The current scientific data deluge, in which datasets grow faster in size and complexity than scientists can keep up with, defines several new challenges for information systems.
Specifically, our project offers two distinct services: I) a preservation service, in which datasets are digitally preserved, and kept externally inaccessible, and II) a publication service, in which datasets receive a DOI and are accessible, free of costs, through our site [4,5].
To maximize the knowledge that can be obtained from large-scale genomic and proteomic experiments, focus is now being placed on systems biology approaches in which datasets are combined to learn more information than can be gathered from any one dataset alone.
The predicted target genes are listed on the web page and there are links to spreadsheets giving more detailed information on each target's relationship with the regulator, for example, the number of datasets, and in which datasets, the relationship is significant.
Each of these is strongly supported in different positions depending on which dataset is analysed.
Factors that should be taken into account in determining which datasets should be linked for enhancement purposes include: previous validations studies, representativeness of the community, and the extent to which information in each dataset is collected independently.
The inner dimension in the right half of Equation 2 determines the number of co-occurring patterns in which the dataset is decomposed.
For each subject, a stratified five-fold cross-validation was performed in which the dataset was partitioned into five random subsets.
In cases in which the dataset consisted of only 2 groups of samples, Student's t-test was applied to test for statistical significance.
All modules in this method are evaluated using ten-fold cross-validation, in which the dataset was divided into ten equal size sets.
