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New insights in Rett syndrome using pathway analysis for transcriptomics data

The analysis of transcriptomics data is able to give an overview of cellular processes, but requires sophisticated bioinformatics tools and methods to identify the changes. Pathway analysis software, like PathVisio, captures the information about biological pathways from databases and brings this to...

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Autores principales: Ehrhart, Friederike, Coort, Susan L. M., Cirillo, Elisa, Smeets, Eric, Evelo, Chris T., Curfs, Leopold
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Vienna 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5005393/
https://www.ncbi.nlm.nih.gov/pubmed/27517371
http://dx.doi.org/10.1007/s10354-016-0488-4
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author Ehrhart, Friederike
Coort, Susan L. M.
Cirillo, Elisa
Smeets, Eric
Evelo, Chris T.
Curfs, Leopold
author_facet Ehrhart, Friederike
Coort, Susan L. M.
Cirillo, Elisa
Smeets, Eric
Evelo, Chris T.
Curfs, Leopold
author_sort Ehrhart, Friederike
collection PubMed
description The analysis of transcriptomics data is able to give an overview of cellular processes, but requires sophisticated bioinformatics tools and methods to identify the changes. Pathway analysis software, like PathVisio, captures the information about biological pathways from databases and brings this together with the experimental data to enable visualization and understanding of the underlying processes. Rett syndrome is a rare disease, but still one of the most abundant causes of intellectual disability in females. Cause of this neurological disorder is mutation of one single gene, the methyl-CpG-binding protein 2 (MECP2) gene. This gene is responsible for many steps in neuronal development and function. Although the genetic mutation and the clinical phenotype are well described, the molecular pathways linking them are not yet fully elucidated. In this study we demonstrate a workflow for the analysis of transcriptomics data to identify biological pathways and processes which are changed in a Mecp2(-/y) mouse model. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi: 10.1007/s10354-016-0488-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-50053932016-09-15 New insights in Rett syndrome using pathway analysis for transcriptomics data Ehrhart, Friederike Coort, Susan L. M. Cirillo, Elisa Smeets, Eric Evelo, Chris T. Curfs, Leopold Wien Med Wochenschr Main Topic The analysis of transcriptomics data is able to give an overview of cellular processes, but requires sophisticated bioinformatics tools and methods to identify the changes. Pathway analysis software, like PathVisio, captures the information about biological pathways from databases and brings this together with the experimental data to enable visualization and understanding of the underlying processes. Rett syndrome is a rare disease, but still one of the most abundant causes of intellectual disability in females. Cause of this neurological disorder is mutation of one single gene, the methyl-CpG-binding protein 2 (MECP2) gene. This gene is responsible for many steps in neuronal development and function. Although the genetic mutation and the clinical phenotype are well described, the molecular pathways linking them are not yet fully elucidated. In this study we demonstrate a workflow for the analysis of transcriptomics data to identify biological pathways and processes which are changed in a Mecp2(-/y) mouse model. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi: 10.1007/s10354-016-0488-4) contains supplementary material, which is available to authorized users. Springer Vienna 2016-08-12 2016 /pmc/articles/PMC5005393/ /pubmed/27517371 http://dx.doi.org/10.1007/s10354-016-0488-4 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Main Topic
Ehrhart, Friederike
Coort, Susan L. M.
Cirillo, Elisa
Smeets, Eric
Evelo, Chris T.
Curfs, Leopold
New insights in Rett syndrome using pathway analysis for transcriptomics data
title New insights in Rett syndrome using pathway analysis for transcriptomics data
title_full New insights in Rett syndrome using pathway analysis for transcriptomics data
title_fullStr New insights in Rett syndrome using pathway analysis for transcriptomics data
title_full_unstemmed New insights in Rett syndrome using pathway analysis for transcriptomics data
title_short New insights in Rett syndrome using pathway analysis for transcriptomics data
title_sort new insights in rett syndrome using pathway analysis for transcriptomics data
topic Main Topic
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5005393/
https://www.ncbi.nlm.nih.gov/pubmed/27517371
http://dx.doi.org/10.1007/s10354-016-0488-4
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