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

20 December 2017

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

8 / 8 papers shown

Title
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 24 1 0 03 Dec 2022
Investigation of chemical structure recognition by encoder-decoder models in learning progress Katsuhisa Morita T. Mizuno Hiroyuki Kusuhara 19 8 0 24 Oct 2022
Controlled Molecule Generator for Optimizing Multiple Chemical Properties Bonggun Shin Sungsoo Park Jinyeong Bak Joyce C. Ho 33 15 0 26 Oct 2020
GuacaMol: Benchmarking Models for De Novo Molecular Design Nathan Brown Marco Fiscato Marwin H. S. Segler Alain C. Vaucher ELM 44 693 0 22 Nov 2018
Generating equilibrium molecules with deep neural networks Niklas W. A. Gebauer M. Gastegger Kristof T. Schütt BDL 19 38 0 26 Oct 2018
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation Jiaxuan You Bowen Liu Rex Ying Vijay S. Pande J. Leskovec GNN 215 886 0 07 Jun 2018
Constrained Bayesian Optimization for Automatic Chemical Design Ryan-Rhys Griffiths José Miguel Hernández-Lobato BDL 39 76 0 16 Sep 2017
Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models G. L. Guimaraes Benjamín Sánchez-Lengeling Carlos Outeiral Pedro Luis Cunha Farias Alán Aspuru-Guzik GAN 34 519 0 30 May 2017