Hidden Markov Models for Bioinformatics [Paperback]

1 Prerequisites in probability calculus.- 2 Information and the Kullback Distance.- 3 Probabilistic Models and Learning.- 4 EM Algorithm.- 5 Alignment and Scoring.- 6 Mixture Models and Profiles.- 7 Markov Chains.- 8 Learning of Markov Chains.- 9 Markovian Models for DNA sequences.- 10 Hidden Markov Models an Overview.- 11 HMM for DNA Sequences.- 12 Left to Right HMM for Sequences.- 13 Derins Algorithm.- 14 ForwardBackward Algorithm.- 15 BaumWelch Learning Algorithm.- 16 Limit Points of Baum-Welch.- 17 Asymptotics of Learning.- 18 Full Probabilistic HMM.