ISSN:
1432-0541
Keywords:
Approximate match
;
Dynamic programming
;
Index
;
word neighborhood
Source:
Springer Online Journal Archives 1860-2000
Topics:
Computer Science
,
Mathematics
Notes:
Abstract Given a relatively short query stringW of lengthP, a long subject stringA of lengthN, and a thresholdD, theapproximate keyword search problem is to find all substrings ofA that align withW with not more than D insertions, deletions, and mismatches. In typical applications, such as searching a DNA sequence database, the size of the “database”A is much larger than that of the queryW, e.g.,N is on the order of millions or billions andP is a hundred to a thousand. In this paper we present an algorithm that given a precomputedindex of the databaseA, finds rare matches in time that issublinear inN, i.e.,N c for somec〈1. The sequenceA must be overa. finite alphabet σ. More precisely, our algorithm requires 0(DN pow(ɛ) logN) expected-time where ɛ=D/P is the maximum number of differences as a percentage of query length, and pow(ɛ) is an increasing and concave function that is 0 when ɛ=0. Thus the algorithm is superior to current O(DN) algorithms when ɛ is small enough to guarantee that pow(ɛ) 〈 1. As seen in the paper, this is true for a wide range of ɛ, e.g., ɛ. up to 33% for DNA sequences (¦⌆¦=4) and 56% for proteins sequences (¦⌆¦=20). In preliminary practical experiments, the approach gives a 50-to 500-fold improvement over previous algorithms for prolems of interest in molecular biology.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF01185432
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