Emission probabilities refer to the likelihood of observing a specific output (or symbol) from a hidden state in a Hidden Markov Model (HMM). This concept is crucial in understanding how biological sequences can be modeled, as these probabilities quantify the relationship between hidden states—such as underlying biological processes—and observable data, like DNA or protein sequences. Essentially, emission probabilities help connect the dots between unobserved biological phenomena and the measurable data we collect.
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