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| 題 名 | A Recognition Machine for CpG-islands Based on Boltzmann Model |
|---|---|
| 作 者 | Lai, Ho-ming; Chiang, Yung-yen; Hsu, Ching-chi; Wu, Fan; | 書刊名 | Journal of Medical and Biological Engineering |
| 卷 期 | 28:1 2008.03[民97.03] |
| 頁 次 | 頁23-30 |
| 分類號 | 410.1644 |
| 關鍵詞 | CpG-island; Hidden Markov chain; Boltzmann model; Gene recognition; |
| 語 文 | 英文(English) |
| 英文摘要 | The cytosines in the CpG dinucleotides in mammalian DNA are very likely methylated. Through deamination, the C will be converted into T. But methylation is suppressed around genes in the areas, called CpG-islands, where CpG appears relatively frequently. These CpG-islands are known to appear in the significant ports of the genome. The ability to identify CpG-islands mill therefore help us spot the significant regions of interest along the genome. To locate the CpG-islands is very costly using deterministic algorithms. We propose a stochastic algorithm to recognize and locate the CpG-islands in the gene sequence. We first use hidden Markov model (HMM) as a graph model to represent the problem of the CpG-island. Based on the HMM, we construct the corresponding CpG-Boltzmann model to recognize the CpG-island. Since the Boltzmann model has the property that its learning algorithm guarantees getting the global minimum, the proposed model has the recognition ability for the CpG-island with the least biased value. Finally, we have performed experiments to show the proposed model has better false positive rate compared with deterministic algorithms. |
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