Detection of selective cationic amphipatic antibacterial peptides by Hidden Markov models

Antibacterial peptides are researched mainly for the potential benefit they have in a variety of socially relevant diseases, used by the host to protect itself from different types of pathogenic bacteria. We used the mathematical-computational method known as Hidden Markov models (HMMs) in targeting...

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Detalles Bibliográficos
Autores: Polanco, C, Samaniego, JL
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2009
País:México
Institución:Universidad Nacional Autónoma de México
Repositorio:Sistema de Información de la Facultad de Ciencias, UNAM
OAI Identifier:oai:repositorio.fciencias.unam.mx:11154/3152
Acceso en línea:http://hdl.handle.net/11154/3152
Access Level:acceso abierto
Palabra clave:Biochemistry & Molecular Biology
antibacterial peptides
Hidden Markov models
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spelling Detection of selective cationic amphipatic antibacterial peptides by Hidden Markov modelsPolanco, CSamaniego, JLBiochemistry & Molecular Biologyantibacterial peptidesHidden Markov modelsAntibacterial peptides are researched mainly for the potential benefit they have in a variety of socially relevant diseases, used by the host to protect itself from different types of pathogenic bacteria. We used the mathematical-computational method known as Hidden Markov models (HMMs) in targeting a subset of antibacterial peptides named Selective Cationic Amphipatic Antibacterial Peptides (SCAAPs). The main difference in the implementation of HMMs was focused on the detection of SCAAP using principally five physical-chemical properties for each candidate SCAAPs, instead of using the statistical information about the amino acids which form a peptide. By this method a cluster of antibacterial peptides was detected and as a result the following were found: 9 SCAAPs, 6 synthetic antibacterial peptides that belong to a subregion of Cecropin A and Magainin 2, and 19 peptides from the Cecropin A family. A scoring function was developed using HMMs as its core, uniquely employing information accessible from the databases.2011-01-22T10:25:55Z2011-01-22T10:25:55Z2009info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article0001-527Xhttp://hdl.handle.net/11154/315259656(1):167-176reponame:Sistema de Información de la Facultad de Ciencias, UNAMinstname:Universidad Nacional Autónoma de Méxicoinstacron:UNAMenActa Biochimica Polonicainfo:eu-repo/semantics/openAccessoai:repositorio.fciencias.unam.mx:11154/31522025-09-17T19:21:33Z
dc.title.none.fl_str_mv Detection of selective cationic amphipatic antibacterial peptides by Hidden Markov models
title Detection of selective cationic amphipatic antibacterial peptides by Hidden Markov models
spellingShingle Detection of selective cationic amphipatic antibacterial peptides by Hidden Markov models
Polanco, C
Biochemistry & Molecular Biology
antibacterial peptides
Hidden Markov models
title_short Detection of selective cationic amphipatic antibacterial peptides by Hidden Markov models
title_full Detection of selective cationic amphipatic antibacterial peptides by Hidden Markov models
title_fullStr Detection of selective cationic amphipatic antibacterial peptides by Hidden Markov models
title_full_unstemmed Detection of selective cationic amphipatic antibacterial peptides by Hidden Markov models
title_sort Detection of selective cationic amphipatic antibacterial peptides by Hidden Markov models
dc.creator.none.fl_str_mv Polanco, C
Samaniego, JL
author Polanco, C
author_facet Polanco, C
Samaniego, JL
author_role author
author2 Samaniego, JL
author2_role author
dc.subject.none.fl_str_mv Biochemistry & Molecular Biology
antibacterial peptides
Hidden Markov models
topic Biochemistry & Molecular Biology
antibacterial peptides
Hidden Markov models
description Antibacterial peptides are researched mainly for the potential benefit they have in a variety of socially relevant diseases, used by the host to protect itself from different types of pathogenic bacteria. We used the mathematical-computational method known as Hidden Markov models (HMMs) in targeting a subset of antibacterial peptides named Selective Cationic Amphipatic Antibacterial Peptides (SCAAPs). The main difference in the implementation of HMMs was focused on the detection of SCAAP using principally five physical-chemical properties for each candidate SCAAPs, instead of using the statistical information about the amino acids which form a peptide. By this method a cluster of antibacterial peptides was detected and as a result the following were found: 9 SCAAPs, 6 synthetic antibacterial peptides that belong to a subregion of Cecropin A and Magainin 2, and 19 peptides from the Cecropin A family. A scoring function was developed using HMMs as its core, uniquely employing information accessible from the databases.
publishDate 2009
dc.date.none.fl_str_mv 2009
2011-01-22T10:25:55Z
2011-01-22T10:25:55Z
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv 0001-527X
http://hdl.handle.net/11154/3152
596
identifier_str_mv 0001-527X
596
url http://hdl.handle.net/11154/3152
dc.language.none.fl_str_mv en
language_invalid_str_mv en
dc.relation.none.fl_str_mv Acta Biochimica Polonica
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv 56(1):167-176
reponame:Sistema de Información de la Facultad de Ciencias, UNAM
instname:Universidad Nacional Autónoma de México
instacron:UNAM
instname_str Universidad Nacional Autónoma de México
instacron_str UNAM
institution UNAM
reponame_str Sistema de Información de la Facultad de Ciencias, UNAM
collection Sistema de Información de la Facultad de Ciencias, UNAM
repository.name.fl_str_mv
repository.mail.fl_str_mv
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