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We recommend choosing a single topic so that students can later compare their recollections and interpretations.
In general, we recommend choosing the simplest model, with the least number of fitting parameters, when multiple models produce statistically inseparable results.
For comparing the two so obtained bounds, we recommend choosing the mean-variance bound if we can assume that the mean residual life is large with respect to the residual variance.
We recommend choosing a dataset of at least 10 controls for 2 3 test samples.
We recommend choosing an illness rather than a disease and measuring patient-oriented outcomes rather than disease-oriented outcomes.
We recommend choosing a tool that is customizable, as it gives the user more flexibility to adjust many of the gene-related characteristics such as minimum intron length, number of UTRs, etc., based on their specific needs.
Similar(51)
In general, from our experience working with various videos, we recommend choose a window size that is between 1/100 and 1/25 of the segmented vehicle size in the image.
We do recommend choosing an explicit definition and using it consistently throughout the analysis.
We highly recommend choosing appropriate mouse models for both IFN-negative and IFN-positive disease subtypes in future studies.
SNV calling precision after strand bias testing was relatively robust to choice of dispersion factor σ. Using a very low value of σ, however, compromised SNV recall, thus we would recommend choosing a value of σ closer to our upper estimate of 0.0111 when applying our test to real data.
Many bartenders and tequila experts recommend choosing a family-owned tequila over a large conglomerate.[2] (We're looking at you, Cuervo).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com