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。Application of deep learning methods in biological networks
Shuting Jin et al.
BRIEFINGS IN BIOINFORMATICS (2021)
Attentional multi-level representation encoding based on convolutional and variance autoencoders for lncRNA-disease association prediction
Nan Sheng et al.
BRIEFINGS IN BIOINFORMATICS (2021)
Bidirectional Molecule Generation with Recurrent Neural Networks
Francesca Grisoni et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2020)
De novo generation of hit-like molecules from gene expression signatures using artificial intelligence
Oscar Mendez-Lucio et al.
NATURE COMMUNICATIONS (2020)
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
Daniil Polykovskiy et al.
FRONTIERS IN PHARMACOLOGY (2020)
Direct steering of de novo molecular generation with descriptor conditional recurrent neural networks
Panagiotis-Christos Kotsias et al.
NATURE MACHINE INTELLIGENCE (2020)
Generative molecular design in low data regimes
Michael Moret et al.
NATURE MACHINE INTELLIGENCE (2020)
Graph convolutional networks for computational drug development and discovery
Mengying Sun et al.
BRIEFINGS IN BIOINFORMATICS (2020)
Recent applications of deep learning and machine intelligence on in silico drug discovery: methods, tools and databases
Ahmet Sureyya Rifaioglu et al.
BRIEFINGS IN BIOINFORMATICS (2019)
Coupling of Contact Nucleation Kinetics with Breakage Model for Crystallization of Sodium Chloride Crystal in Fluidized Bed Crystallizer
Dan Zheng et al.
JOURNAL OF CHEMISTRY (2019)
Deep learning for molecular design-a review of the state of the art
Daniel C. Elton et al.
MOLECULAR SYSTEMS DESIGN & ENGINEERING (2019)
Review of Deep Learning Algorithms and Architectures
Ajay Shrestha et al.
IEEE ACCESS (2019)
DrugBank 5.0: a major update to the DrugBank database for 2018
David S. Wishart et al.
NUCLEIC ACIDS RESEARCH (2018)
Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks
Marwin H. S. Segler et al.
ACS CENTRAL SCIENCE (2018)
Deep Learning for Drug Design: an Artificial Intelligence Paradigm for Drug Discovery in the Big Data Era
Yankang Jing et al.
AAPS JOURNAL (2018)
MoleculeNet: a benchmark for molecular machine learning
Zhenqin Wu et al.
CHEMICAL SCIENCE (2018)
Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules
Rafael Gomez-Bombarelli et al.
ACS CENTRAL SCIENCE (2018)
Frechet ChemNet Distance: A Metric for Generative Models for Molecules in Drug Discovery
Kristina Preuer et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2018)
Mastering the game of Go without human knowledge
David Silver et al.
NATURE (2017)
THE DRUG-MAKER'S GUIDE TO THE GALAXY
Asher Mullard
NATURE (2017)
Quantum-chemical insights from deep tensor neural networks
Kristof T. Schuett et al.
NATURE COMMUNICATIONS (2017)
Machine learning of accurate energy-conserving molecular force fields
Stefan Chmiela et al.
SCIENCE ADVANCES (2017)
A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles
Aravind Subramanian et al.
CELL (2017)
PubChem Substance and Compound databases
Sunghwan Kim et al.
NUCLEIC ACIDS RESEARCH (2016)
ZINC 15-Ligand Discovery for Everyone
Teague Sterling et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2015)
Estimation of the size of drug-like chemical space based on GDB-17 data
P. G. Polishchuk et al.
JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN (2013)
Enumeration of 166 Billion Organic Small Molecules in the Chemical Universe Database GDB-17
Lars Ruddigkeit et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2012)
ZINC: A Free Tool to Discover Chemistry for Biology
John J. Irwin et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2012)
Quantifying the chemical beauty of drugs
G. Richard Bickerton et al.
NATURE CHEMISTRY (2012)
ChEMBL: a large-scale bioactivity database for drug discovery
Anna Gaulton et al.
NUCLEIC ACIDS RESEARCH (2012)
The Harvard Clean Energy Project: Large-Scale Computational Screening and Design of Organic Photovoltaics on the World Community Grid
Johannes Hachmann et al.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS (2011)
How to improve R&D productivity: the pharmaceutical industry's grand challenge
Steven M. Paul et al.
NATURE REVIEWS DRUG DISCOVERY (2010)
970 Million Druglike Small Molecules for Virtual Screening in the Chemical Universe Database GDB-13
Lorenz C. Blum et al.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY (2009)
Quantifying biogenic bias in screening libraries
Jerome Hert et al.
NATURE CHEMICAL BIOLOGY (2009)
Reducing the dimensionality of data with neural networks
G. E. Hinton et al.
SCIENCE (2006)