MATISSE (Module Analysis via Topology of Interactions and Similarity SEts) is a program for detection of functional modules using interaction networks and expression data. A functioncal module is a group of cellular components and their interactions that can be attributed a specific biological function.
GENIE3 is an algorithm for the inference of gene regulatory networks from expression data. It decomposes the prediction of a regulatory network between p genes into p different regression problems. In each of the regression problems, the expression pattern of one of the genes (target gene) is predicted from the expression patterns of all the other genes (input genes), using tree-based ensemble methods Random Forests or Extra-Trees. The importance of an input gene in the prediction of the target gene expression pattern is taken as an indication of a putative regulatory link.
Sylamer is a system for finding significantly over or under-represented words in sequences according to a sorted gene list. Typically it is used to find significant enrichment or depletion of microRNA or siRNA seed sequences from microarray expression data. Sylamer is extremely fast and can be applied to genome-wide datasets with ease. Results are plotted in terms of a significance landscape plot. These plots show significance profiles for each word studied across the sorted genelist.
CNAmet is an algorithm and R package that facilitates the integration of copy number, methylation and expression data. In addition to the CNAmet algorithm, the R package includes the S2N algorithm for the integration of copy number to expression data.