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The application of PYTHON for analysis of big data can be explored.
The kinetic fitting data can be explored to design a nanopatterned surface for a specific application.
Similarly, genomics data can be explored by geWorkbench[28], StratomeX[29], GENE-E[30], Qcanvas[31] or Gitools[32].
Once the nature of this parameter is estimated, other patterns in the data can be explored.3.3
Specifically, the quality of big data can be explored along the dimensions of volume, variety, velocity, and veracity.
The data can be explored and analyzed using the IMG/M system or downloaded for further analyses using stand-alone tools.
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The data provided are not complete to dissect the sequences and cellular functions required for late replication of subtelomere segments, but provide useful data that can be explored for further studies.
While MICA is an asthma study, this rich data set can be explored for relationships between early indicators of cardiovascular disease, obesity, and asthma and to demonstrate the complex nature of childhood health and environmental disease.
For example, it is essential to identify the data types that can be explored and studied in this domain.
Once a compelling motif has been identified from a set of ChIP data, the motif can be explored using the MochiView motif scoring utilities and the plot browser to identify instances of a motif that occur in intergenic regions but not within the binding regions called by the ChIP-analysis algorithm.
The data for each country can be explored in more detail on YouGov's website.
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