Sequence-To-Graph Alignment
This is pattern matching where you are given a pattern and a hypertext graph. The hypertext model is that the text forms a graph of nodes and edges, where a string is stored inside each node, and the edges indicate alternative texts that may follow the current node. The pattern is still a simple string of length . It is also customary to transform this graph into a one-character hypertext, i.e. one where there is exactly one character per node (by converting each node containing a text of length into a chain of nodes). This graph has nodes and edges (note that is the text size and ). Additonal notes: (changes are allowed in the query sequence alone) Linear gap penalty
Parameters
- : number of vertices in original hypertext graph
- : number of edges in original hypertext graph
- : length of pattern
- : number of vertices in converted graph (total text size)
- : number of edges in converted graph
Filters
Computational Model
Randomization
Approximation
Algorithms Table
Displaying 6 of 6 algorithms
| See more | ||||
|---|---|---|---|---|
| Jain, Chang | 2019 | |||
| V-ALIGN | 2018 | |||
| Rautiainen and Marschall | 2017 | |||
| HybridSpades | 2015 | |||
| Navarro | 2000 | |||
| Amir et al. | 1997 |
Reductions Table
Insuffient Data to display table
Other relevant algorithms
Insuffient Data to display table