Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In population based human genetic studies, unrelated individuals are collected and SNPs are measured. There are several kinds of generative models proposed for modeling the data containing a large number of SNPs loci according to the characters of human genome. Hover, such models can only deal with ordered loci. ,  try to model the same data without using the order information. Firstly,  present a clustering model for SNPs by modifying the multi-block model used in GERBIL. It is a two-layer Bayesian network with multiple latent variables. It does not use the order information of the loci. Secondly,  solve the model by employing a structural EM algorithm combined with simulated annealing mechanism. A real data set was analyzed by the model. The results show that the SNPs can be clustered effectively. Such a model is potentially useful for clustering distantly correlated SNPs loci.
['Yulong Zhang', 'Liang Ji']
I am writing a research paper on a idea Clustering of SNPs by a Structural EM Algorithm
[{"from": "human", "value": "I am writing a research paper on a idea Clustering of SNPs by a Structural EM Algorithm"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In population based human genetic studies, unrelated individuals are collected and SNPs are measured. There are several kinds of generative models proposed for modeling the data containing a large number of SNPs loci according to the characters of human genome. Hover, such models can only deal with ordered loci. ,  try to model the same data without using the order information. Firstly,  present a clustering model for SNPs by modifying the multi-block model used in GERBIL. It is a two-layer Bayesian network with multiple latent variables. It does not use the order information of the loci. Secondly,  solve the model by employing a structural EM algorithm combined with simulated annealing mechanism. A real data set was analyzed by the model. The results show that the SNPs can be clustered effectively. Such a model is potentially useful for clustering distantly correlated SNPs loci."}]