קלים יפרמנקו

אקדמי בכיר

Mismatch sampling

Raphaël Clifford, Klim Efremenko, Benny Porat, Ely Porat, Amir Rothschild

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.

שפת פרסום אנגלית
דפים 99-108
כתב עת Lecture Notes in Computer Science
כרך 5280 LNCS
סטטוס פרסום פורסם - 01.01.2008

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science
גישה למסמך
10.1007/978-3-540-89097-3_11
קבצים וקישורים אחרים
Link to publication in Scopus