Sentence examples for many prediction studies from inspiring English sources

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Many prediction studies of T2D have been reported, yet the genetic contribution to their predictive accuracy has been disappointing: genes alone yield ~60% AUC, and adding genes to clinical risk factors yields incremental improvements of ~1-2% AUC [ 16, 17].

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Many genomic prediction studies showed that the prediction accuracy of the GBLUP model decreases as more individuals are added to the training population.

Further, many recent supervised drug target prediction studies seem to have ignored these lessons when introducing new and improved prediction models, although there are few exceptions [ 8, 41].

PSSMs have been successfully applied in the prediction studies of many aspects in structural bioinformatics and have been shown to be helpful for improving the prediction performance [72], [73], [74], [75], [76], [77].

Third, many prediction methods, including the two studies compared to here, consider only annotated proteins with at least one annotated interaction partner for their studies [ 16, 19, 26, 27, 62].

Reporting guidelines have been published for various research designs [ 15] and these contain many items that are also relevant to genetic risk prediction studies.

Reporting guidelines have been published for various research designs, and these contain many items that are also relevant to genetic risk prediction studies.

This result depicted the dynamic response of yeast when exposed to oxidative stress and many predictions are supported by previous studies.

The theory of natural selection has given rise to many predictions that have withstood tests both in field studies and in laboratory settings (Ruse 1977; 2000).

Since St. John's fiery prose, there have been many predictions of the end, including the modern cult studied by social psychologist Leon Festinger in When Prophecy Fails (1956).

Despite limited research on space time predictions, many studies have addressed management effects on soil hydraulic properties and processes relevant to improved understanding of the sources of variability and their interactions in space and time.

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