Fetching the paper…
Reading the bibliography…
Accurate prediction of drug-target interactions (DTI) is crucial for drug discovery.
Comprehensive analysis of kinase inhibitor selectivity
Mindy I. Davis, Jeremy P. Hunt, Sanna Herrgard, Pietro Ciceri, Lisa M. Wodicka, Gabriel Pallares, Michael Hocker, Daniel K. Treiber, and Patrick P. Zarrinkar · 1990
Earlier work this paper cites.
The def data base of sequence based protein fold class predictions
M Reczko and H Bohr · 1994
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
Earlier work this paper cites.
Prediction of protein subcellular locations by incorporating quasi-sequence-order effect
Kuo-Chen Chou · 2000
Earlier work this paper cites.
Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes
Kuo-Chen Chou · 2005
Earlier work this paper cites.
BindingDB: a web-accessible database of experimentally determined protein–ligand binding affinities
Tiqing Liu, Yuhmei Lin, Xin Wen, Robert N. Jorissen, and Michael K. Gilson · 2007
Earlier work this paper cites.
Predicting protein–protein interactions based only on sequences information
Juwen Shen, Jian Zhang, Xiaomin Luo, Weiliang Zhu, Kunqian Yu, Kaixian Chen, Yixue Li, and Hualiang Jiang · 2007
Earlier work this paper cites.
Extended-connectivity fingerprints
David Rogers and Mathew Hahn · 2010
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
Earlier work this paper cites.
Toward more realistic drug–target interaction predictions
Tapio Pahikkala, Antti Airola, Sami Pietilä, Sushil Shakyawar, Agnieszka Szwajda, Jing Tang, and Tero Aittokallio · 2015
Cited alongside, same era.
A Modular Probe Strategy for Drug Localization, Target Identification and Target Occupancy Measurement on Single Cell Level
Anna Rutkowska, Douglas W. Thomson, Johanna Vappiani, Thilo Werner, Katrin M. Mueller, Lars Dittus, Jana Krause, Marcel Muelbaier, Giovanna Bergamini, and Marcus Bantscheff · 2016
Cited alongside, same era.
A comprehensive map of molecular drug targets
Rita Santos, Oleg Ursu, Anna Gaulton, A Patrícia Bento, Ramesh S Donadi, Cristian G Bologa, Anneli Karlsson, Bissan Al-Lazikani, Anne Hersey, Tudor I Oprea, et al · 2017
Cited alongside, same era.
The drug repurposing hub: a next-generation drug library and information resource
Steven M Corsello, Joshua A Bittker, Zihan Liu, Joshua Gould, Patrick McCarren, Jodi E Hirschman, Stephen E Johnston, Anita Vrcic, Bang Wong, Mariya Khan, et al · 2017
Cited alongside, same era.
SimBoost: a read-across approach for predicting drug–target binding affinities using gradient boosting machines
Tong He, Marten Heidemeyer, Fuqiang Ban, Artem Cherkasov, and Martin Ester · 2017
DeepDTA: deep drug–target binding affinity prediction
Hakime Öztürk, Arzucan Özgür, and Elif Ozkirimli · 2018
Later among the works it cites.
DeepConv-DTI: Prediction of drug-target interactions via deep learning with convolution on protein sequences
Ingoo Lee, Jongsoo Keum, and Hojung Nam · 2019
Later among the works it cites.
Analyzing Learned Molecular Representations for Property Prediction
Kevin Yang, Kyle Swanson, Wengong Jin, Connor Coley, Philipp Eiden, Hua Gao, Angel Guzman-Perez, Timothy Hopper, Brian Kelley, Miriam Mathea, Andrew Palmer, Volker Settels, Tommi Jaakkola, Klavs Jensen, and Regina Barzilay · 2019
Later among the works it cites.
Pubchem 2019 update: improved access to chemical data
Sunghwan Kim, Jie Chen, Tiejun Cheng, Asta Gindulyte, Jia He, Siqian He, Qingliang Li, Benjamin A Shoemaker, Paul A Thiessen, Bo Yu, et al · 2019
Later among the works it cites.
Gradio: Hassle-free sharing and testing of ml models in the wild
Abubakar Abid, Ali Abdalla, Ali Abid, Dawood Khan, Abdulrahman Alfozan, and James Zou · 2019
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Cited alongside, same era.
Neural message passing for quantum chemistry
Justin Gilmer, Samuel S Schoenholz, Patrick F Riley, Oriol Vinyals, and George E Dahl · 2017
Cited alongside, same era.
Machine learning for integrating data in biology and medicine: Principles, practice, and opportunities
Marinka Zitnik, Francis Nguyen, Bo Wang, Jure Leskovec, Anna Goldenberg, and Michael M. Hoffman · 2018
Cited alongside, same era.
On the Properties of Neural Machine Translation: Encoder–Decoder Approaches
Kyunghyun Cho, Bart van Merriënboer, Dzmitry Bahdanau, and Yoshua Bengio
Cited in the paper.
Learning phrase representations using RNN encoder–decoder for statistical machine translation
Kyunghyun Cho, Bart van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio
Cited in the paper.
Later among the works it cites.
The COVID19 epidemic
Thirumalaisamy P. Velavan and Christian G. Meyer · 2020
Closest in time.
GraphDTA: Predicting drug–target binding affinity with graph neural networks
Thin Nguyen, Hang Le, Thomas P. Quinn, Thuc Le, and Svetha Venkatesh · 2020
Closest in time.
Caster: Predicting drug interactions with chemical substructure representation
Kexin Huang, Cao Xiao, Trong Nghia Hoang, Lucas M Glass, and Jimeng Sun · 2020
Closest in time.