Table_1_On the Origin of Biomolecular Networks.pdf

Biomolecular networks have already found great utility in characterizing complex biological systems arising from pairwise interactions amongst biomolecules. Here, we explore the important and hitherto neglected role of information asymmetry in the genesis and evolution of such pairwise biomolecular interactions. Information asymmetry between sender and receiver genes is identified as a key feature distinguishing early biochemical reactions from abiotic chemistry, and a driver of network topology as biomolecular systems become more complex. In this context, we review how graph theoretical approaches can be applied not only for a better understanding of various proximate (mechanistic) relations, but also, ultimate (evolutionary) structures encoded in such networks from among all types of variations they induce. Among many possible variations, we emphasize particularly the essential role of gene duplication in terms of signaling game theory, whereby sender and receiver gene players accrue benefit from gene duplication, leading to a preferential attachment mode of network growth. The study of the resulting dynamics suggests many mathematical/computational problems, the majority of which are intractable yet yield to efficient approximation algorithms, when studied through an algebraic graph theoretic lens. We relegate for future work the role of other possible generalizations, additionally involving horizontal gene transfer, sexual recombination, endo-symbiosis, etc., which enrich the underlying graph theory even further.

生物分子网络在表征由生物分子之间的成对相互作用产生的复杂生物系统中已显示出极大的实用性。在此，我们探讨了信息不对称在成对生物分子相互作用起源和进化中的重要且迄今为止未被忽视的作用。发送者和接收者基因之间的信息不对称被确认为区分早期生化反应与无机化学的关键特征，也是随着生物分子系统变得更加复杂而驱动网络拓扑的关键因素。在此背景下，我们回顾了图论方法如何被应用于不仅加深对各种近端（机制性）关系的理解，而且揭示出这些网络中编码的最终（进化性）结构，这些结构来源于它们所诱导的所有类型的变异。在众多可能的变异中，我们特别强调基因复制在信号博弈论中的关键作用，发送者和接收者基因玩家通过基因复制获得利益，导致网络增长偏好附着模式。对由此产生的动力学的研究提出了许多数学/计算问题，其中大多数问题是难以解决的，但通过代数图论视角的研究，它们则屈服于高效的近似算法。我们将涉及其他可能的推广作用留待未来研究，这些推广作用还涉及水平基因转移、性重组、内共生等，这些将进一步丰富基础图论。