基于二元定量构效关系模型的高活性噻加宾类似物分类 - Suppr

Classification of High-Activity Tiagabine Analogs by Binary QSAR Modeling.

作者信息

Jurik Andreas, Reicherstorfer Regina, Zdrazil Barbara, Ecker Gerhard F

机构信息

University of Vienna, Department of Medicinal Chemistry Althanstraße 14, A-1090 Vienna, Austria phone/fax: +431-4277-55110/-9551.

出版信息

Mol Inform. 2013 Jun;32(5-6):415-419. doi: 10.1002/minf.201300020. Epub 2013 May 15.

DOI:10.1002/minf.201300020

PMID:23956803

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3743161/

Abstract

摘要

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Classification of High-Activity Tiagabine Analogs by Binary QSAR Modeling.

Mol Inform. 2013 Jun;32(5-6):415-419. doi: 10.1002/minf.201300020. Epub 2013 May 15.

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Classification of High-Activity Tiagabine Analogs by Binary QSAR Modeling.

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Classification of High-Activity Tiagabine Analogs by Binary QSAR Modeling.

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