All of these results suggest a good fit of the models and the ability to discriminate from random chance was high [63].
However, conventional techniques of nonlinear time series analysis generally lack sufficient sensitivity, specificity and robustness to discriminate chaos from random noise, much less quantify the chaos level.
However, prevailing tests of chaotic dynamics using myriad nonlinear or complexity measures generally lack sufficient sensitivity, specificity and robustness to discriminate chaos from random noise, much less quantify the chaos level (see Appendix S1 for critique of methods).
To facilitate our approach, we developed our scanning method using criteria based on the features of 207 known human pre-miRNAs to discriminate miRNAs from random sequences.
Furthermore, single-base mutation oligonucleotides and random oligonucleotides can be easily discriminated from complementary target DNAs.
In particular, Fe3 + could be obviously discriminated from Fe2 +.
Further filtration steps were deployed using MiPred, which uses mfe and machine learning methods to discriminate real miRNAs from random miRNAs [ 73].
However, compared with a SVM model with the same feature set [area under receiver operating characteristic curve (AUC) > 0.9], the NBc preformed significantly less accurately in discriminating active enhancers from random sequences (AUC < 0.79).
Food does not discriminate from party to party.
This typically leads to a huge number of short match fragments that require sophisticated post-processing to discriminate single random hits from sets of adjacent hits potentially indicating true homologs.
