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基因组学中的归一化最大似然模型

Normalized maximum likelihood models in genomics
课程网址: http://videolectures.net/icml08_tabus_nml/  
主讲教师: Ioan Tabus
开课单位: 坦佩雷理工大学
开课时间: 2008-08-13
课程语种: 英语
中文简介:
标准化最大似然(NML)模型(Rissanen,1996; Rissanen,2001,Shtarkov,1987)对于一类马尔可夫源(Tabus和Korodi,2008)最近用于压缩全基因组,获得人类基因组最佳现有压缩结果(Korodi和Tabus,2007)。我们证明压缩算法隐含揭示的潜在生物学特征之一是近似基因重复的存在。我们提出了一种基于相同NML模型的精细方法,用于分析DNA序列以揭示基因重复(Tabus,Yang和Astola,2008)。基因组序列中的若干分析任务涉及数据的初步分割或聚类,其可基于各种相似性度量通过多种技术来执行。在这里,我们回顾并进一步探索MDL技术在基因组序列分析中的应用。序列匹配的过程将用于通过复杂DNA基因座的初步分割来解决发现基因重复的问题,已知通过一系列重复进化。
课程简介: The normalized maximum likelihood (NML) model (Rissanen, 1996; Rissanen, 2001, Shtarkov, 1987) for a class of Markov sources (Tabus and Korodi, 2008) was recently used for the compression of full genomes, obtaining for the human genome the best existing compression results (Korodi and Tabus, 2007). We show that one of the underlying biological features that the compression algorithm implicitly uncovers is the existence of approximate gene duplication. We proposed a refined method based on the same NML models for the segmentation of DNA sequences for uncovering gene duplications (Tabus, Yang, and Astola, 2008). Several analysis tasks in genomic sequences involve preliminary segmentation or clustering of the data, which can be performed by a number of techniques, based on various similarity measures. Here we review and further pursue the application of MDL techniques for genomic sequence analysis. The process of sequence matching will be used for solving the problem of uncovering gene duplications with the help of a preliminary segmentation of a complex DNA locus, known to have evolved through a series of duplications.
关 键 词: 标准化最大似然模型; 全基因组; 近似基因重复
课程来源: 视频讲座网
最后编审: 2019-04-21:lxf
阅读次数: 97