Fighting against uncertainty: an essential issue in bioinformatics
Fighting against uncertainty: an essential issue in bioinformatics
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DOI：
10.1093/bib/bbt038
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发表时间：
2014-09-01
影响因子：
9.5
通讯作者：
Hamada, Michiaki
中科院分区：
文献类型：
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作者：
Hamada, Michiaki
许多生物信息学问题，如序列比对、基因预测、系统发育树估计和RNA二级结构预测，往往受到解决方案的“不确定性”的影响，即解决方案的概率极小。这种情况出现在高维离散空间的估计问题中，其中可能的离散解的数量是巨大的。在分析生物数据或开发预测算法时，这种不确定性应谨慎而适当地处理。在这篇综述中，我将解释几种方法来对抗这种不确定性，并在生物信息学中提出一些例子。这些方法包括(i)避免点估计，（ii）最大期望精度（MEA）估计和（iii）设计涉及多种预测方法的管道的几种策略。我相信这篇综述中描述的基本概念和思想将对生物信息学各个领域的估计问题普遍有用。
Many bioinformatics problems, such as sequence alignment, gene prediction, phylogenetic tree estimation and RNA secondary structure prediction, are often affected by the 'uncertainty' of a solution, that is, the probability of the solution is extremely small. This situation arises for estimation problems on high-dimensional discrete spaces in which the number of possible discrete solutions is immense. In the analysis of biological data or the development of prediction algorithms, this uncertainty should be handled carefully and appropriately. In this review, I will explain several methods to combat this uncertainty, presenting a number of examples in bioinformatics. The methods include (i) avoiding point estimation, (ii) maximum expected accuracy (MEA) estimations and (iii) several strategies to design a pipeline involving several prediction methods. I believe that the basic concepts and ideas described in this review will be generally useful for estimation problems in various areas of bioinformatics.