The Limits of Measuring Information in Biology: an Ontological Approach

Reyes, Agustín; Arroyo-Santos, Alfonso

doi:10.1007/s12304-018-9336-9

Cited by 1 publication

(1 citation statement)

References 28 publications

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“…Thus, it is possible that this result may be explained by pleiotropy, as a gene may have multiple biological functions that are yet uncaptured in HPO or GO. There are notable limitations to biological ontologies [79][80][81] , including the fact that they are often curated manually based on individual biological expertise.…”

Section: Discussionmentioning

confidence: 99%

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

Sullivan,

Miller,

Townsend

et al. 2024

Preprint

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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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Section: Discussionmentioning

confidence: 99%