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The data were matched against heart disease mortality over a typical period of 14.6 years, during which a total of 831 CVD deaths were recorded.
HUS surveillance data were matched against hospital discharge data by last name, first name, and date of birth.
Service utilisation data were matched against age and gender cohorts and, once mapped, were projected against future demographic structures.
Data were matched against the databases with the use of the MS-Fit program (accessible through ProteinProspector).
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Likewise, in nuclear vector replacement, residual dipolar coupling data are matched against predictions from an available structure (or high-quality model).
In patients treated with MoAbs against EGFR, the molecular and clinical data were matched.
Data were matched by age and parity.
In the challenge data set, 208 MS/MS spectra were matched against the combined MassBank and NIST libraries.
Altered genes were matched against these data using the meta information to select appropriate drug-gene partners.
All reconstructed transcripts were matched against annotated transcripts.
Additionally substance data can be matched against in-silico generated tandem mass spectra [5] or can be used in approaches using substructure detection algorithms and molecular isomer generators [6].
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CEO of Professional Science Editing for Scientists @ prosciediting.com