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Updated: Jun 28, 2025

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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使用有序的隐藏马尔科夫模型与排放密度 (oHMMed) 来推断基因组景观

Claus Vogl1,2, Mariia Karapetiants3, Burçin Yıldırım3,4,5

  • 1Department of Biomedical Sciences and Pathobiology, Vetmeduni Vienna, Veterinärplatz 1, Vienna, Austria. Claus.Vogl@vetmeduni.ac.at.

BMC bioinformatics
|April 16, 2024
PubMed
概括

我们开发了oHMMed,一种新的隐藏马尔科夫模型 (HMM) 方法,通过分析自身相关的序列模式来识别不同的基因组区域. 这种方法基于持续变化的基因组细分,有助于进化和生物医学研究.

关键词:
自动相关性 自动相关性构成性域理论的组成领域理论.基因密度 基因密度 基因密度基因组细分算法 基因组细分算法隐藏的马尔科夫模型隔离器是隔离器.马尔科夫链蒙特卡洛采样机顺序的隐藏状态 (凸起的排放密度)在R包中,R包是R包.在GC比例的变化.

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