To detect the robustness of the proposed method we applied FiloDetect on noisy images.
We tested the robustness of detecting the PS when the LNS patterns in images have different orientations, scales, contrasts, articulated and twisted parts, as well as other noises.
The real data analysis and computer simulation show that the new method confers not only significantly improved statistical power for detecting the associations but also robustness to the difficulties stemmed from non-randomly sampling and genetic structures when compared to its rivals.
In the optimization of benchmark test functions, this method showed very good performance, with parallel efficiency between 80% and 100%, and excellent robustness, always detecting the global optimum.
While analysis of the data from single domain like mutations or gene expression is often the first choice in a project, integrative genomic approaches have more advantages such as robustness in detecting the biological signals or biomarkers and low false discovery rates due to the evidence from multiple domains.
In particular we found that our choice of weights is very conservative and far from the limits detected in the robustness analysis (see the Additional file 1: Figure S1).
The experiment for detecting the three types of DS, N-terminal-, C-terminal-, and middle-domain swapping, discloses the robustness of the proposed method.
A statistical factor of synchronization in the two-dimensional space is defined to detect the appearance and robustness of spiral wave in the network of neurons.
Bp-distance had difficulty detecting mutational robustness in the data, likely due to the high stringency of the neutrality measure.
The successful metabolic profiling of such tissue, as evidenced by the high reproducibility and number of metabolites detected, further demonstrates the robustness of our pipeline and developed methodologies.
