MENTOR: Multiplex Embedding of Networks for Team-Based Omics Research.
bioRxiv
; 2024 Jul 22.
Article
en En
| MEDLINE
| ID: mdl-39091782
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 genetic architectures in Populus trichocarpa associated with microbial abundance of multiple taxa. Moreover, as open source software designed with scientific teams in mind, we demonstrate the ability to use the output of MENTOR to facilitate distributed interpretation of omics experiments.
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1
Colección:
01-internacional
Banco de datos:
MEDLINE
Idioma:
En
Revista:
BioRxiv
Año:
2024
Tipo del documento:
Article
País de afiliación:
Estados Unidos