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Both data types have been used in studies of neurodegenerative diseases such as Alzheimer's, Parkinson's, and healthy mouse brain.
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Both of the data types have been shown to be especially useful for annotation of splice-variants.
During the last decades several approaches using active [9 11], passive [12] or both [13] remote sensing data types have proven sufficient accuracies for carbon quantification.
As it is shown, these data types have significantly different probability distributions.
These standard data types have therefore been used to calculate the meteorological parameters required by LINCOM-T.
Significant discrepancies concerning the availability of the data types have been identified when posting items.
In order to cope with data abstractions in the development of experiments, complex data types have been included in ESL.
All data types have different temporal resolution, but in each case a minimal resolution of 5 minute is ensured.
The definitions of complex data types have to be included in the preamble before the definition of the variables that will be used in the experiment.
All data types have strengths and weaknesses and all datasets are prone to artifacts specific to the dataset.
In addition to gene expression data, a range of other data types have been used to enhance the reconstruction of gene networks.
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CEO of Professional Science Editing for Scientists @ prosciediting.com