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Additional supplementary materials for approved article OAK ID 31984

Martin, Eric and Polyakov, Valery and Tian, Li (2017) Additional supplementary materials for approved article OAK ID 31984. Journal of chemical information and modeling.

Abstract

These are the exact public-domain ChEMBL data sets, training/test set splits and activity predictions from the paper. There is no internal Novartis data. (After a presentation at ACS, many people asked for them.) They were already approved and released to an informal collaborator (Steven Kearnes) at google, OAK ID 32130 & 31607. Profile-QSAR on our "realistic" test set has come to be seen as the method to beat by other machine-learning virtual screening algorithms, so we are offering this as the test set for other researchers to use as a bench mark.

Item Type: Article
Date Deposited: 14 Sep 2017 00:45
Last Modified: 14 Sep 2017 00:45
URI: https://oak.novartis.com/id/eprint/32745

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