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Nonclinical Statistics for Pharmaceutical and Biotechnology IndustriesQuantitative-Structure Activity Relationship Modeling and Cheminformatics

Nonclinical Statistics for Pharmaceutical and Biotechnology Industries: Quantitative-Structure... [This chapter describes quantitative tools for analyzing chemical structures and relating them to assay results using statistical models. The focus is on prediction of new compounds as well as the exploratory analysis and data mining of large compound databases. Other issues related to how these analytical methods are used are discussed.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Nonclinical Statistics for Pharmaceutical and Biotechnology IndustriesQuantitative-Structure Activity Relationship Modeling and Cheminformatics

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Publisher
Springer International Publishing
Copyright
© Springer International Publishing Switzerland 2016
ISBN
978-3-319-23557-8
Pages
141 –155
DOI
10.1007/978-3-319-23558-5_6
Publisher site
See Chapter on Publisher Site

Abstract

[This chapter describes quantitative tools for analyzing chemical structures and relating them to assay results using statistical models. The focus is on prediction of new compounds as well as the exploratory analysis and data mining of large compound databases. Other issues related to how these analytical methods are used are discussed.]

Published: Dec 29, 2015

Keywords: Machine learning; Molecular descriptors; Applicability domain

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