Improving (Q)SAR predictions by examining bias in the selection of compounds for experimental testing-Reference-Cited by-同舟云学术

Improving (Q)SAR predictions by examining bias in the selection of compounds for experimental testing

Published:2019-09-24 Issue:10 Volume:30 Page:759-773
ISSN:1062-936X
Container-title:SAR and QSAR in Environmental Research
language:en
Short-container-title:SAR and QSAR in Environmental Research

Author:

Pogodin P.V.¹,Lagunin A.A.¹²^ORCID,Filimonov D.A.¹^ORCID,Nicklaus M.C.³,Poroikov V.V.¹^ORCID

Affiliation:

1. Department of Bioinformatics, Institute of Biomedical Chemistry, Moscow, Russia

2. Department of Bioinformatics, Medical-Biological Department, Pirogov Russian National Research Medical University, Moscow, Russia

3. Computer-Aided Drug Design Group, Chemical Biology Laboratory, Center for Cancer Research, National Cancer Institute, NIH, NCI-Frederick, Frederick, MD, USA

Publisher

Informa UK Limited

Subject

Drug Discovery,Molecular Medicine,General Medicine,Bioengineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/1062936X.2019.1665580

Reference35 articles.

1. Association, correlation and causation

2. Insights and Pitfalls: Selection Bias in Qualitative Research

3. SELECTION BIAS CORRECTIONS BASED ON THE MULTINOMIAL LOGIT MODEL: MONTE CARLO COMPARISONS

4. Sample Selection Bias Correction Theory

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