A novel gene identification algorithm with Bayesian classification
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- 作者：Mohammad Al Bataineha ; mohamadfa@yu.edu.jo" class="auth_mail" title="E-mail the corresponding author ; mffbataineh@yahoo.com" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Zouhair Al-qudahb ; qudahz@ahu.edu.jo" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae
- 关键词：Gene detection ; Correlation ; Maximal ratio combining ; Period-3 filter ; Bayesian classification
- 刊名：Biomedical Signal Processing and Control
- 出版年：2017
- 出版时间：January 2017
- 年：2017
- 卷：31
- 期：Complete
- 页码：6-15
- 全文大小：1850 K
文摘
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A novel gene detection algorithm for prokaryotes is proposed.
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The algorithm applies concepts and principles in communications theory and DSP to identify coding and noncoding regions.
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The proposed algorithm is applied to several prokaryotic genome sequences.
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Two Bayesian classifiers are designed to evaluate the performance of the proposed gene detection algorithm.
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The algorithm performance is comparable to well-known ab initio gene detection methods such as GLIMMER and GeneMark.