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Table 1 Positive and negative characteristics of different workflows shown in Figure 1 for the discovery of functional regulatory units

From: An integrative computational approach to effectively guide experimental identification of regulatory elements in promoters

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   + 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