To compute the significant of finding specific COGs functional modules, we generated 10,000 random module sets of the same size, and counted the number of times we found each COGs module in each randomized network.
To compute the significant of finding specific COGs modules, a p-value for each module was calculated based on the distribution of 10,000 random module sets of the same size (assuming a normal distribution) and our module predictions, therefore, representing the probability of seeing such modules at chance.
The constraint hypothesis predicts that "strong" modules, sets of highly-correlated traits, should display low morphological disparity.
By examining the networks of these relationships, one can identify modules, sets of highly-correlated traits that have only weak correlations with traits outside of the module.
S-MAP calculates scores for gene modules, sets of related genes, based on the pattern of differential expression of each module's constituent genes observed in several studies.
In Biology 35500, "modules"—sets of journal articles published sequentially from single laboratories are the focus for an intensive elective.
Specifically, we combined different types of interaction data to find gene modules, sets of highly interacting genes that often share similar function.
These topological modules often correspond to functional modules: aggregations of nodes similar in function, and to disease modules: sets of nodes that contribute to a specific disease phenotype [ 26].
A key question is how to extend integrative analysis of somatic genomic aberration data to expand known cancer pathways and interactions, or discover completely new modules (sets of related genes).
