Brain transcriptome atlases
A computational perspective
Ahmed Mahfouz (Leiden University Medical Center, TU Delft - Pattern Recognition and Bioinformatics)
Sjoerd M.H. Huisman (Leiden University Medical Center, TU Delft - Pattern Recognition and Bioinformatics)
Boudewijn P.F. Lelieveldt (Leiden University Medical Center, TU Delft - Pattern Recognition and Bioinformatics)
Marcel J.T. Reinders (TU Delft - Pattern Recognition and Bioinformatics)
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Abstract
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.
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