Supervised non-negative matrix factorization methods for MALDI imaging applications

MOTIVATION: Non-negative matrix factorization (NMF) is a common tool for obtaining low-rank approximations of non-negative data matrices and has been widely used in machine learning, e.g. for supporting feature extraction in high-dimensional classification tasks. In its classical form, NMF is an uns...

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Detalles Bibliográficos
Autores principales: Leuschner, Johannes, Schmidt, Maximilian, Fernsel, Pascal, Lachmund, Delf, Boskamp, Tobias, Maass, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Original Papers
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6546133/
https://www.ncbi.nlm.nih.gov/pubmed/30395171
http://dx.doi.org/10.1093/bioinformatics/bty909

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6546133/
https://www.ncbi.nlm.nih.gov/pubmed/30395171
http://dx.doi.org/10.1093/bioinformatics/bty909

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