A clustering method of chromosome fluorescence profiles using modified self organizing map controlled by simulated annealing
説明
The clustering method by the self organizing map algorithm of chromosome profiles measured by a slit-scan flow-cytometer is proposed. Moreover, the physical models of chromosomes have been introduced in order to take into account the rotation of chromosomes in the flow-cytometer. By this modification, the lengths of chromosomes and the intensity distribution of chromosome fluorescence can be estimated from chromosome profile data measured by the flow-cytometer. But the clustering results did not converge identically in some experiments and the distribution of the rotation angles was unnatural. So, we introduced simulated annealing to improve the convergence of our SOM algorithm. We compared the clustering results of this method with those of the K-means method and the SOM method.
収録刊行物
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- Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium
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Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium 103-106 vol.4, 2000-01-01
IEEE