High-dimensional QSAR classification model for anti-hepatitis C virus activity of thiourea derivatives based on the sparse logistic regression model with a bridge penalty

High-dimensional QSAR classification model for anti-hepatitis C virus activity of thiourea derivatives based on the sparse logistic regression model with a bridge penalty

This study addresses the problem of the high-dimensionality of quantitative structure-activity relationship (QSAR) classification modeling. A new selection of descriptors that truly affect biological activity and a QSAR classification model estimation method are proposed by combining the sparse logi...

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Main Authors: Algamal, Z. Y., Lee, M. H., Al-Fakih, A. M., Aziz, M.
Format: Article
Published: John Wiley and Sons Ltd 2017
Subjects:
QA Mathematics
Online Access:http://eprints.utm.my/id/eprint/76444/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85017532383&doi=10.1002%2fcem.2889&partnerID=40&md5=92b3166570641182f2b42a6a5c827275
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Institution: Universiti Teknologi Malaysia
id my.utm.76444
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spelling my.utm.764442018-05-31T09:20:57Z http://eprints.utm.my/id/eprint/76444/ High-dimensional QSAR classification model for anti-hepatitis C virus activity of thiourea derivatives based on the sparse logistic regression model with a bridge penalty Algamal, Z. Y. Lee, M. H. Al-Fakih, A. M. Aziz, M. QA Mathematics This study addresses the problem of the high-dimensionality of quantitative structure-activity relationship (QSAR) classification modeling. A new selection of descriptors that truly affect biological activity and a QSAR classification model estimation method are proposed by combining the sparse logistic regression model with a bridge penalty for classifying the anti-hepatitis C virus activity of thiourea derivatives. Compared to other commonly used sparse methods, the proposed method shows superior results in terms of classification accuracy and model interpretation. John Wiley and Sons Ltd 2017 Article PeerReviewed Algamal, Z. Y. and Lee, M. H. and Al-Fakih, A. M. and Aziz, M. (2017) High-dimensional QSAR classification model for anti-hepatitis C virus activity of thiourea derivatives based on the sparse logistic regression model with a bridge penalty. Journal of Chemometrics, 31 (6). ISSN 0886-9383 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85017532383&doi=10.1002%2fcem.2889&partnerID=40&md5=92b3166570641182f2b42a6a5c827275 DOI:10.1002/cem.2889
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA Mathematics
spellingShingle QA Mathematics
Algamal, Z. Y.
Lee, M. H.
Al-Fakih, A. M.
Aziz, M.
High-dimensional QSAR classification model for anti-hepatitis C virus activity of thiourea derivatives based on the sparse logistic regression model with a bridge penalty
description This study addresses the problem of the high-dimensionality of quantitative structure-activity relationship (QSAR) classification modeling. A new selection of descriptors that truly affect biological activity and a QSAR classification model estimation method are proposed by combining the sparse logistic regression model with a bridge penalty for classifying the anti-hepatitis C virus activity of thiourea derivatives. Compared to other commonly used sparse methods, the proposed method shows superior results in terms of classification accuracy and model interpretation.
format Article
author Algamal, Z. Y.
Lee, M. H.
Al-Fakih, A. M.
Aziz, M.
author_facet Algamal, Z. Y.
Lee, M. H.
Al-Fakih, A. M.
Aziz, M.
author_sort Algamal, Z. Y.
title High-dimensional QSAR classification model for anti-hepatitis C virus activity of thiourea derivatives based on the sparse logistic regression model with a bridge penalty
title_short High-dimensional QSAR classification model for anti-hepatitis C virus activity of thiourea derivatives based on the sparse logistic regression model with a bridge penalty
title_full High-dimensional QSAR classification model for anti-hepatitis C virus activity of thiourea derivatives based on the sparse logistic regression model with a bridge penalty
title_fullStr High-dimensional QSAR classification model for anti-hepatitis C virus activity of thiourea derivatives based on the sparse logistic regression model with a bridge penalty
title_full_unstemmed High-dimensional QSAR classification model for anti-hepatitis C virus activity of thiourea derivatives based on the sparse logistic regression model with a bridge penalty
title_sort high-dimensional qsar classification model for anti-hepatitis c virus activity of thiourea derivatives based on the sparse logistic regression model with a bridge penalty
publisher John Wiley and Sons Ltd
publishDate 2017
url http://eprints.utm.my/id/eprint/76444/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85017532383&doi=10.1002%2fcem.2889&partnerID=40&md5=92b3166570641182f2b42a6a5c827275
_version_ 1643657312027541504

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