PT  - JOURNAL ARTICLE
AU  - Hamid Teimouri
AU  - Dorsa Sattari Khavas
AU  - Cade Spaulding
AU  - Christopher Li
AU  - Anatoly B. Kolomeisky
TI  - Theoretical understanding of evolutionary dynamics on inhomogeneous networks
AID  - 10.1101/2023.02.02.526861
DP  - 2023 Jan 01
TA  - bioRxiv
PG  - 2023.02.02.526861
4099  - http://biorxiv.org/content/early/2023/02/03/2023.02.02.526861.short
4100  - http://biorxiv.org/content/early/2023/02/03/2023.02.02.526861.full
AB  - Evolution is the main feature of all biological systems that allows populations to change their characteristics over successive generations. A powerful approach to understand evolutionary dynamics is to investigate fixation probabilities and fixation times of novel mutations on networks that mimic biological populations. It is now well established that the structure of such networks can have dramatic effects on evolutionary dynamics. In particular, there are population structures that might amplify the fixation probabilities while simultaneously delaying the fixation events. However, the microscopic origins of such complex evolutionary dynamics remain not well understood. We present here a theoretical investigation of the microscopic mechanisms of mutation fixation processes on inhomogeneous networks. It views evolutionary dynamics as a set of stochastic transitions between discrete states specified by different numbers of mutated cells. By specifically considering star networks, we obtain a comprehensive description of evolutionary dynamics. Our approach allows us to employ physics-inspired free-energy landscape arguments to explain the observed trends in fixation times and fixation probabilities, providing a better microscopic understanding of evolutionary dynamics in complex systems.Competing Interest StatementThe authors have declared no competing interest.