Alignment-based sequence methods
This notebook introduces the alignment-based sequence methods (operationalized by the Optimal Matching (OM) algorithm), which was originally developed for matching protein and DNA sequences in biology and used extensively for analyzing strings in computer science and recently widely applied to explore the neighborhood change.
It generally works by finding the minimum cost for aligning one sequence to match another using a combination of operations including substitution, insertion, deletion and transposition. The cost of each operation can be parameterized diferently and may be theory-driven or data-driven. The minimum cost is considered as the distance between the two sequences.
The sequence
module in giddy
provides a suite of alignment-based sequence methods.
Author: Wei Kang weikang9009@gmail.com
Import Sequence
class from giddy.sequence
:
"tran"
Biemann, T. (2011). A Transition-Oriented Approach to Optimal Matching. Sociological Methodology, 41(1), 195–221. https://doi.org/10.1111/j.1467-9531.2011.01235.x