Discriminative local subspaces in gene expression data for effective gene function prediction

Motivation: Massive amounts of genome-wide gene expression data have become available, motivating the development of computational approaches that leverage this information to predict gene function. Among successful approaches, supervised machine learning methods, such as Support Vector Machines (SV...

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Detalles Bibliográficos
Autores principales: Puelma, Tomas, Gutiérrez, Rodrigo A., Soto, Alvaro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2012
Materias:
Original Papers
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3426849/
https://www.ncbi.nlm.nih.gov/pubmed/22820203
http://dx.doi.org/10.1093/bioinformatics/bts455

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3426849/
https://www.ncbi.nlm.nih.gov/pubmed/22820203
http://dx.doi.org/10.1093/bioinformatics/bts455

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