Intelligent Database Systems Lab
Presenter : YAN-SHOU SIE
Authors : Christos Ferles , Andreas Stafylopatis∗
2013. NN
Self-Organizing Hidden Markov Model Map (SOHMMM)
Intelligent Database Systems Lab
Outlines
MotivationObjectivesMethodologyExperimentsConclusionsComments
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.
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.
Intelligent Database Systems Lab
Methodology• Hidden Markov Model(HMM)
Intelligent Database Systems Lab
Methodology• Hidden Markov Model(HMM)–Hidden Markov model
Intelligent Database Systems Lab
Methodology• Hidden Markov Model(HMM)– Estimating model parameters
Intelligent Database Systems Lab
Methodology• SOHMMM– Generic framework
Intelligent Database Systems Lab
Methodology• SOHMMM– Analysis of the SOHMMM
Intelligent Database Systems Lab
Methodology• SOHMMM– Analysis of the SOHMMM
Intelligent Database Systems Lab
Methodology• SOHMMM– The SOHMMM learning algorithm
Forward-backward Algorithm
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Experiments• Artificial sequence data
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Experiments• Splice junction gene sequences
Intelligent Database Systems Lab
Experiments• Splice junction gene sequences
Intelligent Database Systems Lab
Experiments• Splice junction gene sequences
Intelligent Database Systems Lab
Experiments• Splice junction gene sequences
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.
Intelligent Database Systems Lab
Comments• Advantages– For the analysis of biological information is very
helpful.• Applications– bioinformaticsetwork forensics
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