Dissection of gene expression datasets into clinically relevant interaction signatures via high-dimensional correlation maximization

Identification of clinically relevant gene expression signatures for cancer stratification remains challenging. Here, the authors introduce a flexible nonlinear signal superposition model that enables dissection of large gene expression data sets into signatures and extraction of gene interactions.

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Autores principales: Michael Grau, Georg Lenz, Peter Lenz
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2019
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Q
Acceso en línea:https://doaj.org/article/e6122c78f3584f9387082cbd4ab6e29f
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