Related references
Note: Only part of the references are listed.Deep learning approaches for de novo drug design: An overview
Mingyang Wang et al.
CURRENT OPINION IN STRUCTURAL BIOLOGY (2022)
A machine learning framework for predicting synergistic and antagonistic drug combinatorial efficacy
Suyu Mei
JOURNAL OF MATHEMATICAL CHEMISTRY (2022)
Pocket2Drug: An Encoder-Decoder Deep Neural Network for the Target-Based Drug Design
Wentao Shi et al.
FRONTIERS IN PHARMACOLOGY (2022)
Deep learning tools for advancing drug discovery and development
Sagorika Nag et al.
3 BIOTECH (2022)
MatchMaker: A Deep Learning Framework for Drug Synergy Prediction
Halil Ibrahim Kuru et al.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS (2022)
Memory augmented recurrent neural networks for de-novo drug design
Naveen Suresh et al.
PLOS ONE (2022)
Diabetes precision medicine: plenty of potential, pitfalls and perils but not yet ready for prime time
Simon Griffin
DIABETOLOGIA (2022)
From Traditional Herbal Medicine to Rational Drug Discovery: Strategies, Challenges, and Future Perspectives
Dev Bukhsh Singh et al.
REVISTA BRASILEIRA DE FARMACOGNOSIA-BRAZILIAN JOURNAL OF PHARMACOGNOSY (2022)
OpenChem: A Deep Learning Toolkit for Computational Chemistry and Drug Design
Maria Korshunova et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2021)
Deep learning is widely applicable to phenotyping embryonic development and disease
Thomas Naert et al.
DEVELOPMENT (2021)
Artificial intelligence and machine learning-aided drug discovery in central nervous system diseases: State-of-the-arts and future directions
Sezen Vatansever et al.
MEDICINAL RESEARCH REVIEWS (2021)
DeepGRN: prediction of transcription factor binding site across cell-types using attention-based deep neural networks
Chen Chen et al.
BMC BIOINFORMATICS (2021)
Effective gene expression prediction from sequence by integrating long-range interactions
Ziga Avsec et al.
NATURE METHODS (2021)
Advances in De Novo Drug Design: From Conventional to Machine Learning Methods
Varnavas D. Mouchlis et al.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES (2021)
Deep Learning Driven Drug Discovery: Tackling Severe Acute Respiratory Syndrome Coronavirus 2
Yang Zhang et al.
FRONTIERS IN MICROBIOLOGY (2021)
Artificial intelligence in drug discovery: recent advances and future perspectives
Jose Jimenez-Luna et al.
EXPERT OPINION ON DRUG DISCOVERY (2021)
A Deep Learning and XGBoost-Based Method for Predicting Protein-Protein Interaction Sites
Pan Wang et al.
FRONTIERS IN GENETICS (2021)
DeepBAR: A Fast and Exact Method for Binding Free Energy Computation
Xinqiang Ding et al.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS (2021)
Deep Learning for Human Disease Detection, Subtype Classification, and Treatment Response Prediction Using Epigenomic Data
Thi Mai Nguyen et al.
BIOMEDICINES (2021)
HELLO: improved neural network architectures and methodologies for small variant calling
Anand Ramachandran et al.
BMC BIOINFORMATICS (2021)
SWnet: a deep learning model for drug response prediction from cancer genomic signatures and compound chemical structures
Zhaorui Zuo et al.
BMC BIOINFORMATICS (2021)
Machine learning approaches for drug combination therapies
Betul Guvenc Paltun et al.
BRIEFINGS IN BIOINFORMATICS (2021)
A deep-learning framework for multi-level peptide-protein interaction prediction
Yipin Lei et al.
NATURE COMMUNICATIONS (2021)
Navigating Ownership in the Context of the Security Sector Reform (SSR) in Mali: A Comparison of External Actors' Approaches
Karoline Eickhoff
JOURNAL OF INTERVENTION AND STATEBUILDING (2021)
Deep-learning approach to identifying cancer subtypes using high-dimensional genomic data
Runpu Chen et al.
BIOINFORMATICS (2020)
CapsCarcino: A novel sparse data deep learning tool for predicting carcinogens
Yi-Wei Wang et al.
FOOD AND CHEMICAL TOXICOLOGY (2020)
Deep learning improves the ability of sgRNA off-target propensity prediction
Qiaoyue Liu et al.
BMC BIOINFORMATICS (2020)
A Deep Learning Approach to Antibiotic Discovery
Jonathan M. Stokes et al.
CELL (2020)
An Introduction to Machine Learning
Solveig Badillo et al.
CLINICAL PHARMACOLOGY & THERAPEUTICS (2020)
DeepScaffold: A Comprehensive Tool for Scaffold-Based De Novo Drug Discovery Using Deep Learning
Yibo Li et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2020)
Multiobjective de novo drug design with recurrent neural networks and nondominated sorting
Jacob Yasonik
JOURNAL OF CHEMINFORMATICS (2020)
Deep Generative Models for 3D Linker Design
Fergus Imrie et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2020)
Deep Docking: A Deep Learning Platform for Augmentation of Structure Based Drug Discovery
Francesco Gentile et al.
ACS CENTRAL SCIENCE (2020)
A Review on Applications of Computational Methods in Drug Screening and Design
Xiaoqian Lin et al.
MOLECULES (2020)
History of artificial intelligence in medicine
Vivek Kaul et al.
GASTROINTESTINAL ENDOSCOPY (2020)
A Deep-Learning View of Chemical Space Designed to Facilitate Drug Discovery
Paul Maragakis et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2020)
Generative Model for Proposing Drug Candidates Satisfying Anticancer Properties Using a Conditional Variational Autoencoder
Sunghoon Joo et al.
ACS OMEGA (2020)
Predicting Drug Response and Synergy Using a Deep Learning Model of Human Cancer Cells
Brent M. Kuenzi et al.
CANCER CELL (2020)
Generative Adversarial Networks
Ian Goodfellow et al.
COMMUNICATIONS OF THE ACM (2020)
Targeted free energy estimation via learned mappings
Peter Wirnsberger et al.
JOURNAL OF CHEMICAL PHYSICS (2020)
A Machine Learning Method for Drug Combination Prediction
Jiang Li et al.
FRONTIERS IN GENETICS (2020)
3D Deep Learning for Biological Function Prediction from Physical Fields
Vladimir Golkov et al.
2020 INTERNATIONAL CONFERENCE ON 3D VISION (3DV 2020) (2020)
Personalized deep learning of individual immunopeptidomes to identify neoantigens for cancer vaccines
Ngoc Hieu Tran et al.
NATURE MACHINE INTELLIGENCE (2020)
SyntaLinker: automatic fragment linking with deep conditional transformer neural networks
Yuyao Yang et al.
CHEMICAL SCIENCE (2020)
Are 2D fingerprints still valuable for drug discovery?
Kaifu Gao et al.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS (2020)
DEEPScreen: high performance drug-target interaction prediction with convolutional neural networks using 2-D structural compound representations
Ahmet Sureyya Rifaioglu et al.
CHEMICAL SCIENCE (2020)
NeoDTI: neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions
Fangping Wan et al.
BIOINFORMATICS (2019)
DeepAffinity: interpretable deep learning of compound-protein affinity through unified recurrent and convolutional neural networks
Mostafa Karimi et al.
BIOINFORMATICS (2019)
A bright future for fragment-based drug discovery: what does it hold?
Celien Jacquemard et al.
EXPERT OPINION ON DRUG DISCOVERY (2019)
Deep learning for molecular generation
Youjun Xu et al.
FUTURE MEDICINAL CHEMISTRY (2019)
Applications of machine learning in drug discovery and development
Jessica Vamathevan et al.
NATURE REVIEWS DRUG DISCOVERY (2019)
DeepACLSTM: deep asymmetric convolutional long short-term memory neural models for protein secondary structure prediction
Yanbu Guo et al.
BMC BIOINFORMATICS (2019)
Multi-channel PINN: investigating scalable and transferable neural networks for drug discovery
Munhwan Lee et al.
JOURNAL OF CHEMINFORMATICS (2019)
DeepConv-DTI: Prediction of drug-target interactions via deep learning with convolution on protein sequences
Ingo Lee et al.
PLOS COMPUTATIONAL BIOLOGY (2019)
Predicting drug response of tumors from integrated genomic profiles by deep neural networks (vol 12, pg 18, 2019)
Yu-Chiao Chiu et al.
BMC MEDICAL GENOMICS (2019)
Deep learning enables rapid identification of potent DDR1 kinase inhibitors
Alex Zhavoronkov et al.
NATURE BIOTECHNOLOGY (2019)
Advancing Drug Discovery via Artificial Intelligence
H. C. Stephen Chan et al.
TRENDS IN PHARMACOLOGICAL SCIENCES (2019)
Comparison Study of Computational Prediction Tools for Drug-Target Binding Affinities
Maha Thafar et al.
FRONTIERS IN CHEMISTRY (2019)
DeepHINT: understanding HIV-1 integration via deep learning with attention
Hailin Hu et al.
BIOINFORMATICS (2019)
De Novo Molecule Design by Translating from Reduced Graphs to SMILES
Peter Pogany et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2019)
Advances and Perspectives in Applying Deep Learning for Drug Design and Discovery
Celio F. Lipinski et al.
FRONTIERS IN ROBOTICS AND AI (2019)
Performance Evaluation of cuDNN Convolution Algorithms on NVIDIA Volta GPUs
Marc Jorda et al.
IEEE ACCESS (2019)
Identification of Bioactive Scaffolds Based on QSAR Models
Tomoki Nakagawa et al.
MOLECULAR INFORMATICS (2018)
Generative Recurrent Networks for De Novo Drug Design
Anvita Gupta et al.
MOLECULAR INFORMATICS (2018)
Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks
Marwin H. S. Segler et al.
ACS CENTRAL SCIENCE (2018)
DeepDTA: deep drug-target binding affinity prediction
Hakime Ozturk et al.
BIOINFORMATICS (2018)
KDEEP: Protein-Ligand Absolute Binding Affinity Prediction via 3D-Convolutional Neural Networks
Jose Jimenez et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2018)
Generative Models for Artificially-intelligent Molecular Design
Gisbert Schneider
MOLECULAR INFORMATICS (2018)
Deep learning in pharmacogenomics: from gene regulation to patient stratification
Alexandr A. Kalinin et al.
PHARMACOGENOMICS (2018)
In silico identification of protein targets for chemical neurotoxins using ToxCast in vitro data and read-across within the QSAR toolbox
Y. G. Chushak et al.
TOXICOLOGY RESEARCH (2018)
Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules
Rafael Gomez-Bombarelli et al.
ACS CENTRAL SCIENCE (2018)
Deep Learning in Drug Discovery and Medicine; Scratching the Surface
Dibyendu Dana et al.
MOLECULES (2018)
A deep learning approach to automate refinement of somatic variant calling from cancer sequencing data
Benjamin J. Ainscough et al.
NATURE GENETICS (2018)
The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology
Artur Kadurin et al.
ONCOTARGET (2017)
druGAN: An Advanced Generative Adversarial Autoencoder Model for de Novo Generation of New Molecules with Desired Molecular Properties in Silico
Artur Kadurin et al.
MOLECULAR PHARMACEUTICS (2017)
Molecular de-novo design through deep reinforcement learning
Marcus Olivecrona et al.
JOURNAL OF CHEMINFORMATICS (2017)
Machine Learning for Nuclear Mechano-Morphometric Biomarkers in Cancer Diagnosis
Adityanarayanan Radhakrishnan et al.
SCIENTIFIC REPORTS (2017)
Low Data Drug Discovery with One-Shot Learning
Han Altae-Tran et al.
ACS CENTRAL SCIENCE (2017)
From machine learning to deep learning: progress in machine intelligence for rational drug discovery
Lu Zhang et al.
DRUG DISCOVERY TODAY (2017)
6 Deep Learning in Drug Discovery
Erik Gawehn et al.
MOLECULAR INFORMATICS (2016)
Identifying compound efficacy targets in phenotypic drug discovery
Markus Schirle et al.
DRUG DISCOVERY TODAY (2016)
Use of machine learning approaches for novel drug discovery
Angelica Nakagawa Lima et al.
EXPERT OPINION ON DRUG DISCOVERY (2016)
Inverse QSPR/QSAR Analysis for Chemical Structure Generation (from y to x)
Tomoyuki Miyao et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2016)
Molecular graph convolutions: moving beyond fingerprints
Steven Kearnes et al.
JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN (2016)
Boosting compound-protein interaction prediction by deep learning
Kai Tian et al.
METHODS (2016)
Applications of Deep Learning in Biomedicine
Polina Mamoshina et al.
MOLECULAR PHARMACEUTICS (2016)
Deep Learning Applications for Predicting Pharmacological Properties of Drugs and Drug Repurposing Using Transcriptomic Data
Alexander Aliper et al.
MOLECULAR PHARMACEUTICS (2016)
Deep learning for computational biology
Christof Angermueller et al.
MOLECULAR SYSTEMS BIOLOGY (2016)
Twenty years on: the impact of fragments on drug discovery
Daniel A. Erlanson et al.
NATURE REVIEWS DRUG DISCOVERY (2016)
Organic Synthesis: March of the Machines
Steven V. Ley et al.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION (2015)
Machine-learning approaches in drug discovery: methods and applications
Antonio Lavecchia
DRUG DISCOVERY TODAY (2015)
Predicting effects of noncoding variants with deep learning-based sequence model
Jian Zhou et al.
NATURE METHODS (2015)
Deep learning in neural networks: An overview
Juergen Schmidhuber
NEURAL NETWORKS (2015)
Comparing Multilabel Classification Methods for Provisional Biopharmaceutics Class Prediction
Danielle Newby et al.
MOLECULAR PHARMACEUTICS (2015)
Characterization of drug-induced transcriptional modules: towards drug repositioning and functional understanding
Murat Iskar et al.
MOLECULAR SYSTEMS BIOLOGY (2013)
Machine Learning Techniques and Drug Design
J. C. Gertrudes et al.
CURRENT MEDICINAL CHEMISTRY (2012)
Quantifying the chemical beauty of drugs
G. Richard Bickerton et al.
NATURE CHEMISTRY (2012)
The Graph Neural Network Model
Franco Scarselli et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS (2009)
Artificial intelligence approaches for rational drug design and discovery
Wlodzislaw Duch et al.
CURRENT PHARMACEUTICAL DESIGN (2007)
Share Paper
