Nonlinear dimension reduction and clustering by Minimum Curvilinearity unfold neuropathic pain and tissue embryological classes

Motivation: Nonlinear small datasets, which are characterized by low numbers of samples and very high numbers of measures, occur frequently in computational biology, and pose problems in their investigation. Unsupervised hybrid-two-phase (H2P) procedures—specifically dimension reduction (DR), couple...

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Detalles Bibliográficos
Autores principales: Cannistraci, Carlo Vittorio, Ravasi, Timothy, Montevecchi, Franco Maria, Ideker, Trey, Alessio, Massimo
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2010
Materias:
Eccb 2010 Conference Proceedings September 26 to September 29, 2010, Ghent, Belgium
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2935424/
https://www.ncbi.nlm.nih.gov/pubmed/20823318
http://dx.doi.org/10.1093/bioinformatics/btq376

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2935424/
https://www.ncbi.nlm.nih.gov/pubmed/20823318
http://dx.doi.org/10.1093/bioinformatics/btq376

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