Seleção de variáveis em QSAR
Autor(a) principal: | |
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Data de Publicação: | 2002 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Química Nova (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-40422002000300017 |
Resumo: | The process of building mathematical models in quantitative structure-activity relationship (QSAR) studies is generally limited by the size of the dataset used to select variables from. For huge datasets, the task of selecting a given number of variables that produces the best linear model can be enormous, if not unfeasible. In this case, some methods can be used to separate good parameter combinations from the bad ones. In this paper three methodologies are analyzed: systematic search, genetic algorithm and chemometric methods. These methods have been exposed and discussed through practical examples. |
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Química Nova (Online) |
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Seleção de variáveis em QSARsystematic searchgenetic algorithmchemometric methodsThe process of building mathematical models in quantitative structure-activity relationship (QSAR) studies is generally limited by the size of the dataset used to select variables from. For huge datasets, the task of selecting a given number of variables that produces the best linear model can be enormous, if not unfeasible. In this case, some methods can be used to separate good parameter combinations from the bad ones. In this paper three methodologies are analyzed: systematic search, genetic algorithm and chemometric methods. These methods have been exposed and discussed through practical examples.Sociedade Brasileira de Química2002-05-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-40422002000300017Química Nova v.25 n.3 2002reponame:Química Nova (Online)instname:Sociedade Brasileira de Química (SBQ)instacron:SBQ10.1590/S0100-40422002000300017info:eu-repo/semantics/openAccessFerreira,Márcia Miguel CastroMontanari,Carlos AlbertoGaudio,Anderson Coserpor2002-08-07T00:00:00Zoai:scielo:S0100-40422002000300017Revistahttps://www.scielo.br/j/qn/ONGhttps://old.scielo.br/oai/scielo-oai.phpquimicanova@sbq.org.br1678-70640100-4042opendoar:2002-08-07T00:00Química Nova (Online) - Sociedade Brasileira de Química (SBQ)false |
dc.title.none.fl_str_mv |
Seleção de variáveis em QSAR |
title |
Seleção de variáveis em QSAR |
spellingShingle |
Seleção de variáveis em QSAR Ferreira,Márcia Miguel Castro systematic search genetic algorithm chemometric methods |
title_short |
Seleção de variáveis em QSAR |
title_full |
Seleção de variáveis em QSAR |
title_fullStr |
Seleção de variáveis em QSAR |
title_full_unstemmed |
Seleção de variáveis em QSAR |
title_sort |
Seleção de variáveis em QSAR |
author |
Ferreira,Márcia Miguel Castro |
author_facet |
Ferreira,Márcia Miguel Castro Montanari,Carlos Alberto Gaudio,Anderson Coser |
author_role |
author |
author2 |
Montanari,Carlos Alberto Gaudio,Anderson Coser |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Ferreira,Márcia Miguel Castro Montanari,Carlos Alberto Gaudio,Anderson Coser |
dc.subject.por.fl_str_mv |
systematic search genetic algorithm chemometric methods |
topic |
systematic search genetic algorithm chemometric methods |
description |
The process of building mathematical models in quantitative structure-activity relationship (QSAR) studies is generally limited by the size of the dataset used to select variables from. For huge datasets, the task of selecting a given number of variables that produces the best linear model can be enormous, if not unfeasible. In this case, some methods can be used to separate good parameter combinations from the bad ones. In this paper three methodologies are analyzed: systematic search, genetic algorithm and chemometric methods. These methods have been exposed and discussed through practical examples. |
publishDate |
2002 |
dc.date.none.fl_str_mv |
2002-05-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-40422002000300017 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-40422002000300017 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
10.1590/S0100-40422002000300017 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Química |
publisher.none.fl_str_mv |
Sociedade Brasileira de Química |
dc.source.none.fl_str_mv |
Química Nova v.25 n.3 2002 reponame:Química Nova (Online) instname:Sociedade Brasileira de Química (SBQ) instacron:SBQ |
instname_str |
Sociedade Brasileira de Química (SBQ) |
instacron_str |
SBQ |
institution |
SBQ |
reponame_str |
Química Nova (Online) |
collection |
Química Nova (Online) |
repository.name.fl_str_mv |
Química Nova (Online) - Sociedade Brasileira de Química (SBQ) |
repository.mail.fl_str_mv |
quimicanova@sbq.org.br |
_version_ |
1750318102682271744 |