BACKGROUND: De Brujin graphs are widely used in bioinformatics for processing 
next-generation sequencing data. Due to a very large size of NGS datasets, it is 
essential to represent de Bruijn graphs compactly, and several approaches to 
this problem have been proposed recently.
RESULTS: In this work, we show how to reduce the memory required by the data 
structure of Chikhi and Rizk (WABI'12) that represents de Brujin graphs using 
Bloom filters. Our method requires 30% to 40% less memory with respect to their 
method, with insignificant impact on construction time. At the same time, our 
experiments showed a better query time compared to the method of Chikhi and 
Rizk.
CONCLUSION: The proposed data structure constitutes, to our knowledge, currently 
the most efficient practical representation of de Bruijn graphs.