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Knowledge-based gene expression classification via matrix factorization

Schachtner, R. ; Lutter, D. ; Knollmüller, P. ; Tomé, A. M. ; Theis, Fabian J. ; Schmitz, G. ; Stetter, M. ; Gómez Vilda, P. ; Lang, Elmar



Abstract

Motivation: Modern machine learning methods based on matrix decomposition techniques, like independent component analysis (ICA) or non-negative matrix factorization (NMF), provide new and efficient analysis tools which are currently explored to analyze gene expression profiles. These exploratory feature extraction techniques yield expression modes (ICA) or metagenes (NMF). These extracted ...

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