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Despite its power, there are several challenges to using ARB for massive collections of ss-RNA sequences including that alignments need to be manually created within ARB and that taxonomic assignments require visual inspection of trees and manual input from users.
This implies that only a few alignments need to be provided as examples of manual editing to properly train the classifier.
For both algorithms, we found that the 99% fastest alignments need nearly as much computing time as the remaining 1% slowest alignments.
When such alignments need to be extended, e.g. after new sequences become available, it may be preferable to keep the relative alignment of existing sequences intact and have the new sequences aligned to this reference alignment.
Since local structural alignments need not involve a large number of residues, the similarity that is detected could in fact be a frequently occurring 3D motif, having no relationship to common protein function.
Because genetic variations are rare, this practice greatly reduces 1) the number of sites where mate-reads need to be aligned; 2) the number of inserts that need to be further analyzed; and 3) the number of reads whose alignments need to be stored, without losing information of potential variant reads.
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Without Chain Length Indexing, the 20 dataset of no homologous template chains should be aligned with each of chains in template database, which mean that there are 20 × 101,315 time-consuming structural alignments needed to be done.
Without Homology Indexing, 48 unbound dataset should be aligned with each of chains in template database, which means that there are 48 × 101,315 time-consuming structural alignments needed to be done.
This guarantees that all the alignments needed to compose these biclusters are considered.
For instance, when the selectivity is 3%, our method's running time is almost that of the smallest number of alignments needed for that selectivity.
However, apart the from availability of one or more informant genomes, their approach to integrate information from EST alignments needs a training step.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com