We have organized the rest of the paper as follows: the computational methods adopted are presented in "Computational Method" section.
Call this the computational argument, which unfolds as follows: minds are computational problem solving devices; there are specific types of solutions to specific types of problems; and so for minds to be (successful) general problem solving devices, they must consist of collections of specific problem solving devices, i.e. many computational modules.
Here we review a strategy that we have followed for the last few years, based on the combination of modern tools from computational chemistry with experimental biophysical methods.
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This was soon followed by computational models for studying bioelectrical activity at the tissue level.
For computational convenience, SEATS follows an alternative approach based on spectral analysis, as in Burman (1980).
High-throughput technologies, including array comparative genomic hybridization (aCGH), single nucleotide polymorphism (SNP) arrays and high-throughput sequencing (HTS) follow a similar computational analysis workflow for the detection of CNAs: preprocessing of raw data, copy number profile segmentation and CNA calling, based on the average values of the resulting segments.
Thus, in order to identify those genes and enzymes with a relevant role in bacteroid metabolism and, in turn, form a set of genes that serve as a benchmark for computational assessment, we followed an integrative, rather than, selective strategy.
In general, obtaining complete genome sequences for a given organism is immediately followed by the computational and manual annotation of its gene catalog.
Following the experiments, computational results obtained by the CFD package OpenFOAM are presented for both vertical and horizontal forces.
