Factors associated with the burden of influenza among vulnerable populations have mainly been identified using statistical methodologies.
Inferences about the presence and importance of DIF require a process of so-called test purification where items with DIF are identified using statistical tests and DIF is modeled using group-specific item parameters.
Differentially expressed genes were identified using statistical analyses, and were validated with external databases and with immunohistochemistry.
Initially, differential expression patterns were identified using statistical analysis, and specific transcriptional profiles were established for each evaluated interaction.
These methods begin with molecular dynamics (MD) simulations from which representative "non-redundant" structures are identified using statistical methods.
Tissue-specific behavior has also been identified using statistical tests to compare sample distributions between tissue types [ 1, 15, 16].
The largest variance is explained by known or unknown study-specific effects that will disturb clustering unless they are identified using statistical modeling, and removed before analysis.
BDL, below detection limit Patterns were identified using statistical pattern matching [ 23, 24] by assigning each gene as significantly "up", "down", or "no change" detected in each tissue.
Candidate cancer genes instead derive from large-scale mutational screenings of cancer samples and have been identified using statistical methods with poor or no experimental follow-up.
To avoid the effects of local technical and biological variations, the differential behaviors of any individual gene were identified using statistical significance tests only.
