Hidden Markov Models

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Hidden Markov Models
Hidden Markov Models is one of the popular machines learning approach that can be used to decipher highly complex biological data.
One example would be CG-Island.

CG is the least frequent nucleotide in many genomes


Reason:
C within CG is easily methylated
Resulting methylation has tendency to mutate into T
However methylation is suppressed around genes in areas called CG-Island. Here CG appears relatively frequently.

Fair Bet Casino:
Through it CG-Islands can be modeled.
Dealer flips coin and player bets on outcome: heads or tails
Dealer uses either a biased coin (head with probability ¾) or fair coin head or tail equally likely
Given a sequence of coin tosses, problem to find out when dealer used a biased coin or a fair coin
Obviously, if you observe long line of heads it’s likely that dealer used biased coin and if you observe even distribution of heads and tails he likely used fair one.

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