BMC Pharmacology and Toxicology
Journal of the American Medical Informatics Association
Bioinformatics
Drug Safety
JOURNAL OF MEDICAL INTERNET RESEARCH
arXiv
Journal of Cheminformations
Journal of Chemical Information and Modeling
Journal of Computer Aided Molecular Design
2020/03/06
Cross-GCN: Enhancing Graph Convolutional Network with k-Order Feature Interactions [paper]
2019
A Model to Search for Synthesizable Molecules [paper] [code]
Machine learning for molecular simulation [paper]
2017
BMC Pharmacology and Toxicology_Data-driven prediction of adverse drug reactions induced by drug-drug interactions
JIMIA_Deep learning for pharmacovigilance recurrent neural network architectures for labeling adverse drug reactions in Twitter posts
2018
Bioinformatics_Modeling polypharmacy side effects with graph convolutional networks
2019
Drug safety_Adverse drug event detection from electronic health records using hierarchical recurrent neural networks with dual-level embedding
Drug safety_Adverse drug events detection in clinical notes by jointly modeling entities and relations using neural networks
Drug safety_Detecting adverse drug events with rapidly trained classification models
JIMAI_Comment on:"Deep learning for pharmacovigilance- recurrent neural network architectures for labeling adverse drug reactions in Twitter posts"
Journal of medical Internet research_Detecting potential adverse drug reactions using a deep neural network model
2015
arXiv_AtomNet- a deep convolutional neural network for bioactivity prediction in structure-based drug discovery
2017
Journal of computational chemistry_The role of different sampling methods in improving biological activity prediction using deep belief network
2018
2018_ICPR_Graph memory networks for molecular activity prediction
2018
Molecular pharmaceutics_Comparing and validating machine learning models for Mycobacterium tuberculosis drug discovery
Molecular pharmaceutics_Prototype-based compound discovery using deep generative models
2019
Journal of cheminformatics_Multi-channel PINN- investigating scalable and transferable neural networks for drug discovery
Drug Bio-Target Interaction
2010
Journal of chemical information and modeling_NNScore- a neural-network-based scoring function for the characterization of protein−ligand complexes
Drug Chem-Target Interaction
2011
Journal of chemical information and modeling_NNScore 2.0- a neural-network receptor¨Cligand scoring function
2013
2013_Bioinformatics_Predicting drug-target interactions using restricted Boltzmann machines
2014
2014_IEEE BIBM_Pairwise input neural network for target-ligand interaction prediction
2015
BMC bioinformatics_BgN-Score and BsN-Score- bagging and boosting based ensemble neural networks scoring functions for accurate binding affinity prediction of protein-ligand complexes
2016
Methods_Boosting compound-protein interaction prediction by deep learning
bioRxiv_Deep learning with feature embedding for compound-protein interaction prediction
2017
Bioinformatics_Deep mining heterogeneous networks of biomedical linked data to predict novel drug¨Ctarget associations
IEEE BIBM_Drug¡ªtarget interaction prediction with a deep-learning-based model
Journal of chemical information and modeling_Protein¨Cligand scoring with convolutional neural networks
Journal of proteome research_Deep-learning-based drug¨Ctarget interaction prediction
arXiv_Atomic convolutional networks for predicting protein-ligand binding affinity
2018
BMC_genomics_Deep learning-based transcriptome data classification for drug-target interaction prediction
Bioinformatics_Compound¨Cprotein interaction prediction with end-to-end learning of neural networks for graphs and sequences
Bioinformatics_DeepDTA deep drug¨Ctarget binding affinity prediction
Bioinformatics_Development and evaluation of a deep learning model for protein¨Cligand binding affinity prediction
Current opinion in structural biology_Statistical and machine learning approaches to predicting protein¨Cligand interactions
Journal of chemical information and modeling_DEEP- protein¨Cligand absolute binding affinity prediction via 3D-convolutional neural networks
2019
BioRxiv_GraphDTA prediction of drug¨Ctarget binding affinity using graph convolutional networks
PLoS computational biology_DeepConv-DTI Prediction of drug-target interactions via deep learning with convolution on protein sequences
1997
Journal of chemical information and computer sciences_A neural device for searching direct correlations between structures and properties of chemical compounds
2017
Journal of chemical information and modeling_Convolutional embedding of attributed molecular graphs for physical property prediction
arXiv_Smiles2vec- An interpretable general-purpose deep neural network for predicting chemical properties
2018
Scientific reports_Prediction of pKa values for neutral and basic drugs based on hybrid artificial intelligence methods
2019
International journal of molecular sciences_Chemi-Net- a molecular graph convolutional network for accurate drug property prediction
2005
Current Computer-Aided Drug Design_Kohonen artificial neural network and counter propagation neural network in molecular structure-toxicity studies
2015
Journal of chemical information and modeling_Deep learning for drug-induced liver injury
arXiv_Toxicity prediction using deep learning
2016
Frontiers in Environmental Science_DeepTox toxicity prediction using deep learning
2017
Chemical research in toxicology_Deep learning to predict the formation of quinone species in drug metabolism
Journal of chemical information and modeling_Deep learning based regression and multiclass models for acute oral toxicity prediction with automatic chemical feature extraction
2018
Journal of chemical information and modeling_Comparative Study of Multitask Toxicity Modeling on a Broad Chemical Space
2019
Journal of chemical information and modeling_Deep Learning-Based Prediction of Drug-Induced Cardiotoxicity
2016
arXiv_Modeling industrial ADMET data with multitask networks
2017
Journal of cheminformatics_Beyond the hype- deep neural networks outperform established methods using a ChEMBL bioactivity benchmark set
2019
Journal of chemical information and modeling_Predictive Multitask Deep Neural Network Models for ADME-Tox Properties- Learning from Large Data Sets
2016
Journal of computer-aided molecular design_Molecular graph convolutions moving beyond fingerprints
2017
Journal of cheminformatics_Molecular de-novo design through deep reinforcement learning
2018
Journal of chemical information and modeling_De Novo Molecule Design by Translating from Reduced Graphs to SMILES
Journal of chemical information and modeling_Reinforced adversarial neural computer for de novo molecular design
Journal of cheminformatics_Multi-objective de novo drug design with conditional graph generative model
Molecular informatics_Application of generative autoencoder in de novo molecular design
Molecular informatics_De novo design of bioactive small molecules by artificial intelligence
Molecular informatics_Generative recurrent networks for de novo drug design
Molecular pharmaceutics_Adversarial threshold neural computer for molecular de novo design
Molecular pharmaceutics_Entangled conditional adversarial autoencoder for de novo drug discovery
Science advances_Deep reinforcement learning for de novo drug design
2019
Journal of chemical information and modeling_De Novo Molecular Design by Combining Deep Autoencoder Recurrent Neural Networks with Generative Topographic Mapping
Journal of chemical information and modeling_Guacamol- benchmarking models for de novo molecular design
Journal of cheminformatics_An exploration strategy improves the diversity of de novo ligands using deep reinforcement learning- a case for the adenosine A 2A receptor
Shape-Based Generative Modeling for de Novo Drug Design
2013
Journal of chemical information and modeling_Deep architectures and deep learning in chemoinformatics the prediction of aqueous solubility for drug-like molecules
Journal of chemical information and modeling_Deep architectures and deep learning in chemoinformatics- the prediction of aqueous solubility for drug-like molecules
2015
ACS central science_Modeling epoxidation of drug-like molecules with a deep machine learning network
1996
Journal of pharmaceutical sciences_Artificial neural networks as a novel approach to integrated pharmacokinetic¡ªpharmacodynamic analysis
2006
Journal of chemical information and modeling_Applications of self-organizing neural networks in virtual screening and diversity selection
2011
European Journal of Medicinal Chemistry_Ligand-based virtual screening procedure for the prediction and the identification of novel ¦Â-amyloid aggregation inhibitors
2014
Proceedings of the deep learning workshop at NIPS_Deep learning as an opportunity in virtual screening
2016
Journal of chemical information and modeling_Boosting docking-based virtual screening with deep learning
arXiv_Learning Deep Architectures for Interaction Prediction in Structure-based Virtual Screening
2018
Computers in biology and medicine_Interaction prediction in structure-based virtual screening using deep learning
2019
Journal of chemical information and modeling_In need of bias control- Evaluating chemical data for machine learning in structure-based virtual screening
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