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)

- Approaches related to RoBiC:

* How RoBiC**differs from SVD and related approaches**

* How RoBiC relates to other relevant results. - RoBiC finds a set of BiClusters, then uses them to produce a classifier.

This page presents**other ways to use BiClusters to build a classifier** - RoBiC uses a particular "hinge" function to decide which patients and
which genes belong to a bicluster.

This page describes**other "hinge functions"** - As suggested by the Figure above, we first form biclusters based on both
test and (unlabeled) training instances.

This page describes how this compares to simply**adding a**(to the training set) when finding the biclusters.*single*test instance at a time

- Summary of the Data/Results on
**Prognostic**datasets - Summary of the Data/Results on
**Diagnostic**datasets - Timing Information

- If you have better results on these data sets, based on hold-out
data (or CrossValidation), please email the relevant information

- dataset, approach, results

to Nasimeh Asgarian. - We are looking for other microarray datasets:
- Binary classification labels (either included with each sample, or better: some withheld until we produce our predictions)
- Complete data (ie, include a meaningful numeric score for each gene/sample pair)

If you have such datasets, please send them to us. We will, of course, accept standard confidentiality agreements; just let us know.

Our system uses data in the same format as the Plaid System; see here.

(Of course, we can convert from other formats.)