 Documents: clustering by content relatedness, position within citation networks, connections via authors or institutional affiliations  Assays: classified by various assay ontologies  Results: log transformations (e.g. pIC50 or pKi) for potency sorting and implicit molecular mechanism of action (mmoa), (e.g. where A-R indicates C to be a potent inhibitor of P)  Compounds: a full range of cheminformatic analysis including 2D or 3D clustering, property prediction and chemical ontology assignments  Proteins: a full range of bioinformatic analysis including Gene Ontology (GO) assignments, pathway annotation, structural homology, disease associations and genetic variation (e.g. for target validation).