Unsupervised Machine Learning for Differential Analysis in Proteomics.
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DOI: 10.1021/acs.analchem.5c03117
Abstract: Differential analysis in proteomics is pivotal for biomarker discovery and disease mechanism elucidation, yet traditional statistical methods are constrained by distributional assumptions and empirical fold change threshold dependencies. This study systematically evaluates 18 unsupervised anomaly… read more here.
Keywords: analysis; differential analysis; machine learning; analysis proteomics ... See more keywords