Sparse Manifold Clustering and Embedding to discriminate gene expression profiles of glioblastoma and meningioma tumors.
Juan Miguel García-GómezJuan Gómez-SanchísPablo Escandell-MonteroElies Fuster-GarcíaEmilio Soria-OlivasPublished in: Comput. Biol. Medicine (2013)
Keyphrases
- gene expression profiles
- gene expression
- high dimensional
- tissue samples
- microarray
- self organizing maps
- gene expression data
- clustering analysis
- manifold embedding
- cluster ensemble
- microarray data
- yeast cell cycle
- cancer diagnosis
- cancer classification
- tumor classification
- low dimensional
- graph embedding
- clustering algorithm
- euclidean space
- nonlinear dimensionality reduction
- gene selection
- geodesic distance
- clustering method
- manifold learning
- data sets
- high dimensionality
- vector space
- data points
- magnetic resonance imaging
- feature space
- dimensionality reduction
- k means
- pattern recognition
- sparse representation