Sentence examples for intensive data analysis from inspiring English sources

A P2P bio-inspired algorithm for distributed spatial clustering as an example of distributed knowledge discovery service for intensive data analysis is presented.

Clinical application of DTI is challenging due to long acquisition times, high field strengths, and intensive data analysis.

In qualitative research and studies with focus group methodology, sample sizes typically remain small because intensive data analysis is required [ 30, 32].

Given the intensive data analysis required per patient dataset in this study, 30 datasets represents an upper-limit in terms of manageability.

As BDS is intended to solve or simplify the main challenges in implementing, testing and programming data processing pipelines without introducing a steep learning curve, our main design goals are (i) simple programming language; (ii) abstraction from system's architecture; and (iii) robustness to hardware and software failure during computationally intensive data analysis tasks.

These tools and solutions are promising but still too rudimentary to be routinely used in an intensive NGS data analysis workflow.

After a year of intensive data gathering and analysis, he believes he has for the first time begun to quantify the damage done to the scientific enterprise by contaminated cell lines.

Enterprises need two distinct types of self-service data environments based on different business analytical requirements: analytical sandboxes, to enable business users to be able to add data and derive metrics, and analytical hubs, which accommodate more extensive and intensive data gathering and analysis.

These assays offer an easier workflow for larger sample numbers compared to alternative methods such as quantitative polymerase chain reaction (qPCR), microarray, and sequencing, which can be resource intensive or require challenging data analysis.

A sample size of 20 women was chosen, being small enough to manage the intensive process of qualitative data analysis and large enough that some variation might be captured.

This signifies that job processing is read intensive (xR) at the beginning of microarray data analysis and then compute intensive (xP) afterwards.