1. Intelligent Database Systems Lab Presenter : YAN-SHOU SIE Authors : Christos Ferles ∗, Andreas Stafylopatis 2013. NN Self-Organizing Hidden Markov Model Map (SOHMMM)

2. Intelligent Database Systems Lab Outlines Motivation Objectives Methodology Experiments Conclusions Comments

3. Intelligent Database Systems Lab Motivation The advent of efficient experimental technologies has led to an exponential growth of linear descriptions of protein, DNA and RNA chain molecules requiring automated analysis. Therefore, the need for computational /statistical / machine learning algorithms and techniques, for the qualitative and quantitative description of biological molecules, is today stronger than ever.

4. Intelligent Database Systems Lab Objectives Here proposed a SOHMMM model to help analyze the DNA/protein sequences. SOHMMM is an integration of the SOM and the HMM principles.

5. Intelligent Database Systems Lab Methodology Hidden Markov Model(HMM)

6. Intelligent Database Systems Lab Methodology Hidden Markov Model(HMM) – Hidden Markov model

7. Intelligent Database Systems Lab Methodology Hidden Markov Model(HMM) – Estimating model parameters

8. Intelligent Database Systems Lab Methodology SOHMMM – Generic framework

9. Intelligent Database Systems Lab Methodology SOHMMM – Analysis of the SOHMMM

10. Intelligent Database Systems Lab Methodology SOHMMM – Analysis of the SOHMMM

11. Intelligent Database Systems Lab Methodology SOHMMM – The SOHMMM learning algorithm Forward-backward Algorithm

12. Intelligent Database Systems Lab Experiments Artificial sequence data

13. Intelligent Database Systems Lab Experiments Splice junction gene sequences

14. Intelligent Database Systems Lab Experiments Splice junction gene sequences

15. Intelligent Database Systems Lab Experiments Splice junction gene sequences

16. Intelligent Database Systems Lab Experiments Splice junction gene sequences

17. Intelligent Database Systems Lab Conclusions SOHMMM can provide useful automated analysis and visualization capabilities help analyze DNA Chain. Compare other method have a lower error rate and better analyze result.

18. Intelligent Database Systems Lab Comments Advantages – For the analysis of biological information is very helpful. Applications – bioinformaticsetwork forensics