Highlights: Predicting the cross-immunoreactivity of hepatitis C virus hyper-variable region 1 peptides using polynomial neural networks PNN models of HCV-HVR1 cross-reactivity
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/161611 |
Resumo: | Ctr Dis Control, Div Viral Hepatitis, Atlanta, GA 30333 USA |
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Repositório Institucional da UNESP |
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Highlights: Predicting the cross-immunoreactivity of hepatitis C virus hyper-variable region 1 peptides using polynomial neural networks PNN models of HCV-HVR1 cross-reactivityhepatitis C viruspolynomial neural networks (PNN)predictionvaccinelinear projectionquantitative-structure-activity-relationship (QSAR)Ctr Dis Control, Div Viral Hepatitis, Atlanta, GA 30333 USAUNESP, IBILCE, Dept Biol, Sao Jose Do Rio Preto, BrazilUNESP, IBILCE, Dept Biol, Sao Jose Do Rio Preto, BrazilIeeeCtr Dis ControlUniversidade Estadual Paulista (Unesp)Lara, JamesKhudyakov, YuryRossi, Livia [UNESP]Vaughan, GilbertaIEEE2018-11-26T16:40:40Z2018-11-26T16:40:40Z2015-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject12015 Ieee 5th International Conference On Computational Advances In Bio And Medical Sciences (iccabs). New York: Ieee, 1 p., 2015.2164-229Xhttp://hdl.handle.net/11449/161611WOS:000377899500030Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2015 Ieee 5th International Conference On Computational Advances In Bio And Medical Sciences (iccabs)info:eu-repo/semantics/openAccess2021-10-23T21:44:22Zoai:repositorio.unesp.br:11449/161611Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T19:18:27.996478Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Highlights: Predicting the cross-immunoreactivity of hepatitis C virus hyper-variable region 1 peptides using polynomial neural networks PNN models of HCV-HVR1 cross-reactivity |
title |
Highlights: Predicting the cross-immunoreactivity of hepatitis C virus hyper-variable region 1 peptides using polynomial neural networks PNN models of HCV-HVR1 cross-reactivity |
spellingShingle |
Highlights: Predicting the cross-immunoreactivity of hepatitis C virus hyper-variable region 1 peptides using polynomial neural networks PNN models of HCV-HVR1 cross-reactivity Lara, James hepatitis C virus polynomial neural networks (PNN) prediction vaccine linear projection quantitative-structure-activity-relationship (QSAR) |
title_short |
Highlights: Predicting the cross-immunoreactivity of hepatitis C virus hyper-variable region 1 peptides using polynomial neural networks PNN models of HCV-HVR1 cross-reactivity |
title_full |
Highlights: Predicting the cross-immunoreactivity of hepatitis C virus hyper-variable region 1 peptides using polynomial neural networks PNN models of HCV-HVR1 cross-reactivity |
title_fullStr |
Highlights: Predicting the cross-immunoreactivity of hepatitis C virus hyper-variable region 1 peptides using polynomial neural networks PNN models of HCV-HVR1 cross-reactivity |
title_full_unstemmed |
Highlights: Predicting the cross-immunoreactivity of hepatitis C virus hyper-variable region 1 peptides using polynomial neural networks PNN models of HCV-HVR1 cross-reactivity |
title_sort |
Highlights: Predicting the cross-immunoreactivity of hepatitis C virus hyper-variable region 1 peptides using polynomial neural networks PNN models of HCV-HVR1 cross-reactivity |
author |
Lara, James |
author_facet |
Lara, James Khudyakov, Yury Rossi, Livia [UNESP] Vaughan, Gilberta IEEE |
author_role |
author |
author2 |
Khudyakov, Yury Rossi, Livia [UNESP] Vaughan, Gilberta IEEE |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Ctr Dis Control Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Lara, James Khudyakov, Yury Rossi, Livia [UNESP] Vaughan, Gilberta IEEE |
dc.subject.por.fl_str_mv |
hepatitis C virus polynomial neural networks (PNN) prediction vaccine linear projection quantitative-structure-activity-relationship (QSAR) |
topic |
hepatitis C virus polynomial neural networks (PNN) prediction vaccine linear projection quantitative-structure-activity-relationship (QSAR) |
description |
Ctr Dis Control, Div Viral Hepatitis, Atlanta, GA 30333 USA |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-01-01 2018-11-26T16:40:40Z 2018-11-26T16:40:40Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
2015 Ieee 5th International Conference On Computational Advances In Bio And Medical Sciences (iccabs). New York: Ieee, 1 p., 2015. 2164-229X http://hdl.handle.net/11449/161611 WOS:000377899500030 |
identifier_str_mv |
2015 Ieee 5th International Conference On Computational Advances In Bio And Medical Sciences (iccabs). New York: Ieee, 1 p., 2015. 2164-229X WOS:000377899500030 |
url |
http://hdl.handle.net/11449/161611 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2015 Ieee 5th International Conference On Computational Advances In Bio And Medical Sciences (iccabs) |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
1 |
dc.publisher.none.fl_str_mv |
Ieee |
publisher.none.fl_str_mv |
Ieee |
dc.source.none.fl_str_mv |
Web of Science reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129050223312896 |