Sentence examples for most prominent clusters from inspiring English sources

Perhaps more striking than the large number of Lbx1-affected nodes was the observation that 65 of the affected nodes were in the 150 most prominent clusters of ultra-conserved non-coding regions (UCRs) in the mammalian genome [44] and 29 were associated with highly conserved noncoding regions (HCNRs) enriched in Hox, Sox, and POU binding sites [45].

Among genes in the initially responsive category, the most prominent clusters were involved in ion and trans-membrane transport, specifically calcium and sodium ion transport.

The complete clustering tree as well as a table of the most prominent clusters is given in the Additional file 1.

This result was further confirmed by interaction network analysis, which was used to construct the most prominent clusters of genes in each of the forebrain regions based on known molecular interactions in the literature.

The two most prominent clusters are component 1 (34.8% of variance), which includes many ARG, Cu, and ampicillin, and component 2 (19.2% of variance) that clusters the rest of the metals and benzyl-penicillin.

As shown in Table  2, functional analysis of the five most prominent clusters with contrasting gene expression revealed enrichment of integrin linked kinase (ILK) signaling and epithelial adherens junction signaling pathways, glutathione metabolism, and interferon and pro-inflammatory signaling pathways.

The most prominent clustering of traits occurred on chromosome E10, which also proved to harbor the most genes/QTL underlying variation in anthocyanin content and fruit color.

The third most prominent cluster of deactivation included the most anterior portion of FG, a finding consistent with reports of modality-specific BOLD decreases during demanding auditory tasks (McKiernan et al. 2003).

For GEL count-associated genes, the three most prominent enrichment clusters were all attributable to processes and pathways of the immune system (inflammatory responses, antigen presentation, and NF-kB signaling).

Venn diagrams drawn using only these most prominent sequence clusters, encompassing altogether 90 93% of sample sequences, showed that there existed a larger overlap between the post-capture samples H1 and H2 than between the pre-capture samples H0 and H1 or H2 (Fig.  3B).

The most prominent fuzzy clustering algorithm is the fuzzy c-means clustering [43].