@article {1225,
	title = {The pan-cancer pathological regulatory landscape.},
	journal = {Scientific reports},
	volume = {6},
	year = {2016},
	month = {2016 Dec 21},
	pages = {39709},
	abstract = {Dysregulation of the normal gene expression program is the cause of a broad range of diseases, including cancer. Detecting the specific perturbed regulators that have an effect on the generation and the development of the disease is crucial for understanding the disease mechanism and for taking decisions on efficient preventive and curative therapies. Moreover, detecting such perturbations at the patient level is even more important from the perspective of personalized medicine. We applied the Transcription Factor Target Enrichment Analysis, a method that detects the activity of transcription factors based on the quantification of the collective transcriptional activation of their targets, to a large collection of 5607 cancer samples covering eleven cancer types. We produced for the first time a comprehensive catalogue of altered transcription factor activities in cancer, a considerable number of them significantly associated to patient{\textquoteright}s survival. Moreover, we described several interesting TFs whose activity do not change substantially in the cancer with respect to the normal tissue but ultimately play an important role in patient prognostic determination, which suggest they might be promising therapeutic targets. An additional advantage of this method is that it allows obtaining personalized TF activity estimations for individual patients.},
	issn = {2045-2322},
	doi = {10.1038/srep39709},
	url = {http://www.nature.com/articles/srep39709},
	author = {Falco, Matias M and Bleda, Marta and Carbonell-Caballero, Jos{\'e} and Joaqu{\'\i}n Dopazo}
}
@article {1149,
	title = {A Parallel and Sensitive Software Tool for Methylation Analysis on Multicore Platforms.},
	journal = {Bioinformatics (Oxford, England)},
	volume = {31},
	number = {19},
	year = {2015},
	month = {2015 Jun 10},
	pages = {3130-3138},
	abstract = {MOTIVATION: DNA methylation analysis suffers from very long processing time, since the advent of Next-Generation Sequencers (NGS) has shifted the bottleneck of genomic studies from the sequencers that obtain the DNA samples to the software that performs the analysis of these samples. The existing software for methylation analysis does not seem to scale efficiently neither with the size of the dataset nor with the length of the reads to be analyzed. Since it is expected that the sequencers will provide longer and longer reads in the near future, efficient and scalable methylation software should be developed. RESULTS: We present a new software tool, called HPG-Methyl, which efficiently maps bisulfite sequencing reads on DNA, analyzing DNA methylation. The strategy used by this software consists of leveraging the speed of the Burrows-Wheeler Transform to map a large number of DNA fragments (reads) rapidly, as well as the accuracy of the Smith-Waterman algorithm, which is exclusively employed to deal with the most ambiguous and shortest reads. Experimental results on platforms with Intel multicore processors show that HPGMethyl significantly outperforms in both execution time and sensitivity state-of-the-art software such as Bismark, BS-Seeker or BSMAP, particularly for long bisulfite reads. AVAILABILITY: Software in the form of C libraries and functions, together with instructions to compile and execute this software. Available by sftp to anonymous@clariano.uv.es (password "anonymous"). CONTACT: Juan.Orduna@uv.es.},
	keywords = {BS-seq, HPC, methylation, NGS},
	issn = {1367-4811},
	doi = {10.1093/bioinformatics/btv357},
	url = {http://bioinformatics.oxfordjournals.org/content/31/19/3130.long},
	author = {T{\'a}rraga, Joaqu{\'\i}n and P{\'e}rez, Mariano and Ordu{\~n}a, Juan M and Duato, Jos{\'e} and Medina, Ignacio and Joaqu{\'\i}n Dopazo}
}
@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}
}
@article {21098431,
	title = {Paintomics: a web based tool for the joint visualization of transcriptomics and metabolomics data.},
	journal = {Bioinformatics (Oxford, England)},
	volume = {27},
	year = {2011},
	month = {2011 Jan 1},
	pages = {137-9},
	abstract = {<p>The development of the omics technologies such as transcriptomics, proteomics and metabolomics has made possible the realization of systems biology studies where biological systems are interrogated at different levels of biochemical activity (gene expression, protein activity and/or metabolite concentration). An effective approach to the analysis of these complex datasets is the joined visualization of the disparate biomolecular data on the framework of known biological pathways.</p>},
	author = {Garc{\'\i}a-Alcalde, Fernando and Garc{\'\i}a-L{\'o}pez, Federico and Joaqu{\'\i}n Dopazo and Ana Conesa}
}
@article {21605378,
	title = {Profiling the venom gland transcriptomes of Costa Rican snakes by 454 pyrosequencing.},
	journal = {BMC genomics},
	volume = {12},
	year = {2011},
	month = {2011},
	pages = {259},
	abstract = {<p>A long term research goal of venomics, of applied importance for improving current antivenom therapy, but also for drug discovery, is to understand the pharmacological potential of venoms. Individually or combined, proteomic and transcriptomic studies have demonstrated their feasibility to explore in depth the molecular diversity of venoms. In the absence of genome sequence, transcriptomes represent also valuable searchable databases for proteomic projects.</p>},
	author = {Durban, Jordi and Ju{\'a}rez, Paula and Angulo, Yamileth and Lomonte, Bruno and Flores-Diaz, Marietta and Alape-Gir{\'o}n, Alberto and Sasa, Mahmood and Sanz, Libia and Guti{\'e}rrez, Jos{\'e} M and Joaqu{\'\i}n Dopazo and Ana Conesa and Calvete, Juan J}
}
