标题
Artificial Intelligence in Drug Design
作者
关键词
-
出版物
MOLECULES
Volume 23, Issue 10, Pages 2520
出版商
MDPI AG
发表日期
2018-10-02
DOI
10.3390/molecules23102520
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Deep Learning for Drug Design: an Artificial Intelligence Paradigm for Drug Discovery in the Big Data Era
- (2018) Yankang Jing et al. AAPS Journal
- Recent applications of machine learning in medicinal chemistry
- (2018) Jane Panteleev et al. BIOORGANIC & MEDICINAL CHEMISTRY LETTERS
- Statistical and machine learning approaches to predicting protein–ligand interactions
- (2018) Lucy J Colwell CURRENT OPINION IN STRUCTURAL BIOLOGY
- Machine learning in chemoinformatics and drug discovery
- (2018) Yu-Chen Lo et al. DRUG DISCOVERY TODAY
- Computational prediction of chemical reactions: current status and outlook
- (2018) Ola Engkvist et al. DRUG DISCOVERY TODAY
- The rise of deep learning in drug discovery
- (2018) Hongming Chen et al. DRUG DISCOVERY TODAY
- Neural network and deep-learning algorithms used in QSAR studies: merits and drawbacks
- (2018) Fahimeh Ghasemi et al. DRUG DISCOVERY TODAY
- Advancing drug discovery via GPU-based deep learning
- (2018) Erik Gawehn et al. Expert Opinion on Drug Discovery
- Data analytics and deep learning in medicinal chemistry
- (2018) Jürgen Bajorath Future Medicinal Chemistry
- Recurrent Neural Network Model for Constructive Peptide Design
- (2018) Alex T. Müller et al. Journal of Chemical Information and Modeling
- Deep Generative Models for Molecular Science
- (2018) Peter B. Jørgensen et al. Molecular Informatics
- De Novo Design of Bioactive Small Molecules by Artificial Intelligence
- (2018) Daniel Merk et al. Molecular Informatics
- Large-scale comparison of machine learning methods for drug target prediction on ChEMBL
- (2018) Andreas Mayr et al. Chemical Science
- MoleculeNet: a benchmark for molecular machine learning
- (2018) Zhenqin Wu et al. Chemical Science
- Planning chemical syntheses with deep neural networks and symbolic AI
- (2018) Marwin H. S. Segler et al. NATURE
- Demystifying Multitask Deep Neural Networks for Quantitative Structure–Activity Relationships
- (2017) Yuting Xu et al. Journal of Chemical Information and Modeling
- Is Multitask Deep Learning Practical for Pharma?
- (2017) Bharath Ramsundar et al. Journal of Chemical Information and Modeling
- Deep learning for computational chemistry
- (2017) Garrett B. Goh et al. JOURNAL OF COMPUTATIONAL CHEMISTRY
- Generative Recurrent Networks for De Novo Drug Design
- (2017) Anvita Gupta et al. Molecular Informatics
- Application of Generative Autoencoder in De Novo Molecular Design
- (2017) Thomas Blaschke et al. Molecular Informatics
- Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Data Sets
- (2017) Alexandru Korotcov et al. MOLECULAR PHARMACEUTICS
- Artificial Intelligence: Chess match of the century
- (2017) Demis Hassabis NATURE
- Beyond the hype: deep neural networks outperform established methods using a ChEMBL bioactivity benchmark set
- (2017) Eelke B. Lenselink et al. Journal of Cheminformatics
- Molecular de-novo design through deep reinforcement learning
- (2017) Marcus Olivecrona et al. Journal of Cheminformatics
- Retrosynthetic Reaction Prediction Using Neural Sequence-to-Sequence Models
- (2017) Bowen Liu et al. ACS Central Science
- Prediction of Organic Reaction Outcomes Using Machine Learning
- (2017) Connor W. Coley et al. ACS Central Science
- Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks
- (2017) Marwin H. S. Segler et al. ACS Central Science
- ANI-1, A data set of 20 million calculated off-equilibrium conformations for organic molecules
- (2017) Justin S. Smith et al. Scientific Data
- Computer-Assisted Synthetic Planning: The End of the Beginning
- (2016) Sara Szymkuć et al. ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
- Use of machine learning approaches for novel drug discovery
- (2016) Angélica Nakagawa Lima et al. Expert Opinion on Drug Discovery
- Synergies Between Quantum Mechanics and Machine Learning in Reaction Prediction
- (2016) Peter Sadowski et al. Journal of Chemical Information and Modeling
- Molecular graph convolutions: moving beyond fingerprints
- (2016) Steven Kearnes et al. JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN
- De Novo Design at the Edge of Chaos
- (2016) Petra Schneider et al. JOURNAL OF MEDICINAL CHEMISTRY
- Profiling Prediction of Kinase Inhibitors: Toward the Virtual Assay
- (2016) Benjamin Merget et al. JOURNAL OF MEDICINAL CHEMISTRY
- Mastering the game of Go with deep neural networks and tree search
- (2016) David Silver et al. NATURE
- The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology
- (2016) Artur Kadurin et al. Oncotarget
- Deep Learning for Drug-Induced Liver Injury
- (2015) Youjun Xu et al. Journal of Chemical Information and Modeling
- Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships
- (2015) Junshui Ma et al. Journal of Chemical Information and Modeling
- Deep Learning in Drug Discovery
- (2015) Erik Gawehn et al. Molecular Informatics
- PASS Targets: Ligand-based multi-target computational system based on a public data and naïve Bayes approach
- (2015) P.V. Pogodin et al. SAR AND QSAR IN ENVIRONMENTAL RESEARCH
- Target prediction utilising negative bioactivity data covering large chemical space
- (2015) Lewis H. Mervin et al. Journal of Cheminformatics
- Deep Architectures and Deep Learning in Chemoinformatics: The Prediction of Aqueous Solubility for Drug-Like Molecules
- (2013) Alessandro Lusci et al. Journal of Chemical Information and Modeling
- Time-Split Cross-Validation as a Method for Estimating the Goodness of Prospective Prediction.
- (2013) Robert P. Sheridan Journal of Chemical Information and Modeling
- ReactionPredictor: Prediction of Complex Chemical Reactions at the Mechanistic Level Using Machine Learning
- (2012) Matthew A. Kayala et al. Journal of Chemical Information and Modeling
- Machine Learning Methods for Property Prediction in Chemoinformatics: Quo Vadis?
- (2012) Alexandre Varnek et al. Journal of Chemical Information and Modeling
- Quantifying the chemical beauty of drugs
- (2012) G. Richard Bickerton et al. Nature Chemistry
- Learning to Predict Chemical Reactions
- (2011) Matthew A. Kayala et al. Journal of Chemical Information and Modeling
- Profile-QSAR: A Novelmeta-QSAR Method that Combines Activities across the Kinase Family To Accurately Predict Affinity, Selectivity, and Cellular Activity
- (2011) Eric Martin et al. Journal of Chemical Information and Modeling
- Enabling future drug discovery by de novo design
- (2011) Markus Hartenfeller et al. Wiley Interdisciplinary Reviews-Computational Molecular Science
- PaDEL-descriptor: An open source software to calculate molecular descriptors and fingerprints
- (2010) Chun Wei Yap JOURNAL OF COMPUTATIONAL CHEMISTRY
- Synthesis Explorer: A Chemical Reaction Tutorial System for Organic Synthesis Design and Mechanism Prediction
- (2009) Jonathan H. Chen et al. JOURNAL OF CHEMICAL EDUCATION
- Route Designer: A Retrosynthetic Analysis Tool Utilizing Automated Retrosynthetic Rule Generation
- (2009) James Law et al. Journal of Chemical Information and Modeling
- Predicting new molecular targets for known drugs
- (2009) Michael J. Keiser et al. NATURE
- Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions
- (2009) Peter Ertl et al. Journal of Cheminformatics
- Mold2, Molecular Descriptors from 2D Structures for Chemoinformatics and Toxicoinformatics
- (2008) Huixiao Hong et al. Journal of Chemical Information and Modeling
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