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Adopting culturally sensitive methods can result in complex and heterogeneous data sets which present challenges for analysis and interpretation.
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Finally, the richness of MOOC data also presents challenges for analysis.
Though it is one of the primary databases used in epidemiologic research [ 1– 3], the unique structure and coding of the CPRD data presents challenges for analysis and for comparisons with other databases.
While being highly successful at gathering data, the high-throughput technologies also present challenges for data analysis by requiring sophisticated computational methods not only in correcting technical artifacts but also for organizing the output and extraction of biologically meaningful features.
Both new developments present challenges for structural reliability analysis.
We find that organisms with multiple compartments and extremophiles present challenges for modeling and thermodynamics-based flux analysis.
The recording of more than one ethnic group presents challenges for ethnic analysis including measuring ethnic intermarriage.
The unique structure and coding of the Clinical Practice Research Datalink (CPRD) presents challenges for epidemiologic analysis and for comparisons with other databases.
At the same time, this will present challenges for utilities that lack the systems and data analysis skills to deal with these data.
However, drones also present challenges for cities.
Does that present challenges for material?
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