Evolutionary Dynamics on Complex Networks

Many complex systems such as the Internet can be represented as networks, with vertices denoting the constituent components of the systems and edges denoting the patterns of interactions among the components. In this thesis, we are interested in how the structural properties of a network, such as its average degree, degree distribution, clustering, and homophily affect the processes that take place on it. In the first part of the thesis we focus on evolutionary game theory models for studying the evolution of cooperation in a population of predominantly selfish individuals. In the second part we turn our attention to an evolutionary model of disease dynamics and the impact of vaccination on the spread of infection. Throughout the thesis we use a network as an abstraction for a population, with vertices representing individuals in the population and edges specifying who can interact with whom. We analyze our models for a well-mixed population, i.e., an infinite population with random mixing, and compare the theoretical results with those obtained from computer simulations on model and empirical networks

An Application of Evolutionary Game Theory to Social Dilemmas: The Traveler's Dilemma and the Minimum Effort Coordination Game

The Traveler's Dilemma game and the Minimum Effort Coordination game are two social dilemmas that have attracted considerable attention due to the fact that the predictions of classical game theory are at odds with the results found when the games are studied experimentally. Moreover, a direct application of deterministic evolutionary game theory, as embodied in the replicator dynamics, to these games does not explain the observed behavior. In this work, we formulate natural variants of these two games as smoothed continuous-strategy games. We study the evolutionary dynamics of these continuous-strategy games, both analytically and through agent-based simulations, and show that the behavior predicted theoretically is in accord with that observed experimentally. Thus, these variants of the Traveler's Dilemma and the Minimum Effort Coordination games provide a simple resolution of the paradoxical behavior associated with the original games

DNA repair pathways underlie a common genetic mechanism modulating onset in polyglutamine diseases

Objective: The polyglutamine diseases, including Huntington’s disease (HD) and multiple spinocerebellar ataxias (SCAs), are amongst the commonest hereditary neurodegenerative diseases. They are caused by expanded CAG tracts, encoding glutamine, in different genes. Longer CAG repeat tracts are associated with earlier ages at onset, but this does not account for all of the difference, and the existence of additional genetic modifying factors has been suggested in these diseases. A recent GWAS in HD found association between age at onset and genetic variants in DNA repair pathways and we therefore tested whether the modifying effects of variants in DNA repair genes have wider effects in the polyglutamine diseases. Methods: We assembled an independent cohort of 1462 subjects with HD and polyglutamine SCAs, and genotyped SNPs selected from the most significant hits in the HD study. Results: In the analysis of DNA repair genes as a group, we found the most significant association with age at onset when grouping all polyglutamine diseases (HD+SCAs, p=1.43x10-5). In individual SNP analysis, we found significant associations for rs3512 in FAN1 with HD+SCAs (p=1.52x10-5) and All SCAs (p=2.22x10-4) and rs1805323 in PMS2 with HD+SCAs (p=3.14x10-5), all in the same direction as in the HD GWAS. Interpretation: We show that DNA repair genes significantly modify the age at onset in HD and SCAs, suggesting a common pathogenic mechanism, which could operate through the observed somatic expansion of repeats that can be modulated by genetic manipulation of DNA repair in disease models. This offers novel therapeutic opportunities in multiple diseases

Methods for assessing DNA repair and repeat expansion in Huntington's Disease

Huntington’s disease (HD) is caused by a CAG repeat expansion in the HTT gene. Repeat length can change over time, both in individual cells and between generations, and longer repeats may drive pathology. Cellular DNA repair systems have long been implicated in CAG repeat instability but recent genetic evidence from humans linking DNA repair variants to HD onset and progression has reignited interest in this area. The DNA damage response plays an essential role in maintaining genome stability, but may also license repeat expansions in the context of HD. In this chapter we summarize the methods developed to assay CAG repeat expansion/contraction in vitro and in cells, and review the DNA repair genes tested in mouse models of HD. While none of these systems is currently ideal, new technologies, such as long-read DNA sequencing, should improve the sensitivity of assays to assess the effects of DNA repair pathways in HD. Improved assays will be essential precursors to high-throughput testing of small molecules that can alter specific steps in DNA repair pathways and perhaps ameliorate expansion or enhance contraction of the HTT CAG repeat

Evolutionary dynamics on complex networks

Many complex systems such as the Internet can be represented as networks, with vertices denoting the constituent components of the systems and edges denoting the patterns of interactions among the components. In this thesis, we are interested in how the structural properties of a network, such as its average degree, degree distribution, clustering, and homophily affect the processes that take place on it. In the first part of the thesis we focus on evolutionary game theory models for studying the evolution of cooperation in a population of predominantly selfish individuals. In the second part we turn our attention to an evolutionary model of disease dynamics and the impact of vaccination on the spread of infection. Throughout the thesis we use a network as an abstraction for a population, with vertices representing individuals in the population and edges specifying who can interact with whom. We analyze our models for a well-mixed population, i.e., an infinite population with random mixing, and compare the theoretical results with those obtained from computer simulations on model and empirical networks

Evolution of Cooperation in Social Dilemmas on Complex Networks.

Cooperation in social dilemmas is essential for the functioning of systems at multiple levels of complexity, from the simplest biological organisms to the most sophisticated human societies. Cooperation, although widespread, is fundamentally challenging to explain evolutionarily, since natural selection typically favors selfish behavior which is not socially optimal. Here we study the evolution of cooperation in three exemplars of key social dilemmas, representing the prisoner's dilemma, hawk-dove and coordination classes of games, in structured populations defined by complex networks. Using individual-based simulations of the games on model and empirical networks, we give a detailed comparative study of the effects of the structural properties of a network, such as its average degree, variance in degree distribution, clustering coefficient, and assortativity coefficient, on the promotion of cooperative behavior in all three classes of games

Evolution of Cooperation in Social Dilemmas with Assortative Interactions

Cooperation in social dilemmas plays a pivotal role in the formation of systems at all levels of complexity, from replicating molecules to multi-cellular organisms to human and animal societies. In spite of its ubiquity, the origin and stability of cooperation pose an evolutionary conundrum, since cooperation, though beneficial to others, is costly to the individual cooperator. Thus natural selection would be expected to favor selfish behavior in which individuals reap the benefits of cooperation without bearing the costs of cooperating themselves. Many proximate mechanisms have been proposed to account for the origin and maintenance of cooperation, including kin selection, direct reciprocity, indirect reciprocity, and evolution in structured populations. Despite the apparent diversity of these approaches they all share a unified underlying logic: namely, each mechanism results in assortative interactions in which individuals using the same strategy interact with a higher probability than they would at random. Here we study the evolution of cooperation in both discrete strategy and continuous strategy social dilemmas with assortative interactions. For the sake of tractability, assortativity is modeled by an individual interacting with another of the same type with probability r and interacting with a random individual in the population with probability 1−r, where r is a parameter that characterizes the degree of assortativity in the system. For discrete strategy social dilemmas we use both a generalization of replicator dynamics and individual-based simulations to elucidate the donation, snowdrift, and sculling games with assortative interactions, and determine the analogs of Hamilton’s rule, which govern the evolution of cooperation in these games. For continuous strategy social dilemmas we employ both a generalization of deterministic adaptive dynamics and individual-based simulations to study the donation, snowdrift, and tragedy of the commons games, and determine the effect of assortativity on the emergence and stability of cooperation

Business Plan – Establishment and Operation of Crossfit Gym

This Bachelor thesis deals with the business plan for the establishment and operation of crossfit gym. The Bachelor thesis is divided into two parts, theoretical, analytical and practical. In the theoretical part are described aims and defined basic terms. In the analytical part, the current market situation is analyzed using theoretical knowledge. In the practical part is the actual implementation of the business plan