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Similar to the PPCA experiments with additive noise, we randomly generate five input datasets for each setup to obtain statistically significant results.
As the input datasets for individual proteins, we use condition-dependent abundance (arbitrary units) of proteins [ 27] and the MIPS functional database for individual proteins [ 28].
The input datasets for three of these strains came from the Broad Institute database; while the remaining three came from the supplementary material of [ 16].
Input datasets for these analyses included the entire DNA sequences of individual ORFs or, where noted, a set of multiple ORFs.
Subsequently, the resulting center sequences were used as input datasets for the downstream analysis steps that are commonly used in different application fields, such as assembly and genome/transcriptome alignment steps.
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The histograms of each input dataset for favorable output showed that each information layer had a certain pattern.
Fig. 5 System load and network activity of all sites when executing the phylogenetic profiling workflow with the 64 genome input dataset for both our approach and Swift Fig. 6 System load and network activity of site 0 when executing the phylogenetic profiling workflow with the 64 genome input dataset for both our approach and Swift.
Computer vision algorithms mainly focus on the analysis of a given set of input images and videos without much considering what would be the most effective input dataset for the analysis.
To further analyze the behavior of our framework against Swift, in Fig. 5 we present the system load and network activity of all sites when executing the phylogenetic profiling workflow with the 64 genome input dataset for both our approach and Swift.
The authors thank Ms. Bhakti Limaye for generating the input dataset for phylogenetic profiling.
The remaining 20,234 probe sets formed the input dataset for further statistical testing.
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