PaccMannRL: De novo generation of hit-like anticancer molecules from transcriptomic data via reinforcement learning
Summary: With the advent of deep generative models in computational chemistry, in-silico drug design is undergoing an unprecedented transformation. Although deep learning approaches have shown potential in generating compounds with desired chemical properties, they disregard the cellular environment...
Main Authors: | Jannis Born, Matteo Manica, Ali Oskooei, Joris Cadow, Greta Markert, María Rodríguez Martínez |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2021-04-01
|
Series: | iScience |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2589004221002376 |
Similar Items
-
Ecological and Evolutionary Consequences of Anticancer Adaptations
by: Justine Boutry, et al.
Published: (2020-11-01) -
Mutational analysis of the PacC binding sites within the aflR promoter in Aspergillus flavus
by: Suleman, Essa
Published: (2011) -
The production of arabitol by a novel plant yeast isolate Candida parapsilosis 27RL-4
by: Kordowska-Wiater Monika, et al.
Published: (2017-10-01) -
Predicting anticancer hyperfoods with graph convolutional networks
by: Guadalupe Gonzalez, et al.
Published: (2021-06-01) -
The role of pacC in Aspergillus flavus
by: Suleman, Essa
Published: (2007)