Sentence examples for binding motifs were compared from inspiring English sources
All the identified TF binding motifs were compared by TOMTOM [ 21], since similarity of motifs could suggest a cross-regulation between different EBPs.
The predicted TF-binding motifs were compared using Pearson correlation coefficients calculated using Tomtom [ 62] and further clustered using Hierarchical Clustering Explorer 3.5 [ 63].
GERP scores were cataloged for all base positions within the position weight matrix, and binding sites harboring motifs were compared across tissues to determine tissue specificity.
The motifs were compared to the binding motifs of TFs using the TOMTOM program of the MEME suite [ 69].
The putative motifs were compared with known TF binding motifs in a transcription factor database JASPAR [ 24] by TomTom [ 25].
Matrices for over-represented motifs were compared to existing TF binding motifs in JASPAR and TRANSFAC [ 48, 49] using STAMP [ 50].
The binding abilities of AhR to the XRE-like, XRE-I and XRE-II motifs were compared by competition experiments using HeLa cells (Fig. 8).
The resulting motifs were compared to the TRANSFAC and JASPAR databases for identifying known binding sites.
Both 200-nt long neighboring flanking sequences and 12-nt long TCF4 binding motifs were more conserved compared to random genomic locations, where the conservation score of the TCF4 binding motif was on average higher than neighboring flanking regions (Fig. 3B), indicating selective pressure on these motifs and pointing to functional relevance.
In order to identify which transcription factors could bind to the motifs, each motif was compared to the transcription factor binding sites in the TRANSFAC database [ 33].
