whatIsHMM_seanEddy_nbt04

# For most problems there are so many possible state

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Unformatted text preview: s the six highest-scoring paths (those 1316 with G at the 5′SS). The best one has a log probability of –41.22, which infers that the most likely 5′SS position is at the fifth G. For most problems, there are so many possible state sequences that we could not afford to enumerate them. The efficient Viterbi algorithm is guaranteed to find the most probable state path given a sequence and an HMM. The Viterbi algorithm is a dynamic programming algorithm quite similar to those used for standard sequence alignment. Beyond best scoring alignments Figure 1 shows that one alternative state path differs only slightly in score from putting the 5′SS at the fifth G (log probabilities of –41.71 versus –41.22). How confident are we that the fifth G is the right choice? This is an example of an advantage of probabilistic modeling: we can calculate our confidence directly. The probability that residue i was emitted by state k is the sum of the probabilities of all the state paths that use state k to generate residue i (that is,...
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