Using Expert Driven Machine Learning to Enhance Dynamic Metabolomics Data Analysis

Using Expert Driven Machine Learning to Enhance Dynamic Metabolomics Data Analysis

Data analysis for metabolomics is undergoing rapid progress thanks to the proliferation of novel tools and the standardization of existing workflows. As untargeted metabolomics datasets and experiments continue to increase in size and complexity, standardized workflows are often not sufficiently sop...

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Bibliographic Details
Main Authors: Charlie Beirnaert, Laura Peeters, Pieter Meysman, Wout Bittremieux, Kenn Foubert, Deborah Custers, Anastasia Van der Auwera, Matthias Cuykx, Luc Pieters, Adrian Covaci, Kris Laukens
Format: Article
Language:English
Published: MDPI AG 2019-03-01
Series:Metabolites
Subjects:
machine learning
dynamic metabolomics
data simulation
Online Access:https://www.mdpi.com/2218-1989/9/3/54

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