Abstract:
Rapid development of technologies for the collection of biological
data have led to large increases in the amount of information
available for understanding diseases and biological mechanisms. However,
progress has not been as fast in comprehending the data. Developments
in understanding diseases and biological mechanisms governing
them may come from combining data from different sources. We describe
a method of clustering lists of genes identified as important to the understanding
of a childhood cancer using functional information about
the genes from the Gene Ontology. The measure of distance used in the
clustering algorithm is notable for considering the relationship between
terms in the ontology. Meaningful descriptions of clusters are automatically
generated from the Gene Ontology terms.
