Deep Learning Publication Navigator - subtopic: drug


Year TitleAuthor
2017   Learning Graph-Level Representation for Drug Discovery  J Li, D Cai, X He
2017   Machine learning-based prediction of adverse drug effects: an example of seizure-inducing compounds  M Gao, H Igata, A Takeuchi, K Sato, Y Ikegaya
2017   From machine learning to deep learning: progress in machine intelligence for rational drug discovery  L Zhang, J Tan, D Han, H Zhu
2017   Deep Learning to Predict the Formation of Quinone Species in Drug Metabolism  TB Hughes, SJ Swamidass
2017   ChemGAN challenge for drug discovery: can AI reproduce natural chemical diversity?  M Benhenda
2017   De novo Drug Design–Ye olde Scoring Problem Revisited  G Schneider, K Funatsu, Y Okuno, D Winkler
2017   Computational Methods for the Prediction of Drug-Target Interactions from Drug Fingerprints and Protein Sequences by Stacked Auto-Encoder Deep Neural Network  L Wang, ZH You, X Chen, SX Xia, F Liu, X Yan, Y Zhou
2016   Discovery of the relations between genetic polymorphism and adverse drug reactions  Z Liang, G Zhang, JX Huang
2016   A New Data Representation Based on Training Data Characteristics to Extract Drug Name Entity in Medical Text  M Sadikin, MI Fanany, T Basaruddin
2016   Fully unsupervised low-dimensional representation of adverse drug reaction events through distributional semantics  A Pérez, A Casillas, K Gojenola
2016   A New Data Representation Based on Training Data Characteristics to Extract Drug Named-Entity in Medical Text  S Mujionoa, MI Fananyc, T Basaruddinc
2016   Application of Computational Drug Discovery Techniques for Designing New Drugs against Zika Virus  JP Ceron
2016   Deep learning applications for predicting pharmacological properties of drugs and drug repurposing using transcriptomic data  A Aliper, S Plis, A Artemov, A Ulloa, P Mamoshina
2016   Students who developed logical reasoning skills reported improved confidence in drug dose calculation: Feedback from remedial maths classes  C Shelton
2016   Algorithms for Drug Sensitivity Prediction  C De Niz, R Rahman, X Zhao, R Pal
2016   A renaissance of neural networks in drug discovery  I Tetko, D Winkler, I Baskin
2016   Advanced use of EEG in drug development and personalized medicine  S Simpraga, R Alvarez
2016   Low Data Drug Discovery with One-shot Learning  H Altae
2016   Deep Learning in Drug Discovery  E Gawehn, JA Hiss, G Schneider
2016   Large-scale Computational Screening and Machine Learning Approaches to Drug Discovery  BK Allen
2016   DL-ADR: a novel deep learning model for classifying genomic variants into adverse drug reactions  Z Liang, JX Huang, X Zeng, G Zhang
2015   Massively Multitask Networks for Drug Discovery  B Ramsundar, S Kearnes, P Riley, D Webster
2015   Massively Multitask Deep Learning for Drug Discovery  J Feriante
2015   Providing data science support for systems pharmacology and its implications to drug discovery  T Hart, L Xie
2015   AtomNet: A Deep Convolutional Neural Network for Bioactivity Prediction in Structure-based Drug Discovery  I Wallach, M Dzamba, A Heifets
2015   Analysis of Drug Design for a Selection of G Protein-Coupled Neuro-Receptors Using Neural Network Techniques  C Agerskov, RM Mortensen, HG Bohr
2015   Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features  A Nikfarjam, A Sarker, K O'Connor, R Ginn, G Gonzalez
2015   Drug pipeline: 2Q15  L DeFrancesco
2015   Prediction of Clinical Drug Response Based on Differential Gene Expression Levels  Z Yue, Y Chen, J Xia
2015   Drug-Induced liver injury: interactions between drug properties and host factors  M Chen, A Suzuki, J Borlak, RJ Andrade, MI Lucena
2014   Multi-Task Deep Networks for Drug Target Prediction  T Unterthiner, A Mayr, G Klambauer, M Steijaert