Metabolic Modeling Combined With Machine Learning Integrates Longitudinal Data and Identifies the Origin of LXR-Induced Hepatic Steatosis

Metabolic Modeling Combined With Machine Learning Integrates Longitudinal Data and Identifies the Origin of LXR-Induced Hepatic Steatosis

Temporal multi-omics data can provide information about the dynamics of disease development and therapeutic response. However, statistical analysis of high-dimensional time-series data is challenging. Here we develop a novel approach to model temporal metabolomic and transcriptomic data by combining...

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Bibliographic Details
Main Authors: Natal A. W. van Riel, Christian A. Tiemann, Peter A. J. Hilbers, Albert K. Groen
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-02-01
Series:Frontiers in Bioengineering and Biotechnology
Subjects:
longitudinal trajectory modeling
regularization
cholesterol
LXR agonist
systems biology
machine learning
Online Access:https://www.frontiersin.org/articles/10.3389/fbioe.2020.536957/full

Internet

https://www.frontiersin.org/articles/10.3389/fbioe.2020.536957/full

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