Sentence examples for predictions in higher from inspiring English sources

It would be informative to conduct functional genomic analysis similar to that described in this paper on recently discovered coding fRNA predictions in higher eukaryotes to determine the role of fRNAs on coding sequence evolution.

From an acoustic viewpoint, the limited oceanographic measurements and today's ocean computational capabilities are not always able to provide oceanic-acoustic predictions in high-resolution and with enough accuracy.

Recently, network-based approaches have gained considerable popularity for expression quantitative trait loci (eQTL) studies and clinical outcome predictions in high-dimensional regression settings.

Given the doubts that currently exist about the rate of FP predictions in high-throughput data [ 35], the substantial contribution of Y2H studies to these public databases requires us to filter the data in generating a high-confidence PPI dataset, and thereafter to remain cautious in using such sets for inferring SCL.

In contrast, in eukaryotic genomes (especially higher eukaryotes such as humans and rice) the noncoding regions are much longer, which is believed to be one main reason as to why prediction in higher eukaryotes is more difficult.

While it is impossible to know whether new gene prediction evidence (transcript, peptide, homolog, genome conservation) affected the ability to predict the Type I New genes, the identification of Type II New genes in regions with slightly higher GC content than Previously Known genes suggested that the addition of new gene evidence had a greater impact on gene prediction in higher GC regions.

Heart rate variability (HRV) is a noninvasive method for cardiovascular risk prediction in high prevalent groups.

This paper presents a procedure for response prediction in high-rise buildings under wind loads.

This property has been used to enhance the confidence of prediction in high-throughput data [23, 28].

In this paper, a new criterion for in-phase multiaxial fatigue life prediction in high-cycle fatigue is proposed.

In this way, here we present a Bayesian-network-based model that allows error detection and prediction in high-precision foundries.