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信号超图的通路分析。

Pathway Analysis with Signaling Hypergraphs.

出版信息

IEEE/ACM Trans Comput Biol Bioinform. 2017 Sep-Oct;14(5):1042-1055. doi: 10.1109/TCBB.2015.2459681.

Abstract

Signaling pathways play an important role in the cell's response to its environment. Signaling pathways are often represented as directed graphs, which are not adequate for modeling reactions such as complex assembly and dissociation, combinatorial regulation, and protein activation/inactivation. More accurate representations such as directed hypergraphs remain underutilized. In this paper, we present an extension of a directed hypergraph that we call a signaling hypergraph. We formulate a problem that asks what proteins and interactions must be involved in order to stimulate a specific response downstream of a signaling pathway. We relate this problem to computing the shortest acyclic B-hyperpath in a signaling hypergraph-an NP-hard problem-and present a mixed integer linear program to solve it. We demonstrate that the shortest hyperpaths computed in signaling hypergraphs are far more informative than shortest paths, Steiner trees, and subnetworks containing many short paths found in corresponding graph representations. Our results illustrate the potential of signaling hypergraphs as an improved representation of signaling pathways and motivate the development of novel hypergraph algorithms.

摘要

信号通路在细胞对其环境的反应中起着重要作用。信号通路通常表示为有向图,但对于建模复杂组装和解离、组合调控以及蛋白质激活/失活等反应来说并不足够。更准确的表示形式,如有向超图,仍然未得到充分利用。在本文中,我们提出了一种有向超图的扩展,我们称之为信号超图。我们提出了一个问题,即要刺激信号通路下游的特定反应,必须涉及哪些蛋白质和相互作用。我们将这个问题与计算信号超图中的最短非循环 B-超路径相关联——这是一个 NP 难问题——并提出了一个混合整数线性规划来解决它。我们证明,在信号超图中计算出的最短超路径比最短路径、Steiner 树和包含许多短路径的子网更具信息量,这些短路径存在于相应的图表示中。我们的结果说明了信号超图作为信号通路的改进表示形式的潜力,并激发了新的超图算法的发展。

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本文引用的文献

1
Signaling hypergraphs.
Trends Biotechnol. 2014 Jul;32(7):356-62. doi: 10.1016/j.tibtech.2014.04.007. Epub 2014 May 22.
2
Using biological pathway data with paxtools.
PLoS Comput Biol. 2013;9(9):e1003194. doi: 10.1371/journal.pcbi.1003194. Epub 2013 Sep 19.
3
Modeling approaches for qualitative and semi-quantitative analysis of cellular signaling networks.
Cell Commun Signal. 2013 Jun 26;11(1):43. doi: 10.1186/1478-811X-11-43.
4
Modeling formalisms in Systems Biology.
AMB Express. 2011 Dec 5;1:45. doi: 10.1186/2191-0855-1-45.
5
KEGG for integration and interpretation of large-scale molecular data sets.
Nucleic Acids Res. 2012 Jan;40(Database issue):D109-14. doi: 10.1093/nar/gkr988. Epub 2011 Nov 10.
6
Finding undetected protein associations in cell signaling by belief propagation.
Proc Natl Acad Sci U S A. 2011 Jan 11;108(2):882-7. doi: 10.1073/pnas.1004751108. Epub 2010 Dec 27.
7
Reactome: a database of reactions, pathways and biological processes.
Nucleic Acids Res. 2011 Jan;39(Database issue):D691-7. doi: 10.1093/nar/gkq1018. Epub 2010 Nov 9.
8
The BioPAX community standard for pathway data sharing.
Nat Biotechnol. 2010 Sep;28(9):935-42. doi: 10.1038/nbt.1666. Epub 2010 Sep 9.
9
Inference of patient-specific pathway activities from multi-dimensional cancer genomics data using PARADIGM.
Bioinformatics. 2010 Jun 15;26(12):i237-45. doi: 10.1093/bioinformatics/btq182.
10
Algorithms for effective querying of compound graph-based pathway databases.
BMC Bioinformatics. 2009 Nov 16;10:376. doi: 10.1186/1471-2105-10-376.

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