Sentence examples for data have driven from inspiring English sources

Relative to the traditional molecular biology methods that had been used to study the role of a single gene, single protein, or single small-molecule model, those "-omic" data have driven the rapid development of systems biology to study a multiple-factor model of disease and to address the network of interaction and regulatory events that contribute to a disease.

2) Realise that less is more If engagement data has driven marketers to cats, babies and competitions then the seeming pressure to post something every day has driven them to stock photography and possible insanity.

The recent need to extract real-time insights from data has driven the need for machine learning algorithms that can operate on data streams.

The growing use of Internet among public masses and the abundant availability of public and private digital data has driven industry professionals and researchers to pay a particular attention to data protection.

The combination of new security threats, regulatory compliance mandates, and the need to protect customer and organizational data has driven the demand for a more efficient use of network security technologies within architectures.

While scientists do not always agree on how to classify organisms, molecular phylogenetics, which uses DNA sequences as data, has driven many recent revisions along evolutionary lines and is likely to continue to do so.

The need to manage and share very large amounts of data has driven innovations on many fronts.

The generation of enormous amounts of data has driven the need for more advanced storage solutions and shared access through a range of public repositories.

In the past decade, the demand for DNA sequence data has driven the transformation of sequencing from a research activity into a manufacturing process.

However, the necessity for well-annotated tissues that can be re-annotated with experimental data has driven many of these multi-institutional collaborations to develop standards of sharing data with other groups.

These massive complex data sets have driven enthusiasm to study the molecular mechanism of cancers through computational approaches [ 1, 6- 8].