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If addition of a new cluster led to a model with two clinically indistinguishable developmental clusters, the model was not considered to be improved.
From a developmental perspective, rostral (prepontine and pontine) and caudal (pontomedullary and medullary) developmental clusters were already identified previously (Olson and Seiger 1972; Seiger and Olson 1973; Lidov and Molliver 1982; Wallace and Lauder 1983; Goto and Sano 1984).
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We therefore looked for the 30 most highly expressed transcripts in each developmental cluster (Table 3).
Many well-studied genes known to be important for development such as Gli2, Notch3, Foxc2[ 37- 39] were found in this developmental cluster.
To form developmental-clusters, genes were centered to have a mean expression intensity of zero across the 79 developmental series conditions, and the cosine angle similarity metric was used to cluster expression profiles of Hsf/Hsp genes within each family.
Members of developmental-cluster 60 (see Table 2) exhibited a pattern of tissue-specificity that was found among certain genes from each of the four Hsp families.
Chromatin conformation analyses have established the importance of cohesin for the architecture of developmental gene clusters and in vivo studies in mouse and zebrafish demonstrated how cohesin defects lead to gene misregulation and to malformations similar to the related human syndromes.
In analyses of selected developmental genes, clusters were manually validated using NCBI-BLAST+ [ 53].
Clustering analysis of the datasets indicated that the two SE developmental stages clustered closest to the profile of the mature developmental stage of ZE as might be expected.
Several less well characterized putative regulators closely follow the expression pattern of the developmental gene cluster that is repressed upon the metabolic switch.
Mixed model analysis and neighbor – joining trees showed that tissues with similar developmental origin clustered closer than those with different embryonic origins.
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