Evolutionary Systems

Research Summary

The main interest of our group is the theoretical study of evolutionary systems of different kinds. We develop models inspired by the phenomenology observed in natural systems, chiefly molecular populations, viruses, and interacting agents at the cellular level and up.

Research Lines

The main research topic of the group is the understanding, modelling and analysis of evolutionary mechanisms in biological and social systems. For almost two decades, we have investigated the adaptive dynamics of viruses and RNA populations and addressed broader problems, such as the relationship between genotype and phenotype (figure 1).

Figure 1. Illustration of phenotypic redundancy in a neutral nucleotide-to-amino-acid-sequence model. (A) The space of protein sequences of the same length is vast and contains a variety of functional sequences. (B) The number of codons representing each amino acid varies: codons coding for glycine (G), alanine (A), threonine (T), cysteine (C), arginine (R), glutamic acid (E), aspartic acid (D), and serine (S) are shown here explicitly as examples. (C) Possible nucleotide sequences coding for GATTACA (above) and REDRESS (below). From Villanueva et al., Biophysica 2022.

Recently, we have explored the topological structure that genotype-to-phenotype maps endow in sequence spaces, and its effects in the dynamics of heterogeneous molecular populations. We have uncovered some universal features of sequence spaces topology which are independent of the definition of phenotype and, therefore, have generic consequences for evolution and adaptation. Our results highlight the role of entropic effects in microscopic evolution: abundant, sufficiently functional phenotypes, are much more common in nature than highly adapted, but rare ones.

A full understanding of microscopic evolution is important to update current evolutionary theories and to derive useful effective models. In this sense, we question the role played by classical metaphors of evolution, and suggest that smooth fitness landscapes must be substituted by network-based representations. General evolutionary and adaptive processes affect multiple disciplines beyond biology.

Game theory, understood as the search for strategies that optimize fitness, can be applied to economic and other processes involving agents able to take decisions. In rigged economies, where market rules allow agents to artificially modify stock market prices, we have shown that economies increase in complexity: while growing economic complexity spontaneously defuses cartels, it also leads to large-fluctuations regimes that threaten the system’s stability.

In the context of epidemic propagation, we have shown that, even in the absence of non-pharmaceutical measures, epidemic waves and a convergence towards the critical propagation rate (figure 2) can originate from a self-adapting population behaviour, where individuals vary their degree of exposure according to their subjective perception of the external threat.

Figure 2. Effective reproduction number R₀ as a function of time. (a) Empirical estimation of COVID-19 R₀ for various countries and the World since 23 January 2020. (b) Evolution of R₀ value for a model that incorporates the risk-aversion response of individuals to the pandemic state. The model generates epidemic waves and a value of R₀ around 1, in agreement with natural progression (from Manrubia and Zanette, RSOS 2022). 

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