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For Greedy and QCUT, we used the relevant software to evaluate modules and estimate the resulting modularity.
The modulePreservation function implements several powerful network based statistics for evaluating module preservation.
The modulePreservation function implements a permutation test involving several powerful network based statistics for evaluating module preservation.
In addition to evaluating module preservation between the two Rhodobacter species, we wanted to assess pairwise conservation of expression between orthologs.
We tried using a novel method for evaluating module preservation [ 34] to check whether modules are preserved in terms of density and connectivity between the species regardless of the parameters used to obtain the modules.
Our study has several strengths including the use of multiple large data sets, carefully validated brain co-expression modules from Oldham et al 2008, and a powerful statistical approach for evaluating module preservation.
The theoretical development approach can be applied to hollow fiber membrane modules for other applications and the theoretical solutions can be utilized for evaluating modules using various eddy promoting designs.
To evaluate the module functionality, we performed the GO/pathway enrichment analysis for each isoform module.
We therefore endeavoured to formatively evaluate this module by answering the following questions: Does the content of the module foreground the steps involved in EBM?
We used mixed methods to evaluate this module: A document review to assess whether the content of the module reflects important EBM competencies; a survey of the students to determine their experiences of the module; and semi-structured interviews with the tutors to explore their perspectives of the module.
We evaluate the module performance metrics based on differential measurement between the cooling powers with temperature difference across the module under transient conditions.
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