TY - JOUR T1 - Differential metabolic activity and discovery of therapeutic targets using summarized metabolic pathway models. JF - NPJ Syst Biol Appl Y1 - 2019 A1 - Cubuk, Cankut A1 - Hidalgo, Marta R A1 - Amadoz, Alicia A1 - Rian, Kinza A1 - Salavert, Francisco A1 - Pujana, Miguel A A1 - Mateo, Francesca A1 - Herranz, Carmen A1 - Carbonell-Caballero, José A1 - Dopazo, Joaquin KW - Computational Biology KW - Computer Simulation KW - Drug discovery KW - Gene Regulatory Networks KW - Humans KW - Internet KW - Metabolic Networks and Pathways KW - Models, Biological KW - Neoplasms KW - Phenotype KW - Software KW - Transcriptome AB -

In spite of the increasing availability of genomic and transcriptomic data, there is still a gap between the detection of perturbations in gene expression and the understanding of their contribution to the molecular mechanisms that ultimately account for the phenotype studied. Alterations in the metabolism are behind the initiation and progression of many diseases, including cancer. The wealth of available knowledge on metabolic processes can therefore be used to derive mechanistic models that link gene expression perturbations to changes in metabolic activity that provide relevant clues on molecular mechanisms of disease and drug modes of action (MoA). In particular, pathway modules, which recapitulate the main aspects of metabolism, are especially suitable for this type of modeling. We present Metabolizer, a web-based application that offers an intuitive, easy-to-use interactive interface to analyze differences in pathway metabolic module activities that can also be used for class prediction and in silico prediction of knock-out (KO) effects. Moreover, Metabolizer can automatically predict the optimal KO intervention for restoring a diseased phenotype. We provide different types of validations of some of the predictions made by Metabolizer. Metabolizer is a web tool that allows understanding molecular mechanisms of disease or the MoA of drugs within the context of the metabolism by using gene expression measurements. In addition, this tool automatically suggests potential therapeutic targets for individualized therapeutic interventions.

VL - 5 U1 - https://www.ncbi.nlm.nih.gov/pubmed/30854222?dopt=Abstract ER - TY - JOUR T1 - High throughput estimation of functional cell activities reveals disease mechanisms and predicts relevant clinical outcomes. JF - Oncotarget Y1 - 2017 A1 - Hidalgo, Marta R A1 - Cubuk, Cankut A1 - Amadoz, Alicia A1 - Salavert, Francisco A1 - Carbonell-Caballero, José A1 - Dopazo, Joaquin KW - Computational Biology KW - gene expression KW - Gene Regulatory Networks KW - Humans KW - mutation KW - Neoplasms KW - Precision Medicine KW - Sequence Analysis, RNA KW - Signal Transduction AB -

Understanding the aspects of the cell functionality that account for disease or drug action mechanisms is a main challenge for precision medicine. Here we propose a new method that models cell signaling using biological knowledge on signal transduction. The method recodes individual gene expression values (and/or gene mutations) into accurate measurements of changes in the activity of signaling circuits, which ultimately constitute high-throughput estimations of cell functionalities caused by gene activity within the pathway. Moreover, such estimations can be obtained either at cohort-level, in case/control comparisons, or personalized for individual patients. The accuracy of the method is demonstrated in an extensive analysis involving 5640 patients from 12 different cancer types. Circuit activity measurements not only have a high diagnostic value but also can be related to relevant disease outcomes such as survival, and can be used to assess therapeutic interventions.

VL - 8 IS - 3 U1 - https://www.ncbi.nlm.nih.gov/pubmed/28042959?dopt=Abstract ER - TY - JOUR T1 - Actionable pathways: interactive discovery of therapeutic targets using signaling pathway models. JF - Nucleic acids research Y1 - 2016 A1 - Salavert, Francisco A1 - Hidago, Marta R A1 - Amadoz, Alicia A1 - Cubuk, Cankut A1 - Medina, Ignacio A1 - Crespo, Daniel A1 - Carbonell-Caballero, José A1 - Joaquín Dopazo KW - actionable genes KW - Disease mechanism KW - drug action mechanism KW - Drug discovery KW - pathway analysis KW - personalized medicine KW - signalling KW - therapeutic targets AB - 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. UR - http://nar.oxfordjournals.org/content/early/2016/05/02/nar.gkw369.full ER - TY - JOUR T1 - Web-based network analysis and visualization using CellMaps. JF - Bioinformatics Y1 - 2016 A1 - Salavert, Francisco A1 - García-Alonso, Luz A1 - Sánchez, Rubén A1 - Alonso, Roberto A1 - Bleda, Marta A1 - Medina, Ignacio A1 - Dopazo, Joaquin KW - Biochemical Phenomena KW - Internet KW - Software AB -

UNLABELLED: : CellMaps is an HTML5 open-source web tool that allows displaying, editing, exploring and analyzing biological networks as well as integrating metadata into them. Computations and analyses are remotely executed in high-end servers, and all the functionalities are available through RESTful web services. CellMaps can easily be integrated in any web page by using an available JavaScript API.

AVAILABILITY AND IMPLEMENTATION: The application is available at: http://cellmaps.babelomics.org/ and the code can be found in: https://github.com/opencb/cell-maps The client is implemented in JavaScript and the server in C and Java.

CONTACT: jdopazo@cipf.es

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

VL - 32 IS - 19 U1 - https://www.ncbi.nlm.nih.gov/pubmed/27296979?dopt=Abstract ER - TY - JOUR T1 - Assessing the impact of mutations found in next generation sequencing data over human signaling pathways. JF - Nucleic acids research Y1 - 2015 A1 - Hernansaiz-Ballesteros, Rosa D A1 - Salavert, Francisco A1 - Sebastián-Leon, Patricia A1 - Alemán, Alejandro A1 - Medina, Ignacio A1 - Joaquín Dopazo KW - NGS KW - pathways KW - signalling KW - Systems biology AB - 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. VL - 43 UR - http://nar.oxfordjournals.org/content/43/W1/W270 ER - TY - JOUR T1 - Babelomics 5.0: functional interpretation for new generations of genomic data. JF - Nucleic acids research Y1 - 2015 A1 - Alonso, Roberto A1 - Salavert, Francisco A1 - Garcia-Garcia, Francisco A1 - Carbonell-Caballero, José A1 - Bleda, Marta A1 - García-Alonso, Luz A1 - Sanchis-Juan, Alba A1 - Perez-Gil, Daniel A1 - Marin-Garcia, Pablo A1 - Sánchez, Rubén A1 - Cubuk, Cankut A1 - Hidalgo, Marta R A1 - Amadoz, Alicia A1 - Hernansaiz-Ballesteros, Rosa D A1 - Alemán, Alejandro A1 - Tárraga, Joaquín A1 - Montaner, David A1 - Medina, Ignacio A1 - Dopazo, Joaquin KW - babelomics KW - data integration KW - gene set analysis KW - interactome KW - network analysis KW - NGS KW - RNA-seq KW - Systems biology KW - transcriptomics AB - 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. VL - 43 UR - http://nar.oxfordjournals.org/content/43/W1/W117 ER - TY - JOUR T1 - Using activation status of signaling pathways as mechanism-based biomarkers to predict drug sensitivity. JF - Sci Rep Y1 - 2015 A1 - Amadoz, Alicia A1 - Sebastián-Leon, Patricia A1 - Vidal, Enrique A1 - Salavert, Francisco A1 - Dopazo, Joaquin KW - Algorithms KW - Antineoplastic Agents KW - biomarkers KW - Cell Line, Tumor KW - Cell Survival KW - gene expression KW - Humans KW - Lethal Dose 50 KW - Neoplasms KW - Phosphorylation KW - Proteins KW - Signal Transduction AB -

Many complex traits, as drug response, are associated with changes in biological pathways rather than being caused by single gene alterations. Here, a predictive framework is presented in which gene expression data are recoded into activity statuses of signal transduction circuits (sub-pathways within signaling pathways that connect receptor proteins to final effector proteins that trigger cell actions). Such activity values are used as features by a prediction algorithm which can efficiently predict a continuous variable such as the IC50 value. The main advantage of this prediction method is that the features selected by the predictor, the signaling circuits, are themselves rich-informative, mechanism-based biomarkers which provide insight into or drug molecular mechanisms of action (MoA).

VL - 5 U1 - https://www.ncbi.nlm.nih.gov/pubmed/26678097?dopt=Abstract ER - TY - JOUR T1 - Understanding disease mechanisms with models of signaling pathway activities. JF - BMC systems biology Y1 - 2014 A1 - Sebastián-Leon, Patricia A1 - Vidal, Enrique A1 - Minguez, Pablo A1 - Ana Conesa A1 - Sonia Tarazona A1 - Amadoz, Alicia A1 - Armero, Carmen A1 - Salavert, Francisco A1 - Vidal-Puig, Antonio A1 - Montaner, David A1 - Joaquín Dopazo KW - Disease mechanism KW - pathway KW - signalling KW - Systems biology AB - BackgroundUnderstanding the aspects of the cell functionality that account for disease or drug action mechanisms is one of the main challenges in the analysis of genomic data and is on the basis of the future implementation of precision medicine.ResultsHere we propose a simple probabilistic model in which signaling pathways are separated into elementary sub-pathways or signal transmission circuits (which ultimately trigger cell functions) and then transforms gene expression measurements into probabilities of activation of such signal transmission circuits. Using this model, differential activation of such circuits between biological conditions can be estimated. Thus, circuit activation statuses can be interpreted as biomarkers that discriminate among the compared conditions. This type of mechanism-based biomarkers accounts for cell functional activities and can easily be associated to disease or drug action mechanisms. The accuracy of the proposed model is demonstrated with simulations and real datasets.ConclusionsThe proposed model provides detailed information that enables the interpretation disease mechanisms as a consequence of the complex combinations of altered gene expression values. Moreover, it offers a framework for suggesting possible ways of therapeutic intervention in a pathologically perturbed system. VL - 8 UR - http://www.biomedcentral.com/1752-0509/8/121/abstract ER - TY - JOUR T1 - A web-based interactive framework to assist in the prioritization of disease candidate genes in whole-exome sequencing studies. JF - Nucleic acids research Y1 - 2014 A1 - Alemán, Alejandro A1 - Garcia-Garcia, Francisco A1 - Salavert, Francisco A1 - Medina, Ignacio A1 - Joaquín Dopazo KW - NGS. prioritization AB - Whole-exome sequencing has become a fundamental tool for the discovery of disease-related genes of familial diseases and the identification of somatic driver variants in cancer. However, finding the causal mutation among the enormous background of individual variability in a small number of samples is still a big challenge. Here we describe a web-based tool, BiERapp, which efficiently helps in the identification of causative variants in family and sporadic genetic diseases. The program reads lists of predicted variants (nucleotide substitutions and indels) in affected individuals or tumor samples and controls. In family studies, different modes of inheritance can easily be defined to filter out variants that do not segregate with the disease along the family. Moreover, BiERapp integrates additional information such as allelic frequencies in the general population and the most popular damaging scores to further narrow down the number of putative variants in successive filtering steps. BiERapp provides an interactive and user-friendly interface that implements the filtering strategy used in the context of a large-scale genomic project carried out by the Spanish Network for Research in Rare Diseases (CIBERER) in which more than 800 exomes have been analyzed. BiERapp is freely available at: http://bierapp.babelomics.org/ VL - 42 UR - http://nar.oxfordjournals.org/content/42/W1/W88 ER - TY - JOUR T1 - Genome Maps, a new generation genome browser. JF - Nucleic acids research Y1 - 2013 A1 - Medina, Ignacio A1 - Salavert, Francisco A1 - Sánchez, Rubén A1 - De Maria, Alejandro A1 - Alonso, Roberto A1 - Escobar, Pablo A1 - Bleda, Marta A1 - Joaquín Dopazo KW - BAM KW - genome viewer KW - HTML5 KW - javascript KW - Next Generation Sequencing KW - NGS KW - SVG KW - VCF AB - Genome browsers have gained importance as more genomes and related genomic information become available. However, the increase of information brought about by new generation sequencing technologies is, at the same time, causing a subtle but continuous decrease in the efficiency of conventional genome browsers. Here, we present Genome Maps, a genome browser that implements an innovative model of data transfer and management. The program uses highly efficient technologies from the new HTML5 standard, such as scalable vector graphics, that optimize workloads at both server and client sides and ensure future scalability. Thus, data management and representation are entirely carried out by the browser, without the need of any Java Applet, Flash or other plug-in technology installation. Relevant biological data on genes, transcripts, exons, regulatory features, single-nucleotide polymorphisms, karyotype and so forth, are imported from web services and are available as tracks. In addition, several DAS servers are already included in Genome Maps. As a novelty, this web-based genome browser allows the local upload of huge genomic data files (e.g. VCF or BAM) that can be dynamically visualized in real time at the client side, thus facilitating the management of medical data affected by privacy restrictions. Finally, Genome Maps can easily be integrated in any web application by including only a few lines of code. Genome Maps is an open source collaborative initiative available in the GitHub repository (https://github.com/compbio-bigdata-viz/genome-maps). Genome Maps is available at: http://www.genomemaps.org. VL - 41 UR - http://nar.oxfordjournals.org/content/41/W1/W41 ER - TY - JOUR T1 - Inferring the functional effect of gene expression changes in signaling pathways. JF - Nucleic Acids Res Y1 - 2013 A1 - Sebastián-Leon, Patricia A1 - Carbonell, José A1 - Salavert, Francisco A1 - Sánchez, Rubén A1 - Medina, Ignacio A1 - Dopazo, Joaquin KW - Animals KW - Humans KW - Internet KW - Mice KW - Models, Statistical KW - Receptors, Cell Surface KW - Signal Transduction KW - Software KW - Transcriptome AB -

Signaling pathways constitute a valuable source of information that allows interpreting the way in which alterations in gene activities affect to particular cell functionalities. There are web tools available that allow viewing and editing pathways, as well as representing experimental data on them. However, few methods aimed to identify the signaling circuits, within a pathway, associated to the biological problem studied exist and none of them provide a convenient graphical web interface. We present PATHiWAYS, a web-based signaling pathway visualization system that infers changes in signaling that affect cell functionality from the measurements of gene expression values in typical expression microarray case-control experiments. A simple probabilistic model of the pathway is used to estimate the probabilities for signal transmission from any receptor to any final effector molecule (taking into account the pathway topology) using for this the individual probabilities of gene product presence/absence inferred from gene expression values. Significant changes in these probabilities allow linking different cell functionalities triggered by the pathway to the biological problem studied. PATHiWAYS is available at: http://pathiways.babelomics.org/.

VL - 41 IS - Web Server issue U1 - https://www.ncbi.nlm.nih.gov/pubmed/23748960?dopt=Abstract ER - TY - CONF T1 - Multicore and Cloud-based Solutions for Genomic Variant Analysis T2 - Proceedings of the 18th International Conference on Parallel Processing Workshops Y1 - 2013 A1 - Gonzalez, Cristina Y. A1 - Bleda, Marta A1 - Salavert, Francisco A1 - Sánchez, Rubén A1 - Dopazo, Joaquin A1 - Medina, Ignacio KW - genomic variant analysis KW - multicore KW - mutation KW - OpenMP KW - web service JF - Proceedings of the 18th International Conference on Parallel Processing Workshops PB - Springer-Verlag CY - Berlin, Heidelberg SN - 978-3-642-36948-3 UR - http://dx.doi.org/10.1007/978-3-642-36949-0_30 ER - TY - JOUR T1 - CellBase, a comprehensive collection of RESTful web services for retrieving relevant biological information from heterogeneous sources. JF - Nucleic acids research Y1 - 2012 A1 - Bleda, Marta A1 - Tárraga, Joaquín A1 - De Maria, Alejandro A1 - Salavert, Francisco A1 - García-Alonso, Luz A1 - Celma, Matilde A1 - Martin, Ainoha A1 - Dopazo, Joaquin A1 - Medina, Ignacio AB - During the past years, the advances in high-throughput technologies have produced an unprecedented growth in the number and size of repositories and databases storing relevant biological data. Today, there is more biological information than ever but, unfortunately, the current status of many of these repositories is far from being optimal. Some of the most common problems are that the information is spread out in many small databases; frequently there are different standards among repositories and some databases are no longer supported or they contain too specific and unconnected information. In addition, data size is increasingly becoming an obstacle when accessing or storing biological data. All these issues make very difficult to extract and integrate information from different sources, to analyze experiments or to access and query this information in a programmatic way. CellBase provides a solution to the growing necessity of integration by easing the access to biological data. CellBase implements a set of RESTful web services that query a centralized database containing the most relevant biological data sources. The database is hosted in our servers and is regularly updated. CellBase documentation can be found at http://docs.bioinfo.cipf.es/projects/cellbase. VL - 40 UR - http://nar.oxfordjournals.org/content/40/W1/W609.long ER - TY - JOUR T1 - Inferring the regulatory network behind a gene expression experiment. JF - Nucleic Acids Res Y1 - 2012 A1 - Bleda, Marta A1 - Medina, Ignacio A1 - Alonso, Roberto A1 - De Maria, Alejandro A1 - Salavert, Francisco A1 - Dopazo, Joaquin KW - Binding Sites KW - Databases, Genetic KW - Fanconi Anemia KW - Gene Regulatory Networks KW - Internet KW - MicroRNAs KW - Software KW - Transcription Factors KW - Transcriptome AB -

Transcription factors (TFs) and miRNAs are the most important dynamic regulators in the control of gene expression in multicellular organisms. These regulatory elements play crucial roles in development, cell cycling and cell signaling, and they have also been associated with many diseases. The Regulatory Network Analysis Tool (RENATO) web server makes the exploration of regulatory networks easy, enabling a better understanding of functional modularity and network integrity under specific perturbations. RENATO is suitable for the analysis of the result of expression profiling experiments. The program analyses lists of genes and search for the regulators compatible with its activation or deactivation. Tests of single enrichment or gene set enrichment allow the selection of the subset of TFs or miRNAs significantly involved in the regulation of the query genes. RENATO also offers an interactive advanced graphical interface that allows exploring the regulatory network found.RENATO is available at: http://renato.bioinfo.cipf.es/.

VL - 40 IS - Web Server issue U1 - https://www.ncbi.nlm.nih.gov/pubmed/22693210?dopt=Abstract ER - TY - JOUR T1 - VARIANT: Command Line, Web service and Web interface for fast and accurate functional characterization of variants found by Next-Generation Sequencing. JF - Nucleic Acids Res Y1 - 2012 A1 - Medina, Ignacio A1 - De Maria, Alejandro A1 - Bleda, Marta A1 - Salavert, Francisco A1 - Alonso, Roberto A1 - Gonzalez, Cristina Y A1 - Dopazo, Joaquin KW - Databases, Nucleic Acid KW - Genetic Variation KW - High-Throughput Nucleotide Sequencing KW - Internet KW - Molecular Sequence Annotation KW - mutation KW - Polymorphism, Single Nucleotide KW - Software KW - User-Computer Interface AB -

The massive use of Next-Generation Sequencing (NGS) technologies is uncovering an unexpected amount of variability. The functional characterization of such variability, particularly in the most common form of variation found, the Single Nucleotide Variants (SNVs), has become a priority that needs to be addressed in a systematic way. VARIANT (VARIant ANalyis Tool) reports information on the variants found that include consequence type and annotations taken from different databases and repositories (SNPs and variants from dbSNP and 1000 genomes, and disease-related variants from the Genome-Wide Association Study (GWAS) catalog, Online Mendelian Inheritance in Man (OMIM), Catalog of Somatic Mutations in Cancer (COSMIC) mutations, etc). VARIANT also produces a rich variety of annotations that include information on the regulatory (transcription factor or miRNA-binding sites, etc.) or structural roles, or on the selective pressures on the sites affected by the variation. This information allows extending the conventional reports beyond the coding regions and expands the knowledge on the contribution of non-coding or synonymous variants to the phenotype studied. Contrarily to other tools, VARIANT uses a remote database and operates through efficient RESTful Web Services that optimize search and transaction operations. In this way, local problems of installation, update or disk size limitations are overcome without the need of sacrifice speed (thousands of variants are processed per minute). VARIANT is available at: http://variant.bioinfo.cipf.es.

VL - 40 IS - Web Server issue U1 - https://www.ncbi.nlm.nih.gov/pubmed/22693211?dopt=Abstract ER -