RoBiC System Overview

The RoBiC system learns microarray classifiers by first reducing the dimentionality of data matrix using biclusters.
In general, a bicluster is a subset of genes and a subset of samples whose expression values have similar patterns; here, each bicluster is a sparse rank-one matrix -- ie, the outer product of two sparse vector.

TechReport (9page): "Using Rank-1 Biclusters to Classify Microarray Data"   (9/Apr/07)     

TechReport (7page): "Using Rank-One Biclusters to Classify Microarray Data"   (21/May/07)
    Nasimeh Asgarian, Russell Greiner

MSc Dissertation: "Using Rank-1 BiClusters", (Jan 2007; Nasimeh Asgarian)

Related Algorithms and Approaches

Details of Empirical Studies


Reading Group