GLARE: discovering hidden patterns in spaceflight transcriptome using representation learning.

ABSTRACT: Spaceflight studies present novel insights into biological processes through exposure to stressors outside the evolutionary path of terrestrial organisms. Despite limited access to space environments, numerous transcriptomic datasets from spaceflight experiments are now available through NASA's GeneLab data repository, which allows public access, encouraging further analysis. While various computational pipelines and methods have been used to process these transcriptomic datasets, learning-model-driven analyses have yet to be applied to a broad array of such spaceflight-related datasets. In this study, we present an open-source pipeline, GLARE: GeneLAb Representation learning pipelinE, which consists of training different representation learning approaches from manifold learning to self-su

SUBMITTER: Seo D 

PROVIDER: S-EPMC12569054 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature