dc.date.accessioned2016-12-27T21:48:55Z
dc.date.accessioned2018-06-13T23:04:11Z
dc.date.available2016-12-27T21:48:55Z
dc.date.available2018-06-13T23:04:11Z
dc.date.created2016-12-27T21:48:55Z
dc.date.issued1999
dc.identifier0-7695-0268-7 
dc.identifierhttp://hdl.handle.net/10533/165078
dc.identifier1990627
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1543880
dc.description.abstractWe 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.
dc.languageeng
dc.publisherIEEE TECHNICAL COMMITTEE ON DATA ENGINEERING
dc.relationinfo:eu-repo/grantAgreement/Fondecyt/1990627
dc.relationinfo:eu-repo/semantics/dataset/hdl.handle.net/10533/93479
dc.relationinstname: Conicyt
dc.relationreponame: Repositorio Digital RI2.0
dc.relationinstname: Conicyt
dc.relationreponame: Repositorio Digital RI 2.0
dc.rightsinfo:eu-repo/semantics/openAccess
dc.titleA FAST ALGORITHM ON AVERAGE FOR ALL-AGAINST-ALL SEQUENCE MATCHING
dc.typeCapitulo de libro


Este ítem pertenece a la siguiente institución