All-Assay-Max2 pQSAR: Activity Predictions as Accurate as Four-Concentration IC50s for 8558 Novartis Assays-Reference-Cited by-同舟云学术

All-Assay-Max2 pQSAR: Activity Predictions as Accurate as Four-Concentration IC50s for 8558 Novartis Assays

Published:2019-09-13 Issue:10 Volume:59 Page:4450-4459
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Martin Eric J.¹^ORCID,Polyakov Valery R.¹,Zhu Xiang-Wei¹,Tian Li¹²,Mukherjee Prasenjit¹,Liu Xin¹²

Affiliation:

1. Novartis Institute for Biomedical Research, 5300 Chiron Way, Emeryville, California 94608-2916, United States

2. China Novartis Institutes for BioMedical Research Company, Limited, 2F, Building 4, Novartis Campus, No. 4218 Jinke Road, Zhangjiang, Pudong, Shanghai 201203, China

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.9b00375

Reference27 articles.

1. Predictive QSAR Modeling Workflow, Model Applicability Domains, and Virtual Screening

2. Ramsundar, B. K.; Steven, M.; Riley, P.; Webster, D.; Konerding, D. E.; Pande, V. S. Massively Multitask Networks for Drug Discovery. ArXiv 2015, 1502.02072.

3. Predicting ligand binding to proteins by affinity fingerprinting

4. Use of Cell Viability Assay Data Improves the Prediction Accuracy of Conventional Quantitative Structure–Activity Relationship Models of Animal Carcinogenicity

5. CIIPro: a new read-across portal to fill data gaps using public large-scale chemical and biological data

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