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首页> 外文期刊>Journal of computational biology: A journal of computational molecular cell biology >Information Flow in Interaction Networks II: Channels, Path Lengths, and Potentials
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Information Flow in Interaction Networks II: Channels, Path Lengths, and Potentials

机译：交互网络中的信息流II：通道，路径长度和电位

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In our previous publication, a framework for information flow in interaction networks based on random walks with damping was formulated with two fundamental modes: emitting and absorbing. While many other network analysis methods based on random walks or equivalent notions have been developed before and after our earlier work, one can show that they can all be mapped to one of the two modes. In addition to these two fundamental modes, a major strength of our earlier formalism was its accommodation of context-specific directed information flow that yielded plausible and meaningful biological interpretation of protein functions and pathways. However, the directed flow from origins to destinations was induced via a potential function that was heuristic. Here, with a theoretically sound approach called the channel mode, we extend our earlier work for directed information flow. This is achieved by constructing a potential function facilitating a purely probabilistic interpretation of the channel mode. For each network node, the channel mode combines the solutions of emitting and absorbing modes in the same context, producing what we call a channel tensor. The entries of the channel tensor at each node can be interpreted as the amount of flow passing through that node from an origin to a destination. Similarly to our earlier model, the channel mode encompasses damping as a free parameter that controls the locality of information flow. Through examples involving the yeast pheromone response pathway,we illustrate the versatility and stability of our new framework.
机译：在我们以前的出版物中，基于带有阻尼的随机游动的交互网络中的信息流框架是用两种基本模式制定的：发射和吸收。尽管在我们较早的工作之前和之后已经开发了许多其他基于随机游走或等效概念的网络分析方法，但可以证明它们都可以映射到两种模式之一。除了这两种基本模式之外，我们早期形式主义的主要优势在于其适应特定于上下文的定向信息流，从而产生了对蛋白质功能和途径的合理且有意义的生物学解释。但是，从起点到目的地的定向流是通过启发式的潜在函数引起的。在这里，我们采用一种称为通道模式的理论上合理的方法，将我们先前的工作扩展到定向信息流。这是通过构造一个潜在函数来实现的，该函数促进了信道模式的纯概率解释。对于每个网络节点，通道模式在相同的上下文中结合了发射和吸收模式的解决方案，从而产生了我们所说的通道张量。每个节点上的通道张量的条目可以解释为从原点到目的地通过该节点的流量。与我们的早期模型相似，通道模式将阻尼作为自由参数包含在内，该参数控制信息流的局部性。通过涉及酵母信息素反应途径的实例，我们说明了我们新框架的多功能性和稳定性。

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