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。Automated De Novo Drug Design: Are We Nearly There Yet?
Gisbert Schneider et al.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION (2019)
Ultra-large library docking for discovering new chemotypes
Jiankun Lyu et al.
NATURE (2019)
Exploring the GDB-13 chemical space using deep generative models
Josep Arus-Pous et al.
JOURNAL OF CHEMINFORMATICS (2019)
BRUSELAS: HPC Generic and Customizable Software Architecture for 3D Ligand-Based Virtual Screening of Large Molecular Databases
Antonio J. Banegas-Luna et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2019)
Dealing with frequent hitters in drug discovery: a multidisciplinary view on the issue of filtering compounds on biological screenings
Rafael Ferreira Dantas et al.
EXPERT OPINION ON DRUG DISCOVERY (2019)
Computational Approaches for Drug Discovery
Simone Brogi
MOLECULES (2019)
Advances in distributed computing with modern drug discovery
Antonio Jesus Banegas-Luna et al.
EXPERT OPINION ON DRUG DISCOVERY (2019)
METADOCK: A parallel metaheuristic schema for virtual screening methods
Baldomero Imbernon et al.
INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS (2018)
POAP: A GNU parallel based multithreaded pipeline of open babel and AutoDock suite for boosted high throughput virtual screening
A. Samdani et al.
COMPUTATIONAL BIOLOGY AND CHEMISTRY (2018)
Machine learning in chemoinformatics and drug discovery
Yu-Chen Lo et al.
DRUG DISCOVERY TODAY (2018)
Reinforced Adversarial Neural Computer for de Novo Molecular Design
Evgeny Putin et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2018)
Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening
Zixuan Cang et al.
PLOS COMPUTATIONAL BIOLOGY (2018)
Deep learning and virtual drug screening
Kristy A. Carpenter et al.
FUTURE MEDICINAL CHEMISTRY (2018)
Protein-Ligand Scoring with Convolutional Neural Networks
Matthew Ragoza et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2017)
Performance of machine-learning scoring functions in structure-based virtual screening
Maciej Wojcikowski et al.
SCIENTIFIC REPORTS (2017)
Structure-based discovery of clinically approved drugs as Zika virus NS2B-NS3 protease inhibitors that potently inhibit Zika virus infection in vitro and in vivo
Shuofeng Yuan et al.
ANTIVIRAL RESEARCH (2017)
Use of machine learning approaches for novel drug discovery
Angelica Nakagawa Lima et al.
EXPERT OPINION ON DRUG DISCOVERY (2016)
Boosting Docking-Based Virtual Screening with Deep Learning
Janaina Cruz Pereira et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2016)
Machine-learning approaches in drug discovery: methods and applications
Antonio Lavecchia
DRUG DISCOVERY TODAY (2015)
Deep learning in neural networks: An overview
Juergen Schmidhuber
NEURAL NETWORKS (2015)
PARS: a web server for the prediction of Protein Allosteric and Regulatory Sites
Alejandro Panjkovich et al.
BIOINFORMATICS (2014)
The cloud and other new computational methods to improve molecular modelling
Oliver Korb et al.
EXPERT OPINION ON DRUG DISCOVERY (2014)
Optimization Methods for Virtual Screening on Novel Computational Architectures
Horacio Perez-Sanchez et al.
CURRENT COMPUTER-AIDED DRUG DESIGN (2011)
Virtual screening of chemical libraries
BK Shoichet
NATURE (2004)
分享论文
