In many genomic studies, one works with genome-position-dependent data, e.g. 
ChIP-chip or ChIP-Seq scores. Using conventional tools, it can be difficult to 
get a good feel for the data, especially the distribution of features. This 
article argues that the so-called Hilbert curve visualization can complement 
genome browsers and help to get further insights into the structure of one's 
data. This is demonstrated with examples from different use cases. An 
open-source application, called HilbertVis, is presented that allows the user to 
produce and interactively explore such plots.
AVAILABILITY: http://www.ebi.ac.uk/huber-srv/hilbert/.