Leveraging ML for profiling lipidomic alterations in breast cancer tissues: a methodological perspective

Leveraging ML for profiling lipidomic alterations in breast cancer tissues: a methodological perspective

Abstract In this study, a comprehensive methodology combining machine learning and statistical analysis was employed to investigate alterations in the metabolite profiles, including lipids, of breast cancer tissues and their subtypes. By integrating biological and machine learning feature selection...

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Bibliographic Details
Main Authors: Parisa Shahnazari, Kaveh Kavousi, Zarrin Minuchehr, Bahram Goliaei, Reza M Salek
Format: Article
Language:English
Published: Nature Portfolio 2024-10-01
Series:Scientific Reports
Subjects:
Lipidomics
Breast cancer
Feature selection
Machine learning
Univariate analysis
Multivariate analysis
Online Access:https://doi.org/10.1038/s41598-024-71439-7
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https://doi.org/10.1038/s41598-024-71439-7

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