Table 1 Positive and negative characteristics of different workflows shown in Figure 1 for the discovery of functional regulatory units
Workflow A | Workflow B | Workflow C |
|---|---|---|
+ ease of application | + very straightforward, no parameters or thresholds | + can integrate many existing programs |
+ software is available | + guaranteed result in several rounds | + different algorithms address particular properties of promoters |
+ the spectrum of existing methods covers all particular aspects of transcriptional regulation | Â | + optimization of a collection of combinatorial modules instead of optimization of each module separately |
– big number of methods to choose from (over 150 can be found in the Internet) | – may lead to a scission of a functional module rendering all parts non functional | – huge number of predicted features require much memory and CPU = > specificity filtering should be applied before modules optimization |
– relative performance of methods differs for different datasets | – high lab work and time investments | |
– chance of a correct prediction is ~5-10% [5] |  | |
– impossible to estimate the number of required rounds |  |