Diversity oriented Deep Reinforcement Learning for targeted molecule generation

Diversity oriented Deep Reinforcement Learning for targeted molecule generation

Abstract In this work, we explore the potential of deep learning to streamline the process of identifying new potential drugs through the computational generation of molecules with interesting biological properties. Two deep neural networks compose our targeted generation framework: the Generator, w...

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Bibliographic Details
Main Authors: Tiago Pereira, Maryam Abbasi, Bernardete Ribeiro, Joel P. Arrais
Format: Article
Language:English
Published: BMC 2021-03-01
Series:Journal of Cheminformatics
Subjects:
Drug Design
SMILES
Reinforcement Learning
RNN
Online Access:https://doi.org/10.1186/s13321-021-00498-z

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