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Multifactorial data analyses revealed that the transformation assay discriminated between nonmutagenic carcinogens and noncarcinogens; it detected 64% of the carcinogens and only 26% of the noncarcinogens.
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Extensive, multifactorial data sharing is a crucial prerequisite for current and future (radiotherapy) research.
Data analyses will continue for at least another year.
Network 5 demonstrates the utility of the multifactorial data (Fig. 9) for network reconstruction.
Multifactorial data might correspond for example to expression profiles obtained from different patients or biological replicates.
Data analyses consisted of four parts.
Data analyses were conducted with SPSS16.
Data analyses were performed with Openstat3 software.
Multifactorial data are defined as static steady-state expression profiles resulting from slight perturbations of all genes simultaneously.
Knockout data are more informative for network inference than knockdown or multifactorial data.
In this work, we have combined multifactorial data to identify network-based biomarkers.
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