Ovarian cancer classification based on dimensionality reduction for SELDI-TOF data

BACKGROUND: Recent advances in proteomics technologies such as SELDI-TOF mass spectrometry has shown promise in the detection of early stage cancers. However, dimensionality reduction and classification are considerable challenges in statistical machine learning. We therefore propose a novel approac...

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Detalles Bibliográficos
Autores principales: Tang, Kai-Lin, Li, Tong-Hua, Xiong, Wen-Wei, Chen, Kai
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Research article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2846906/
https://www.ncbi.nlm.nih.gov/pubmed/20187963
http://dx.doi.org/10.1186/1471-2105-11-109

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2846906/
https://www.ncbi.nlm.nih.gov/pubmed/20187963
http://dx.doi.org/10.1186/1471-2105-11-109

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