Classification DNA sequences using Gap–Weighted subsequences kernel

The aim of this paper is to show experimental results of classification DNA sequences using gap–weighted subsequences kernel including the assess the expected error rate of a classification algorithm. The process involve a type of kernel specific with a classification algorithm for learn to recogniz...

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Autor principal: Soto, Wilson
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2009
Materias:
Ciencias Informáticas
Algorithms
ADN
bioinformatics
gap–weighted subsequences kerne
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/20888
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-20888
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Algorithms
ADN
bioinformatics
gap–weighted subsequences kerne
spellingShingle Ciencias Informáticas
Algorithms
ADN
bioinformatics
gap–weighted subsequences kerne
Soto, Wilson
Classification DNA sequences using Gap–Weighted subsequences kernel
topic_facet Ciencias Informáticas
Algorithms
ADN
bioinformatics
gap–weighted subsequences kerne
description The aim of this paper is to show experimental results of classification DNA sequences using gap–weighted subsequences kernel including the assess the expected error rate of a classification algorithm. The process involve a type of kernel specific with a classification algorithm for learn to recognize sites that regulate transcription, sites that can be detected in the laboratory as DNaseI hypersensitive sites (HSs) on DNA sequences. The classification algorithm is support vector machine (SVM), which learns by example to discriminate between two given classes of data. The DNA sequences are converted using gap–weighted subsequences kernel in a matrix kernel, which is processed by the classification algorithm to produce a model with the which we can predict the classification of new examples. It is important to know that a high accuracy with computational methods for the identification of the DNaseI hypersensitive sites would to help to speed up the functional annotation of the human genome
format Objeto de conferencia
Objeto de conferencia
author Soto, Wilson
author_facet Soto, Wilson
author_sort Soto, Wilson
title Classification DNA sequences using Gap–Weighted subsequences kernel
title_short Classification DNA sequences using Gap–Weighted subsequences kernel
title_full Classification DNA sequences using Gap–Weighted subsequences kernel
title_fullStr Classification DNA sequences using Gap–Weighted subsequences kernel
title_full_unstemmed Classification DNA sequences using Gap–Weighted subsequences kernel
title_sort classification dna sequences using gap–weighted subsequences kernel
publishDate 2009
url http://sedici.unlp.edu.ar/handle/10915/20888
work_keys_str_mv AT sotowilson classificationdnasequencesusinggapweightedsubsequenceskernel
bdutipo_str Repositorios
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