POC is an algorithm that searches for over represented cis-regulatory binding motifs in a group of genes with shared biological function. The input is a list (functional group or cluster) of human or mouse genes. The hyper-geometric test is used in order to find motifs that are over represented among the genes on the input gene list. Finding this connection between DNA motifs and a cluster of genes enables us to decipher the regulatory network that controls the input cluster.

This workshop is intended to demonstrate how the program can be used, and its capabilities. In particular, the following will be addressed:

What is POC?
What is it good for?
How is it working?
What can it do?
How to use it?

Examples on previous results:
Using POC on cell cycle genes (Tabach et al MSB 2005).
Using POC on 130 different genes group (Tabach et al PLoS ONE 2007)