Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A new method for building a gene tree from Single Nucleotide Polymor- phism (SNP) data was developed by Chen and Lindsay (Biometrika 93(4):843-860, 2006). Called the mixture tree, it was based on an ancestral mixture model. The sieve parameter in the model plays the role of time in the evolutionary tree of the sequences. By varying the sieve parameter, one can create a hierarchical tree that estimates the population structure at each fixed backward point in time. In this chap- ter,  will review the model and then present an application to the clustering of the mitochondrial sequences to show that the approach performs ll. A simulator that simulates real SNPs sequences with unknown ancestral history will be introduced. Using the simulator  will compare the mixture trees with true trees to evaluate how ll the mixture tree method performs. Comparison with some existing meth- ods including neighbor-joining method and maximum parsimony method will also be presented in this chapter.
['Grace Shu-Chuan Chen', 'Mingze Li', 'Michael S. Rosenberg', 'Bruce G. Lindsay']
I am writing a research paper on a idea Mixture Tree Construction and Its Applications
[{"from": "human", "value": "I am writing a research paper on a idea Mixture Tree Construction and Its Applications"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A new method for building a gene tree from Single Nucleotide Polymor- phism (SNP) data was developed by Chen and Lindsay (Biometrika 93(4):843-860, 2006). Called the mixture tree, it was based on an ancestral mixture model. The sieve parameter in the model plays the role of time in the evolutionary tree of the sequences. By varying the sieve parameter, one can create a hierarchical tree that estimates the population structure at each fixed backward point in time. In this chap- ter,  will review the model and then present an application to the clustering of the mitochondrial sequences to show that the approach performs ll. A simulator that simulates real SNPs sequences with unknown ancestral history will be introduced. Using the simulator  will compare the mixture trees with true trees to evaluate how ll the mixture tree method performs. Comparison with some existing meth- ods including neighbor-joining method and maximum parsimony method will also be presented in this chapter."}]