In contrast to the strong and stable RNAz signals of the known ncRNA genes, the signals of predictions in the coding sequences are systematically weaker and are less likely to be destroyed by the shuffling procedure: only 2.4% of shuffled windows were again classified as 'structured RNA' compared to 3.8% of the entire screen.
The simulations also demonstrated that the overhead introduced by the shuffling procedure is low.
In estimating the parameters, we have used the shuffling procedure described in Pisarenko et al. (2009), which is similar to the bootstrap method, with NS = 100 realizations.
After the shuffling procedure, the users' tweeting frequency and the frequency of a hashtag being used by all users remain the same, but which hashtags were used by which users were randomized.
The shuffling procedure described above yields a set of randomized sequences.
The shuffling procedure was repeated 1,000 times and all values were plotted (Figure 6c, lower panel).
After the shuffling procedure we can define two distributions, the real distribution found from the actual sequence and the Maximal Entropy Distribution (MED) which we use as the surrogate for the background.
A potential problem is that this shuffling procedure essentially shuffles the trace less thoroughly, and so the difference between surrogates and the original may not be detectable, even if deterministic repeats do exist.
(3) Subsequently, we applied a shuffling procedure to each COG class proteome as follows: (a) we shuffled the sequence of all the proteins within each COG class one thousand times, and therefore generated 1000 random proteomes for the same COG; (b) predicted CP were then identified using the predictive CSPD model, thus leading to the determination of a shuffled predicted CP percentage.
This shuffling procedure was repeated for all model orders.
A shuffling procedure is used to assess the significance of this selection process.
