Sentence examples for analytical data processing from inspiring English sources

Analytical data processing utilizing proprietary algorithms provide final answers on the screen.

Analytical data processing utilizing proprietary algorithms provides answers directly to the user.

For SQL-on-Hadoop engines, this can mean faster query times and increased performance, as experienced by Baidu as they adopted Alluxio to speed up their analytical data processing.

Overall, says McVean, the center "will bring together analytical data processing and genetics in one institute, so we can tackle some of the thorny but fascinating questions about collecting and analyzing big data sets".

However, as a high-throughput technology, metabolomics datasets are extremely large and require multiple tools for data information and management, raw analytical data processing, compound standardization and ontology, statistics, integration, visualization, mathematical modeling of metabolic networks, and interpretation (Figure 1D,E) [69].

In addition, the commonly used analytical and semi-analytical data processing methods are not suitable for miscible flooding for ignoring the mechanism of vaporizing and dissolving mechanism.

We discuss the design, analytical prerequisites, data processing and interpretation of single and dual-SIP experiments and highlight a case study on anaerobic methanotrophic communities inhabiting hydrothermally heated marine sediments.

Figure 1 Material of choice (A), sample preparation and extraction (B), analytical methods (C), data processing (D), and data analysis and interpretation (E).

Metabolomics is a complex field of analytical chemistry and bioinformatics in which advanced techniques to determine the levels of a wide range of metabolites are employed in a series of procedures, including sample extraction and preparation, metabolite detection using analytical instruments, and data processing and mining by means of bioinformatics techniques.

Because of this, numerous protocols for metabolite analysis have been developed to cover a broad range of compound classes, which are frequently characterized by the following workflow, as summarized in Figure 1: (i) material of choice, (ii) sample preparation and extraction, (iii) analytical methods, (iv) data processing and (v) data analysis and interpretation.

The sequences minimized possible analytical artifacts during further data processing.