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These include the analysis of data on strengths or density of connections, the investigation of refined partitioning schemes in different cortical functional systems, the spatial embedding of brain regions and pathways (e.g. [15]), the consideration of hierarchical network measures (e.g. [67]) and application of the graph theory framework to functional connectivity data (e.g. [21], [22], [24]).
Upon application of the graph decomposition routine, we successfully unfold the underlying modular structure of the TNF- α network.
G2SBC Database web interface provides two tools that rely on the application of the graph theory to biological networks.
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In this paper, we will focus on the application of the graphs to opportunistic communication where each object in sensor networks communicates with the others in every given period of time [6].
This article presents a novel approach to constructing a reachability graph, and discusses the application of the reachability graph to Petri nets analysis.
Other promising applications of the graph-based approaches in bioinformatics include immune cells detection (Chang et al., 2008), cell images segmentation (Isfahani et al., 2008) and protein function prediction (Borgwardt et al., 2005).
These experiments on real data open the door to the application of the median graph to a number of more complex machine learning algorithms where a representative of a set of graphs is needed.
As an immediate application of this graph-theoretic setting, the preservation of the finite-model property by graph-theoretic fibring was proved in Coniglio et al. 2011.
Another application to the graph-theoretic account of logic is the definition of an asymmetric combination technique called importing logics (cf. Rasga et al. 2011).
Application of the causal graph-based method TIE* to the training set of NARAC subjects results in two five-SNP information equivalent Markov boundaries of the rheumatoid arthritis phenotypic response variable (denoting case and control status of the subjects).
Note, however, that de novo genome assembly is not the only application of those graphs when dealing with NGS data.
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