Sentence examples for data-driven engineering from inspiring English sources

I must admit, this sunshine-and-serendipity advice sounds more fitting from my friend who is an aspiring astrologist, than from a presumably cold-hearted data-driven engineering professor at one of the U.S.'s most prestigious educational institutions.

Its low computational demand makes it especially valuable for the analysis of large data sets, e.g., for data-driven protein engineering.

Overall, these findings suggest that CNA can be applied as a pre-filter in data-driven protein engineering to focus on residues that are highly likely to improve thermostability upon mutation.

Another main area of development is the integration of data-driven reverse engineering tools to find links missing in the starting network [ 15].

Although a number of data-driven reverse engineering techniques were previously proposed to identify regulatory relationships between regulators and their targets [e.g. TFs and downstream genes (5)], the low accuracy of these existing methods due to the curse of dimensionality significantly limits their applications in practice (6).

First of all, the measurement model of established big data-driven biological embedded engineering was proposed based on the research of biological engineering with non-linear and unpredictability.

"Section 2" describes the big data-driven biological embedded engineering measurement model.

With various analytical and computing technologies, software analytics is to obtain insightful and actionable information for data-driven tasks in engineering software and services.

"There are a lot of public policy programs, but our strength is taking an engineering, data-driven approach to a range of issues that are global in nature.

The work is a step forward towards the introduction of data-driven approaches in the engineering practices of water control.

The engineering-dominated, data-driven culture of the search engine is light-years away from the convoluted "political" approach of legacy media that don't understand or look down on the peculiar culture of tech companies.