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references.bib
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@article{HumanWater,
title={Studies on Body Water in Man},
author={Denjiro Musha},
journal={The Tohoku Journal of Experimental Medicine},
volume={63},
number={4},
pages={309-317},
year={1956},
doi={10.1620/tjem.63.309}
}
@article{LIPINSKI1997,
title = {Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings},
journal = {Advanced Drug Delivery Reviews},
volume = {23},
number = {1},
pages = {3 - 25},
year = {1997},
doi = {https://doi.org/10.1016/S0169-409X(96)00423-1},
url = {http://www.sciencedirect.com/science/article/pii/S0169409X96004231},
author = {Christopher A. Lipinski and Franco Lombardo and Beryl W. Dominy and Paul J. Feeney}
}
@article{DI2006446,
title = {Biological assay challenges from compound solubility: strategies for bioassay optimization},
journal = {Drug Discovery Today},
volume = {11},
number = {9},
pages = {446 - 451},
year = {2006},
doi = {https://doi.org/10.1016/j.drudis.2006.03.004},
url = {http://www.sciencedirect.com/science/article/pii/S135964460600047X},
author = {Li Di and Edward H. Kerns}
}
@article{EKINS2002305,
title = {In silico ADME/Tox: the state of the art},
journal = {Journal of Molecular Graphics and Modelling},
volume = {20},
number = {4},
pages = {305 - 309},
year = {2002},
doi = {https://doi.org/10.1016/S1093-3263(01)00127-9},
url = {http://www.sciencedirect.com/science/article/pii/S1093326301001279},
author = {Sean Ekins and John Rose}
}
@article{NatureVS,
title = {Ultra-large library docking for discovering new chemotypes.},
journal = {Nature},
volume = {566},
pages = {224-229},
year = {2019},
doi = {https://doi.org/10.1038/s41586-019-0917-9},
url = {https://www.nature.com/articles/s41586-019-0917-9},
author = {Jiankun Lyu and Sheng Wang and Trent E. Balius and Isha Singh and Anat Levit and Yurii S. Moroz and Matthew J. O'Meera and Tao Che and Enkhjargal Algaa and Kateryna Tolmachova and Andrey A. Tolmachev and Brian K. Shoichet and Bryan L. Roth and John J. Irwin}
}
@article{denseStates,
title={Solubility prediction from first principles: a density of states approach},
journal={Physical Chemistry Chemical Physics},
volume={20},
pages={20981-20987},
year={2018},
doi={10.1039/C8CP01786G},
url={https://pubs.rsc.org/en/content/articlehtml/2018/cp/c8cp01786g},
author={Simon Boothroyd and Andy Kerridge and Anders Broo and David Buttar and Jamshed Anwar}
}
@article{solrev1,
title={A review of methods for the calculation of solution free energies and the modelling of systems in solution},
journal={Physical Chemstry Chemical Physics},
volume={17},
pages={6174-6191},
year={2015},
doi={10.1039/C5CP00288E},
url={https://pubs.rsc.org/en/content/articlehtml/2015/cp/c5cp00288e},
author={R. E. Skyner and J. L. McDonagh and C. R. Groom and T. van Mourik and J. B. O. Mitchell},
}
@article{solrev2,
title = {Prediction of drug solubility from structure},
journal = {Advanced Drug Delivery Reviews},
volume = {54},
number = {3},
pages = {355 - 366},
year = {2002},
doi = {https://doi.org/10.1016/S0169-409X(02)00008-X},
url = {http://www.sciencedirect.com/science/article/pii/S0169409X0200008X},
author = {William L. Jorgensen and Erin M. Duffy},
}
@article{llinas,
author = {Llinas, Antonio and Oprisiu, Ioana and Avdeef, Alex},
title = {Findings of the Second Challenge to Predict Aqueous Solubility},
journal = {Journal of Chemical Information and Modeling},
volume = {60},
number = {10},
pages = {4791-4803},
year = {2020},
doi = {10.1021/acs.jcim.0c00701},
url = {https://doi.org/10.1021/acs.jcim.0c00701}
}
@article{boobier,
author = {Samuel Boobier and Anne Osbourn and John B. O. Mitchell},
title = {Can human experts predict solubility better than computers?},
journal = {Journal of Cheminformatics},
volume = {9},
number = {63},
year = {2017},
doi = {10.1186/s13321-017-0250-y},
url = {https://jcheminf.biomedcentral.com/articles/10.1186/s13321-017-0250-y#citeas}
}
@article{lovric,
title={Machine Learning in Prediction of Intrinsic Aqueous Solubility of Drug-like Compounds: Generalization, Complexity or Predictive Ability?},
author={Mario Lovric and Kristina Pavlovic and Petar Zuvela and Adrian Spataru and Bono Lucic and Roman Kern and Ming Wah Wong},
year={2020},
journal={ChemRxiv},
url={https://chemrxiv.org/articles/preprint/Machine_Learning_in_Prediction_of_Intrinsic_Aqueous_Solubility_of_Drug-like_Compounds_Generalization_Complexity_or_Predictive_Ability_/12746948/1}
}
@article{cui,
author={Cui, Qiuji and Lu, Shuai and Ni, Bingwei and Zeng, Xian and Tan, Ying and Chen, Ya Dong and Zhao, Hongping},
title={Improved Prediction of Aqueous Solubility of Novel Compounds by Going Deeper With Deep Learning},
journal={Frontiers in Oncology},
volume={10},
pages={121},
year={2020},
url={https://www.frontiersin.org/article/10.3389/fonc.2020.00121},
doi={10.3389/fonc.2020.00121},
}
@article{MAT,
title={Molecule Attention Transformer},
author={Lukasz Maziarka and Tomasz Danel and Sławomir Mucha and Krzysztof Rataj and Jacek Tabor and Stanisław Jastrzebski},
year={2020},
journal={arXiv},
url={arXiv:2002.08264v1}
}
@article{AqSol,
title = {AqSolDB, a curated reference set of aqueous solubility and 2D descriptors for a diverse set of compounds},
journal = {Scientific Data},
volume = {6},
pages = {143},
year = {2019},
doi = {https://doi.org/10.1038/s41597-019-0151-1},
url = {https://www.nature.com/articles/s41597-019-0151-1#citeas},
author = {Murat Cihan Sorkun and Abhishek Khetan}
}
@article{SMILES,
author = {Weininger, David},
title = {SMILES, a Chemical Language and Information System. 1. Introduction to Methodology and Encoding Rules},
year = {1988},
issue_date = {February 1988},
publisher = {American Chemical Society},
address = {USA},
volume = {28},
number = {1},
issn = {0095-2338},
url = {https://doi.org/10.1021/ci00057a005},
doi = {10.1021/ci00057a005},
journal = {J. Chem. Inf. Comput. Sci.},
pages = {31–36},
numpages = {6}
}
@misc{rdkit,
howpublished = {http://www.rdkit.org},
key = {rdkit},
note = {accessed November 6, 2017.},
title = {{RDKit: Open-Source Cheminformatics.}}
}
@misc{wandb,
title = {Experiment Tracking with Weights and Biases},
year = {2020},
note = {Software available from wandb.com},
url={https://www.wandb.com/},
author = {Biewald, Lukas},
}
@article{esol,
author = {Delaney, John S.},
title = {ESOL: Estimating Aqueous Solubility Directly from Molecular Structure},
journal = {Journal of Chemical Information and Computer Sciences},
volume = {44},
number = {3},
pages = {1000-1005},
year = {2004},
doi = {10.1021/ci034243x},
note ={PMID: 15154768},
URL = {
https://doi.org/10.1021/ci034243x
},
eprint = {
https://doi.org/10.1021/ci034243x
}
}
@article{cd2020,
author = {Francoeur, Paul G. and Masuda, Tomohide and Sunseri, Jocelyn and Jia, Andrew and Iovanisci, Richard B. and Snyder, Ian and Koes, David R.},
title = {Three-Dimensional Convolutional Neural Networks and a Cross-Docked Data Set for Structure-Based Drug Design},
journal = {Journal of Chemical Information and Modeling},
volume = {60},
number = {9},
pages = {4200-4215},
year = {2020},
doi = {10.1021/acs.jcim.0c00411},
note ={PMID: 32865404},
URL = {https://doi.org/10.1021/acs.jcim.0c00411},
eprint = {https://doi.org/10.1021/acs.jcim.0c00411}
}
@article{freesolv,
title={FreeSolv: a database of experimental and calculated hydration free energies, with input files.},
journal={Journal of Computer Aided Molecular Design},
volume={28},
pages={771-720},
year={2014},
doi={https://doi.org/10.1007/s10822-014-9747-x},
url={https://link.springer.com/article/10.1007/s10822-014-9747-x#citeas},
author={David L. Mobley and J. Peter Guthrie},
}
@InProceedings{ mckinney-proc-scipy-2010,
author = { {W}es {M}c{K}inney },
title = { {D}ata {S}tructures for {S}tatistical {C}omputing in {P}ython },
booktitle = { {P}roceedings of the 9th {P}ython in {S}cience {C}onference },
pages = { 56 - 61 },
year = { 2010 },
editor = { {S}t\'efan van der {W}alt and {J}arrod {M}illman },
doi = { 10.25080/Majora-92bf1922-00a }
}
@Article{ numpy,
title = {Array programming with {NumPy}},
author = {Charles R. Harris and K. Jarrod Millman and St{'{e}}fan J. van der Walt and Ralf Gommers and Pauli Virtanen and David Cournapeau and Eric Wieser and Julian Taylor and Sebastian Berg and Nathaniel J. Smith and Robert Kern and Matti Picus and Stephan Hoyer and Marten H. van Kerkwijk and Matthew Brett and Allan Haldane and Jaime Fern{'{a}}ndez del R{'{\i}}o and Mark Wiebe and Pearu Peterson and Pierre G{'{e}}rard-Marchant and Kevin Sheppard and Tyler Reddy and Warren Weckesser and Hameer Abbasi and Christoph Gohlke and Travis E. Oliphant},
year = {2020},
month = sep,
journal = {Nature},
volume = {585},
number = {7825},
pages = {357--362},
doi = {10.1038/s41586-020-2649-2},
publisher = {Springer Science and Business Media {LLC}},
url = {https://doi.org/10.1038/s41586-020-2649-2}
}
@article{pytorch,
title = {PyTorch: An Imperative Style, High-Performance Deep Learning Library},
author = {Paszke, Adam and Gross, Sam and Massa, Francisco and Lerer, Adam and Bradbury, James and Chanan, Gregory and Killeen, Trevor and Lin, Zeming and Gimelshein, Natalia and Antiga, Luca and Desmaison, Alban and Kopf, Andreas and Yang, Edward and DeVito, Zachary and Raison, Martin and Tejani, Alykhan and Chilamkurthy, Sasank and Steiner, Benoit and Fang, Lu and Bai, Junjie and Chintala, Soumith},
booktitle = {Advances in Neural Information Processing Systems 32},
editor = {H. Wallach and H. Larochelle and A. Beygelzimer and F. d\textquotesingle Alch\'{e}-Buc and E. Fox and R. Garnett},
pages = {8024--8035},
year = {2019},
journal = {Curran Associates, Inc.},
url = {http://papers.neurips.cc/paper/9015-pytorch-an-imperative-style-high-performance-deep-learning-library.pdf}
}
@book{deepchem,
title={Deep Learning for the Life Sciences},
author={Bharath Ramsundar and Peter Eastman and Patrick Walters and Vijay Pande and Karl Leswing and Zhenqin Wu},
publisher={O'Reilly Media},
note={\url{https://www.amazon.com/Deep-Learning-Life-Sciences-Microscopy/dp/1492039837}},
year={2019}
}
@article{chemprop,
author = {Yang, Kevin and Swanson, Kyle and Jin, Wengong and Coley, Connor and Eiden, Philipp and Gao, Hua and Guzman-Perez, Angel and Hopper, Timothy and Kelley, Brian and Mathea, Miriam and Palmer, Andrew and Settels, Volker and Jaakkola, Tommi and Jensen, Klavs and Barzilay, Regina},
title = {Analyzing Learned Molecular Representations for Property Prediction},
journal = {Journal of Chemical Information and Modeling},
volume = {59},
number = {8},
pages = {3370-3388},
year = {2019},
doi = {10.1021/acs.jcim.9b00237},
note ={PMID: 31361484},
URL = {
https://doi.org/10.1021/acs.jcim.9b00237
},
eprint = {
https://doi.org/10.1021/acs.jcim.9b00237
}
}
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V. and Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P. and Weiss, R. and Dubourg, V. and Vanderplas, J. and Passos, A. and Cournapeau, D. and Brucher, M. and Perrot, M. and Duchesnay, E.},
journal={Journal of Machine Learning Research},
volume={12},
pages={2825--2830},
year={2011}
}