Abstract
We consider the well known problem of pattern matching under the Hamming distance. Previous approaches have shown how to count the number of mismatches efficiently, especially when a bound is known for the maximum Hamming distance. Our interest is different in that we wish collect a random sample of mismatches of fixed size at each position in the text. Given a pattern p of length m and a text t of length n, we show how to sample with high probability c mismatches where possible from every alignment of p and t in O((c∈+∈logn) (n∈+∈mlogm)logm) time. Further, we guarantee that the mismatches are sampled uniformly and can therefore be seen as representative of the types of mismatches that occur. © 2009 Springer Berlin Heidelberg.
| Original language | English |
|---|---|
| Pages (from-to) | 99-108 |
| Number of pages | 10 |
| Journal | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Volume | 5280 LNCS |
| DOIs | |
| State | Published - 31 Dec 2008 |
| Event | 15th International Symposium on String Processing and Information Retrieval, SPIRE 2008 - Melbourne. VIC, Australia Duration: 10 Nov 2008 → 12 Nov 2008 |
Bibliographical note
Funding Information:This work was supported in part by the Binational Science Foundation (BSF) grant 2006334 and Israel Science Foundation (ISF) grant 1484/08 as well as the Engineering and Physical Sciences Research Council (EPSRC).
Funding
This work was supported in part by the Binational Science Foundation (BSF) grant 2006334 and Israel Science Foundation (ISF) grant 1484/08 as well as the Engineering and Physical Sciences Research Council (EPSRC).