Sentence examples for module detection problem from inspiring English sources
It should be noted that global network alignment methods such as IsoRank and GNA do not directly address the conserved module detection problem.
Here, the module detection problem is transformed to finding the optimum partitioning of the network in order to minimize the value of the clustering cost function.
Just to cite few, Heimo et al. 2008 studied the problem of multiresolution module detection in dense weighted networks, using a weighted version of the q‐state Potts method.
After network creation and module detection, the GMAT of detected modules with other (correlated) phenotypes can be calculated.
In addition to seed-and-extend approaches and hierarchical clustering, module detection can also be formulated as an optimization problem.
Motivation: Functional module detection within protein interaction networks is a challenging problem due to the sparsity of data and presence of errors.
Such wide differences clearly confirm that accurate module detection is particularly challenging in large networks where resolution problems are more pronounced.
Module detection in an eQTL network can be formulated as an optimization problem: searching for a set of m+n nodes that maximizes the objective function Q m, n, k) = k/(m×n), where m is the number of eQTLs, n is the number of target genes and k is the number of edges between them.
Median and best modularity values (Q) are reported after module detection with iMod (out of ten runs) and after accounting for resolution problems with ResMod (Q_Reso).
Here, we aim to enhance the application of mathematical programming to community structure identification by: (i) developing an efficient methodology for module detection that is capable of handling large size networks and (ii) incorporating strategies for dealing systematically with the problem of a resolution limit in module detection through modularity optimisation approaches.
For the BioGRID PPI network, module detection was performed using the Bioconductor package BioNet [ 14], which enables the determination of an exact solution to the problem of finding connected sub-graphs with low P-values.
