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Deep learning methods such as multitask neural networks have recently been applied to ligand-based virtual screening and other drug discovery applications.
Multitask learning
Rich Caruana · 1997
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Multitask learning
Rich Caruana · 1997
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Collaborative filtering on a family of biological targets
Dumitru Erhan, Pierre-Jean L’Heureux, Shi Yi Yue, and Yoshua Bengio · 2006
Earlier work this paper cites.
Collaborative filtering on a family of biological targets
Dumitru Erhan, Pierre-Jean L’Heureux, Shi Yi Yue, and Yoshua Bengio · 2006
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Recommendations for evaluation of computational methods
Ajay N Jain and Anthony Nicholls · 2008
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Similarity methods in chemoinformatics
Peter Willett · 2009
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Extended-connectivity fingerprints
David Rogers and Mathew Hahn · 2010
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Statsmodels: Econometric and statistical modeling with python
Skipper Seabold and Josef Perktold · 2010
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Adaptive subgradient methods for online learning and stochastic optimization
John Duchi, Elad Hazan, and Yoram Singer · 2011
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Scikit-learn: Machine learning in python
Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, et al · 2011
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Deep Learning How I Did It: Merck 1st place interview
George Dahl · 2012
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Directory of useful decoys, enhanced (DUD-E): better ligands and decoys for better benchmarking
Michael M Mysinger, Michael Carchia, John J Irwin, and Brian K Shoichet · 2012
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PubChem’s BioAssay database
Yanli Wang, Jewen Xiao, Tugba O Suzek, Jian Zhang, Jiyao Wang, Zhigang Zhou, Lianyi Han, Karen Karapetyan, Svetlana Dracheva, Benjamin A Shoemaker, et al · 2012
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Time-split cross-validation as a method for estimating the goodness of prospective prediction
Robert P Sheridan · 2013
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Multi-task neural networks for QSAR predictions
George E Dahl, Navdeep Jaitly, and Ruslan Salakhutdinov · 2014
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Convolutional networks on graphs for learning molecular fingerprints
David K Duvenaud, Dougal Maclaurin, Jorge Iparraguirre, Rafael Bombarell, Timothy Hirzel, Alán Aspuru-Guzik, and Ryan P Adams · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Deep learning
Yann LeCun, Yoshua Bengio, and Geoffrey Hinton · 2015
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Deep neural nets as a method for quantitative structure-activity relationships
Junshui Ma, Robert P Sheridan, Andy Liaw, George Dahl, and Vladimir Svetnik · 2015
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DeepTox: Toxicity prediction using deep learning
Andreas Mayr, Günter Klambauer, Thomas Unterthiner, and Sepp Hochreiter · 2015
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Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
Cited alongside, same era.
Deep learning as an opportunity in virtual screening
Thomas Unterthiner, Andreas Mayr, G Klambauer, Marvin Steijaert, Jörg K Wegner, Hugo Ceulemans, and Sepp Hochreiter · 2014
Cited alongside, same era.
The use of 2D fingerprint methods to support the assessment of structural similarity in orphan drug legislation
Pedro Franco, Nuria Porta, John D Holliday, and Peter Willett · 2014
Cited alongside, same era.
TensorFlow: Large-scale machine learning on heterogeneous systems
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, et al · 2015
Cited alongside, same era.
URL http://www.eyesopen.com
OpenEye GraphSim Toolkit
Cited in the paper.
Bharath Ramsundar, Steven Kearnes, Patrick Riley, Dale Webster, David Konerding, and Vijay Pande · 2015
Later among the works it cites.
Massively multitask networks for drug discovery
Bharath Ramsundar, Steven Kearnes, Patrick Riley, Dale Webster, David Konerding, and Vijay Pande · 2015
Later among the works it cites.
Molecular graph convolutions: Moving beyond fingerprints
Steven Kearnes, Kevin McCloskey, Marc Berndl, Vijay Pande, and Patrick Riley · 2016
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Understanding covariate shift in model performance [version 1; referees: 2 approved with reservations]
Georgia McGaughey, W Patrick Walters, and Brian Goldman · 2016
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