Most transcription factors (TFs) belong to protein families that share a common 
DNA binding domain and have very similar DNA binding preferences. However, many 
paralogous TFs (i.e. members of the same TF family) perform different regulatory 
functions and interact with different genomic regions in the cell. A potential 
mechanism for achieving this differential in vivo specificity is through 
interactions with protein co-factors. Computational tools for studying the 
genomic binding profiles of paralogous TFs and identifying their putative 
co-factors are currently lacking. Here, we present an interactive web 
implementation of COUGER, a classification-based framework for identifying 
protein co-factors that might provide specificity to paralogous TFs. COUGER 
takes as input two sets of genomic regions bound by paralogous TFs, and it 
identifies a small set of putative co-factors that best distinguish the two sets 
of sequences. To achieve this task, COUGER uses a classification approach, with 
features that reflect the DNA-binding specificities of the putative co-factors. 
The identified co-factors are presented in a user-friendly output page, together 
with information that allows the user to understand and to explore the 
contributions of individual co-factor features. COUGER can be run as a 
stand-alone tool or through a web interface: http://couger.oit.duke.edu.