@article {1203,
	title = {Actionable pathways: interactive discovery of therapeutic targets using signaling pathway models.},
	journal = {Nucleic acids research},
	year = {2016},
	month = {2016 May 2},
	abstract = {The discovery of actionable targets is crucial for targeted therapies and is also a constituent part of the drug discovery process. The success of an intervention over a target depends critically on its contribution, within the complex network of gene interactions, to the cellular processes responsible for disease progression or therapeutic response. Here we present PathAct, a web server that predicts the effect that interventions over genes (inhibitions or activations that simulate knock-outs, drug treatments or over-expressions) can have over signal transmission within signaling pathways and, ultimately, over the cell functionalities triggered by them. PathAct implements an advanced graphical interface that provides a unique interactive working environment in which the suitability of potentially actionable genes, that could eventually become drug targets for personalized or individualized therapies, can be easily tested. The PathAct tool can be found at: http://pathact.babelomics.org.},
	keywords = {actionable genes, Disease mechanism, drug action mechanism, Drug discovery, pathway analysis, personalized medicine, signalling, therapeutic targets},
	issn = {1362-4962},
	doi = {10.1093/nar/gkw369},
	url = {http://nar.oxfordjournals.org/content/early/2016/05/02/nar.gkw369.full},
	author = {Salavert, Francisco and Hidago, Marta R and Amadoz, Alicia and Cubuk, Cankut and Medina, Ignacio and Crespo, Daniel and Carbonell-Caballero, Jos{\'e} and Joaqu{\'\i}n Dopazo}
}
@article {1128,
	title = {Assessing the impact of mutations found in next generation sequencing data over human signaling pathways.},
	journal = {Nucleic acids research},
	volume = {43},
	number = {W1},
	year = {2015},
	month = {2015 Apr 16},
	pages = {W270-W275},
	abstract = {Modern sequencing technologies produce increasingly detailed data on genomic variation. However, conventional methods for relating either individual variants or mutated genes to phenotypes present known limitations given the complex, multigenic nature of many diseases or traits. Here we present PATHiVar, a web-based tool that integrates genomic variation data with gene expression tissue information. PATHiVar constitutes a new generation of genomic data analysis methods that allow studying variants found in next generation sequencing experiment in the context of signaling pathways. Simple Boolean models of pathways provide detailed descriptions of the impact of mutations in cell functionality so as, recurrences in functionality failures can easily be related to diseases, even if they are produced by mutations in different genes. Patterns of changes in signal transmission circuits, often unpredictable from individual genes mutated, correspond to patterns of affected functionalities that can be related to complex traits such as disease progression, drug response, etc. PATHiVar is available at: http://pathivar.babelomics.org.},
	keywords = {NGS, pathways, signalling, Systems biology},
	issn = {1362-4962},
	doi = {10.1093/nar/gkv349},
	url = {http://nar.oxfordjournals.org/content/43/W1/W270},
	author = {Hernansaiz-Ballesteros, Rosa D and Salavert, Francisco and Sebasti{\'a}n-Leon, Patricia and Alem{\'a}n, Alejandro and Medina, Ignacio and Joaqu{\'\i}n Dopazo}
}
