
	volume = {43},
	number = {W1},
	year = {2015},
	month = {2015 Apr 20},
	pages = {W117-W121},
	abstract = {Babelomics has been running for more than one decade offering a user-friendly interface for the functional analysis of gene expression and genomic data. Here we present its fifth release, which includes support for Next Generation Sequencing data including gene expression (RNA-seq), exome or genome resequencing. Babelomics has simplified its interface, being now more intuitive. Improved visualization options, such as a genome viewer as well as an interactive network viewer, have been implemented. New technical enhancements at both, client and server sides, makes the user experience faster and more dynamic. Babelomics offers user-friendly access to a full range of methods that cover: (i) primary data analysis, (ii) a variety of tests for different experimental designs and (iii) different enrichment and network analysis algorithms for the interpretation of the results of such tests in the proper functional context. In addition to the public server, local copies of Babelomics can be downloaded and installed. Babelomics is freely available at: http://www.babelomics.org.},
	keywords = {babelomics, data integration, gene set analysis, interactome, network analysis, NGS, RNA-seq, Systems biology, transcriptomics},
	issn = {1362-4962},
	doi = {10.1093/nar/gkv384},
	url = {http://nar.oxfordjournals.org/content/43/W1/W117},
	author = {Alonso, Roberto and Salavert, Francisco and Garcia-Garcia, Francisco and Carbonell-Caballero, Jos{\'e} and Bleda, Marta and Garc{\'\i}a-Alonso, Luz and Sanchis-Juan, Alba and Perez-Gil, Daniel and Marin-Garcia, Pablo and S{\'a}nchez, Rub{\'e}n and Cubuk, Cankut and Hidalgo, Marta R and Amadoz, Alicia and Hernansaiz-Ballesteros, Rosa D and Alem{\'a}n, Alejandro and T{\'a}rraga, Joaqu{\'\i}n and Montaner, David and Medina, Ignacio and Dopazo, Joaquin}
}
@article {1005,
	title = {Genomics and transcriptomics in drug discovery.},
	journal = {Drug discovery today},
	volume = {19},
	number = {2},
	year = {2014},
	month = {2013 Jun 14},
	pages = {126-32},
	abstract = {The popularization of genomic high-throughput technologies is causing a revolution in biomedical research and, particularly, is transforming the field of drug discovery. Systems biology offers a framework to understand the extensive human genetic heterogeneity revealed by genomic sequencing in the context of the network of functional, regulatory and physical protein-drug interactions. Thus, approaches to find biomarkers and therapeutic targets will have to take into account the complex system nature of the relationships of the proteins with the disease. Pharmaceutical companies will have to reorient their drug discovery strategies considering the human genetic heterogeneity. Consequently, modeling and computational data analysis will have an increasingly important role in drug discovery.},
	keywords = {adverse effects, Drug discovery, drug repositioning, metagenomics, modeling, network analysis, pathway analysis},
	issn = {1878-5832},
	doi = {10.1016/j.drudis.2013.06.003},
	url = {http://www.ncbi.nlm.nih.gov/pubmed/23773860},
	author = {Dopazo, Joaquin}
}
@article {1033,
	title = {Pathways systematically associated to Hirschsprung{\textquoteright}s disease.},
	journal = {Orphanet journal of rare diseases},
	volume = {8},
	year = {2013},
	month = {2013 Dec 2},
	pages = {187},
	abstract = {Despite it has been reported that several loci are involved in Hirschsprung{\textquoteright}s disease, the molecular basis of the disease remains yet essentially unknown. The study of collective properties of modules of functionally-related genes provides an efficient and sensitive statistical framework that can overcome sample size limitations in the study of rare diseases. Here, we present the extension of a previous study of a Spanish series of HSCR trios to an international cohort of 162 HSCR trios to validate the generality of the underlying functional basis of the Hirschsprung{\textquoteright}s disease mechanisms previously found. The Pathway-Based Analysis (PBA) confirms a strong association of gene ontology (GO) modules related to signal transduction and its regulation, enteric nervous system (ENS) formation and other processes related to the disease. In addition, network analysis recovers sub-networks significantly associated to the disease, which contain genes related to the same functionalities, thus providing an independent validation of these findings. The functional profiles of association obtained for patients populations from different countries were compared to each other. While gene associations were different at each series, the main functional associations were identical in all the five populations. These observations would also explain the reported low reproducibility of associations of individual disease genes across populations.},
	keywords = {GWAS, Hirschprung, network analysis, Pathway Based Analysis},
	issn = {1750-1172},
	doi = {10.1186/1750-1172-8-187},
	url = {http://www.ojrd.com/content/8/1/187/abstract},
	author = {Fern{\'a}ndez, Raquel M and Bleda, Marta and Luz{\'o}n-Toro, Berta and Garc{\'\i}a-Alonso, Luz and Arnold, Stacey and Sribudiani, Yunia and Besmond, Claude and Lantieri, Francesca and Doan, Betty and Ceccherini, Isabella and Lyonnet, Stanislas and Hofstra, Robert Mw and Chakravarti, Aravinda and Anti{\v n}olo, Guillermo and Joaqu{\'\i}n Dopazo and Borrego, Salud}
}
