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Methods used for case classification have been described (10, 11 ).
The methods for MC1R genotyping and classification have been described in detail elsewhere [ 15].
To date a large number of different algorithms for disease classification have been described.
Details about embryo classification have been described previously (Capalbo et al., 2014a).
More examples of voice classification have been described in our previous work [ 1] which attempted to classify voice data by using hierarchical time-series clustering methods.
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Blood tests were determined in all studies; we only evaluated here those for which a detailed fibrosis class classification has been described, i.e., FibroMeter [ 14] (Biolivescale, Angers, France) and Fibrotest [ 5] (Biopredictive, Paris, France).
Consequently, several molecular classifications have been described using different approaches and important progress has been made particularly with the transcriptomic, genetic, chromosomal, miRNA and methylation profiling.
Their bizarre forms defy classification; some have been described alternately as jellyfish or worms, algae or fungi.
The UFO web server has been built around an efficient implementation of machine learning techniques for protein sequence classification which have been described in [ 10- 12].
Although many different classification manners have been described, two major subsets of DCs are recognized: myeloid DCs (mDCs) and plasmacytic DCs (pDCs) [ 18, 19].
Several β-lactamase classification schemes have been described, but the most commonly used are the Ambler molecular scheme, based on the amino acid and subsequent structural similarity between enzymes and the Bush Jacoby Medeiros classification, based on the functionality or activity of the enzymes on different β-lactam antimicrobial agents.
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