Investigation of early molecular alterations in tauopathy with generative adversarial networks
Abstract The recent advances in deep learning-based approaches hold great promise for unravelling biological mechanisms, discovering biomarkers, and predicting gene function. Here, we deployed a deep generative model for simulating the molecular progression of tauopathy and dissecting its early feat...
Main Authors: | Hyerin Kim, Yongjin Kim, Chung-Yeol Lee, Do-Geun Kim, Mookyung Cheon |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2023-01-01
|
Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-023-28081-6 |
Similar Items
-
Unveiling OASIS family as a key player in hypoxia–ischemia cases induced by cocaine using generative adversarial networks
by: Kyoungmin Lee, et al.
Published: (2022-04-01) -
Altered Synapse Stability in the Early Stages of Tauopathy
by: Johanna S. Jackson, et al.
Published: (2017-03-01) -
Evaluating Differentially Private Generative Adversarial Networks Over Membership Inference Attack
by: Cheolhee Park, et al.
Published: (2021-01-01) -
Potent of strategic approaches for tauopathies ranging from single-cell transcriptome to microbiome
by: Sung-Hyun Kim, et al.
Published: (2023-12-01) -
Simplified Fréchet Distance for Generative Adversarial Nets
by: Chung-Il Kim, et al.
Published: (2020-03-01)