Complexity reduction in context-dependent DNA substitution models.
Complexity reduction in context-dependent DNA substitution models.
复制标题
降低上下文相关 DNA 替换模型的复杂性。
DOI：
10.1093/bioinformatics/btn598
复制
发表时间：
2009
期刊：
影响因子：
--
通讯作者：
Ohler,Uwe
中科院分区：
文献类型：
--
作者：
Majoros,WilliamH;Ohler,Uwe
动机：基因组DNA中的保守模式的建模在许多生物信息学应用中变得越来越流行。虽然到目前为止已开发的几个系统在它们的替换模型中引入了上下文依赖，但所产生的高阶模型对计算复杂性和泛化能力的影响引发了这样一个问题：在不牺牲预测精度的情况下，更简单的上下文建模方法是否可以显著降低模型复杂性和计算成本。结果：我们提出了几种基于加窗贝叶斯网络的上下文建模方法，并比较了它们在区分脊椎动物DNA中不同功能片段的任务中对精度和计算复杂性的影响。我们的结果表明，在不减少预测性accuracy.Contact:bmajoros@duke.eduSupplementary信息的情况下，可以大幅降低模型和相关推理算法的复杂性：补充数据可以在生物信息学在线上获得。
Motivation:The modeling of conservation patterns in genomic DNA has become increasingly popular for a number of bioinformatic applications. While several systems developed to date incorporate context-dependence in their substitution models, the impact on computational complexity and generalization ability of the resulting higher order models invites the question of whether simpler approaches to context modeling might permit appreciable reductions in model complexity and computational cost, without sacrificing prediction accuracy.Results:We formulate several alternative methods for context modeling based on windowed Bayesian networks, and compare their effects on both accuracy and computational complexity for the task of discriminating functionally distinct segments in vertebrate DNA. Our results show that substantial reductions in the complexity of both the model and the associated inference algorithm can be achieved without reducing predictive accuracy.Contact:bmajoros@duke.eduSupplementary information:Supplementary data are available atBioinformaticsonline.