A survey of some tensor analysis techniques for biological systems

A survey of some tensor analysis techniques for biological systems
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生物系统一些张量分析技术综述

DOI:
10.1007/s40484-019-0186-5
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发表时间:
2019
影响因子:
3.1
通讯作者:
DasGupta, Bhaskar
DasGupta, Bhaskar
中科院分区:
生物学4区
文献类型:
--
作者:
Yahyanejad, Farzane;Albert, Réka;DasGupta, Bhaskar

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由于生物系统是复杂的,往往涉及多种类型的基因组关系,张量分析方法可以用来阐明这些隐藏的复杂关系。有一个迫切的需要,因为高通量实验的结果的解释已经在一个慢得多的速度比积累的data.ResultsIn这篇评论中,我们提供了一个概述的一些张量分析方法为biologicalsystem.ConclusionsTensors是自然和强大的概括向量和矩阵更高的维度,并发挥了重要作用,在物理,数学和许多其他领域。张量分析方法可用于提供系统方法的基础,通过寻找少量简化系统的集合来区分复杂系统元素之间显着的高阶相关性,这些系统提供了这些相关性的简洁且有代表性的总结。
BackgroundSince biological systems are complex and often involve multiple types of genomic relationships, tensor analysis methods can be utilized to elucidate these hidden complex relationships. There is a pressing need for this, as the interpretation of the results of high-throughput experiments has advanced at a much slower pace than the accumulation of data.ResultsIn this review we provide an overview of some tensor analysis methods for biological systems.ConclusionsTensors are natural and powerful generalizations of vectors and matrices to higher dimensions and play a fundamental role in physics, mathematics and many other areas. Tensor analysis methods can be used to provide the foundations of systematic approaches to distinguish significant higher order correlations among the elements of a complex systems via finding ensembles of a small number of reduced systems that provide a concise and representative summary of these correlations.
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发表时间: 2015
期刊: ArXiv
影响因子: --
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