Searching journal content for articles similar to Miller et al. 9 (11): 1143.

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  1. ...benchmark data sets, including sequencing technologies, species, organism/disease types, numbers of spots, genes, and cell types, etc.To comprehensively assess the performance of these diverse consensus strategies, we have collected seven SRT data sets with manual annotations by pathologists as ground truth...
  2. ...-specific networks. Central genes in consensus networks are enriched for evolutionarily constrained genes and ubiquitous biological pathways, whereas context-specific central nodes include tissue-specific transcription factors. The increased statistical power from data aggregation facilitates the derivation...
  3. ...(Ashuach et al. 2023). For example, GLUE is a representative method of this category, which integrates gene expression and peak count data and leverages prior regulatory knowledge to guide cross-omics alignment (Cao and Gao 2022). This approach preserves as much information as possible in the raw sc...
  4. ...the genomic position on the chromosomes (1 Mb bins), and the y-axis indicates copy numbers. (C) Correlation of CNA-derived TF between NanoRCS and NovaSeq. (D) NanoRCS copy number of genes often amplified (red) and deleted (blue) according to literature. The boxplots show the observed copy number distribution...
  5. ..., lead to the formation of G4 structures (Fig. 1A; Spiegel et al. 2020). Their presence and formation in telomeric regions provided early evidence that G4s are a native DNA conformation (Parkinson et al. 2002). Furthermore, an array of studies have shown that G4s are involved in processes such as gene...
  6. ...sequence is functional, the reporter gene is expressed/induced and the cellular concentration of the gene product is measured (Smale 2010).TF binding predictionTFs bind DNA in a sequence-specific manner based on motifs, with each binding site having a consensus sequence that indicates prerequisites...
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  7. ...spot of ≈2000, compared to ≈4000 spots and ≈5000 median UMI per spot in the 10x Visium DLPFC data set. They derived the cell type of each spot by unsupervised clustering of gene expression followed by annotation based on marker genes. The publication used PASTE to align all slices from the same stage...
  8. ...of the three simulated data sets into four clusters, with each data set containing clusters labeled from zero to three (Supplemental Fig. S1). We applied consensus clustering (Wilkerson and Hayes 2010) to the highly variable genes in each data set to generate functional gene lists and performed De...
  9. ...sequence-based variant discovery (Gürsoy et al. 2020), and inference using gene expression values and associated loci (Harmanci and Gerstein 2016). The ubiquity of large-scale omics projects make this source of variants especially concerning (Gürsoy et al. 2020). Several studies have showed identification...
  10. ...length distribution for various choices of the NGx fraction threshold. (D) Quality value scores. (E) Running time analysis. (F) Memory usage analysis (legend on panel D also applies to panels E,F).Second, the completeness was assessed by BUSCO. The set of conserved genes in gramineae (4896 genes in total...
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