The traditional edit-distance problem is to find the minimum number of insert-character and delete-character (and sometimes change character) operations required to transform one string into another. Here we consider the more general problem of a string represented by a singly linked list (one character per node) and being able to apply these operations to the pointer associated with a vertex a...

These days genomic sequence analysis provides a key way of understanding the biology of an organism. However, since these sequences contain much private information, it can be very dangerous to reveal any part of them. It is desirable to protect this sensitive information when performing sequence analysis in public. As a first step in this direction, we present a method to perform the edit dist...

The simplest form of sequence comparison is based on editing strings and counting the number of edits required to get from one sequence to the other. The formulation of string-edit distance de balances two different types of edits. The simplest is replacement of a single letter by another letter. To start with, we need a metric on the set of letters in the alphabet Σ for our sets of sequences. ...

The edit distance between strings A and B is defined as the minimum number of edit operations needed in converting A into B or vice versa. Typically the allowed edit operations are one or more of the following: an insertion, a deletion or a substitution of a character, or a transposition between two adjacent characters. Simple edit distance allows the first two operation types, Levenshtein edit...

Edit distance metrics are widely used for many applications such as string comparison and spelling error corrections. Hamming distance is a metric for two equal length strings and Damerau-Levenshtein distance is a well-known metrics for making spelling corrections through string-to-string comparison. Previous distance metrics seems to be appropriate for alphabetic languages like English and Eur...

We introduce the notion of conservative edit distance and mapping between two RNA stem-loops. We show that unlike the general edit distance between RNA secondary structures, the conservative edit distance can be computed in polynomial time and space, and we describe an algorithm for this problem. We show how this algorithm can be used in the more general problem of complete RNA secondary struct...