This observation is consistent with our assumption that hub genes have little expression changes between difference phenotypes, so that they have less variations across different data sets as compared to their down-stream genes.
But we had no way of easily running algorithms across different data sources to pull together a comprehensive picture of potential breaches.
These analyses require highly specific data of materials that are scattered across different data sources.
As such, they can provide a way map across different data formats with essentially the same semantics.
When data are quantified in this way, they can be used to compare across different data sets obtained from properly designed questionnaires.
The best model is then found across different data splits and cross-validation schemes, based on the averaged data splits statistics.
Therefore, they cannot take into account the common information shared across different data platforms and may fail in identifying driver genes that lead to the change of network.
To address this challenge, in this paper we propose a diversification scheme that targets the problem of efficiently diversifying the results of multiple queries within and across different data exploratory sessions.
Statistic and stochastic models are employed that are not only consistent with topographic data structures simulated in this research, but also can track the correlation of errors over time and across different data sources to establish reliable detection levels.
The outer optimization problem follows a two-stage stochastic programming approach to optimize the expected objective across different data classes; adaptive robust optimization is nested as the inner problem to ensure the robustness of the solution while maintaining computational tractability.
We consider a number of energy efficiency factors (such as energy cost, carbon emission rate, workload, and CPU power efficiency) which change across different data centers depending on their location, architectural design, and management system.
