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Datasets are processed to build a similarity matrix S that contains the similarities between all pairs of users in the user-based version or items in the item-based version.
The datasets are processed one-by-one and are then stitched together to form a collage for further analysis.
The trend in residual values is not present when datasets are processed with the SPOT technique or with Agilent foreground and SPOT background.
While the ExpressionData resource is expected to grow as new datasets are processed and made available, it does not aim at having complete sets of data for every organism.
In ChIP-chip the reconstructed signal intensity is generated by comparing the immunoprecipitated information (IP) with the control dataset, while in ChIP-seq the IP and control datasets are processed separately.
Typically large proteomics datasets are processed using either a large set of ORF overpredictions or using the entire genome itself in order to identify sequences that are translated to protein but do not yet appear in annotated protein lists.
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The obtained datasets were processed with the software Amptek PMCA.
EELS-SI datasets were processed by the following procedure.
All datasets were processed by both PPP method and relative GPS method.
Datasets were processed and scaled using the HKL2000 package (Otwinowski and Minor, 1997).
This choice is due to the general applications discussed here, where four different datasets were processed by the same algorithm.
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units are processed
kits are processed
arrays are processed
figures are processed
assemblies are processed
pairs are processed
blocks are processed
breaks are processed
series are processed
datasets are restricted
datasets are tested
datasets are illustrated
datasets are used
datasets are performed
datasets are combined
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