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In silico generation of novel, drug-like chemical matter using the LSTM
  neural network

In silico generation of novel, drug-like chemical matter using the LSTM neural network

20 December 2017
P. Ertl
Richard A. Lewis
E. Martin
V. Polyakov
ArXivPDFHTML

Papers citing "In silico generation of novel, drug-like chemical matter using the LSTM neural network"

6 / 6 papers shown
Title
Multi-view deep learning based molecule design and structural
  optimization accelerates the SARS-CoV-2 inhibitor discovery
Multi-view deep learning based molecule design and structural optimization accelerates the SARS-CoV-2 inhibitor discovery
Chao Pang
Yu Wang
Yi Jiang
Ruheng Wang
R. Su
Leyi Wei
8
1
0
03 Dec 2022
Investigation of chemical structure recognition by encoder-decoder
  models in learning progress
Investigation of chemical structure recognition by encoder-decoder models in learning progress
Katsuhisa Morita
T. Mizuno
Hiroyuki Kusuhara
19
8
0
24 Oct 2022
GuacaMol: Benchmarking Models for De Novo Molecular Design
GuacaMol: Benchmarking Models for De Novo Molecular Design
Nathan Brown
Marco Fiscato
Marwin H. S. Segler
Alain C. Vaucher
ELM
44
691
0
22 Nov 2018
Generating equilibrium molecules with deep neural networks
Generating equilibrium molecules with deep neural networks
Niklas W. A. Gebauer
M. Gastegger
Kristof T. Schütt
BDL
17
38
0
26 Oct 2018
Graph Convolutional Policy Network for Goal-Directed Molecular Graph
  Generation
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation
Jiaxuan You
Bowen Liu
Rex Ying
Vijay S. Pande
J. Leskovec
GNN
203
885
0
07 Jun 2018
Constrained Bayesian Optimization for Automatic Chemical Design
Constrained Bayesian Optimization for Automatic Chemical Design
Ryan-Rhys Griffiths
José Miguel Hernández-Lobato
BDL
39
76
0
16 Sep 2017
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