隐马尔可夫模型
计算生物学
计算机科学
推论
DNA结合位点
马尔可夫链
主题(音乐)
马尔可夫模型
贝叶斯概率
贝叶斯推理
模块化设计
人工智能
机器学习
生物
遗传学
基因
发起人
操作系统
物理
基因表达
声学
出处
期刊:Methods in molecular biology
日期:2009-12-15
卷期号:: 405-416
被引量:18
标识
DOI:10.1007/978-1-60761-580-4_13
摘要
Hidden Markov models have wide applications in pattern recognition. In genome sequence analysis, hidden Markov models (HMMs) have been applied to the identification of regions of the genome that contain regulatory information, i.e., binding sites. In higher eukaryotes, the regulatory information is organized into modular units called cis-regulatory modules. Each module contains multiple binding sites for a specific combination of several transcription factors. In this chapter, we gave a brief review of hidden Markov models, standard algorithms from HMM, and their applications to motif findings. We then introduce the application of HMM to a complex system in which an HMM is combined with Bayesian inference to identify transcription factor binding sites and cis-regulatory modules.
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