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Higher-order molecular organization as a source of biological function

机译:高阶分子组织作为生物学功能的来源

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Motivation: Molecular interactions have widely been modelled as networks. The local wiring patterns around molecules in molecular networks are linked with their biological functions. However, networks model only pairwise interactions between molecules and cannot explicitly and directly capture the higher-order molecular organization, such as protein complexes and pathways. Hence, we ask if hypergraphs (hypernetworks), that directly capture entire complexes and pathways along with protein-protein interactions (PPIs), carry additional functional information beyond what can be uncovered from networks of pairwise molecular interactions. The mathematical formalism of a hypergraph has long been known, but not often used in studying molecular networks due to the lack of sophisticated algorithms for mining the underlying biological information hidden in the wiring patterns of molecular systems modelled as hypernetworks.
机译:动机:分子相互作用已被广泛建模为网络。 分子网络中分子周围的局部布线图案与其生物功能相关联。 然而,网络模型仅成对分子之间的相互作用,不能明确地直接捕获高阶分子组织,例如蛋白质复合物和途径。 因此,我们询问直接捕获整个复合物和途径以及蛋白质 - 蛋白质相互作用(PPI)的超图(HypernetWorks),携带超出可以从成对分子相互作用网络揭示的额外功能信息。 长图的数学形式主义长期以来,但由于缺乏特勤算法,而不是用于研究隐藏在被模拟的分子系统的布线模式中的底层生物学信息的复杂算法,通常用于研究分子网络。

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