A new adaptive L1-norm for optimal descriptor selection of high-dimensional QSAR classification model for anti-hepatitis C virus activity of thiourea derivatives-Reference-Cited by-同舟云学术

A new adaptive L1-norm for optimal descriptor selection of high-dimensional QSAR classification model for anti-hepatitis C virus activity of thiourea derivatives

Published:2017-01-02 Issue:1 Volume:28 Page:75-90
ISSN:1062-936X
Container-title:SAR and QSAR in Environmental Research
language:en
Short-container-title:SAR and QSAR in Environmental Research

Author:

Algamal Z. Y.¹,Lee M. H.¹

Affiliation:

1. Department of Mathematical Sciences, Universiti Teknologi Malaysia, Skudai, Johor, Malaysia

Funder

Ministry of Higher Education, Malaysia

Universiti Teknologi Malaysia

Publisher

Informa UK Limited

Subject

Drug Discovery,Molecular Medicine,General Medicine,Bioengineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/1062936X.2017.1278618

Reference39 articles.

1. Synthesis, activity, and pharmacokinetic properties of a series of conformationally-restricted thiourea analogs as novel hepatitis C virus inhibitors

2. Design and efficient synthesis of novel arylthiourea derivatives as potent hepatitis C virus inhibitors

3. Diverse classification models for anti-hepatitis C virus activity of thiourea derivatives

4. QSAR based modeling of hepatitis C virus NS5B inhibitors

5. 2D and 3D Quantitative Structure–Activity Relationship Study of Hepatitis C Virus NS5B Polymerase Inhibitors by Comparative Molecular Field Analysis and Comparative Molecular Similarity Indices Analysis Methods

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