CGGA: Co-expressed Gene Groups Analysis application for extracting bi-clusters of co-expressed genes from integrated gene expression data and gene annotations obtained from biological knowledge. The gene rank hierarchy is first constructed using SAM F-Scores and the CGGA algorithm is then applied to cluster co-expressed genes.
ExCIS: Extraction from Conceptual Information System application for the integration of background knowledge and expert knowledge in the data mining process in order to improve the data preprocessing and interpretation of extracted patterns phases.
FIST: Frequent Itemset mining using Suffix-Trees application for the integrated extraction of conceptual bi-clusters and association rules from massive data repositories.
GenMiner: Genomic Data Miner application for extracting the equivalence classes and the Informative Basis of association rules from genomic data. Gene expression data are discretized using the Normal Discretization algorithm and both equivalence classes of frequent itemsets and the Informative Basis of association rules are generated according to the user defined parameters.
JClose: JClose application for extracting equivalence classes and Informative Bases of association rules from datasets in CSV and ARFF (Weka) formats. This implementation generates the list of frequent equivalence classes of itemsets and the minimal non-redundant exact and approximate association rules according to the user defined thresholds.
Nordi: Normalized Discretization application for normal discretization of gene expression data suppressing the influence of outliers on the computation of threshold cutoffs for gene under-expression and over-expression. The user defined parameter of the Nordi algorithm sets the confidence level for the discretization.