At least two complications arise in this analysis.
It is assumed that questions arising in the analysis of the simplest model are inherent in the general model as well.
We elaborate on applications of our algorithm arising in the analysis of cosmological N-body data, computer graphics, and continuum mechanics problems.
A major complication arising in the analysis of the GC content of higher eukaryotes lies in the existence of so-called CpG islands, which are regions of DNA with a high GC content and a high frequency of CpG dinucleotides.
These challenges are similar but not identical to the challenges arising in the analysis of metagenomic samples and require specific solutions.
While numerous tools have been introduced for metagenomic data analysis (see Teeling and Glockner (2012) for an overview), only comparatively few tools exist with focus on the specific difficulties arising in the analysis of metaproteomic data.
Our framework can also solve more general problems arising in the analysis of structured data, like dense subgraph detection in multi-partite graphs (cf. Everett et al., 2006; Tanay et al., 2004) or in hypergraphs (cf. Zhao and Zaki, 2005).
An important problem that arises in the analysis of this data is determining if a set of genes are collectively regulated by a set of transcription factors and whether this combinatorial regulation changes when the cell is exposed to stress.
This parameter arises in the analysis of coupled rectangular plates and gives a conservative estimate for irregularily shaped plates.
This problem arises in the analysis of clinical trials in which selection is made between a number of experimental treatments that are compared with each other either with or without an additional control treatment.
This particular problem arose in the analysis of oscillatory Riemann Hilbert problems associated with partial differential equations in the Ablowitz Kaup Newell Segur hierarchy, but is interesting in its own right as a question in harmonic analysis and oscillatory integrals.
