Sequence-To-Graph Alignment: Difference between revisions
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== Parameters == | == Parameters == | ||
N: number of vertices in original hypertext graph | $N$: number of vertices in original hypertext graph | ||
E: number of edges in original hypertext graph | $E$: number of edges in original hypertext graph | ||
m: length of pattern | $m$: length of pattern | ||
n: number of vertices in converted graph (total text size) | $n$: number of vertices in converted graph (total text size) | ||
e: number of edges in converted graph | $e$: number of edges in converted graph | ||
== Table of Algorithms == | == Table of Algorithms == | ||
Currently no algorithms in our database for the given problem. | Currently no algorithms in our database for the given problem. |
Latest revision as of 08:24, 10 April 2023
Description
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 $N$ nodes and $E$ 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 $m$. 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 $l$ into a chain of $l$ nodes). This graph has $n$ nodes and $e$ edges (note that $n$ is the text size and $e = n − N + E$).
Additonal notes: (changes are allowed in the query sequence alone) Linear gap penalty?
Parameters
$N$: number of vertices in original hypertext graph
$E$: number of edges in original hypertext graph
$m$: length of pattern
$n$: number of vertices in converted graph (total text size)
$e$: number of edges in converted graph
Table of Algorithms
Currently no algorithms in our database for the given problem.