Collaborative Profile-QSAR: A Natural Platform for Building Collaborative Models among Competing Companies

MAIP: a web service for predicting blood‐stage malaria inhibitors

(2021) Nicolas Bosc et al.   Journal of Cheminformatics

Imputation of Assay Bioactivity Data Using Deep Learning

(2019) T. M. Whitehead et al.   Journal of Chemical Information and Modeling

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

(2019) Eric J. Martin et al.   Journal of Chemical Information and Modeling

Transfer and Multi-task Learning in QSAR Modeling: Advances and Challenges

(2018) Rodolfo S. Simões et al.   Frontiers in Pharmacology

Developing Collaborative QSAR Models Without Sharing Structures

(2017) Peter Gedeck et al.   Journal of Chemical Information and Modeling

Profile-QSAR 2.0: Kinase Virtual Screening Accuracy Comparable to Four-Concentration IC50s for Realistically Novel Compounds

(2017) Eric J. Martin et al.   Journal of Chemical Information and Modeling

Shared Consensus Machine Learning Models for Predicting Blood Stage Malaria Inhibition

(2017) Andreas Verras et al.   Journal of Chemical Information and Modeling

Demystifying Multitask Deep Neural Networks for Quantitative Structure–Activity Relationships

(2017) Yuting Xu et al.   Journal of Chemical Information and Modeling

Multitasking models for quantitative structure–biological effect relationships: current status and future perspectives to speed up drug discovery

(2015) Alejandro Speck-Planche et al.   Expert Opinion on Drug Discovery

Profile-QSAR: A Novelmeta-QSAR Method that Combines Activities across the Kinase Family To Accurately Predict Affinity, Selectivity, and Cellular Activity

(2011) Eric Martin et al.   Journal of Chemical Information and Modeling