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    Hidden Markov Model

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    CpG islands are stretches of CG-rich sequences in the genome. They are often of functional important, as 50% of the human genes have a CpG island around 500bp upstream of the transcription site. Of course, CpG sequence is not only CG, and non-CpG island sequences could still contain some CG. Therefore, we could use HMM to predict CpG islands by looking at a long stretch of DNA. Now as a HMM practise, we just have a short-sequence AGGCGT, can you use HMM to predict the possibility of each base is part of a CpG island sequence? The parameters of the HMM Model are seen in the attachment as well as the probabilities.

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    Solution Summary

    This solution looks at the transition and base probabilities and finds the mathematical relationship between them. It calculates the probabilities in the forward algorithm, backward algorithm and forward-backward algorithm. All steps are shown and references are included.