The phrase "a dense module" is correct and usable in written English.
It can be used in contexts related to mathematics, computer science, or any field where the term "module" is applicable, often referring to a module that has a high level of complexity or compactness.
Example: "In our analysis, we found that a dense module can significantly improve the efficiency of the algorithm."
Alternatives: "a compact module" or "a complex module".
For genome-wide association studies (GWAS), Jia and Zhao [ 9] applies a dense module search algorithm for locating network modules that are jointly associated with a disease.
The contribution of our article consists in (i) the development of a dense module enumeration (DME) algorithm for weighted networks, including a ranking scheme and an efficient strategy to identify locally maximal modules, (ii) its application to the protein interaction networks of yeast and human and (iii) the effective integration of constraints from additional data sources.
In black, we indicate the percentage of the known complex that is covered by a conserved dense module.
This is because all dense modules formed are enriched with complex terms, violating the bound.
A comparative performance analysis is then achieved between a porous and a dense membrane module.
By taking advantage of our previously developed dense module search method, we proposed an alternative search strategy in this work and demonstrated it in the CATIE GWAS dataset, one of the major available GWAS datasets for schizophrenia.
In this work, we proposed a restricted search strategy to implement our previously developed dense module search (DMS) method [ 8].
there exist at least n0 conditions c∈ C with m uc =0 ∀ u∈ U and there exist at least n1 c∈ C with m uc =1 ∀ u∈ U. Given such a consistency constraint, we can stop the module extension during the dense module mining as soon as the constraint is violated.
In this study, we proposed an alternative restricted search approach based on our previously developed dense module search algorithm, and we demonstrated it in the CATIE GWAS dataset for schizophrenia.
While previous approaches use approximations to extract dense modules, our approach exactly solves the problem of dense module enumeration.
This subnetwork-searching algorithm was named the "edgewise dense module searching" (eDMS).
