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In this work, the TG analysis data were gained from three measurements.
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Further data were gained from medical records.
Consequently, no useful data was gained.
Developing event-based models that allow analysis of sequential data are gaining a new popularity in the social networks literature by providing a way of handling long sequences of exchanges within the context of a relational system.
Large-scale genome characterisations, through the analysis of gene sequence and expression data, are gaining increasing interest and have the potential to greatly improve our understanding of the physiological and molecular mechanisms underlying disease pathogenesis and progression.
Before statistical analysis data were normalized.
The homogeneous access to sensor data in data monitoring and analysis applications is gaining much interest nowadays.
By combining gene expression data in a meta-analysis, greater power and more information can be gained from existing data.
We show that valuable new information can be gained from meta analysis of existing microarray data deposited in public repositories.
As data streams are gaining prominence in a growing number of emerging applications, advanced analysis and mining of data streams is becoming increasingly important.
Training samples are gained by FEM analysis.
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