It is well-known that Claude Shannon, the father of information theory, spent all his days at Bell labs playing chess and thinking about Chess moves. In the same vein, maybe the best ideas of modern day bioinformatics will come from those, who ‘waste their time’ playing card :)
We describe a new variation of a mathematical card trick, whose analysis leads to new lower bounds for data compression and estimating the entropy of Markov sources.
Several years ago, an article in the popular press  described the following mathematical card trick: the magician gives a deck of cards to an audience member, who cuts the deck, draws six cards and lists their colours; the magician then says which cards were drawn. The key to the trick is that the magician prearranges the deck so that the sequence of the cards colours is a substring of a binary De Bruijn cycle of order six, i.e., so that every sextuple of colours occurs at most once. Although the trick calls only for the magician to name the cards drawn, he or she could also name the next card, for example, with absolute certainty. At the time we ran across the article, we were studying empirical entropy, and one way to de?ne the kth-order empirical entropy of a string s is as our expected uncertainty about the character in a randomly chosen position when given the preceding k characters . After reading the tricks description, it occurred to us that the kth-order empirical entropy of any De Bruijn cycle of order at most k is 0. Using this and other properties of De Bruijn cycles, we were able to prove several lower bounds for data compression [3, 4].
If you do not understand the context of this commentary, it is related to a very cool paper from Rayan Chikhi and collaborators that we are not supposed to talk about :). They supposedly compress de Bruijn graphs into 3.5-4.5 bits/kmer, which is close to the theoretical limit of 2.43 bits per k-mer derived in their paper !!