Sentence examples for multiple predictions is from inspiring English sources

A simple way to incorporate multiple predictions is to rank each NS according to the number of algorithms that predict it as deleterious.

That is, an allele with multiple predictions is considered correct if the true solution is included.

Yet multiple predictions are typically required regarding variables which are stochastically dependent, such as ozone measured in multiple stations or assessed according to by different indicators.

In this methodology, multiple predictions are made for each missing item, so that the uncertainty in these predictions is automatically accounted for in any analyses.

Multiple predictions were validated experimentally, including homologs of genes functioning in yeast cellular resistance to HMG-CoA reductase inhibition influence angiogenesis in Xenopus embryos [ 66].

The effects of multiple predictions are greater for genes relative to species for both systems, and influence precision and recall differentially for text2genome and GNAT.

When multiple predictions are present in a exonerate output, only the main prediction (defined as the highest scoring among those overlapping the original input 'superexon') is reported by selenoprofiles.

Neither variations in a patient's blood volume, the number of nurses making observations, nor large variations in the nurses' estimates alter the facts that multiple observations were obtained from some patients and multiple predictions were made by some nurses.

Empirical evidence for the proposed mechanism from both molecular evolution and evolution at the organismal level is discussed, and multiple predictions are offered by which it may be tested.

The resulting dataset still contains a significant intrinsic redundancy, due to the fact that multiple predictions are produced in overlapping regions when more than one hairpin structure can be predicted, or when miRNA-like structures are detected on both genomic strands.

It is recognized that multiple prediction is the most general approach to the study of the automaton and its environment in the sense that it is a formulation of prediction free of the linearity restriction earlier mentioned with reference to single series (see 3).