Quantifying Selection Pressure

2018 ◽  
Vol 26 (2) ◽  
pp. 213-235
Author(s):  
Evert Haasdijk ◽  
Jacqueline Heinerman
Keyword(s):  
Selection Pressure ◽  
Selection Process ◽  
Evolutionary Process ◽  
Evolutionary Development ◽  
Control Mechanisms ◽  
Evolutionary Systems ◽  
Chain Analysis ◽  
Crucial Component ◽  
Number Of Publications ◽  
Post Hoc

Selection is an essential component of any evolutionary system and analysing this fundamental force in evolution can provide relevant insights into the evolutionary development of a population. The 1990s and early 2000s saw a substantial number of publications that investigated selection pressure through methods such as takeover time and Markov chain analysis. Over the last decade, however, interest in the analysis of selection in evolutionary computing has waned. The established methods for analysis of selection pressure provide little insight when selection is based on more than comparison-of-fitness values. This can, for instance, be the case in coevolutionary systems, when measures unrelated to fitness affect the selection process (e.g., niching) or in systems that lack a crisply defined objective function. This article proposes two metrics that holistically consider the statistics of the evolutionary process to quantify selection pressure in evolutionary systems and so can be applied where traditionally used methods fall short. The metrics are based on a statistical analysis of the relation between reproductive success and a quantifiable trait: one method builds on an estimate of the probability that this relation is random; the other uses a correlation measure. These metrics provide convenient tools to analyse selection pressure and so allow researchers to better understand this crucial component of evolutionary systems. Both metrics are straightforward to implement and can be used in post-hoc analyses as well as during the evolutionary process, for example, to inform parameter control mechanisms. A number of case studies and a critical analysis show that the proposed metrics provide relevant and reliable measures of selection pressure.

scholarly journals Intrinsic Noise and the Design of the Genetic Machinery

1983 ◽  
Vol 36 (1) ◽  
pp. 77 ◽  
Author(s):  
DC Reanney ◽  
DG MacPhee ◽  
J Pressing
Keyword(s):  
Life Style ◽  
Selection Pressure ◽  
Evolutionary Process ◽  
Intrinsic Noise ◽  
Darwinian Theory ◽  
Transmission Of Information ◽  
Genetic Mechanisms ◽  
Translational Mechanisms

Darwinian theory envisages 'selection pressure' as a stress imposed on the genotype by the environment. However, noise in the replicative and translational mechanisms in itself imposes a significant 'pressure' on the adaptive fitness of the organism. We propose that the biosphere has been shaped by both extrinsic (environmental) and intrinsic (noise-generated) factors. Because noise has been a remorseless and ever-present background to the evolutionary process, adaptations to this intrinsic pressure include not only a variety of familiar genetic mechanisms but also many anatomical and life-style characteristics that focus on the transmission of information between generations.

Evolutionary Growth and Control in User Tailorable Systems

2003 ◽  
pp. 30-58 ◽  
Author(s):  
Anders I. Morch
Keyword(s):  
Dominant Role ◽  
Evolutionary Process ◽  
End Users ◽  
Object Oriented Programming ◽  
Evolutionary Development ◽  
Software Systems ◽  
Application Development ◽  
Art Objects ◽  
Evolutionary Growth ◽  
Informal Design

This chapter is about evolutionary application development as a means for including end users in further development of existing software systems. The chapter presents concepts and techniques for evolutionary development that reuses ideas from other domains in which evolution plays a dominant role (biology, architecture, and art objects). It argues that end users need access to representations of a system that are less formal than program code, but more powerful than informal design representations, and that this information can be obtained from the system’s past use and development history. The “resemblance relation” is presented as a tentative solution. It includes elements of object-oriented programming and component-based development. It is hoped that this chapter will provide the reader with a new view on systems development, and how end users can participate as designers in the evolutionary process.

Error Thresholds in Genetic Algorithms

2006 ◽  
Vol 14 (2) ◽  
pp. 157-182 ◽  
Author(s):  
Gabriela Ochoa
Keyword(s):  
Genetic Algorithms ◽  
Selection Pressure ◽  
Evolutionary Process ◽  
Critical Value ◽  
Mutation Rates ◽  
Genomic Information ◽  
Quasispecies Model ◽  
Error Catastrophe ◽  
Important Notion ◽  
Quasispecies Evolution

The error threshold of replication is an important notion in the quasispecies evolution model; it is a critical mutation rate (error rate) beyond which structures obtained by an evolutionary process are destroyed more frequently than selection can reproduce them. With mutation rates above this critical value, an error catastrophe occurs and the genomic information is irretrievably lost. Therefore, studying the factors that alter this magnitude has important implications in the study of evolution. Here we use a genetic algorithm, instead of the quasispecies model, as the underlying model of evolution, and explore whether the phenomenon of error thresholds is found on finite populations of bit strings evolving on complex landscapes. Our empirical results verify the occurrence of error thresholds in genetic algorithms. In this way, this notion is brought from molecular evolution to evolutionary computation. We also study the effect of modifying the most prominent evolutionary parameters on the magnitude of this critical value, and found that error thresholds depend mainly on the selection pressure and genotype length.

scholarly journals Optimalisasi Penyelesaian Knapsack Problem Dengan Algoritma Genetika

2016 ◽  
pp. 182
Author(s):  
I Wayan Supriana
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Everyday Life ◽  
Knapsack Problem ◽  
Selection Process ◽  
Optimization Algorithms ◽  
Evolutionary Process ◽  
Knapsack Problems ◽  
Theory Of Evolution ◽  
Selection Of

Knapsack problems is a problem that often we encounter in everyday life. Knapsack problem itself is a problem where a person faced with the problems of optimization on the selection of objects that can be inserted into the container which has limited space or capacity. Problems knapsack problem can be solved by various optimization algorithms, one of which uses a genetic algorithm. Genetic algorithms in solving problems mimicking the theory of evolution of living creatures. The components of the genetic algorithm is composed of a population consisting of a collection of individuals who are candidates for the solution of problems knapsack. The process of evolution goes dimulasi of the selection process, crossovers and mutations in each individual in order to obtain a new population. The evolutionary process will be repeated until it meets the criteria o f an optimum of the resulting solution. The problems highlighted in this research is how to resolve the problem by applying a genetic algorithm knapsack. The results obtained by the testing of the system is built, that the knapsack problem can optimize the placement of goods in containers or capacity available. Optimizing the knapsack problem can be maximized with the appropriate input parameters.

Stopping and Restarting an Unfolding Action at Various Times

2003 ◽  
Vol 56 (4) ◽  
pp. 1-20 ◽  
Author(s):  
Tim McGarry ◽  
Romeo Chua ◽  
Ian M. Franks
Keyword(s):  
Nonlinear Function ◽  
Race Model ◽  
Stop Signal ◽  
Stop Signal Task ◽  
Control Mechanisms ◽  
Stochastic Independence ◽  
Timing Task ◽  
Stop And Go ◽  
Post Hoc ◽  
Horse Race Model

The ability to inhibit an unfolding action is usually investigated using a stop signal (or go—stop) task. The data from the stop-signal task are often described using a horse-race model whose key assumption is that each process (i.e., go, stop) exhibits stochastic independence. Using three variations of a coincident-timing task (i.e., go, go—stop, and go—stop—go) we extend previous considerations of stochastic independence by analysing the go latencies for prior effects of stopping. On random trials in the go—stop—go task the signal sweep was paused for various times at various distances before the target. Significant increases in latency errors were reported on those trials on which the signal was paused (p <.005). Further analyses of the pause trials revealed significant effects for both the stopping interval (p <.001) and the pause interval (p <.05). Tukey post hoc analyses demonstrated increased latency errors as a linear function of the stopping interval, as expected, and decreased latency errors as a nonlinear function of the pause interval. These latter results indicate that the latencies of the go process, as reflected in the latency errors, may not exhibit stochastic independence under certain conditions. Various control mechanisms were considered in an attempt to explain these data.

scholarly journals On the Origin of Human Behavior

2020 ◽  
Author(s):  
Igor Kopsov
Keyword(s):  
Human Behavior ◽  
Future Orientation ◽  
Evolutionary Process ◽  
Transient State ◽  
Well Being ◽  
Evolutionary Development ◽  
Human Beings ◽  
Action Execution ◽  
Feedback Mechanisms ◽  
Comparison Algorithms

<p>Numerous behavioral and decision-making theories have been proposed within various branches of physiology, psychology, and social sciences. However, few authors have studied the <i>origin</i> of behavior. It has been suggested that human behavior can be described as an algorithm, defining an action-execution process through a sequence of steps and feedback mechanisms. Given this premise, origins of human behavior are comparatively assessed to other forms of nature; to facilitate this comparison, algorithms were developed to sequence the functionality of inanimate matter (i.e. motionless or inoperative matter) and animate life (i.e. living organisms). Subsequently, the three developed algorithms – for matter, life, and mind – allowed to identify both their common and unique features, as well as to follow the evolutionary flow between the physical, biological, and psychological dimensions of nature. We postulate that algorithms of behavior of physical objects, biological organisms, and human beings are not standalone constructs but phases of the evolutionary process. Furthermore, in this evolutionary <a>process, </a>algorithms are continuously adjusted and enhanced through the addition of new steps and feedback mechanisms. The underlying commonality for these changes in behavior is rising prominence of future-orientation of actions, e.g., when an organism increasingly caters for its future well-being, rather than solely enhancing its transient state. This transformation takes place through shifts from immediate and predetermined reactions, to longer-term orientated and variable responses. Throughout this process, functional algorithms of higher complexity do not invalidate predecessors, but on the contrary, incorporate and build on them. The presented theory offers an explanation on how, and to what extent, operational algorithms are shared between various forms of nature. It also considers possible future directions for evolutionary development.</p>

scholarly journals Concern for Dirofilaria immitis and Macrocyclic Lactone Loss of Efficacy: Current Situation in the USA and Europe, and Future Scenarios

Pathogens ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1323
Author(s):  
Anastasia Diakou ◽  
Roger K. Prichard
Keyword(s):  
Selection Pressure ◽  
Dirofilaria Immitis ◽  
Evolutionary Process ◽  
Resistance Development ◽  
Larval Stages ◽  
Resistance Selection ◽  
The Usa ◽  
Suppression Test ◽  
Resistant Strains ◽  
Geographical Point

Dirofilaria immitis infection is one of the most severe parasitic diseases in dogs. Prevention is achieved by the administration of drugs containing macrocyclic lactones (MLs). These products are very safe and highly effective, targeting the third and fourth larval stages (L3, L4) of the parasite. Until 2011, claims of the ineffectiveness of MLs, reported as “loss of efficacy” (LOE), were generally attributed to owners’ non-compliance, or other reasons associated with inadequate preventative coverage. There was solid argumentation that a resistance problem is not likely to occur because of (i) the great extent of refugia, (ii) the complexity of resistance development to MLs, and (iii) the possible large number of genes involved in resistance selection. Nevertheless, today, it is unequivocally proven that ML-resistant D. immitis strains exist, at least in the Lower Mississippi region, USA. Accordingly, tools have been developed to evaluate and confirm the susceptibility status of D. immitis strains. A simple, in-clinic, microfilariae suppression test, 14-28 days after ML administration, and a “decision tree” (algorithm), including compliance and preventatives’ purchase history, and testing gaps, may be applied for assessing any resistant nature of the parasite. On the molecular level, specific SNPs may be used as markers of ML resistance, offering a basis for the validation of clinically suspected resistant strains. In Europe, no LOE/resistance claims have been reported so far, and the existing conditions (stray dogs, rich wildlife, majority of owned dogs not on preventive ML treatment) do not favor selection pressure on the parasites. Considering the genetic basis of resistance and the epizootiological characteristics of D. immitis, ML resistance neither establishes easily nor spreads quickly, a fact confirmed by the current known dispersion of the problem, which is limited. Nevertheless, ML resistance may propagate from an initial geographical point, via animal and vector mobility, to other regions, while it can also emerge as an independent evolutionary process in a new area. For these reasons, and considering the current chemoprophylaxis recommendations and increasing use of ML endectoparasiticides as a potential selection pressure, it is important to remain vigilant for the timely detection of any ML LOE/resistance, in all continents where D. immitis is enzootic.

scholarly journals On the Origin of Human Behavior

2020 ◽  
Author(s):  
Igor Kopsov
Keyword(s):  
Human Behavior ◽  
Future Orientation ◽  
Evolutionary Process ◽  
Transient State ◽  
Well Being ◽  
Evolutionary Development ◽  
Human Beings ◽  
Action Execution ◽  
Feedback Mechanisms ◽  
Comparison Algorithms

<p>Numerous behavioral and decision-making theories have been proposed within various branches of physiology, psychology, and social sciences. However, few authors have studied the <i>origin</i> of behavior. It has been suggested that human behavior can be described as an algorithm, defining an action-execution process through a sequence of steps and feedback mechanisms. Given this premise, origins of human behavior are comparatively assessed to other forms of nature; to facilitate this comparison, algorithms were developed to sequence the functionality of inanimate matter (i.e. motionless or inoperative matter) and animate life (i.e. living organisms). Subsequently, the three developed algorithms – for matter, life, and mind – allowed to identify both their common and unique features, as well as to follow the evolutionary flow between the physical, biological, and psychological dimensions of nature. We postulate that algorithms of behavior of physical objects, biological organisms, and human beings are not standalone constructs but phases of the evolutionary process. Furthermore, in this evolutionary <a>process, </a>algorithms are continuously adjusted and enhanced through the addition of new steps and feedback mechanisms. The underlying commonality for these changes in behavior is rising prominence of future-orientation of actions, e.g., when an organism increasingly caters for its future well-being, rather than solely enhancing its transient state. This transformation takes place through shifts from immediate and predetermined reactions, to longer-term orientated and variable responses. Throughout this process, functional algorithms of higher complexity do not invalidate predecessors, but on the contrary, incorporate and build on them. The presented theory offers an explanation on how, and to what extent, operational algorithms are shared between various forms of nature. It also considers possible future directions for evolutionary development.</p>

scholarly journals Concern for Dirofilaria immitis and Macrocyclic Lactone Loss of Efficacy: Current Situation in the USA and Europe, and Future Scenarios

2021 ◽  
Author(s):  
Anastasia Diakou ◽  
Roger K. Prichard
Keyword(s):  
Selection Pressure ◽  
Dirofilaria Immitis ◽  
Evolutionary Process ◽  
Resistance Development ◽  
Larval Stages ◽  
Resistance Selection ◽  
The Usa ◽  
Suppression Test ◽  
Resistant Strains ◽  
Geographical Point

Dirofilaria immitis infection is one of the most severe parasitic diseases of dogs. Prevention is achieved by the administration of drugs containing macrocyclic lactones (MLs). These products are very safe and highly effective, targeting the third and fourth larval stages (L3, L4) of the parasite. Until 2011, claims of ineffectiveness of MLs, reported as &ldquo;Lack of Efficacy&rdquo; (LOE), were generally attributed to owners&rsquo; non-compliance, or other reason for inadequate preventative coverage. There was solid argumentation that a resistance problem is not likely to occur because of i) the great extent of refugia, ii) the complexity of resistance development to MLs, and iii) the possible big number of genes involved in resistance selection. Nevertheless, today it is unequivocally proven that ML resistant D. immitis strains exist, at least in the Lower Mississippi region, USA. Accordingly, tools have been developed, to evaluate and confirm the susceptibility status of D. immitis strains. A simple, in-clinic, microfilariae suppression test, 14-28 days after ML administration, and a &ldquo;decision tree&rdquo; (algorithm), including compliance and preventatives&rsquo; purchase history, and testing gaps, may be applied for assessing any resistant nature of the parasite. On the molecular level, specific SNPs may be used as markers of ML resistance, offering a basis for validation of clinically suspected resistant strains. In Europe, no LOE/resistance claims have been reported so far, and the existing conditions (stray dogs, rich wildlife, majority of owned dogs not on preventive MLs treatment) do not favor selection pressure on the parasites. Considering the genetic basis of resistance and the epizootiological characteristics of D. immitis, ML resistance neither establishes easily nor spreads quickly, a fact confirmed by the current known dispersion of the problem, which is limited. Nevertheless, ML resistance may propagate from an initial geographical point, via animal and vector mobility, to other regions, while it can also emerge as an independent evolutionary process in a new area. For these reasons and considering the current chemoprophylaxis recommendations and increasing use of ML endectoparasiticides as a potential selection pressure, it is important to remain vigilant for timely detection of any ML LOE/resistance, in all continents where D. immitis is enzootic.

scholarly journals Evolution of human diseases

2020 ◽  
Vol 4 (1) ◽  
pp. 52-67
Author(s):  
Harem othman Smail
Keyword(s):  
Natural Selection ◽  
Human Disease ◽  
Charles Darwin ◽  
Selection Process ◽  
Evolutionary Process ◽  
Computational Method ◽  
Evolutionary Changes ◽  
The Relationship ◽  
Medical Process ◽  
Multiple Antibiotics

The main aims of this review were to understand the roles of evolutionary process in human disease. The suffering of human from disease may be millions years ago and until now are continuing and the human disease can be classified into many types based on their sources such as bacterial, Genetics and viral. For the past sixty years the scientist carried out high number of experiment to understand   and the decision of the evolutionary process impact of the human disease. the main example of effect of evolution on the human health are using overuse of antibiotics against bacterial infection   and the results to the speedy evolution of bacteria that are resistant to multiple antibiotics such that even vancomycin. The process of natural selection which is proposed by Charles Darwin play vital roles in Biological and medical process and also helps to predict and find the relationship between natural selection process of evolution and phenotypical traits. Understanding the developmental and genetic underpinnings of unique evolutionary changes have been hindered by way of insufficient databases of evolutionary anatomy and through the lack of a computational method to become aware of underlying candidate genes and regulators to the developing o the process of the evolution with helps of other branches of modern sciences such as genetics, Bioinformatics, epidemiology, ecology, microbiology, molecular biology and biochemistry.

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