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The Results and Discussion sections describing the human postnatal brain analyses have been greatly streamlined.
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In the brain, such dynamic transcriptome analyses have been used to analyze the gene expression pattern of well-defined cell populations during development [ 26, 27].
Similar analyses have been undertaken for brain infarcts [ 119].
These signalling pathways identified from our analyses have been shown to regulate NPC proliferation in the adult brain [ 25- 28].
In this work, deformation-based morphometry (DBM) analyses have been performed on magnetic resonance images of the brains of 79 third graders to investigate whether there is a correlation between brain morphological features and mathematical proficiency.
Histological analyses have been used to provide impressive three-dimensional (3D) reconstructions of the human brain (Amunts et al. 2013).
It is equally unjustified to retort that all gloom-and-doom analyses are wrong because gloom-and-doom analyses have been wrong in the past.
This is not the first time Beacon Hill energy analyses have been questioned.
While some eQTL analyses of human brain tissue have been recently reported [ 19], eQTL studies have also been combined with network analyses to identify transcription modules of disease-related, co-expressed genes [ 20- 23] and to find causal pathways in glioblastomas [ 24].
It is worth mentioning that in contrast to structural analyses, some functional brain networks have been described as scale-free [29].
Gene expression analyses of human brain have been used to find genes associated with brain diseases but most of those studies were restricted either to an individual disease or to a couple of diseases.
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