Document
type: Class

Continuant
type: Class

Entity
type: Class

Generically Dependent Continuant
type: Class

individual
rights: termsOfUse
date: 2026-08-26T03:56:51
publisher: vivo
type: Document
label: RDF description of A consensus algorithm for approximate pattern matching in protein sequences [Un algoritmo de consenso para la búsqueda aproximada de patrones en cadenas de proteínas] - http://orbis.uaslp.mx/vivo/individual/scopus2978

Article
type: Class

Information Content Entity
type: Class

A consensus algorithm for approximate pattern matching in protein sequences [Un algoritmo de consenso para la búsqueda aproximada de patrones en cadenas de proteínas]
related by: authorship_17415
crisid: 2979
origen: scopus
related by: authorship_17416
type: Article
type: Information Content Entity
type: Entity
related by: authorship_17417
estado: published
e iscopus: 2-s2.0-84875646929
issue: 2
most specific type: Document
page end: 99
page start: 87
type: Document
most specific type: Article
related by: authorship_17419
date time value: article date 2979
type: Generically Dependent Continuant
type: Thing
has publication venue: Revista Mexicana de Ingenieria Biomedica
volume: 33
abstract: In bioinformatics, one of the main tools which allow scientists to find common characteristics in protein or DNA sequences of different species is the approximate matching of strings. From the computational point of view, the difficulty of approximate string matching lies in finding adequate measures to efficiently compare two strings, since, in many cases, one is interested in performing searches in real time, within large databases. In this paper we propose a novel method for approximate string matching based on a generalization of the algorithm proposed by Baeza-Yates and Perleberg in 1996 for computing the Hamming distance between two sequences. In addition, a post-processing stage which significantly reduces the number of false positives is presented. The proposed method has been evaluated in synthetic cases of random sequences, and with real cases of plant protein sequences. Results show that the proposed algorithm is highly efficient in computational terms and in specificity, especially when compared against a previously published method, which is based on the phase correlation function.
freetext keyword: Approximate string matching; Bioinformatics; Consensus algorithms; Protein sequences
type: Continuant

Revista Mexicana de Ingenieria Biomedica
type: Generically Dependent Continuant
type: Document
type: Entity
type: Periodical
type: Collection
publication venue for: A consensus algorithm for approximate pattern matching in protein sequences [Un algoritmo de consenso para la búsqueda aproximada de patrones en cadenas de proteínas]
type: Journal
type: Thing
type: Continuant
type: Information Content Entity