Hidden Markov Models for Bioinformatics

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