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

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.