Bioinformatics Research at the University of Waterloo

The identification of conserved gene clusters is an important step
towards understanding genome evolution and predicting the function of
genes. Bergeron et. al. formalized the concept of gene teams, which is a
model for conserved gene clusters that takes into account the position
of genes on a genome. Gene teams are also referred to as max-gap
clusters and they are widely used in practice. These methods require a
user-specified parameter, delta, that specifies the maximum distance 
between adjacent genes in a gene team. However, determining reasonable 
values for this delta is non-trivial. Furthermore, different regions of
the genome may have different rates of rearrangement and hence require 
different values of delta  to discover meaningful gene clusters.

In this talk, we briefly survey approaches to finding gene teams.
Then, we present our new approach of generating a gene team tree 
which is a compact representation of all the possible gene teams for
all possible value of the parameter delta. We also develop an efficient 
algorithm for computing the gene team tree. We verify the practicality 
of our approach by running our algorithm on several biological datasets.
We are also exploring new uses for the gene team tree.

(This is joint work with Melvin Zhang.)