标题
Generating property-matched decoy molecules using deep learning
作者
关键词
-
出版物
BIOINFORMATICS
Volume -, Issue -, Pages -
出版商
Oxford University Press (OUP)
发表日期
2021-01-29
DOI
10.1093/bioinformatics/btab080
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。- LIT-PCBA: An Unbiased Data Set for Machine Learning and Virtual Screening
- (2020) Viet-Khoa Tran-Nguyen et al. Journal of Chemical Information and Modeling
- Deep Generative Models for 3D Linker Design
- (2020) Fergus Imrie et al. Journal of Chemical Information and Modeling
- Discovery of Novel Inhibitors of a Critical Brain Enzyme Using a Homology Model and a Deep Convolutional Neural Network
- (2020) Adrian Stecula et al. JOURNAL OF MEDICINAL CHEMISTRY
- Machine learning classification can reduce false positives in structure-based virtual screening
- (2020) Yusuf O. Adeshina et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Ultra-large library docking for discovering new chemotypes
- (2019) Jiankun Lyu et al. NATURE
- In Need of Bias Control: Evaluating Chemical Data for Machine Learning in Structure-Based Virtual Screening
- (2019) Jochen Sieg et al. Journal of Chemical Information and Modeling
- Deep learning enables rapid identification of potent DDR1 kinase inhibitors
- (2019) Alex Zhavoronkov et al. NATURE BIOTECHNOLOGY
- Hidden bias in the DUD-E dataset leads to misleading performance of deep learning in structure-based virtual screening
- (2019) Lieyang Chen et al. PLoS One
- Most Ligand-Based Classification Benchmarks Reward Memorization Rather than Generalization
- (2018) Izhar Wallach et al. Journal of Chemical Information and Modeling
- Decoys Selection in Benchmarking Datasets: Overview and Perspectives
- (2018) Manon Réau et al. Frontiers in Pharmacology
- Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules
- (2018) Rafael Gómez-Bombarelli et al. ACS Central Science
- Protein Family-Specific Models Using Deep Neural Networks and Transfer Learning Improve Virtual Screening and Highlight the Need for More Data
- (2018) Fergus Imrie et al. Journal of Chemical Information and Modeling
- Practical Model Selection for Prospective Virtual Screening
- (2018) Shengchao Liu et al. Journal of Chemical Information and Modeling
- Protein–Ligand Scoring with Convolutional Neural Networks
- (2017) Matthew Ragoza et al. Journal of Chemical Information and Modeling
- Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks
- (2017) Marwin H. S. Segler et al. ACS Central Science
- Performance of machine-learning scoring functions in structure-based virtual screening
- (2017) Maciej Wójcikowski et al. Scientific Reports
- Benchmark of four popular virtual screening programs: construction of the active/decoy dataset remains a major determinant of measured performance
- (2016) Ludovic Chaput et al. Journal of Cheminformatics
- Constructing and Validating High-Performance MIEC-SVM Models in Virtual Screening for Kinases: A Better Way for Actives Discovery
- (2016) Huiyong Sun et al. Scientific Reports
- Benchmarking Data Sets for the Evaluation of Virtual Ligand Screening Methods: Review and Perspectives
- (2015) Nathalie Lagarde et al. Journal of Chemical Information and Modeling
- ZINC 15 – Ligand Discovery for Everyone
- (2015) Teague Sterling et al. Journal of Chemical Information and Modeling
- Challenges and advances in structure-based virtual screening
- (2013) Elizabeth Yuriev Future Medicinal Chemistry
- Evaluation and Optimization of Virtual Screening Workflows with DEKOIS 2.0 – A Public Library of Challenging Docking Benchmark Sets
- (2013) Matthias R. Bauer et al. Journal of Chemical Information and Modeling
- Lessons Learned in Empirical Scoring with smina from the CSAR 2011 Benchmarking Exercise
- (2013) David Ryan Koes et al. Journal of Chemical Information and Modeling
- Estimation of the size of drug-like chemical space based on GDB-17 data
- (2013) P. G. Polishchuk et al. JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN
- The ChEMBL bioactivity database: an update
- (2013) A. Patrícia Bento et al. NUCLEIC ACIDS RESEARCH
- Open-source platform to benchmark fingerprints for ligand-based virtual screening
- (2013) Sereina Riniker et al. Journal of Cheminformatics
- Directory of Useful Decoys, Enhanced (DUD-E): Better Ligands and Decoys for Better Benchmarking
- (2012) Michael M. Mysinger et al. JOURNAL OF MEDICINAL CHEMISTRY
- DEKOIS: Demanding Evaluation Kits for Objectivein SilicoScreening — A Versatile Tool for Benchmarking Docking Programs and Scoring Functions
- (2011) Simon M. Vogel et al. Journal of Chemical Information and Modeling
- Virtual Decoy Sets for Molecular Docking Benchmarks
- (2011) Izhar Wallach et al. Journal of Chemical Information and Modeling
- Extended-Connectivity Fingerprints
- (2010) David Rogers et al. Journal of Chemical Information and Modeling
- Maximum Unbiased Validation (MUV) Data Sets for Virtual Screening Based on PubChem Bioactivity Data
- (2009) Sebastian G. Rohrer et al. Journal of Chemical Information and Modeling
- Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions
- (2009) Peter Ertl et al. Journal of Cheminformatics
- What do we know and when do we know it?
- (2008) Anthony Nicholls JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started