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Brain transcriptome atlases: a computational perspective
The immense complexity of the mammalian brain is largely reflected in the underlying molecular signatures of its billions of cells. Brain transcriptome atlases provide valuable insights into gene expression patterns across different brain areas throughout the course of development. Such atlases allo...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5406417/ https://www.ncbi.nlm.nih.gov/pubmed/27909802 http://dx.doi.org/10.1007/s00429-016-1338-2 |
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author | Mahfouz, Ahmed Huisman, Sjoerd M. H. Lelieveldt, Boudewijn P. F. Reinders, Marcel J. T. |
author_facet | Mahfouz, Ahmed Huisman, Sjoerd M. H. Lelieveldt, Boudewijn P. F. Reinders, Marcel J. T. |
author_sort | Mahfouz, Ahmed |
collection | PubMed |
description | The immense complexity of the mammalian brain is largely reflected in the underlying molecular signatures of its billions of cells. Brain transcriptome atlases provide valuable insights into gene expression patterns across different brain areas throughout the course of development. Such atlases allow researchers to probe the molecular mechanisms which define neuronal identities, neuroanatomy, and patterns of connectivity. Despite the immense effort put into generating such atlases, to answer fundamental questions in neuroscience, an even greater effort is needed to develop methods to probe the resulting high-dimensional multivariate data. We provide a comprehensive overview of the various computational methods used to analyze brain transcriptome atlases. |
format | Online Article Text |
id | pubmed-5406417 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-54064172017-05-12 Brain transcriptome atlases: a computational perspective Mahfouz, Ahmed Huisman, Sjoerd M. H. Lelieveldt, Boudewijn P. F. Reinders, Marcel J. T. Brain Struct Funct Review The immense complexity of the mammalian brain is largely reflected in the underlying molecular signatures of its billions of cells. Brain transcriptome atlases provide valuable insights into gene expression patterns across different brain areas throughout the course of development. Such atlases allow researchers to probe the molecular mechanisms which define neuronal identities, neuroanatomy, and patterns of connectivity. Despite the immense effort put into generating such atlases, to answer fundamental questions in neuroscience, an even greater effort is needed to develop methods to probe the resulting high-dimensional multivariate data. We provide a comprehensive overview of the various computational methods used to analyze brain transcriptome atlases. Springer Berlin Heidelberg 2016-12-01 2017 /pmc/articles/PMC5406417/ /pubmed/27909802 http://dx.doi.org/10.1007/s00429-016-1338-2 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 | Review Mahfouz, Ahmed Huisman, Sjoerd M. H. Lelieveldt, Boudewijn P. F. Reinders, Marcel J. T. Brain transcriptome atlases: a computational perspective |
title | Brain transcriptome atlases: a computational perspective |
title_full | Brain transcriptome atlases: a computational perspective |
title_fullStr | Brain transcriptome atlases: a computational perspective |
title_full_unstemmed | Brain transcriptome atlases: a computational perspective |
title_short | Brain transcriptome atlases: a computational perspective |
title_sort | brain transcriptome atlases: a computational perspective |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5406417/ https://www.ncbi.nlm.nih.gov/pubmed/27909802 http://dx.doi.org/10.1007/s00429-016-1338-2 |
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