Capitulo de libro

### A FAST ALGORITHM ON AVERAGE FOR ALL-AGAINST-ALL SEQUENCE MATCHING

##### Date

1999##### Registration in:

0-7695-0268-7

1990627

##### Institutions

##### Abstract

We present an algorithm which attempts to align pairs of
subsequences from a database of genetic sequences. The algorithm
simulates the classical dynamic programming alignment algorithm over a
suffix array of the database. We provide a detailed average case
analysis which shows that the running time of the algorithm is
subquadratic with respect to the database size. A similar algorithm
solves the approximate string matching problem in sublinear average time.We present an algorithm which attempts to align pairs of
subsequences from a database of genetic sequences. The algorithm
simulates the classical dynamic programming alignment algorithm over a
suffix array of the database. We provide a detailed average case
analysis which shows that the running time of the algorithm is
subquadratic with respect to the database size. A similar algorithm
solves the approximate string matching problem in sublinear average time.We present an algorithm which attempts to align pairs of
subsequences from a database of genetic sequences. The algorithm
simulates the classical dynamic programming alignment algorithm over a
suffix array of the database. We provide a detailed average case
analysis which shows that the running time of the algorithm is
subquadratic with respect to the database size. A similar algorithm
solves the approximate string matching problem in sublinear average time.We present an algorithm which attempts to align pairs of
subsequences from a database of genetic sequences. The algorithm
simulates the classical dynamic programming alignment algorithm over a
suffix array of the database. We provide a detailed average case
analysis which shows that the running time of the algorithm is
subquadratic with respect to the database size. A similar algorithm
solves the approximate string matching problem in sublinear average time.We present an algorithm which attempts to align pairs of
subsequences from a database of genetic sequences. The algorithm
simulates the classical dynamic programming alignment algorithm over a
suffix array of the database. We provide a detailed average case
analysis which shows that the running time of the algorithm is
subquadratic with respect to the database size. A similar algorithm
solves the approximate string matching problem in sublinear average time.We present an algorithm which attempts to align pairs of
subsequences from a database of genetic sequences. The algorithm
simulates the classical dynamic programming alignment algorithm over a
suffix array of the database. We provide a detailed average case
analysis which shows that the running time of the algorithm is
subquadratic with respect to the database size. A similar algorithm
solves the approximate string matching problem in sublinear average time.We present an algorithm which attempts to align pairs of
subsequences from a database of genetic sequences. The algorithm
simulates the classical dynamic programming alignment algorithm over a
suffix array of the database. We provide a detailed average case
analysis which shows that the running time of the algorithm is
subquadratic with respect to the database size. A similar algorithm
solves the approximate string matching problem in sublinear average time.We present an algorithm which attempts to align pairs of
subsequences from a database of genetic sequences. The algorithm
simulates the classical dynamic programming alignment algorithm over a
suffix array of the database. We provide a detailed average case
analysis which shows that the running time of the algorithm is
subquadratic with respect to the database size. A similar algorithm
solves the approximate string matching problem in sublinear average time.We present an algorithm which attempts to align pairs of
subsequences from a database of genetic sequences. The algorithm
simulates the classical dynamic programming alignment algorithm over a
suffix array of the database. We provide a detailed average case
analysis which shows that the running time of the algorithm is
subquadratic with respect to the database size. A similar algorithm
solves the approximate string matching problem in sublinear average time.We present an algorithm which attempts to align pairs of
subsequences from a database of genetic sequences. The algorithm
simulates the classical dynamic programming alignment algorithm over a
suffix array of the database. We provide a detailed average case
analysis which shows that the running time of the algorithm is
subquadratic with respect to the database size. A similar algorithm
solves the approximate string matching problem in sublinear average time.We present an algorithm which attempts to align pairs of
subsequences from a database of genetic sequences. The algorithm
simulates the classical dynamic programming alignment algorithm over a
suffix array of the database. We provide a detailed average case
analysis which shows that the running time of the algorithm is
subquadratic with respect to the database size. A similar algorithm
solves the approximate string matching problem in sublinear average time.We present an algorithm which attempts to align pairs of
subsequences from a database of genetic sequences. The algorithm
simulates the classical dynamic programming alignment algorithm over a
suffix array of the database. We provide a detailed average case
analysis which shows that the running time of the algorithm is
subquadratic with respect to the database size. A similar algorithm
solves the approximate string matching problem in sublinear average time.We present an algorithm which attempts to align pairs of
subsequences from a database of genetic sequences. The algorithm
simulates the classical dynamic programming alignment algorithm over a
suffix array of the database. We provide a detailed average case
analysis which shows that the running time of the algorithm is
subquadratic with respect to the database size. A similar algorithm
solves the approximate string matching problem in sublinear average time.We present an algorithm which attempts to align pairs of
subsequences from a database of genetic sequences. The algorithm
simulates the classical dynamic programming alignment algorithm over a
suffix array of the database. We provide a detailed average case
analysis which shows that the running time of the algorithm is
subquadratic with respect to the database size. A similar algorithm
solves the approximate string matching problem in sublinear average time.We present an algorithm which attempts to align pairs of
subsequences from a database of genetic sequences. The algorithm
simulates the classical dynamic programming alignment algorithm over a
suffix array of the database. We provide a detailed average case
analysis which shows that the running time of the algorithm is
subquadratic with respect to the database size. A similar algorithm
solves the approximate string matching problem in sublinear average time.We present an algorithm which attempts to align pairs of
subsequences from a database of genetic sequences. The algorithm
simulates the classical dynamic programming alignment algorithm over a
suffix array of the database. We provide a detailed average case
analysis which shows that the running time of the algorithm is
subquadratic with respect to the database size. A similar algorithm
solves the approximate string matching problem in sublinear average time.We present an algorithm which attempts to align pairs of
subsequences from a database of genetic sequences. The algorithm
simulates the classical dynamic programming alignment algorithm over a
suffix array of the database. We provide a detailed average case
analysis which shows that the running time of the algorithm is
subquadratic with respect to the database size. A similar algorithm
solves the approximate string matching problem in sublinear average time.We present an algorithm which attempts to align pairs of
subsequences from a database of genetic sequences. The algorithm
simulates the classical dynamic programming alignment algorithm over a
suffix array of the database. We provide a detailed average case
analysis which shows that the running time of the algorithm is
subquadratic with respect to the database size. A similar algorithm
solves the approximate string matching problem in sublinear average time.We present an algorithm which attempts to align pairs of
subsequences from a database of genetic sequences. The algorithm
simulates the classical dynamic programming alignment algorithm over a
suffix array of the database. We provide a detailed average case
analysis which shows that the running time of the algorithm is
subquadratic with respect to the database size. A similar algorithm
solves the approximate string matching problem in sublinear average time.We present an algorithm which attempts to align pairs of
subsequences from a database of genetic sequences. The algorithm
simulates the classical dynamic programming alignment algorithm over a
suffix array of the database. We provide a detailed average case
analysis which shows that the running time of the algorithm is
subquadratic with respect to the database size. A similar algorithm
solves the approximate string matching problem in sublinear average time.