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PerSubs:一种基于图的算法,用于识别复杂疾病引起的扰动子路径。

PerSubs: A Graph-Based Algorithm for the Identification of Perturbed Subpathways Caused by Complex Diseases.

机构信息

Department of Computer Engineering and Informatics, University of Patras, Patras, Greece.

Department of Informatics, Ionian University Corfu, Corfu, Greece.

出版信息

Adv Exp Med Biol. 2017;988:215-224. doi: 10.1007/978-3-319-56246-9_17.

Abstract

In the era of Systems Biology and growing flow of omics experimental data from high throughput techniques, experimentalists are in need of more precise pathway-based tools to unravel the inherent complexity of diseases and biological processes. Subpathway-based approaches are the emerging generation of pathway-based analysis elucidating the biological mechanisms under the perspective of local topologies onto a complex pathway network. Towards this orientation, we developed PerSub, a graph-based algorithm which detects subpathways perturbed by a complex disease. The perturbations are imprinted through differentially expressed and co-expressed subpathways as recorded by RNA-seq experiments. Our novel algorithm is applied on data obtained from a real experimental study and the identified subpathways provide biological evidence for the brain aging.

摘要

在系统生物学时代和高通量技术产生的大量组学实验数据的推动下,实验人员需要更精确的基于通路的工具来揭示疾病和生物过程的固有复杂性。基于子通路的方法是基于通路分析的新一代方法,从局部拓扑的角度阐明复杂通路网络中的生物学机制。为此,我们开发了 PerSub,这是一种基于图的算法,用于检测受复杂疾病影响的子通路。这些扰动通过 RNA-seq 实验记录的差异表达和共表达子通路来标记。我们的新算法应用于从真实实验研究中获得的数据,鉴定出的子通路为大脑衰老提供了生物学证据。

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