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The probability of CNA events are determined by a neural network. g([c^1, c^2]) is the copy number profile generated by applying the two CNA tuples c^1 and c^2 to the normal cell. Then, the probability of the components of CNA tuple c^3 is generated. Ultimately, Pr (c^3 | g([c^1, c^2]), theta ) is the probability of the next CNA c^3 given that CNAs c^1 and c^2 have already been applied

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