Required Fields:
Email Address:     Array Matrix File :   (example)
Types of Module:
Conservation Module
Selected genes are conservatively expressed in the selected samples. It can be row-conserved, column-conserved, or both. These modules correspond to the "traditional biclusters" with constant values on rows and/or columns as discussed in the review paper by Madeira and Oliveira (2004). 		Differential Module
Selected genes are differentially expressed between the selected samples and the unselected samples. These modules correspond to the simultaneous application of two-component mixture model on the expression of selected genes and the phenotypes of samples. 		Intensity Module
The sum of values in the submatrix composed of selected rows and columns are maximized. The sum can be normalized by the size of the module.
Constrain row values: width <=
Constrain column values: width <= 		Differential Test :
    Threshold of the statistics :
    One-sided (UP-regulated in selected samples)
    Two-sided (UP- or DOWN-regulated)

Normalization factor for
      nRows = (SUM /= nRows^Factor)
  nColumns = (SUM /= nColumns^Factor)
Mining Real Data
        Number of Modules :
        Mask previous results:
        Allow duplicated results : No Yes

Permutation Test
        Number of Permutations:  
        Shuffling  Sample Labels Matrix Values
           (only if the sample features are provided)

Processing the Data

Upper bound values greater than: (before Log and normalization)

Lower bound values smaller than: (before Log and normalization)

Transformation No transformation Log transformation

Normalization by shifting and scaling the data into :

Constraints on the Size of Modules:

Minimal number/fraction of Columns:
Maximal number/fraction of Columns :

Minimal number of Rows :
Maximal number of Rows:

Maximization Criteria / Type of scores    

Apply Enrichment Constraint on Gene Features : Yes No

Add bonus score from :
  Sample metrics enrichment (weight = )  
  Sample weight bias statistics ( weight = )
Gene Features: Constraints on Gene Features
  Gene label/weight file :     (example) Enrichment of Gene Labels >=    
  Pairwise link/weight file :  (example) Enrichment of Gene Interactions >=
Sample Features: Constraints on Sample Features
  Main Phenotype (sample metrics) file:  (example)
             		 Type of differential test :
Threshold of test statistics: 
Direction of enrichment One-sided (higher enrichment) Two-sided (higher or lower)
  Additional Feature (sample weights) file:  (example)
             		Threshold of bias statistics :  (Chi-sq for binary, T^2 for real number weights)
Direction of bias : One-sided (higher enrichment) Two-sided (higher or lower)
Query for Modules containing certain Core Genes

Specify the indexes of Core Genes : (e.g. 102,304,55)
or
Upload a file with the indexes   (example)

If multiple genes are given, All At least one
    core genes should be included in the same module.

 Additional options

Short tag string for identification :

Seed Number for Random Value Generator (0=TimeStamp):

Claim illegal values :
  (values that are considered as outliers or coded as missing values, e.g. 999,-1)

  The Bioinformatics Program at BU  

            This web server is supported in part by NSF grants DBI-0239435 and ITR-048715, NHGRI grant #1R33HG002850-01A1 and NIH grant U54 LM008748.