Adaptive Biological Networks
Adaptive Biological Networks
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DOI：
10.1007/978-3-642-01284-6_4
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发表时间：
2009-01-01
期刊：
影响因子：
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通讯作者：
Bebber, Daniel P.
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文献类型：
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作者：
Fricker, Mark D.;Boddy, Lynne;Bebber, Daniel P.
菌丝真菌和非细胞黏菌作为自组织网络生长，探索新的领域以寻找资源，同时在面临持续攻击或随机破坏时保持有效的内部运输系统。这些网络在发展期间作出调整，有选择地加强主要运输路线，并回收中间的多余材料，以支持进一步扩展。在真菌情况下，加权网络的预测传输效率优于相同拓扑的均匀加权网络或标准参考网络。在实验上，可以使用放射性示踪剂和闪烁成像绘制营养物质移动的地图，并显示更复杂的运输动力学，具有同步振荡和在不同的预先存在的路线之间切换。这种动力学对运输控制和拓扑学之间相互作用的意义尚不清楚。以类似的方式，可以在电子计算机上测试该网络的弹性，并使用放牧无脊椎动物进行实验。这两种方法都表明，提供良好传输效率的相同结构也显示出良好的弹性，具有中央连接的核心的持久性。无细胞粘菌多头绒泡菌还在食物来源之间形成了有效的网络，在总成本、转运距离和容错性之间取得了良好的平衡。在这种情况下，网络的形成可以通过一个数学模型来描述，该模型由高通量管子的非线性正强化和低通量管子的衰变驱动。我们认为，这些简单的平面网络的组织已经通过进化得到了磨练，它们可能是现实世界中搜索策略、传输效率、弹性和其他领域成本之间妥协的潜在解决方案。
Mycelial fungi and acellular slime molds grow as self-organized networks that explore new territory to search for resources, whilst maintaining an effective internal transport system in the face of continuous attack or random damage. These networks adapt during development by selective reinforcement of major transport routes and recycling of the intervening redundant material to support further extension. In the case of fungi, the predicted transport efficiency of the weighted network is better than evenly weighted networks with the same topology, or standard reference networks. Experimentally, nutrient movement can be mapped using radio-tracers and scintillation imaging, and shows more complex transport dynamics, with synchronized oscillations and switching between different pre-existing routes. The significance of such dynamics to the interplay between transport control and topology is not yet known. In a similar manner, the resilience of the network can be tested in silico and experimentally using grazing invertebrates. Both approaches suggest that the same structures that confer good transport efficiency also show good resilience, with the persistence of a centrally connected core. The acellular slime mold, Physarum polycephalum also forms efficient networks between food sources, with a good balance between total cost, transit distance and fault tolerance. In this case, network formation can be captured by a mathematical model driven by non-linear positive reinforcement of tubes with high flux, and decay of tubes with low flux. We argue that organization of these simple planar networks has been honed by evolution, and they may exemplify potential solutions to real-world compromises between search strategy, transport efficiency, resilience and cost in other domains.