Ondex enables data from diverse biological data sets to be linked, integrated and visualised through graph analysis techniques. Ondex can be used in a number of important application areas such as transcription analysis, protein interaction analysis, data mining and text mining.

Data may be imported through a number of parsers for public-domain and other databases such as TRANSFAC, TRANSPATH, CHEBI, Gene Ontology, KEGG, Drastic, Enzyme Nomenclature, Pathway Tools Pathway Genomes (PGDBs), Plant Ontology, and Medical Subject Headings Vocabulary (MeSH) together with associated sequence data where available.

The imported data may be visualised using Ondex. It displays the data as a set of linked graphs where nodes represent data objects and edges (or links between the nodes) represent relationships between nodes. FiltersÂ’ are provided to select specific classes of data and relations in order to narrow the graph down to a selectable depth of linkage. In addition, a powerful filter is available to import microarray expression level data to globally analyse the relations between the different genes being expressed.

Ondex is able to handle very large graphs and to represent many hundreds of thousands of data items, examine them for potential relationships through identifying equivalent concepts (data type), filter out unattached nodes (ones with no edges or relations) for the problem under consideration and provides labelled, organised graphs that may also be manipulated through the user interface.

Ondex is freely available and is being developed as an open source project. More about the Ondex SABR project.