Comprehensive cluster analysis with Transitivity Clustering.

Transitivity Clustering is a method for the partitioning of biological data into groups of similar objects, such as genes, for instance. It provides integrated access to various functions addressing each step of a typical cluster analysis. To facilitate this, Transitivity Clustering is accessible online and offers three user-friendly interfaces: a powerful stand-alone version, a web interface, and a collection of Cytoscape plug-ins.

Exact and heuristic algorithms for weighted cluster editing.

Clustering objects according to given similarity or distance values is a ubiquitous problem in computational biology with diverse applications, e.g., in defining families of orthologous genes, or in the analysis of microarray experiments.