A network-based feature selection approach to identify metabolic signatures in disease

DOI10.1016/j.jtbi.2012.06.003zbMath1337.92080OpenAlexW1977176813WikidataQ51346370 ScholiaQ51346370MaRDI QIDQ292792

Karl G. Kugler, Laurin A. J. Müller, Michael Netzer, Armin Graber, Matthias Dehmer, Klaus M. Weinberger, Christian Baumgartner

Publication date: 9 June 2016

Published in: Journal of Theoretical Biology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jtbi.2012.06.003

zbMATH Keywords

networksfeature selectionbiomarkerstopological descriptors

Mathematics Subject Classification ID

Medical applications (general) (92C50) Systems biology, networks (92C42)

Uses Software

• R
• igraph
• QuACN
• caret
• graph

Cites Work

• A history of graph entropy measures
• Support-vector networks
• Ranking of network elements based on functional substructures
• Selection bias in gene extraction on the basis of microarray gene-expression data
• The elements of statistical learning. Data mining, inference, and prediction
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