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However, the number of samples and cost are the main obstacles to the application of microarray.
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Thus, a trade off is needed between costs for obtaining large enough number of samples and costs for detailed analyses of each sample, in order to obtain the most efficient study design.
Four physical and four biological soil indicators were selected based on sensitivity to management, relevance to functional soil processes, ease and cost of sampling, and cost of analysis.
This suggests that sampling for genotyping/sequencing projects can be improved (in terms of diversity of sampling and cost) by taking into account independent knowledge of the demographic history of the populations being sampled.
The following criteria were integrated into the MCDA model covering all dredged material management stages: Transport cost Treatment cost Building and maintenance cost including supply, raw material and energy costs Disposal cost Sampling and analysis costs Aftercare and monitoring cost Subsidies and tax abatements.
Although sample pooling was undertaken for reasons of quantity of sample required and cost, it is not ideal as outlier samples could mask other samples.
We used sampling and cost-sensitive methods on two very different data sets and with four different machine-learning algorithms.
We used sampling and cost-sensitive learning approaches to improve the sensitivity of our classifiers by dealing with this imbalance.
For our sampling and cost-sensitive experiments, we therefore focused on changing the imbalance ratio in the data with set expansion.
We were able to achieve high sensitivity (on a par with the manual annotator) on both data sets using our proposed sampling and cost-sensitive methods.
Laboratory diagnosis is hampered by single samples and high cost and low reliability of diagnostic tests currently available.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com