The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology
Abstract
Recent advances in deep learning and specifically in generative adversarial networks have demonstrated surprising results in generating new images and videos upon request even using natural language as input. In this paper we present the first application of generative adversarial autoencoders (AAE) for generating novel molecular fingerprints with a defined set of parameters. We developed a 7-layer AAE architecture with the latent middle layer...
Paper Details
Title
The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology
Published Date
Dec 22, 2016
Journal
Volume
8
Issue
7
Pages
10883 - 10890
Citation AnalysisPro
You’ll need to upgrade your plan to Pro
Looking to understand the true influence of a researcher’s work across journals & affiliations?
- Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
- Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.
Notes
History