Searching journal content for articles similar to Morin et al. 33 (5): 763.

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  1. ...in silico perturbation methods for drug repurposing. Network proximity analysis identifies potential drugs by assessing the proximity between the drug target set and AD-related gene set. Drug efficacy is evaluated based on the proximity distance and Z-score. GSEA leverages drug–gene signatures from the CMap...
  2. ...results by the ChIP-seq technique, we generally saw several TE subfamilies significantly enriched with a given KZFP bait. However, in most cases a few subfamilies stood out as much more enriched than others. We defined the identified sequences as primary targets of the ChIP'ed KZFPs if within an arbitrary...
  3. ...perturbation, we find that low-complexity ChIP-seq targets are more likely to be factor-responsive than are high-complexity targets. Second, we use the large number of data sets to identify transcription factors that have different sets of targets identified in multiple developmental stages. Analysis...
  4. ...unique ChIP-seq DAP targets in HepG2 and nine histone modifications. This expanded catalog of DAPs and associated gene regulatory data sets provides a rich resource to characterize and understand the functional impact of DAP binding on gene regulation.DAP associations at cCREs reveal the interaction...
  5. ...immunoprecipitation with massively parallel sequencing (ChIP-seq) on CRX to identify thousands of cis -regulatory regions around photoreceptor genes in adult mouse retina. CRX directly regulates downstream photoreceptor transcription factors and their target genes via a network of spatially distributed regulatory...
  6. ...with transcriptional changes (Li et al. 2015). Recent evidence points to defective 3D architecture as a major contributor for diseases, developmental defects, and even aging (Chandra et al. 2015; Lupiáñez et al. 2015; Flavahan et al. 2016; Hnisz et al. 2016; Sun et al. 2018; Kraft et al. 2019; Akdemir et al. 2020...
  7. ...factor's predicted target gene set that is obtained from GTRD databases of ChIP-seq data that has more than 17,485 transcription factor ChIP-seq samples (Yevshin et al. 2019). This information of known ChIP-seq data is used as a prior probability to guide the factorization of scRNA-seq data in a Bayesian...
  8. ...” by a distance <10 kb. (D) Log base 10 FPKM fold change of “neighboring” genes related to eRNA-grouped NR2F2 binding peaks. (E) Histogram of Log base 10 FPKM fold change of “neighboring” genes for all possible eRNA-grouped TF ChIP-seq data sets (n = 255).Given the strong relationship between active chromatin...
  9. ...perturbations (Supplemental Fig. S4E).Although all five transcription factors predominantly occupy gene promoter regions, the majority of ChIP-seq peaks that showed significant increases in occupancy upon DNA methylation loss or HDAC inhibition were situated at promoter distal genomic sites (Supplemental Fig. S...
  10. ...asymmetric pattern corresponding to transcriptional direction, chromatin accessibility, and Pol II ChIP-seq signals compared with the matched GENCODE TSSs (Fig. 4C).View larger version: In this window In a new window Figure 4. RAMPAGE-verified rPeaks are enriched for regulatory signatures. (A) Bar plots...
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