Evaluation of data discretization methods to derive platform independent isoform expression signatures for multi-class tumor subtyping

BACKGROUND: Many supervised learning algorithms have been applied in deriving gene signatures for patient stratification from gene expression data. However, transferring the multi-gene signatures from one analytical platform to another without loss of classification accuracy is a major challenge. He...

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Detalles Bibliográficos
Autores principales: Jung, Segun, Bi, Yingtao, Davuluri, Ramana V
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4652565/
https://www.ncbi.nlm.nih.gov/pubmed/26576613
http://dx.doi.org/10.1186/1471-2164-16-S11-S3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4652565/
https://www.ncbi.nlm.nih.gov/pubmed/26576613
http://dx.doi.org/10.1186/1471-2164-16-S11-S3

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