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Our method is appealing for several reasons.
Finally, by not involving lentiviruses, our method is appealing to a broad research audience.
This method is appealing because it does not modify the biological system, which is unfamiliar to us.
While we cannot completely rid our data of spurious local and global variability due to various measurement factors, this method is appealing both for its simplicity and for its clear empirical findings.
This method is appealing for applications because it is based on algebraic topology, which gives a well-understood theoretical framework to study qualitative features of data with complex structure, is computable via linear algebra, and is robust with respect to small perturbations in input data.
The ability to generate a high order method is appealing for applications on the kind of quasi-uniform grids that are popular for atmospheric modelling, so that the method retains an acceptable level of accuracy even around special points in the grid.
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The simplicity of this method was appealing, but traded off by the potential accuracy inferior to that of the first method.
Predicting expression level of genes through computational methods is appealing because it circumvents expensive and difficult experiment.
In silico methods are appealing because they provide a faster alternative to otherwise time-consuming laboratory and clinical testing methods [4, 5].
Especially, solution-phase methods are appealing because of the low growth temperatures, potentials for scaling up and capability of producing high-density arrays [19].
X-ray spectroscopic methods are appealing since mix into the hot-spot will result in x-ray emission from the high-Z dopant (Cu or Ge) in the ablator material (Be or CH).
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