Genome-scale mechanistic modeling of signaling pathways made easy: A bioconductor/cytoscape/web server framework for the analysis of omic data
| Autor: | Kinza Rian, Marta R. Hidalgo, Cankut Çubuk, Matias M. Falco, Joaquín Dopazo, Carlos Loucera, Maria Peña-Chilet, Inmaculada Alamo-Alvarez, Marina Esteban-Medina |
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| Přispěvatelé: | Ministerio de Economía y Competitividad (España), European Commission, [Rian,K, Çubuk,C, Falco,MM, Loucera,C, Esteban-Medina,M, Alamo-Alvarez,I, Peña-Chilet,M, Dopazo,J] Clinical Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, Sevilla, Spain. [Rian,K] Laboratory of Innovative Technologies (LTI), National School of Applied Sciences in Tangier, UAE, Morocco. [Hidalgo,MR] Bioinformatics and Biostatistics Unit, Centro de Investigación Príncipe Felipe (CIPF), Valencia, Spain. [Falco,MM, Dopazo,J] Bioinformatics in RareDiseases (BiER), Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Sevilla, Spain. [Loucera,C, Dopazo,J] Computational Systems Medicine. Institute of Biomedicine of Seville (IBiS), Sevilla, Spain. [Dopazo,J] Functional Genomics Node (INB-ELIXIR-es), Sevilla, Spain., This work is supported by grants SAF2017-88908-R from the Spanish Ministry of Economy and Competitiveness and PT17/0009/0006 and PI20/01305 from the ISCIII, both co-funded with European Regional Development Funds (ERDF) as well as H2020 Programme of the European Union grants Marie Curie Inno vative Training Network ‘‘Machine Learning Frontiers in Precision Medicine' (MLFPM) (GA 813533) and ‘‘ELIXIR-EXCELERATE fast track ELIXIR implementation and drive early user exploitation across the life sciences' (GA 676559) to JD. Funding for open access charge: from the Spanish Ministry of Economy and Competitive ness / SAF2017-88908-R |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Web server
Phenomena and Processes::Genetic Phenomena::Phenotype [Medical Subject Headings] Phenomena and Processes::Genetic Phenomena::Genetic Variation::Mutation [Medical Subject Headings] Computer science Genomic data Phenomena and Processes::Genetic Phenomena::Genetic Processes::Gene Expression::Transcription Genetic::Transcriptome [Medical Subject Headings] Biophysics Genome scale Genomics Computational biology computer.software_genre Biochemistry Web tool Bioconductor 03 medical and health sciences 0302 clinical medicine Structural Biology Genetics Plug-in 030304 developmental biology Sistema de señalización 0303 health sciences Mutación Mathematical modelling Signaling pathway Potential effect Phenomena and Processes::Chemical Phenomena::Biochemical Phenomena::Biochemical Processes::Signal Transduction [Medical Subject Headings] Method Article Computer Science Applications Causalidad Causality Transcriptomic 030220 oncology & carcinogenesis Disciplines and Occupations::Natural Science Disciplines::Biological Science Disciplines::Biology::Genetics::Genomics [Medical Subject Headings] Phenomena and Processes::Genetic Phenomena::Genotype [Medical Subject Headings] computer Mutations TP248.13-248.65 Biotechnology |
| Zdroj: | Computational and Structural Biotechnology Journal, Vol 19, Iss, Pp 2968-2978 (2021) Computational and Structural Biotechnology Journal Digital.CSIC. Repositorio Institucional del CSIC instname r-FISABIO. Repositorio Institucional de Producción Científica r-CIPF. Repositorio Institucional Producción Científica del Centro de Investigación Principe Felipe (CIPF) Universitat Rovira i virgili (URV) |
| ISSN: | 2001-0370 |
| Popis: | Genome-scale mechanistic models of pathways are gaining importance for genomic data interpretation because they provide a natural link between genotype measurements (transcriptomics or genomics data) and the phenotype of the cell (its functional behavior). Moreover, mechanistic models can be used to predict the potential effect of interventions, including drug inhibitions. Here, we present the implementation of a mechanistic model of cell signaling for the interpretation of transcriptomic data as an R/Bioconductor package, a Cytoscape plugin and a web tool with enhanced functionality which includes building interpretable predictors, estimation of the effect of perturbations and assessment of the effect of mutations in complex scenarios. This work is supported by grants SAF2017-88908-R from the Spanish Ministry of Economy and Competitiveness and PT17/0009/0006 and PI20/01305 from the ISCIII, both co-funded with European Regional Development Funds (ERDF) as well as H2020 Programme of the European Union grants Marie Curie Innovative Training Network “Machine Learning Frontiers in Precision Medicine” (MLFPM) (GA 813533) and “ELIXIR-EXCELERATE fast-track ELIXIR implementation and drive early user exploitation across the life sciences” (GA 676559) to JD. Funding for open access charge: from the Spanish Ministry of Economy and Competitiveness / SAF2017-88908-R. |
| Databáze: | OpenAIRE |
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