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  1. .... Therefore, we hypothesized that EM genes whose expression patterns display this coordinated behavior (coexpression) would differ in their mutational constraint from those who do not. To test this, we constructed tissue-specific coexpression networks and determined modules of coexpressed genes using Weighted...
  2. ...motor-somatosensory cortex are a key point of ASD gene convergence (Willsey et al. 2013). Integrating gene coexpression with protein–protein interaction networks to identify modules that enrich for genes mutated in several NDDs revealed that different NDDs share a major point of gene convergence during...
  3. ...into either excitatory cortical neurons or inhibitory interneurons. Furthermore, scCapture-seq revealed a role for of retinoic acid signaling in the developmental divergence between these different neuronal populations. Our results show that TF targeting improves the characterization of human cellular models...
  4. ...genes is a frequent and significant characteristic of de novo CNVs in patients with developmental disorders ( P = 1 × 10 −3 ). Using three different functional networks, we identified unexpectedly large numbers of functionally related genes within de novo CNVs from two large independent cohorts...
  5. ...and transcriptional perturbators is suppressed by early embryonic epigenetic silencing. Here, we asked how ERE control is maintained during the generation of induced pluripotent stem cells (iPSCs), as this procedure involves profound epigenetic remodeling. We found that all EREs tested were markedly up...
  6. ...an important aspect of biological networks. Therefore, acquiring the knowledge of all possible gene isoforms and their in vivo expression patterns in specific cell populations and tissues, as well as their developmental 4 These authors contributed equally to this work. 5Corresponding author. E-mail rdavuluri...
  7. ...influenced by ASD-linked transcriptional regulatorsNext, we sought to expand these comparisons using more sensitive measures. We therefore used weighted gene coexpression network analysis (WGCNA) (Zhang and Horvath 2005) to capture system-level changes associated with the depletion of ASD...
  8. ...such as brain region, age, sex, RIN, brain bank, and PMI did not drive the similar clustering (Fig. 1I). Our result thus revealed a shared circRNA dysregulation signature among the majority of ASD samples.Construction of signed coexpression networks of circRNA dysregulation in ASDTo probe the correlation...
  9. ...hippocampus. Furthermore, an analysis of the coexpression network revealed an additional module (module 16) closely linked to module 22 and showing human-specific hippocampal overexpression of a smaller magnitude (Fig. 6; Supplemental Fig. S9). This result is notable, because the hippocampus is central...
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