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Computational Methods Of Hidden Markov Models With Respect To Cpg Island Prediction In Dna Sequences, Roberto Angel Ortega
Computational Methods Of Hidden Markov Models With Respect To Cpg Island Prediction In Dna Sequences, Roberto Angel Ortega
Open Access Theses & Dissertations
Hidden Markov models (HMM's) are a specific case of Markov models where, contrary to Markov chains, the observer is unaware of what state the model was in when the symbol is observed. Like Markov chains, HMM's assume that the future state of a sequence is dependent only on the current state of the sequence. The parameters associated with HMM's are transition and emission probabilities, where transition probabilities are associated with the probability of transitioning from one state to another, and emission probabilities are the probabilities associated with observing a symbol given it came from a specific state.
The structure of …