Discovery of functional protein groups by clustering community links and integration of ontological knowledge

In this paper we cluster data from protein networks and integrate the results with chemical databases and ontologies to investigate functional links between related disease states. It is well know that certain genes participate in more than one function and if they are defective are likely to be responsible for several health problems. Furthermore, genes tend to cooperate in associated networks or cascades often with ’crosstalk’ between networks which can subtly alter cellular functions. Understanding the complexity and role of the various cell functions and mechanisms requires the use of computational models to make inferences and link together the interplay between genes, proteins and chemical interactions. A deeper understanding of the mechanisms of diseases will eventually be of benefit for the development new and improved therapies. The particular disease state we investigate in this work is cystinosis which is characterized by the widespread deposition of the amino acid cystine in cells due to a defect in cystine transport. In cystinosis, cystine accumulates in the lysosomes and eventually forms crystals throughout the body causing problems in the kidneys and the eyes. The defect is caused by a mutation in the CTNS gene and this forms the starting point for our investigation.