Uncertainty quantification in drug design.
作者： Lewis H. Mervin , Simon Johansson , Elizaveta Semenova , Kathryn A. Giblin , Ola Engkvist
DOI: 10.1016/J.DRUDIS.2020.11.027
关键词:
摘要: Machine learning and artificial intelligence are increasingly being applied to the drug-design process as a result of the development of novel algorithms, growing access, the falling cost …
sci-hub.st 参考文章(167)
Lars Carlsson, Martin Eklund, Ulf Norinder, Aggregated Conformal Prediction artificial intelligence applications and innovations. pp. 231- 240 ,(2014) , 10.1007/978-3-662-44722-2_25
Konrad Jacobs, Independent Identically Distributed (IID) Random Variables Discrete Stochastics. pp. 65- 101 ,(1992) , 10.1007/978-3-0348-8645-1_4
Eduardo P. Costa, Sicco Verwer, Hendrik Blockeel, Estimating Prediction Certainty in Decision Trees Advances in Intelligent Data Analysis XII. ,vol. 8207, pp. 138- 149 ,(2013) , 10.1007/978-3-642-41398-8_13
Dagmar Stumpfe, Jürgen Bajorath, Exploring Activity Cliffs in Medicinal Chemistry Journal of Medicinal Chemistry. ,vol. 55, pp. 2932- 2942 ,(2012) , 10.1021/JM201706B
Harry Zhang, The Optimality of Naive Bayes. the florida ai research society. pp. 562- 567 ,(2004)
Nicholas T. Thomopoulos, Essentials of Monte Carlo Simulation: Statistical Methods for Building Simulation Models ,(2012)
Matthew D. Segall, Edmund J. Champness, The challenges of making decisions using uncertain data Journal of Computer-aided Molecular Design. ,vol. 29, pp. 809- 816 ,(2015) , 10.1007/S10822-015-9855-2
Sergey M Ivanov, Alexey A Lagunin, Vladimir V Poroikov, None, In silico assessment of adverse drug reactions and associated mechanisms. Drug Discovery Today. ,vol. 21, pp. 58- 71 ,(2016) , 10.1016/J.DRUDIS.2015.07.018
Krishna C. Bulusu, Rajarshi Guha, Daniel J. Mason, Richard P.I. Lewis, Eugene Muratov, Yasaman Kalantar Motamedi, Murat Cokol, Andreas Bender, Modelling of compound combination effects and applications to efficacy and toxicity: state-of-the-art, challenges and perspectives Drug Discovery Today. ,vol. 21, pp. 225- 238 ,(2016) , 10.1016/J.DRUDIS.2015.09.003
Vladimir Vovk, Venn predictors and isotonic regression arXiv: Learning. ,(2012)