隐马尔科夫过程在生物信息学中的应用.pdf

6 3 生命科学研究 Vol. 6 No. 3 2002 9 Life Science Research Sep. 2002 周海廷 ( , 621000) : 隐马尔科夫过程( hidden Marko model, 简称HMM) 是20 世纪70 年代提出来的一种统计方 , 以前主要 [ 1] [ 2] 用于语音识别 . 1989 年Churchill 将其引入计算生物学. 目前, HMM 是生物信息学中应用比较广泛的一种统 计方 [3~ 7] , 主要用于: 线性序列分析模型分析基因发现等方面. 对HMM 进行了简明扼要的描述, 并对其在 上述几 个方面的应用作 一概略介绍. : 隐马尔科夫过程; 序列有哪些信誉好的足球投注网站; 模型估计; 基因识别 : Q811. 4 : A : 1007-7847( 2002) 03-0204-07 An Introduction to the Hidden Markov Models for Bioinformatics ZHOU Ha-i ting ( Southwest University of Science Technology ,Miany ang 621000, Sichuan, China) Abstract:The Hidden Marko Model ( HMM) is a statistical model, which is ery well suited for many tasks in mo- lecular biology, although they ha e been mostly de eloped for speech recognition since the early 1970s. The most popular use of the HMM in molecular biology is as a probabilistic pro-file of a protein family, which is called a profile HMM. From a family of proteins ( or DNA) a profile HMM can be made for searching a database for other members of the family. The HMM can be applied to other types of problems. It is particularly well suited for prob- lems with a simple grammatical structure, such as gene finding. Key words: hidden Marko models; sequence search; model estimation;gene-finding ( Lfi e Science Research , 2002, 6( 3) : 204~ 210) ) . 1 ( , 1. 1 (Markov model) A C, G , Marko model( MM) , ) . ( 0 1 , ,