Repositorio ANID Producción científica asociada a proyectos y becas financiadas por ANID

  • Login
Más tiposGuía de búsquedas avanzadas
  • Programa
  • Institución
  • Año de concurso
  • Disciplinas
    • Disciplinas Fondecyt
    • Áreas Fondef
    • Sector de aplicación
    • Clasificaciones OECD
  • Regiones de Chile
  • Menu
    • Programa
    • Institución
    • Año de concurso
    • Disciplinas Fondecyt
    • Áreas Fondef
    • Sector de aplicación
    • Clasificaciones OECD
    • Regiones de Chile
View Item 
  •   DSpace Home
  • Resultados de Proyectos
  • Productividad
  • Capítulos de Libros
  • View Item
  •   DSpace Home
  • Resultados de Proyectos
  • Productividad
  • Capítulos de Libros
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

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

Type
Capitulo de libro
Program
Programa FONDECYT
Conicyt Instrument
Proyectos Regulares
Author
Baeza Yates, Ricardo Alberto
Gonnet, Gaston H.
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 a...   Ver más
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.   Ver menos
Project Id
1990627
Contest
Concurso Nacional Regular 1999
Book's title
IEEE COMPUTER SOCIETY DL
Publication date of the book
1999
Start page
16
End page
23
Country
ESTADOS UNIDOS DE AMERICA
Metadata
Show full item record

ANID Agencia Nacional de Investigación y Desarrollo

Moneda 1375, Santiago de Chile. Teléfono (+56 2) 365 44 00

¿NECESITAS AYUDA?

Centro de ayuda OIRS

o llámanos directamente al

(+56 2) 365 44 00

  • Políticas de Privacidad
  • Gobierno Transparente
  • Trabaja con Nosotros
  • Donación de Bienes
  • Webmail
  • Contacto
  • Acerca de RI 2.0
  • Otros repositorios
  • Políticas
  • Recursos de Información Anid
  • Ayuda
  • FAQs
Material de Donación
Contacto:

Moneda 1375, piso 13, Santiago.
Teléfono: (+562) 36 54 462.
Horario: L-J: 09:00 a 17:00 hrs.                   Vi: 09:00 a 14:00 hrs.

biblioteca@anid.cl

Nuevo Depósito
Política de Depósito

Browse

All of DSpaceCommunities & CollectionsThis CollectionAuthorsTitlesProject IdDocument TypeSubject

ANID Agencia Nacional de Investigación y Desarrollo

Moneda 1375, Santiago de Chile. Teléfono (+56 2) 365 44 00

¿NECESITAS AYUDA?

Centro de ayuda OIRS

o llámanos directamente al

(+56 2) 365 44 00

  • Políticas de Privacidad
  • Gobierno Transparente
  • Trabaja con Nosotros
  • Donación de Bienes
  • Webmail
  • Contacto
  • Acerca de RI 2.0
  • Otros repositorios
  • Políticas
  • Recursos de Información Anid
  • Ayuda
  • FAQs
       

Guía de búsquedas avanzadas

Nuestro Repositorio Digital cuenta con un gran número de búsquedas avanzadas, te invitamos a conocerlas mediante este video tutorial, aprenderás a utilizarlas para enriquecer tus resultados de búsqueda.

Versión PDF
  • Simple
  • Filtros
  • Frases
  • Metadato
  • Comodín
  • Difusa
  • Proximidad
  • Booleanos
  • Agrupación
  • Fechas
  • Ejemplos
Tu navegador no soporta videos HTML5, Puedes descargarlo.