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QSAR workbench: automating QSAR modeling to drive compound design

We describe the QSAR Workbench, a system for the building and analysis of QSAR models. The system is built around the Pipeline Pilot workflow tool and provides access to a variety of model building algorithms for both continuous and categorical data. Traditionally models are built on a one by one ba...

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Autores principales: Cox, Richard, Green, Darren V. S., Luscombe, Christopher N., Malcolm, Noj, Pickett, Stephen D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3657086/
https://www.ncbi.nlm.nih.gov/pubmed/23615761
http://dx.doi.org/10.1007/s10822-013-9648-4
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author Cox, Richard
Green, Darren V. S.
Luscombe, Christopher N.
Malcolm, Noj
Pickett, Stephen D.
author_facet Cox, Richard
Green, Darren V. S.
Luscombe, Christopher N.
Malcolm, Noj
Pickett, Stephen D.
author_sort Cox, Richard
collection PubMed
description We describe the QSAR Workbench, a system for the building and analysis of QSAR models. The system is built around the Pipeline Pilot workflow tool and provides access to a variety of model building algorithms for both continuous and categorical data. Traditionally models are built on a one by one basis and fully exploring the model space of algorithms and descriptor subsets is a time consuming basis. The QSAR Workbench provides a framework to allow for multiple models to be built over a number of modeling algorithms, descriptor combinations and data splits (training and test sets). Methods to analyze and compare models are provided, enabling the user to select the most appropriate model. The Workbench provides a consistent set of routines for data preparation and chemistry normalization that are also applied for predictions. The Workbench provides a large degree of automation with the ability to publish preconfigured model building workflows for a variety of problem domains, whilst providing experienced users full access to the underlying parameterization if required. Methods are provided to allow for publication of selected models as web services, thus providing integration with the chemistry desktop. We describe the design and implementation of the QSAR Workbench and demonstrate its utility through application to two public domain datasets. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10822-013-9648-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-36570862013-05-21 QSAR workbench: automating QSAR modeling to drive compound design Cox, Richard Green, Darren V. S. Luscombe, Christopher N. Malcolm, Noj Pickett, Stephen D. J Comput Aided Mol Des Article We describe the QSAR Workbench, a system for the building and analysis of QSAR models. The system is built around the Pipeline Pilot workflow tool and provides access to a variety of model building algorithms for both continuous and categorical data. Traditionally models are built on a one by one basis and fully exploring the model space of algorithms and descriptor subsets is a time consuming basis. The QSAR Workbench provides a framework to allow for multiple models to be built over a number of modeling algorithms, descriptor combinations and data splits (training and test sets). Methods to analyze and compare models are provided, enabling the user to select the most appropriate model. The Workbench provides a consistent set of routines for data preparation and chemistry normalization that are also applied for predictions. The Workbench provides a large degree of automation with the ability to publish preconfigured model building workflows for a variety of problem domains, whilst providing experienced users full access to the underlying parameterization if required. Methods are provided to allow for publication of selected models as web services, thus providing integration with the chemistry desktop. We describe the design and implementation of the QSAR Workbench and demonstrate its utility through application to two public domain datasets. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10822-013-9648-4) contains supplementary material, which is available to authorized users. Springer Netherlands 2013-04-25 2013 /pmc/articles/PMC3657086/ /pubmed/23615761 http://dx.doi.org/10.1007/s10822-013-9648-4 Text en © The Author(s) 2013 https://creativecommons.org/licenses/by/2.0/ Open AccessThis article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
spellingShingle Article
Cox, Richard
Green, Darren V. S.
Luscombe, Christopher N.
Malcolm, Noj
Pickett, Stephen D.
QSAR workbench: automating QSAR modeling to drive compound design
title QSAR workbench: automating QSAR modeling to drive compound design
title_full QSAR workbench: automating QSAR modeling to drive compound design
title_fullStr QSAR workbench: automating QSAR modeling to drive compound design
title_full_unstemmed QSAR workbench: automating QSAR modeling to drive compound design
title_short QSAR workbench: automating QSAR modeling to drive compound design
title_sort qsar workbench: automating qsar modeling to drive compound design
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3657086/
https://www.ncbi.nlm.nih.gov/pubmed/23615761
http://dx.doi.org/10.1007/s10822-013-9648-4
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