Sentence examples for as datasets from inspiring English sources

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Similarly, the overall HLA-B27 prevalence of 93.2% in our predominately Caucasian AS patient dataset was consistent with the prevalence previously reported in overseas Caucasian AS datasets [ 6].

While readily available and easy to apply to AS datasets, standard clustering methods such as hierarchical agglomerative clustering and K-means clustering, suffer from several drawbacks.

Since this was an analysis of a single AS trial of just 6 weeks' duration, and with smaller patient numbers compared with responder analyses meta-analyses [ 5, 6] even though there were comparable to numbers studies in CLBP [ 4], these results should be replicated in other AS datasets.

Moreover, the FII may also be indicative of the quality of further downstream analysis of high-throughput AS datasets, as many of the works producing these datasets subsequently try to identify the regulatory elements and underlying mechanisms that govern condition-specific AS.

During a conversation with Dr. Trenberth, he told me: Progress is being made on understanding the energy flows through the climate system as datasets are improved and methods of analyzing the data are being revised and rigorously tested.

"We're seeing situations where companies are being bought primarily for this data, and when it is combined with information the purchasing company already holds, there's a danger that consumers will have little control as datasets are matched and intrusive details revealed," she added.

The linked open data cloud is constantly evolving as datasets get continuously updated with newer versions.

Search results (by identifiers, similarity, or substructure), are available as datasets as well.

Most of the online studies on opinion extraction use blogs as datasets (Qiang and Rob 2009) to perform detailed analysis.

Students can inspect these tracks that are displayed as datasets (showing the total momentum, the angles of the particles, etc).

That's thanks to Crate's "self-configuration and self-healing capabilities", which doesn't sacrifice the ability to scale as datasets grow ever larger and is still easy to develop on top of using SQL.

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