Information Dynamics in Evolving Networks Based on the Birth-Death Process: Random Drift and Natural Selection Perspective

Evolutionary change can occur by nonadaptive processes, such as random genetic drift, and as a consequence of selection on linked genetic variants. In addition, if selective regimes change over time, an allele currently at a high frequency because of past fitness advantage may be suboptimal for its present environment. Small effective population size along the human lineage increased the influence of drift, rendering mutations with slight effects on fitness effectively neutral. Demographic events like spatial expansions and population bottlenecks shape most of the genetic variation within and among modern populations. Natural selection itself may also contribute to nonadaptive or maladaptive change by increasing the frequency of linked deleterious variants. Also, certain maladaptive alleles may have increased in frequency because of compensating fitness advantages they provide. Key Concepts: Reduced effective population size along the human lineage led to an increase in the influence of genetic drift and a reduction in the efficacy of natural selection, especially for mutations with small selective effects. Evidence for this can be seen in comparisons of measures of natural selection in lineages having different effective population sizes. Genome‐wide variation within and between human populations can be almost entirely explained by random drift and demographic forces other natural selection. Spatial expansions in human evolutionary history may cause gene surfing, in which low frequency alleles at the wave of advance can reach high frequencies and spread over large areas merely due to the effects of intense genetic drift. Nonadaptive gene surfing might be a better explanation than adaptive evolution for some high frequency, widespread genetic variants. Population bottlenecks in human evolutionary history can lead to increases in drift and reductions in the efficacy of purifying selection. This leads to an increase in the fraction of slightly deleterious mutations present in human populations that have experienced recent bottlenecks. Natural selection on alleles can result in nonadaptive shifts in the frequencies of alleles that are closely linked to them. Such linkage effects can lead to the increased frequencies of mildly deleterious alleles if they are linked to a beneficial variant, and can interfere with the effectiveness of adaptive evolution in promoting an advantageous allele if it is linked to a deleterious allele. Caution should be exercised in interpreting patterns of genetic variation in human populations as being adaptive without thoroughly ruling out nonadaptive explanations.

Robustness and Optimization of Complex Networks: Reconstructability, Algorithms and Modeling

Analysis of genome sequences of 159 isolates of Plasmodium falciparum from Senegal yields an extraordinarily high proportion (26.85%) of protein-coding genes with the ratio of nonsynonymous to synonymous polymorphism greater than one. This proportion is much greater than observed in other organisms. Also unusual is that the site-frequency spectra of synonymous and nonsynonymous polymorphisms are virtually indistinguishable. We hypothesized that the complicated life cycle of malaria parasites might lead to qualitatively different population genetics from that predicted from the classical Wright-Fisher (WF) model, which assumes a single random-mating population with a finite and constant population size in an organism with nonoverlapping generations. This paper summarizes simulation studies of random genetic drift and selection in malaria parasites that take into account their unusual life history. Our results show that random genetic drift in the malaria life cycle is more pronounced than under the WF model. Paradoxically, the efficiency of purifying selection in the malaria life cycle is also greater than under WF, and the relative efficiency of positive selection varies according to conditions. Additionally, the site-frequency spectrum under neutrality is also more skewed toward low-frequency alleles than expected with WF. These results highlight the importance of considering the malaria life cycle when applying existing population genetic tools based on the WF model. The same caveat applies to other species with similarly complex life cycles.

This paper concludes that the statistical properties of protein evolution are compatible with a particular model of evolution by natural selection. The argument begins with a statistical description of the molecular clock based on a Poisson process with a randomly varying tick rate. If the time scale of the change of the tick rate of the molecular clock is assumed to be much less than the average time between substitutions, then it is shown that the substitution process must be episodic, with bursts of substitutions being separated by long periods of time with no substitutions. This analysis generalizes the recent work of Gillespie (1984a). The second part of the argument shows that a simple model of evolution by natural selection--one that incorporates a changing environment, the molecular landscape, and a simple form of epistasis--exhibits dynamics that are identical to those inferred from the statistical analysis. This leads to the conclusion that natural selection is a viable explanation for protein evolution. In addition, a correction formula for multiple substitutions is given that does not require that the substitution process be a Poisson process, and some comments on the inability of the neutral allele theory to account for the dynamics of the substitution process are presented.

Preferential attachment, also referred to as the “rich-get-richer” mechanism, characterizes the ability of already existing nodes in an evolutionary network to acquire new connections from newly-coming nodes throughout the growing process of the network. This mechanism is responsible for the emergence of some critical structures in many real networks, such as the Saccharomyces cerevisiae protein-protein interaction network, scientific collaboration network, and bitcoin transaction network. Clearly, it is very important to accurately estimate the preferential attachment mechanism for a growing network in interest. Although it has long been aware that the existing widely-used methods yield significantly biased estimates of preferential attachments, the underlying mechanism is not completely understood and not well explained. By rewriting preferential attachment from a deterministic formulation to a stochastic one, this paper reveals two major problems existing in the current methodologies, thereby well explaining why traditional methods introduce biases to the estimates of preferential attachments. To avoid the negative effects of these two problems, a new method is proposed based on the Poisson Pseudo Maximum Likelihood method for estimating preferential attachments, which provides asymptotically consistent estimation to preferential attachments. More importantly, even with insufficient information, the new method can still provide an estimate with high precision, showing a significant advantage in measuring preferential attachments based on small-sized samples. The new method is also robust against network parameter changes. The findings may shed some lights onto deeper understanding of the evolutionary processes of real networks.

We analyze whether proximity effect, preferential attachment and path dependence or three "P" mechanisms would concur within the evolutionary process of inter-regional network. Using a unique database of China's technology transaction between regions, we show that proximity effect, preferential attachment and path dependence have coexisted in the evolutionary process of China's inter-regional network of technology transactions. In particular, the inter-regional relations positively and significantly correlate with the geographical and economic proximity matrix, all regions' three centrality values in current year positively and significantly correlate with their centrality in the last two years, and the inter-regional relations in current year positively and significantly correlate with own relations in last two years. This paper contributes to the existing literature by identifying three evolutionary mechanisms of inter-regional network. An interpretation is that the evolution process of inter-regional network is a very complex process, and one mechanism such as geographical proximity from the perspective of economic geography or preferential attachment from the perspective of network science only could explain a part of the process.

18 albinos were born on Lençóis island. Since 3 of them died and 5 emigrated, the prevalence of albinism is about 3% in the island. 2 inbred brothers with brachydactyly of the index fingers and 1 case of 'achondroplasia' were also found. The analysis of the population structure of the island suggests that its high frequency of albinism may have been produced by random drift. The index of isolation of its present population is roughly 17--27. Genealogical, clinical and histological data are presented and anslyzed. Natural selection is not acting against the albinism gene at a measurable rate. Cytogenetic investigations among albinos and normals did not reveal any difference as regards frequency of aneuploidy, association of acrocentrics and chromatid gaps. The role of random processes in evolution is mentioned and the possibility that they may be more important than it is sometimes assumed is stressed.

Signs of the times

Adjustment for population structure is necessary to avoid bias in genetic association studies of susceptibility variants for complex diseases. Population structure may differ from one genomic region to another due to the variability of individual ancestry associated with migration, random genetic drift or natural selection. Current association methods for correcting population stratification usually involve adjustment of global ancestry between study subjects. We suggest interrogating local population structure for fine mapping to more accurately locate true casual genes by better adjusting the confounding effect due to local ancestry. By extensive simulations on genome-wide datasets, we show that adjusting global ancestry may lead to false positives when local population structure is an important confounding factor. In contrast, adjusting local ancestry can effectively prevent false positives due to local population structure and thus can improve fine mapping for disease gene localization. We applied the local and global adjustments to the analysis of datasets from three genome-wide association studies, including European Americans, African Americans and Nigerians. Both European Americans and African Americans demonstrate greater variability in local ancestry than Nigerians. Adjusting local ancestry successfully eliminated the known spurious association between SNPs in the LCT gene and height due to the population structure existed in European Americans. xiaofeng.zhu@case.edu Supplementary data are available at Bioinformatics online.

Natural selection

Many vertebrates exhibit homing behavior during breeding migration. Such behavior is adaptive, obviously, if individuals reproduce most successfully in habitats where they themselves were spawned. Nevertheless, by reducing gene exchange among local breeding populations, homing behavior may have profound evolutionary consequences at the species level. Considerable divergence in allelic frequencies will develop by random genetic drift among geographically isolated demes or even over continuously distributed populations isolated by virtue of low dispersal and distance (Wright, 1931, 1943, 1951; Malecot, 1969). Moreover, natural selection may promote local adaptation and diversification of demes if unopposed by the homogenizing influence of interdemic gene flow (Ehrlich and Raven, 1969). Studies of genetic variation and population structure in animals with homing instincts, therefore, should yield insight into the process and mechanisms of evolutionary divergence among conspecific populations. How much divergence among demes is due to random genetic drift and how much is due to natural selection has proved difficult to evaluate. Because natural selection may act in a complex manner on complex phenotypes, general consequences of homing behavior on gene frequency distributions cannot be specified. On the other hand, frequency distributions of selectively neutral genes have been precisely stated for a number of applicable population models. Unfortunately, even these testable predictions depend on pa-

Preferential attachment drives the evolution of many complex networks. Its analytical studies mostly consider the simplest case of a network that grows uniformly in time despite the accelerating growth of many real networks. Motivated by the observation that the average degree growth of nodes is time invariant in empirical network data, we study the degree dynamics in the relevant class of network models where preferential attachment is combined with heterogeneous node fitness and aging. We propose an analytical framework based on the time invariance of the studied systems and show that it is self-consistent only for two special network growth forms: the uniform and the exponential network growth. Conversely, the breaking of such time invariance explains the winner-takes-all effect in some model settings, revealing the connection between the Bose-Einstein condensation in the Bianconi-Barabási model and similar gelation in superlinear preferential attachment. Aging is necessary to reproduce realistic node degree growth curves and can prevent the winner-takes-all effect under weak conditions. Our results are verified by extensive numerical simulations.

This thesis is centered on the theory of stochastic processes and their applications in biological systems characterized by a complex environment. Three case studies have been modeled by the use of the three fundamental tools of stochastic processes: the master equation (ME), the stochastic differential equation (SDE) and the partial differential equation (PDE). The principal approach here applied to deal with complexity is the characterization of the system by means of probability distributions describing each a parameter of the model or the introduction of fractional order derivatives to include non-local and memory effects maintaining the linearity in the equations. In Chapter 1 we briefly review the theory of stochastic processes. In Chapter 2 we derive a birth-death process master equation to test if Long Interspersed Elements (LINEs) can be modeled according to the neutral theory of biodiversity. In Chapter 3 we derive a model of anomalous diffusion based on a Langevin approach in which anomalous behavior arise in the asymptotic intermediate state as a consequence of the heterogeneity of the system, from the superposition of Ornstein-Uhlenback processes. In Chapter 4 we propose an extension of the cable equation, used to describe anomalous diffusion phenomena as the signal conduction in spiny dendrites, by introducing a Caputo time fractional derivative.

Coupling interaction impairs knowledge and green behavior diffusion in complex networks

In the last 10 years, policy networks have become a popular concept to analyze policy making in muli-actor settings. This article argues that although stimulating and interesting, the research that has been done in this field can be improved in three ways. The first way to improve the usefulness of the concept network is to pay more attention to the dynamics of policy making. In this article, the concept game is used to conceptualize this dynamic character of policy processes. Second, the concept network stresses the context of policy making, buta coherent theoretical framework on how this coextisformed and changed is lacking. This article attempts to make some steps toward such a theoretical framework.Central in this framework is the idea of the duality of structure proposed by Giddens and the notion of rules. Finally, the literature on networks could gain relevance by directing more systematic attention on how complex policy processes in these networks can be managed Building on earlier work, especially in interorganization theory some management strategies are discussed.