On the other hand, gene-module based methods take advantages of biclustering algorithms [ 7, 8] or item-set mining algorithms [ 9] to detect a cluster of genes which share similar patterns on a subset of gene conditions.
A module based optimization method using genetic algorithms (GA), and multivariate regression analysis has been developed to optimize a set of parameters in the design of a nuclear reactor.
While integrating of gene expression information into identification of gene modules is biologically meaningful, gene-network based methods are rarely satisfactory because they either focus on small networks by using the greedy subgraph search algorithm [ 17, 18] or focus on detecting non-overlapping subnetworks [ 16, 19, 20].
The theoretical approach reflected in the intervention modules is motivational enhancement with use of CBT based methods.
In order to determine the overlaps between the modules we suggest to use one of the local maxima based methods.
This means the modularity density based partition method can produce more biologically significant modules than the modularity based method.
This paper presents an effective method for predicting and optimizing the cooling performance of Parallel-Plain Fin (PPF) heat sink module based on the Taguchi method.
An exergoeconomic module, based on the SPECO method, has been embedded into 'EXRETOpt', a recently developed retrofit-oriented exergy simulation tool based on EnergyPlus.
This development integrated a stand-alone geomechanics module based on finite element method with the reservoir simulator, an advantage of our coupling algorithm, and improved our understanding of the production through various enhanced oil recovery processes such as water and CO2 flooding processes previously coded in UTCOMP.
In the paper "Module Based Differential Coexpression Analysis Method for Type 2 Diabetes," L. Yuan et al. proposed a gene differential coexpression analysis algorithm and applied it to a publicly available type 2 diabetes (T2D) expression dataset.
