MENTOR: Multiplex Embedding of Networks for Team-Based Omics Research.

ABSTRACT: While the proliferation of data-driven omics technologies has continued to accelerate, methods of identifying relationships among large-scale changes from omics experiments have stagnated. It is therefore imperative to develop methods that can identify key mechanisms among one or more omics experiments in order to advance biological discovery. To solve this problem, here we describe the network-based algorithm MENTOR - Multiplex Embedding of Networks for Team-Based Omics Research. We demonstrate MENTOR's utility as a supervised learning approach to successfully partition a gene set containing multiple ontological functions into their respective functions. Subsequently, we used MENTOR as an unsupervised learning approach to identify important biological functions pertaining to the host gene

SUBMITTER: Sullivan KA 

PROVIDER: S-EPMC11291001 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature