ENODAL: an experimentally guided nutriomics data clustering method to unravel complex drug-diet interactions.

ABSTRACT: Unraveling the complex interplay between nutrients and drugs via their effects on "omics" features could revolutionize our fundamental understanding of nutritional physiology, personalized nutrition, and, ultimately, human health span. Experimental studies in nutrition are starting to use large-scale "omics" experiments to pick apart the effects of such interacting factors. However, the high dimensionality of the omics features, coupled with complex fully factorial experimental designs, poses a challenge to the analysis. Current strategies for analyzing such types of data are based on between-feature correlations. However, these techniques risk overlooking important signals that arise from the experimental design and produce clusters that are hard to interpret. We present a novel approach

SUBMITTER: Xu X 

PROVIDER: S-EPMC11843446 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature