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Contrary to most former studies which focus on daily predictions, we compare these models in an intraday stock trading scenario using high-frequency data.
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To test these predictions, we compared plant species composition and richness in residential lawns in seven U.S. metropolitan regions.
To gain insight into the reliability of the SMART2 model predictions, we compared the modelled soil solution chemistry for forest with soil solution measurements in forest soils.
To test our predictions, we compared the thermal tolerances of leaf-cutter ants (Atta sexdens) from colonies inside and outside of São Paulo, Brazil (Fig. 1).
To test the gene models underlying our predictions we compared the DAlFEs to experimental CAGE evidence in K562 cells and found that 45% of our set corresponded to CAGE data at the same position, in proximity to TSSs of genes (see Methods).
To evaluate the accuracy of our predictions we compared our nucleosome calls to several other sources.
To test our main predictions we compared the mean number of defended prey eaten at asymptote across the different groups.
To further evaluate EuGene-P predictions, we compared our data with TSSs experimentally mapped in previous studies.
To estimate the number of false predictions we compared the candidate snoRNAs with common ncRNA databases, in particular Rfam[ 61] and NONCODE[ 62].
> -wrap-foot> testest our predictions, we compared transcriptional profiles of Lineage 1 and 2 strains by RNA sequencing (RNA-seq).
To test these predictions, we compared five mammalian cell lines, cryopreserved as either a pellet or a suspension, in each of the three cryopreservatives.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com