DeepMicroGen: a generative adversarial network-based method for longitudinal microbiome data imputation.

ABSTRACT:

Motivation

The human microbiome, which is linked to various diseases by growing evidence, has a profound impact on human health. Since changes in the composition of the microbiome across time are associated with disease and clinical outcomes, microbiome analysis should be performed in a longitudinal study. However, due to limited sample sizes and differing numbers of timepoints for different subjects, a significant amount of data cannot be utilized, directly affecting the quality of analysis results. Deep generative models have been proposed to address this lack of data issue. Specifically, a generative adversarial network (GAN) has been successfully utilized for data augmentation to improve prediction tasks. Recent studies have also shown improved performance of GAN-based models f

SUBMITTER: Choi JM 

PROVIDER: S-EPMC10196688 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature