Using prefix-tree, it can immediately determine which sequences contain a given sequence as a prefix.
Such findings suggest that online learning is a plausible effect of statistical chunk learning that is possible when ungrammatical sequences contain a large proportion of grammatical chunks.
These sequences contain a promoter region, which is active in the 5′ LTR, and transcription termination signals, which are active in the LTR copy present at the 3′ end.
Although at the promoter region of RAMP1, these sequences contain a number of CpG dinucleotides, few attempts are to investigate the relationship between DNA methylation of RAMP1 gene and migraine.
Figure 2 sequences contain a variety of minor problems that had a large cumulative impact on MOS, such as motion blur, analog noise, camera wobble, poor scene composition, long shot lengths (e.g., no scene cuts), a boring topic, or an uninteresting presentation (e.g., the action in vqegHD5 src2 would be more exciting if seen from a closer zoom).
These sequences contain a 13 bp palindromic motif (GGTCAnnnTGACC) referred to as the estrogen responsive element (ERE) [11].
ΔU3-MLV sequences contain a lower number of TFBSs and show a lower variability, although they are still oriented towards the RV group along the first component axis.
One member has a DEP (Dishevelled, Egl-10 and Pleckstrin) domain N-terminal to the RGS domain, while two sequences contain a C2 domain in addition to the RGS domain.
Although there are a similar number of predicted recombination breakpoints throughout the two sequence sets, the predicted recombinant fragments within the T3SS sequences contain a more conflicting phylogenetic signal.
Like many other (but not all) VirB10 and VirB10-like proteins [100], the Rickettsia sequences contain a proline-rich tract in the periplasmic region of the NTD that is predicted to form an α-helical coiled-coil [98], which could mediate oligomerization [95].
We also assessed whether the motif detection tools could recover motifs in datasets with lower signal to noise levels e.g. by searching for a low IC motif (Figure 2(B)) or by searching for a high IC motif in a dataset where not all sequences contain a motif instance (Figure 2(C)).
