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To make the procedure simple, the synthetic seismic data were created using a convolution technique on a thin-bed reflectivity model.
Network visualizations for our data were created using Cytoscape [ 55].
Simulated data were created using Hudson's ms (Hudson 2002).
Three-dimensional (3D) visualization of CLSM data were created using amira™ 4.0 (Mercury Computer Systems Inc., Chelmsford, MS, USA).
Ten imputed sets of data were created using the data from all of the models being considered.
These data were created using primary cell samples rather than immortalized cell lines, resulting in higher-quality gene expression profiles [ 8].
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A data base of collected qualitative and quantitative data was created using Microsoft Office Excel 2007 (Microsoft).
The visualizations depicting protein and RNA data are created using the R programming language and integrated into the web tool via the RPy2 library.
The motif data was created using the Toucan toolbox to search for putative motifs in the upstream sequence of the genes.
Sequence similarity data was creating using all-against-all BLAST comparisons within the training and test data sets, and between the training and test data sets and the use case data sets (redundant alignments were excluded).
A total of 20 imputed data sets were created using all variables in the analyses together with data on the same covariates collected at other close data sweeps.
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