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We implemented three different types of alignment procedures.
To simulate different types of alignment errors that might be expected with measurement of IOP in alert chickens, for some calibrations the tonometer was positioned (1) at various distances from the cornea, (2) laterally displaced from the visual axis, or (3) angled away from the visual axis.
We had three different types of alignment testing sets.
Test cases from this dataset are designed to expose new methods to many different types of alignment problems.
Motivation: A plethora of alignment tools have been created that are designed to best fit different types of alignment conditions.
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Figure 1 shows examples of CIGAR strings for different types of alignments.
Furthermore, since different types of analysis may require different types of alignments, recovering the original BAM file may not always be sufficient, in which case further processing, such as extracting the original sequences from the alignment file, may be required.
In the rest of this article, we focus on the performance of 3-Opt PISwap when using initial mappings produced by different types of global alignment algorithms, such as sequence-free alignment and integrated approaches, which combine sequence data with topology information.
PISwap can begin with different types of network alignment approaches and then iteratively adjust the initial alignments by incorporating network topology information, trading it off for sequence information.
Third, we use a unified probabilistic model for different types of network alignment (deterministic, part probabilistic, and complete probabilistic), unlike other alignments which use different methods for different types of networks.
We then use a small data set of well characterized kinases and compare different types of distances (alignment-based and alignment-free) both on full-length sequences and catalytic domains.
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