论文标题
部分可观测时空混沌系统的无模型预测
Self-organized critical dynamics of RNA virus evolution
论文作者
论文摘要
RNA病毒（例如SARS-COV-2）以复杂的方式演变。研究RNA病毒进化对于理解分子进化和医学发展至关重要。然而，科学家缺乏直接从经验数据中直接表征RNA病毒进化的动力学的一般框架并确定潜在的物理定律。为了填补这一空白，我们提出了一种理论，将RNA病毒进化为具有吸收状态和雪崩行为的物理系统。这种方法将可访问的生物学数据（例如，系统发育和感染）映射到RNA病毒感染和进化的一般随机过程，使研究人员能够验证RNA病毒进化的潜在自组织的关键性。我们将框架应用于SARS-COV-2，这是Covid-19的全球流行病的病毒。我们发现SARS-COV-2作为平均场理论预测表现出规模不变的雪崩。观察到的缩放关系，普遍崩溃和缓慢衰减的自动相关表明SARS-COV-2进化的临界动力学。有趣的是，从临界进化过程中出现的谱系与威胁性的SARS-COV-2（例如三角洲病毒）的谱系相吻合。我们预计我们的方法是一种一般形式主义，可以描绘RNA病毒进化并有助于确定潜在的病毒谱系。
RNA virus (e.g., SARS-CoV-2) evolves in a complex manner. Studying RNA virus evolution is vital for understanding molecular evolution and medicine development. Scientists lack, however, general frameworks to characterize the dynamics of RNA virus evolution directly from empirical data and identify potential physical laws. To fill this gap, we present a theory to characterize the RNA virus evolution as a physical system with absorbing states and avalanche behaviors. This approach maps accessible biological data (e.g., phylogenetic tree and infection) to a general stochastic process of RNA virus infection and evolution, enabling researchers to verify potential self-organized criticality underlying RNA virus evolution. We apply our framework to SARS-CoV-2, the virus accounting for the global epidemic of COVID-19. We find that SARS-CoV-2 exhibits scale-invariant avalanches as mean-field theory predictions. The observed scaling relation, universal collapse, and slowly decaying auto-correlation suggest a self-organized critical dynamics of SARS-CoV-2 evolution. Interestingly, the lineages that emerge from critical evolution processes coincidentally match with threatening lineages of SARS-CoV-2 (e.g., the Delta virus). We anticipate our approach to be a general formalism to portray RNA virus evolution and help identify potential virus lineages to be concerned.
