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Candidate gene studies have long been used to detect variants in individual genes; such studies are easy to perform but require selection of genes with a proposed role in the disease process of interest.
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The Least Absolute Shrinkage and Selection Operator (lasso), which minimizes the residual sum of squares plus an absolute value penalty, provides a suitable method, but requires selection of a smoothing parameter.
All these techniques require selection of the appropriate target genes (Hjelmevoll et al. 2006).
Application and research of such cell-hydrogel systems require selection of adequate cryopreservation protocols.
Agreement between measured and predicted specific extinction coefficient would require selection of a refractive index outside the range of values widely used by the combustion community.
It is important to remember, therefore, that current methods require selection of motifs.
All penalized regression methods require selection of the regularization parameter (hereafter, λ), which determines the strength of the imposed penalty.
This may require selection of 'awkward' stimulus items, i.e. those that often occur in written or spoken language, but almost never in real life.
Methods based on hypergeometric distribution or equivalently, Fisher's exact test, use only rankings of weights and require selection of 'significant' entities prior to calculation of P-value.
A number of classification methods reported in the literature require selection of the relevant or informative predictor variables before modeling is actually performed.
Many existing enrichment methods require selections of (arbitrary number of) the most significant entities and/or do not account for weights of entities.
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