Machine learning applications in genetics and genomics
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machine
learning methods can be used to ‘learn’ how to recognize the locations of transcription start sites (TSSs)
in a genome sequence2
. Algorithms can similarly be
trained to identify splice sites3
, promoters4
, enhancers5
or positioned nucleosomes6
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Gene expression data can
be used to learn to distinguish between different disease phenotypes and, in the process, to identify potentially valuable disease biomarkers.