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The next-generation sequencing data was generated from samples of four patients at three timepoints during treatment with the co-receptor antagonist Vicriviroc.
Until recently much of the sequence data was generated from isolated organisms, but with the advent of metagenomics and next-generation sequencing technologies, the sequence space that can be surveyed has increased dramatically, thereby providing new opportunities for the discovery and characterization of novel biological functions including biocatalysts.
Present climate data was generated from 50 climate stations within the watershed using co-kriging.
Quantitative analysis of performance took place and qualitative data was generated from a questionnaire assessing the learning experience.
Subsequently, daily flow data was generated from monthly flow data using temporal downscaling technique (Wood et al 2004) for use as input to the HEC-5 model.
The random % change data was generated from Mersenne-Twister set to a uniform distribution between -1 and 1.
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Data sources and characteristics: Data is generated from many different sources in many different formats.
F2 generations were used and all data were generated from littermates.
Stratum data were generated from a geological survey report.
Simulation data were generated from a model developed based on a Phase I study.
Cyber data is generated from a variety of analysis and monitoring tools.
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