Designing a parallel evolutionary algorithm for inferring gene networks on the cloud computing environment

PubMed Central

2014-01-01

Background To improve the tedious task of reconstructing gene networks through testing experimentally the possible interactions between genes, it becomes a trend to adopt the automated reverse engineering procedure instead. Some evolutionary algorithms have been suggested for deriving network parameters. However, to infer large networks by the evolutionary algorithm, it is necessary to address two important issues: premature convergence and high computational cost. To tackle the former problem and to enhance the performance of traditional evolutionary algorithms, it is advisable to use parallel model evolutionary algorithms. To overcome the latter and to speed up the computation, it is advocated to adopt the mechanism of cloud computing as a promising solution: most popular is the method of MapReduce programming model, a fault-tolerant framework to implement parallel algorithms for inferring large gene networks. Results This work presents a practical framework to infer large gene networks, by developing and parallelizing a hybrid GA-PSO optimization method. Our parallel method is extended to work with the Hadoop MapReduce programming model and is executed in different cloud computing environments. To evaluate the proposed approach, we use a well-known open-source software GeneNetWeaver to create several yeast S. cerevisiae sub-networks and use them to produce gene profiles. Experiments have been conducted and the results have been analyzed. They show that our parallel approach can be successfully used to infer networks with desired behaviors and the computation time can be largely reduced. Conclusions Parallel population-based algorithms can effectively determine network parameters and they perform better than the widely-used sequential algorithms in gene network inference. These parallel algorithms can be distributed to the cloud computing environment to speed up the computation. By coupling the parallel model population-based optimization method and the parallel computational framework, high quality solutions can be obtained within relatively short time. This integrated approach is a promising way for inferring large networks. PMID:24428926

An efficient and accurate solution methodology for bilevel multi-objective programming problems using a hybrid evolutionary-local-search algorithm.

PubMed

Deb, Kalyanmoy; Sinha, Ankur

2010-01-01

Bilevel optimization problems involve two optimization tasks (upper and lower level), in which every feasible upper level solution must correspond to an optimal solution to a lower level optimization problem. These problems commonly appear in many practical problem solving tasks including optimal control, process optimization, game-playing strategy developments, transportation problems, and others. However, they are commonly converted into a single level optimization problem by using an approximate solution procedure to replace the lower level optimization task. Although there exist a number of theoretical, numerical, and evolutionary optimization studies involving single-objective bilevel programming problems, not many studies look at the context of multiple conflicting objectives in each level of a bilevel programming problem. In this paper, we address certain intricate issues related to solving multi-objective bilevel programming problems, present challenging test problems, and propose a viable and hybrid evolutionary-cum-local-search based algorithm as a solution methodology. The hybrid approach performs better than a number of existing methodologies and scales well up to 40-variable difficult test problems used in this study. The population sizing and termination criteria are made self-adaptive, so that no additional parameters need to be supplied by the user. The study indicates a clear niche of evolutionary algorithms in solving such difficult problems of practical importance compared to their usual solution by a computationally expensive nested procedure. The study opens up many issues related to multi-objective bilevel programming and hopefully this study will motivate EMO and other researchers to pay more attention to this important and difficult problem solving activity.

Artificial intelligence in peer review: How can evolutionary computation support journal editors?

PubMed Central

Fronczak, Piotr; Fronczak, Agata; Ausloos, Marcel; Nedic, Olgica

2017-01-01

With the volume of manuscripts submitted for publication growing every year, the deficiencies of peer review (e.g. long review times) are becoming more apparent. Editorial strategies, sets of guidelines designed to speed up the process and reduce editors’ workloads, are treated as trade secrets by publishing houses and are not shared publicly. To improve the effectiveness of their strategies, editors in small publishing groups are faced with undertaking an iterative trial-and-error approach. We show that Cartesian Genetic Programming, a nature-inspired evolutionary algorithm, can dramatically improve editorial strategies. The artificially evolved strategy reduced the duration of the peer review process by 30%, without increasing the pool of reviewers (in comparison to a typical human-developed strategy). Evolutionary computation has typically been used in technological processes or biological ecosystems. Our results demonstrate that genetic programs can improve real-world social systems that are usually much harder to understand and control than physical systems. PMID:28931033

Synthesis of Feedback Controller for Chaotic Systems by Means of Evolutionary Techniques

NASA Astrophysics Data System (ADS)

Senkerik, Roman; Oplatkova, Zuzana; Zelinka, Ivan; Davendra, Donald; Jasek, Roman

2011-06-01

This research deals with a synthesis of control law for three selected discrete chaotic systems by means of analytic programming. The novality of the approach is that a tool for symbolic regression—analytic programming—is used for such kind of difficult problem. The paper consists of the descriptions of analytic programming as well as chaotic systems and used cost function. For experimentation, Self-Organizing Migrating Algorithm (SOMA) with analytic programming was used.

Forecasting Caspian Sea level changes using satellite altimetry data (June 1992-December 2013) based on evolutionary support vector regression algorithms and gene expression programming

NASA Astrophysics Data System (ADS)

Imani, Moslem; You, Rey-Jer; Kuo, Chung-Yen

2014-10-01

Sea level forecasting at various time intervals is of great importance in water supply management. Evolutionary artificial intelligence (AI) approaches have been accepted as an appropriate tool for modeling complex nonlinear phenomena in water bodies. In the study, we investigated the ability of two AI techniques: support vector machine (SVM), which is mathematically well-founded and provides new insights into function approximation, and gene expression programming (GEP), which is used to forecast Caspian Sea level anomalies using satellite altimetry observations from June 1992 to December 2013. SVM demonstrates the best performance in predicting Caspian Sea level anomalies, given the minimum root mean square error (RMSE = 0.035) and maximum coefficient of determination (R2 = 0.96) during the prediction periods. A comparison between the proposed AI approaches and the cascade correlation neural network (CCNN) model also shows the superiority of the GEP and SVM models over the CCNN.

Automated discovery of local search heuristics for satisfiability testing.

PubMed

Fukunaga, Alex S

2008-01-01

The development of successful metaheuristic algorithms such as local search for a difficult problem such as satisfiability testing (SAT) is a challenging task. We investigate an evolutionary approach to automating the discovery of new local search heuristics for SAT. We show that several well-known SAT local search algorithms such as Walksat and Novelty are composite heuristics that are derived from novel combinations of a set of building blocks. Based on this observation, we developed CLASS, a genetic programming system that uses a simple composition operator to automatically discover SAT local search heuristics. New heuristics discovered by CLASS are shown to be competitive with the best Walksat variants, including Novelty+. Evolutionary algorithms have previously been applied to directly evolve a solution for a particular SAT instance. We show that the heuristics discovered by CLASS are also competitive with these previous, direct evolutionary approaches for SAT. We also analyze the local search behavior of the learned heuristics using the depth, mobility, and coverage metrics proposed by Schuurmans and Southey.

Support Vector Machines Trained with Evolutionary Algorithms Employing Kernel Adatron for Large Scale Classification of Protein Structures.

PubMed

Arana-Daniel, Nancy; Gallegos, Alberto A; López-Franco, Carlos; Alanís, Alma Y; Morales, Jacob; López-Franco, Adriana

2016-01-01

With the increasing power of computers, the amount of data that can be processed in small periods of time has grown exponentially, as has the importance of classifying large-scale data efficiently. Support vector machines have shown good results classifying large amounts of high-dimensional data, such as data generated by protein structure prediction, spam recognition, medical diagnosis, optical character recognition and text classification, etc. Most state of the art approaches for large-scale learning use traditional optimization methods, such as quadratic programming or gradient descent, which makes the use of evolutionary algorithms for training support vector machines an area to be explored. The present paper proposes an approach that is simple to implement based on evolutionary algorithms and Kernel-Adatron for solving large-scale classification problems, focusing on protein structure prediction. The functional properties of proteins depend upon their three-dimensional structures. Knowing the structures of proteins is crucial for biology and can lead to improvements in areas such as medicine, agriculture and biofuels.

Co-evolutionary data mining for fuzzy rules: automatic fitness function creation phase space, and experiments

NASA Astrophysics Data System (ADS)

Smith, James F., III; Blank, Joseph A.

2003-03-01

An approach is being explored that involves embedding a fuzzy logic based resource manager in an electronic game environment. Game agents can function under their own autonomous logic or human control. This approach automates the data mining problem. The game automatically creates a cleansed database reflecting the domain expert's knowledge, it calls a data mining function, a genetic algorithm, for data mining of the data base as required and allows easy evaluation of the information extracted. The co-evolutionary fitness functions, chromosomes and stopping criteria for ending the game are discussed. Genetic algorithm and genetic program based data mining procedures are discussed that automatically discover new fuzzy rules and strategies. The strategy tree concept and its relationship to co-evolutionary data mining are examined as well as the associated phase space representation of fuzzy concepts. The overlap of fuzzy concepts in phase space reduces the effective strategies available to adversaries. Co-evolutionary data mining alters the geometric properties of the overlap region known as the admissible region of phase space significantly enhancing the performance of the resource manager. Procedures for validation of the information data mined are discussed and significant experimental results provided.

Ignoring heterozygous sites biases phylogenomic estimates of divergence times: implications for the evolutionary history of microtus voles.

PubMed

Lischer, Heidi E L; Excoffier, Laurent; Heckel, Gerald

2014-04-01

Phylogenetic reconstruction of the evolutionary history of closely related organisms may be difficult because of the presence of unsorted lineages and of a relatively high proportion of heterozygous sites that are usually not handled well by phylogenetic programs. Genomic data may provide enough fixed polymorphisms to resolve phylogenetic trees, but the diploid nature of sequence data remains analytically challenging. Here, we performed a phylogenomic reconstruction of the evolutionary history of the common vole (Microtus arvalis) with a focus on the influence of heterozygosity on the estimation of intraspecific divergence times. We used genome-wide sequence information from 15 voles distributed across the European range. We provide a novel approach to integrate heterozygous information in existing phylogenetic programs by repeated random haplotype sampling from sequences with multiple unphased heterozygous sites. We evaluated the impact of the use of full, partial, or no heterozygous information for tree reconstructions on divergence time estimates. All results consistently showed four deep and strongly supported evolutionary lineages in the vole data. These lineages undergoing divergence processes split only at the end or after the last glacial maximum based on calibration with radiocarbon-dated paleontological material. However, the incorporation of information from heterozygous sites had a significant impact on absolute and relative branch length estimations. Ignoring heterozygous information led to an overestimation of divergence times between the evolutionary lineages of M. arvalis. We conclude that the exclusion of heterozygous sites from evolutionary analyses may cause biased and misleading divergence time estimates in closely related taxa.

Evolutionary Nephrology.

PubMed

Chevalier, Robert L

2017-05-01

Progressive kidney disease follows nephron loss, hyperfiltration, and incomplete repair, a process described as "maladaptive." In the past 20 years, a new discipline has emerged that expands research horizons: evolutionary medicine. In contrast to physiologic (homeostatic) adaptation, evolutionary adaptation is the result of reproductive success that reflects natural selection. Evolutionary explanations for physiologically maladaptive responses can emerge from mismatch of the phenotype with environment or evolutionary tradeoffs. Evolutionary adaptation to a terrestrial environment resulted in a vulnerable energy-consuming renal tubule and a hypoxic, hyperosmolar microenvironment. Natural selection favors successful energy investment strategy: energy is allocated to maintenance of nephron integrity through reproductive years, but this declines with increasing senescence after ~40 years of age. Risk factors for chronic kidney disease include restricted fetal growth or preterm birth (life history tradeoff resulting in fewer nephrons), evolutionary selection for APOL1 mutations (that provide resistance to trypanosome infection, a tradeoff), and modern life experience (Western diet mismatch leading to diabetes and hypertension). Current advances in genomics, epigenetics, and developmental biology have revealed proximate causes of kidney disease, but attempts to slow kidney disease remain elusive. Evolutionary medicine provides a complementary approach by addressing ultimate causes of kidney disease. Marked variation in nephron number at birth, nephron heterogeneity, and changing susceptibility to kidney injury throughout life history are the result of evolutionary processes. Combined application of molecular genetics, evolutionary developmental biology (evo-devo), developmental programming and life history theory may yield new strategies for prevention and treatment of chronic kidney disease.

An alternative approach for neural network evolution with a genetic algorithm: crossover by combinatorial optimization.

PubMed

García-Pedrajas, Nicolás; Ortiz-Boyer, Domingo; Hervás-Martínez, César

2006-05-01

In this work we present a new approach to crossover operator in the genetic evolution of neural networks. The most widely used evolutionary computation paradigm for neural network evolution is evolutionary programming. This paradigm is usually preferred due to the problems caused by the application of crossover to neural network evolution. However, crossover is the most innovative operator within the field of evolutionary computation. One of the most notorious problems with the application of crossover to neural networks is known as the permutation problem. This problem occurs due to the fact that the same network can be represented in a genetic coding by many different codifications. Our approach modifies the standard crossover operator taking into account the special features of the individuals to be mated. We present a new model for mating individuals that considers the structure of the hidden layer and redefines the crossover operator. As each hidden node represents a non-linear projection of the input variables, we approach the crossover as a problem on combinatorial optimization. We can formulate the problem as the extraction of a subset of near-optimal projections to create the hidden layer of the new network. This new approach is compared to a classical crossover in 25 real-world problems with an excellent performance. Moreover, the networks obtained are much smaller than those obtained with classical crossover operator.

An Agent-based Model for Groundwater Allocation and Management at the Bakken Shale in Western North Dakota

NASA Astrophysics Data System (ADS)

Lin, T.; Lin, Z.; Lim, S.

2017-12-01

We present an integrated modeling framework to simulate groundwater level change under the dramatic increase of hydraulic fracturing water use in the Bakken Shale oil production area. The framework combines the agent-based model (ABM) with the Fox Hills-Hell Creek (FH-HC) groundwater model. In development of the ABM, institution theory is used to model the regulation policies from the North Dakota State Water Commission, while evolutionary programming and cognitive maps are used to model the social structure that emerges from the behavior of competing individual water businesses. Evolutionary programming allows individuals to select an appropriate strategy when annually applying for potential water use permits; whereas cognitive maps endow agent's ability and willingness to compete for more water sales. All agents have their own influence boundaries that inhibit their competitive behavior toward their neighbors but not to non-neighbors. The decision-making process is constructed and parameterized with both quantitative and qualitative information, i.e., empirical water use data and knowledge gained from surveys with stakeholders. By linking institution theory, evolutionary programming, and cognitive maps, our approach addresses a higher complexity of the real decision making process. Furthermore, this approach is a new exploration for modeling the dynamics of Coupled Human and Natural System. After integrating ABM with the FH-HC model, drought and limited water accessibility scenarios are simulated to predict FH-HC ground water level changes in the future. The integrated modeling framework of ABM and FH-HC model can be used to support making scientifically sound policies in water allocation and management.

From the "Modern Synthesis" to cybernetics: Ivan Ivanovich Schmalhausen (1884-1963) and his research program for a synthesis of evolutionary and developmental biology.

PubMed

Levit, Georgy S; Hossfeld, Uwe; Olsson, Lennart

2006-03-15

Ivan I. Schmalhausen was one of the central figures in the Russian development of the "Modern Synthesis" in evolutionary biology. He is widely cited internationally even today. Schmalhausen developed the main principles of his theory facing the danger of death in the totalitarian Soviet Union. His great services to evolutionary and theoretical biology are indisputable. However, the received view of Schmalhausen's contributions to evolutionary biology makes an unbiased reading of his texts difficult. Here we show that taking all of his works into consideration (including those only available in Russian) paints a much more dynamic and exciting picture of what he tried to achieve. Schmalhausen pioneered the integration of a developmental perspective into evolutionary thinking. A main tool for achieving this was his approach to living objects as complex multi-level self-regulating systems. Schmalhausen put enormous effort into bringing this idea into fruition during the final stages of his career by combining evolutionary theory with cybernetics. His results and ideas remain thought-provoking, and his texts are of more than just historical interest. Copyright 2006 Wiley-Liss, Inc.

The ABCs of an evolutionary education science: The academic, behavioral, and cultural implications of an evolutionary approach to education theory and practice

NASA Astrophysics Data System (ADS)

Kauffman, Rick, Jr.

Calls for improving research-informed policy in education are everywhere. Yet, while there is an increasing trend towards science-based practice, there remains little agreement over which of the sciences to consult and how to organize a collective effort between them. What Education lacks is a general theoretical framework through which policies can be constructed, implemented, and assessed. This dissertation submits that evolutionary theory can provide a suitable framework for coordinating educational policies and practice, and can provide the entire field of education with a clearer sense of how to better manage the learning environment. This dissertation explores two broad paths that outline the conceptual foundations for an Evolutionary Education Science: "Teaching Evolution" and "Using Evolution to Teach." Chapter 1 introduces both of these themes. After describing why evolutionary science is best suited for organizing education research and practice, Chapter 1 proceeds to "teach" an overview of the "evolutionary toolkit"---the mechanisms and principles that underlie the modern evolutionary perspective. The chapter then employs the "toolkit" in examining education from an evolutionary perspective, outlining the evolutionary precepts that can guide theorizing and research in education, describing how educators can "use evolution to teach.". Chapters 2-4 expand on this second theme. Chapters 2 and 3 describe an education program for at-risk 9th and 10th grade students, the Regents Academy, designed entirely with evolutionary principles in mind. The program was rigorously assessed in a randomized control design and has demonstrated success at improving students' academic performance (Chapter 2) and social & behavioral development (Chapter 3). Chapter 4 examines current teaching strategies that underlie effective curriculum-instruction-assessment practices and proposes a framework for organizing successful, evidence-based strategies for neural-/cognitive-focused learning goals. Chapter 5 explores the cognitive effects that "teaching evolution" has on the learner. This chapter examines the effects that a course on evolutionary theory has on university undergraduate students in understanding and applying evolution and how learning the evolutionary toolkit affects critical thinking skills and domain transfer of knowledge. The results demonstrate that a single course on evolutionary theory increases students' acceptance and understanding of evolution and science, and, in effect, increases critical thinking performance.

Efficient Allocation of Resources for Defense of Spatially Distributed Networks Using Agent-Based Simulation.

PubMed

Kroshl, William M; Sarkani, Shahram; Mazzuchi, Thomas A

2015-09-01

This article presents ongoing research that focuses on efficient allocation of defense resources to minimize the damage inflicted on a spatially distributed physical network such as a pipeline, water system, or power distribution system from an attack by an active adversary, recognizing the fundamental difference between preparing for natural disasters such as hurricanes, earthquakes, or even accidental systems failures and the problem of allocating resources to defend against an opponent who is aware of, and anticipating, the defender's efforts to mitigate the threat. Our approach is to utilize a combination of integer programming and agent-based modeling to allocate the defensive resources. We conceptualize the problem as a Stackelberg "leader follower" game where the defender first places his assets to defend key areas of the network, and the attacker then seeks to inflict the maximum damage possible within the constraints of resources and network structure. The criticality of arcs in the network is estimated by a deterministic network interdiction formulation, which then informs an evolutionary agent-based simulation. The evolutionary agent-based simulation is used to determine the allocation of resources for attackers and defenders that results in evolutionary stable strategies, where actions by either side alone cannot increase its share of victories. We demonstrate these techniques on an example network, comparing the evolutionary agent-based results to a more traditional, probabilistic risk analysis (PRA) approach. Our results show that the agent-based approach results in a greater percentage of defender victories than does the PRA-based approach. © 2015 Society for Risk Analysis.

Evolution of apoptosis-like programmed cell death in unicellular protozoan parasites.

PubMed

Kaczanowski, Szymon; Sajid, Mohammed; Reece, Sarah E

2011-03-25

Apoptosis-like programmed cell death (PCD) has recently been described in multiple taxa of unicellular protists, including the protozoan parasites Plasmodium, Trypanosoma and Leishmania. Apoptosis-like PCD in protozoan parasites shares a number of morphological features with programmed cell death in multicellular organisms. However, both the evolutionary explanations and mechanisms involved in parasite PCD are poorly understood. Explaining why unicellular organisms appear to undergo 'suicide' is a challenge for evolutionary biology and uncovering death executors and pathways is a challenge for molecular and cell biology. Bioinformatics has the potential to integrate these approaches by revealing homologies in the PCD machinery of diverse taxa and evaluating their evolutionary trajectories. As the molecular mechanisms of apoptosis in model organisms are well characterised, and recent data suggest similar mechanisms operate in protozoan parasites, key questions can now be addressed. These questions include: which elements of apoptosis machinery appear to be shared between protozoan parasites and multicellular taxa and, have these mechanisms arisen through convergent or divergent evolution? We use bioinformatics to address these questions and our analyses suggest that apoptosis mechanisms in protozoan parasites and other taxa have diverged during their evolution, that some apoptosis factors are shared across taxa whilst others have been replaced by proteins with similar biochemical activities.

Evolution of apoptosis-like programmed cell death in unicellular protozoan parasites

PubMed Central

2011-01-01

Apoptosis-like programmed cell death (PCD) has recently been described in multiple taxa of unicellular protists, including the protozoan parasites Plasmodium, Trypanosoma and Leishmania. Apoptosis-like PCD in protozoan parasites shares a number of morphological features with programmed cell death in multicellular organisms. However, both the evolutionary explanations and mechanisms involved in parasite PCD are poorly understood. Explaining why unicellular organisms appear to undergo 'suicide' is a challenge for evolutionary biology and uncovering death executors and pathways is a challenge for molecular and cell biology. Bioinformatics has the potential to integrate these approaches by revealing homologies in the PCD machinery of diverse taxa and evaluating their evolutionary trajectories. As the molecular mechanisms of apoptosis in model organisms are well characterised, and recent data suggest similar mechanisms operate in protozoan parasites, key questions can now be addressed. These questions include: which elements of apoptosis machinery appear to be shared between protozoan parasites and multicellular taxa and, have these mechanisms arisen through convergent or divergent evolution? We use bioinformatics to address these questions and our analyses suggest that apoptosis mechanisms in protozoan parasites and other taxa have diverged during their evolution, that some apoptosis factors are shared across taxa whilst others have been replaced by proteins with similar biochemical activities. PMID:21439063

PBTE (Performance-Based Teacher Education); Vol 2, No, 2, May 1973.

ERIC Educational Resources Information Center

Andrews, Theodore E., Ed.

This issue of the Multi-State Consortium for Performance-Based Teacher Education (PBTE) newsletter discusses (1) the evolutionary approach adopted by the state of Minnesota toward the implementation of PBTE, which includes discussion of what is known about PBTE, whether Minnesota ought (or wishes) to adopt the program, and state participation in…

Space and transatmospheric propulsion technology

NASA Technical Reports Server (NTRS)

Merkle, Charles; Stangeland, Maynard L.; Brown, James R.; Mccarty, John P.; Povinelli, Louis A.; Northam, G. Burton; Zukoski, Edward E.

1994-01-01

This report focuses primarily on Japan's programs in liquid rocket propulsion and propulsion for spaceplane and related transatmospheric areas. It refers briefly to Japan's solid rocket programs and to new supersonic air-breathing propulsion efforts. The panel observed that the Japanese had a carefully thought-out plan, a broad-based program, and an ambitious but achievable schedule for propulsion activity. Japan's overall propulsion program is behind that of the United States at the time of this study, but the Japanese are gaining rapidly. The Japanese are at the forefront in such key areas as advanced materials, enjoying a high level of project continuity and funding. Japan's space program has been evolutionary in nature, while the U.S. program has emphasized revolutionary advances. Projects have typically been smaller in Japan than in the United States, focusing on incremental advances in technology, with an excellent record of applying proven technology to new projects. This evolutionary approach, coupled with an ability to take technology off the shelf from other countries, has resulted in relatively low development costs, rapid progress, and enhanced reliability. Clearly Japan is positioned to be a world leader in space and transatmospheric propulsion technology by the year 2000.

Detecting and Analyzing Genetic Recombination Using RDP4.

PubMed

Martin, Darren P; Murrell, Ben; Khoosal, Arjun; Muhire, Brejnev

2017-01-01

Recombination between nucleotide sequences is a major process influencing the evolution of most species on Earth. The evolutionary value of recombination has been widely debated and so too has its influence on evolutionary analysis methods that assume nucleotide sequences replicate without recombining. When nucleic acids recombine, the evolution of the daughter or recombinant molecule cannot be accurately described by a single phylogeny. This simple fact can seriously undermine the accuracy of any phylogenetics-based analytical approach which assumes that the evolutionary history of a set of recombining sequences can be adequately described by a single phylogenetic tree. There are presently a large number of available methods and associated computer programs for analyzing and characterizing recombination in various classes of nucleotide sequence datasets. Here we examine the use of some of these methods to derive and test recombination hypotheses using multiple sequence alignments.

Orbital transfer vehicle concept definition and system analysis study, 1985. Volume 3: System and program trades

NASA Technical Reports Server (NTRS)

Nelson, James H.; Mohrman, Gordon W.; Callan, Daniel R.

1986-01-01

The key system and program trade studies performed to arrive at a preferred Orbital Transfer Vehicle (OTV) system concept and evolutionary approach to the acquisition of the requisite capabilites is documented. These efforts were expanded to encompass a Space Transportation Architecture Study (STAS) mission model and recommended unmanned cargo vehicle. The most important factors affecting the results presented are the mission model requirements and selection criteria. The reason for conducting the OTV concept definition and system analyses study is to select a concept and acquisition approach that meets a delivery requirement reflected by the mission model.

Evolutionary use of nuclear electric propulsion

NASA Technical Reports Server (NTRS)

Hack, K. J.; George, J. A.; Riehl, J. P.; Gilland, J. H.

1990-01-01

Evolving new propulsion technologies through a rational and conscious effort to minimize development costs and program risks while maximizing the performance benefits is intuitively practical. A phased approach to the evolution of nuclear electric propulsion from use on planetary probes, to lunar cargo vehicles, and finally to manned Mars missions with a concomitant growth in technology is considered. Technology levels and system component makeup are discussed for nuclear power systems and both ion and magnetoplasmadynamic thrusters. Mission scenarios are described, which include analysis of a probe to Pluto, a lunar cargo mission, Martian split, all-up, and quick-trip mission options. Evolutionary progression of the use of NEP in such missions is discussed.

Theoretical Approaches in Evolutionary Ecology: Environmental Feedback as a Unifying Perspective.

PubMed

Lion, Sébastien

2018-01-01

Evolutionary biology and ecology have a strong theoretical underpinning, and this has fostered a variety of modeling approaches. A major challenge of this theoretical work has been to unravel the tangled feedback loop between ecology and evolution. This has prompted the development of two main classes of models. While quantitative genetics models jointly consider the ecological and evolutionary dynamics of a focal population, a separation of timescales between ecology and evolution is assumed by evolutionary game theory, adaptive dynamics, and inclusive fitness theory. As a result, theoretical evolutionary ecology tends to be divided among different schools of thought, with different toolboxes and motivations. My aim in this synthesis is to highlight the connections between these different approaches and clarify the current state of theory in evolutionary ecology. Central to this approach is to make explicit the dependence on environmental dynamics of the population and evolutionary dynamics, thereby materializing the eco-evolutionary feedback loop. This perspective sheds light on the interplay between environmental feedback and the timescales of ecological and evolutionary processes. I conclude by discussing some potential extensions and challenges to our current theoretical understanding of eco-evolutionary dynamics.

The Comet Cometh: Evolving Developmental Systems.

PubMed

Jaeger, Johannes; Laubichler, Manfred; Callebaut, Werner

In a recent opinion piece, Denis Duboule has claimed that the increasing shift towards systems biology is driving evolutionary and developmental biology apart, and that a true reunification of these two disciplines within the framework of evolutionary developmental biology (EvoDevo) may easily take another 100 years. He identifies methodological, epistemological, and social differences as causes for this supposed separation. Our article provides a contrasting view. We argue that Duboule's prediction is based on a one-sided understanding of systems biology as a science that is only interested in functional, not evolutionary, aspects of biological processes. Instead, we propose a research program for an evolutionary systems biology, which is based on local exploration of the configuration space in evolving developmental systems. We call this approach-which is based on reverse engineering, simulation, and mathematical analysis-the natural history of configuration space. We discuss a number of illustrative examples that demonstrate the past success of local exploration, as opposed to global mapping, in different biological contexts. We argue that this pragmatic mode of inquiry can be extended and applied to the mathematical analysis of the developmental repertoire and evolutionary potential of evolving developmental mechanisms and that evolutionary systems biology so conceived provides a pragmatic epistemological framework for the EvoDevo synthesis.

Toward understanding the evolution of vertebrate gene regulatory networks: comparative genomics and epigenomic approaches.

PubMed

Martinez-Morales, Juan R

2016-07-01

Vertebrates, as most animal phyla, originated >500 million years ago during the Cambrian explosion, and progressively radiated into the extant classes. Inferring the evolutionary history of the group requires understanding the architecture of the developmental programs that constrain the vertebrate anatomy. Here, I review recent comparative genomic and epigenomic studies, based on ChIP-seq and chromatin accessibility, which focus on the identification of functionally equivalent cis-regulatory modules among species. This pioneer work, primarily centered in the mammalian lineage, has set the groundwork for further studies in representative vertebrate and chordate species. Mapping of active regulatory regions across lineages will shed new light on the evolutionary forces stabilizing ancestral developmental programs, as well as allowing their variation to sustain morphological adaptations on the inherited vertebrate body plan. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Fear and Loving in Las Vegas: Evolution, Emotion, and Persuasion.

PubMed

Griskevicius, Vladas; Goldstein, Noah J; Mortensen, Chad R; Sundie, Jill M; Cialdini, Robert B; Kenrick, Douglas T

2009-06-01

How do arousal-inducing contexts, such as frightening or romantic television programs, influence the effectiveness of basic persuasion heuristics? Different predictions are made by three theoretical models: A general arousal model predicts that arousal should increase effectiveness of heuristics; an affective valence model predicts that effectiveness should depend on whether the context elicits positive or negative affect; an evolutionary model predicts that persuasiveness should depend on both the specific emotion that is elicited and the content of the particular heuristic. Three experiments examined how fear-inducing versus romantic contexts influenced the effectiveness of two widely used heuristics-social proof (e.g., "most popular") and scarcity (e.g., "limited edition"). Results supported predictions from an evolutionary model, showing that fear can lead scarcity appeals to be counter-persuasive, and that romantic desire can lead social proof appeals to be counter-persuasive. The findings highlight how an evolutionary theoretical approach can lead to novel theoretical and practical marketing insights.

Available Transfer Capability Determination Using Hybrid Evolutionary Algorithm

NASA Astrophysics Data System (ADS)

Jirapong, Peeraool; Ongsakul, Weerakorn

2008-10-01

This paper proposes a new hybrid evolutionary algorithm (HEA) based on evolutionary programming (EP), tabu search (TS), and simulated annealing (SA) to determine the available transfer capability (ATC) of power transactions between different control areas in deregulated power systems. The optimal power flow (OPF)-based ATC determination is used to evaluate the feasible maximum ATC value within real and reactive power generation limits, line thermal limits, voltage limits, and voltage and angle stability limits. The HEA approach simultaneously searches for real power generations except slack bus in a source area, real power loads in a sink area, and generation bus voltages to solve the OPF-based ATC problem. Test results on the modified IEEE 24-bus reliability test system (RTS) indicate that ATC determination by the HEA could enhance ATC far more than those from EP, TS, hybrid TS/SA, and improved EP (IEP) algorithms, leading to an efficient utilization of the existing transmission system.

Turbopump Performance Improved by Evolutionary Algorithms

NASA Technical Reports Server (NTRS)

Oyama, Akira; Liou, Meng-Sing

2002-01-01

The development of design optimization technology for turbomachinery has been initiated using the multiobjective evolutionary algorithm under NASA's Intelligent Synthesis Environment and Revolutionary Aeropropulsion Concepts programs. As an alternative to the traditional gradient-based methods, evolutionary algorithms (EA's) are emergent design-optimization algorithms modeled after the mechanisms found in natural evolution. EA's search from multiple points, instead of moving from a single point. In addition, they require no derivatives or gradients of the objective function, leading to robustness and simplicity in coupling any evaluation codes. Parallel efficiency also becomes very high by using a simple master-slave concept for function evaluations, since such evaluations often consume the most CPU time, such as computational fluid dynamics. Application of EA's to multiobjective design problems is also straightforward because EA's maintain a population of design candidates in parallel. Because of these advantages, EA's are a unique and attractive approach to real-world design optimization problems.

Using Evolutionary Theory to Guide Mental Health Research.

PubMed

Durisko, Zachary; Mulsant, Benoit H; McKenzie, Kwame; Andrews, Paul W

2016-03-01

Evolutionary approaches to medicine can shed light on the origins and etiology of disease. Such an approach may be especially useful in psychiatry, which frequently addresses conditions with heterogeneous presentation and unknown causes. We review several previous applications of evolutionary theory that highlight the ways in which psychiatric conditions may persist despite and because of natural selection. One lesson from the evolutionary approach is that some conditions currently classified as disorders (because they cause distress and impairment) may actually be caused by functioning adaptations operating "normally" (as designed by natural selection). Such conditions suggest an alternative illness model that may generate alternative intervention strategies. Thus, the evolutionary approach suggests that psychiatry should sometimes think differently about distress and impairment. The complexity of the human brain, including normal functioning and potential for dysfunctions, has developed over evolutionary time and has been shaped by natural selection. Understanding the evolutionary origins of psychiatric conditions is therefore a crucial component to a complete understanding of etiology. © The Author(s) 2016.

Using Evolutionary Theory to Guide Mental Health Research

PubMed Central

Mulsant, Benoit H.; McKenzie, Kwame; Andrews, Paul W.

2016-01-01

Evolutionary approaches to medicine can shed light on the origins and etiology of disease. Such an approach may be especially useful in psychiatry, which frequently addresses conditions with heterogeneous presentation and unknown causes. We review several previous applications of evolutionary theory that highlight the ways in which psychiatric conditions may persist despite and because of natural selection. One lesson from the evolutionary approach is that some conditions currently classified as disorders (because they cause distress and impairment) may actually be caused by functioning adaptations operating “normally” (as designed by natural selection). Such conditions suggest an alternative illness model that may generate alternative intervention strategies. Thus, the evolutionary approach suggests that psychiatry should sometimes think differently about distress and impairment. The complexity of the human brain, including normal functioning and potential for dysfunctions, has developed over evolutionary time and has been shaped by natural selection. Understanding the evolutionary origins of psychiatric conditions is therefore a crucial component to a complete understanding of etiology. PMID:27254091

The Simulation and Analysis of an Evolutionary Model of Deoxyribonucleic Acid (DNA).

DTIC Science & Technology

1983-09-01

current interest in evolutionary biology . This section identifies the organization of the remainder of the paper. The second chapter reports the...the field of evolutionary biology . 77 APPENDIX 78 APPENDIX A PROGRAM SOURCE LISTING -79 PROGRAM SOURCE LISTING 00005 PROGRAM (COMPUTERANDOM MUTATIONS...34Some Theoretical Aspects of the Problem of Life Origin," Journal 2f Theoreical Biology : 13-23, 1975. 27. Chirpich, Thomas P. "Rates of Protein

Moglichkeiten und Grenzen eines evolutionaren Paradigmas in der Erziehungswissenschaft (Possibilities and Limits of an Evolutionary Paradigm in Educational Science).

ERIC Educational Resources Information Center

Nipkow, Karl Ernst

2002-01-01

Describes a sectoral and paradigmatic approach to evolutionary research. Argues that an evolutionary paradigm does not exist. Examines the socio-biological approach and that of a system-theoretical oriented general evolutionary theory. Utilizes the topics of cooperation, delimitation, and indoctrination to explain more promising ways of adoption.…

Social insects: from selfish genes to self organisation and beyond.

PubMed

Boomsma, Jacobus J; Franks, Nigel R

2006-06-01

Selfish gene and self-organisation approaches have revolutionised the study of social insects and have provided unparalleled insights into the highly sophisticated nature of insect social evolution. Here, we briefly review the core programs and interfaces with communication and recognition studies that characterise these fields today, and offer an interdisciplinary future perspective for the study of social insect evolutionary biology.

Algorithmic Trading with Developmental and Linear Genetic Programming

NASA Astrophysics Data System (ADS)

Wilson, Garnett; Banzhaf, Wolfgang

A developmental co-evolutionary genetic programming approach (PAM DGP) and a standard linear genetic programming (LGP) stock trading systemare applied to a number of stocks across market sectors. Both GP techniques were found to be robust to market fluctuations and reactive to opportunities associated with stock price rise and fall, with PAMDGP generating notably greater profit in some stock trend scenarios. Both algorithms were very accurate at buying to achieve profit and selling to protect assets, while exhibiting bothmoderate trading activity and the ability to maximize or minimize investment as appropriate. The content of the trading rules produced by both algorithms are also examined in relation to stock price trend scenarios.

An evolutionary perspective on health psychology: new approaches and applications.

PubMed

Tybur, Joshua M; Bryan, Angela D; Hooper, Ann E Caldwell

2012-12-20

Although health psychologists' efforts to understand and promote health are most effective when guided by theory, health psychology has not taken full advantage of theoretical insights provided by evolutionary psychology. Here, we argue that evolutionary perspectives can fruitfully inform strategies for addressing some of the challenges facing health psychologists. Evolutionary psychology's emphasis on modular, functionally specialized psychological systems can inform approaches to understanding the myriad behaviors grouped under the umbrella of "health," as can theoretical perspectives used by evolutionary anthropologists, biologists, and psychologists (e.g., Life History Theory). We detail some early investigations into evolutionary health psychology, and we provide suggestions for directions for future research.

SHARP's systems engineering challenge: rectifying integrated product team requirements with performance issues in an evolutionary spiral development acquisition

NASA Astrophysics Data System (ADS)

Kuehl, C. Stephen

2003-08-01

Completing its final development and early deployment on the Navy's multi-role aircraft, the F/A-18 E/F Super Hornet, the SHAred Reconnaissance Pod (SHARP) provides the war fighter with the latest digital tactical reconnaissance (TAC Recce) Electro-Optical/Infrared (EO/IR) sensor system. The SHARP program is an evolutionary acquisition that used a spiral development process across a prototype development phase tightly coupled into overlapping Engineering and Manufacturing Development (EMD) and Low Rate Initial Production (LRIP) phases. Under a tight budget environment with a highly compressed schedule, SHARP challenged traditional acquisition strategies and systems engineering (SE) processes. Adopting tailored state-of-the-art systems engineering process models allowd the SHARP program to overcome the technical knowledge transition challenges imposed by a compressed program schedule. The program's original goal was the deployment of digital TAC Recce mission capabilities to the fleet customer by summer of 2003. Hardware and software integration technical challenges resulted from requirements definition and analysis activities performed across a government-industry led Integrated Product Team (IPT) involving Navy engineering and test sites, Boeing, and RTSC-EPS (with its subcontracted hardware and government furnished equipment vendors). Requirements development from a bottoms-up approach was adopted using an electronic requirements capture environment to clarify and establish the SHARP EMD product baseline specifications as relevant technical data became available. Applying Earned-Value Management (EVM) against an Integrated Master Schedule (IMS) resulted in efficiently managing SE task assignments and product deliveries in a dynamically evolving customer requirements environment. Application of Six Sigma improvement methodologies resulted in the uncovering of root causes of errors in wiring interconnectivity drawings, pod manufacturing processes, and avionics requirements specifications. Utilizing the draft NAVAIR SE guideline handbook and the ANSI/EIA-632 standard: Processes for Engineering a System, a systems engineering tailored process approach was adopted for the accelerated SHARP EMD prgram. Tailoring SE processes in this accelerated product delivery environment provided unique opportunities to be technically creative in the establishment of a product performance baseline. This paper provides an historical overview of the systems engineering activities spanning the prototype phase through the EMD SHARP program phase, the performance requirement capture activities and refinement process challenges, and what SE process improvements can be applied to future SHARP-like programs adopting a compressed, evolutionary spiral development acquisition paradigm.

Evolution of Aging Theories: Why Modern Programmed Aging Concepts Are Transforming Medical Research.

PubMed

Goldsmith, Theodore C

2016-12-01

Programmed aging refers to the idea that senescence in humans and other organisms is purposely caused by evolved biological mechanisms to obtain an evolutionary advantage. Until recently, programmed aging was considered theoretically impossible because of the mechanics of the evolution process, and medical research was based on the idea that aging was not programmed. Theorists struggled for more than a century in efforts to develop non-programmed theories that fit observations, without obtaining a consensus supporting any non-programmed theory. Empirical evidence of programmed lifespan limitations continued to accumulate. More recently, developments, especially in our understanding of biological inheritance, have exposed major issues and complexities regarding the process of evolution, some of which explicitly enable programmed aging of mammals. Consequently, science-based opposition to programmed aging has dramatically declined. This progression has major implications for medical research, because the theories suggest that very different biological mechanisms are ultimately responsible for highly age-related diseases that now represent most research efforts and health costs. Most particularly, programmed theories suggest that aging per se is a treatable condition and suggest a second path toward treating and preventing age-related diseases that can be exploited in addition to the traditional disease-specific approaches. The theories also make predictions regarding the nature of biological aging mechanisms and therefore suggest research directions. This article discusses developments of evolutionary mechanics, the consequent programmed aging theories, and logical inferences concerning biological aging mechanisms. It concludes that major medical research organizations cannot afford to ignore programmed aging concepts in assigning research resources and directions.

Hybrid Genetic Agorithms and Line Search Method for Industrial Production Planning with Non-Linear Fitness Function

NASA Astrophysics Data System (ADS)

Vasant, Pandian; Barsoum, Nader

2008-10-01

Many engineering, science, information technology and management optimization problems can be considered as non linear programming real world problems where the all or some of the parameters and variables involved are uncertain in nature. These can only be quantified using intelligent computational techniques such as evolutionary computation and fuzzy logic. The main objective of this research paper is to solve non linear fuzzy optimization problem where the technological coefficient in the constraints involved are fuzzy numbers which was represented by logistic membership functions by using hybrid evolutionary optimization approach. To explore the applicability of the present study a numerical example is considered to determine the production planning for the decision variables and profit of the company.

Dynamic multipopulation and density dependent evolutionary games related to replicator dynamics. A metasimplex concept.

PubMed

Argasinski, Krzysztof

2006-07-01

This paper contains the basic extensions of classical evolutionary games (multipopulation and density dependent models). It is shown that classical bimatrix approach is inconsistent with other approaches because it does not depend on proportion between populations. The main conclusion is that interspecific proportion parameter is important and must be considered in multipopulation models. The paper provides a synthesis of both extensions (a metasimplex concept) which solves the problem intrinsic in the bimatrix model. It allows us to model interactions among any number of subpopulations including density dependence effects. We prove that all modern approaches to evolutionary games are closely related. All evolutionary models (except classical bimatrix approaches) can be reduced to a single population general model by a simple change of variables. Differences between classic bimatrix evolutionary games and a new model which is dependent on interspecific proportion are shown by examples.

[The history of development of evolutionary methods in St. Petersburg school of computer simulation in biology].

PubMed

Menshutkin, V V; Kazanskiĭ, A B; Levchenko, V F

2010-01-01

The history of rise and development of evolutionary methods in Saint Petersburg school of biological modelling is traced and analyzed. Some pioneering works in simulation of ecological and evolutionary processes, performed in St.-Petersburg school became an exemplary ones for many followers in Russia and abroad. The individual-based approach became the crucial point in the history of the school as an adequate instrument for construction of models of biological evolution. This approach is natural for simulation of the evolution of life-history parameters and adaptive processes in populations and communities. In some cases simulated evolutionary process was used for solving a reverse problem, i. e., for estimation of uncertain life-history parameters of population. Evolutionary computations is one more aspect of this approach application in great many fields. The problems and vistas of ecological and evolutionary modelling in general are discussed.

Fear and Loving in Las Vegas: Evolution, Emotion, and Persuasion

PubMed Central

Griskevicius, Vladas; Goldstein, Noah J.; Mortensen, Chad R.; Sundie, Jill M.; Cialdini, Robert B.; Kenrick, Douglas T.

2009-01-01

How do arousal-inducing contexts, such as frightening or romantic television programs, influence the effectiveness of basic persuasion heuristics? Different predictions are made by three theoretical models: A general arousal model predicts that arousal should increase effectiveness of heuristics; an affective valence model predicts that effectiveness should depend on whether the context elicits positive or negative affect; an evolutionary model predicts that persuasiveness should depend on both the specific emotion that is elicited and the content of the particular heuristic. Three experiments examined how fear-inducing versus romantic contexts influenced the effectiveness of two widely used heuristics—social proof (e.g., “most popular”) and scarcity (e.g., “limited edition”). Results supported predictions from an evolutionary model, showing that fear can lead scarcity appeals to be counter-persuasive, and that romantic desire can lead social proof appeals to be counter-persuasive. The findings highlight how an evolutionary theoretical approach can lead to novel theoretical and practical marketing insights. PMID:19727416

Knowing the natural world: The construction of knowledge about evolution in and out of the classroom

NASA Astrophysics Data System (ADS)

Perkins, Alison Emily Havard

Evolution is a central underlying concept to a significant number of discourses in civilized society, but the complexity of understanding basic tenets of this important theory is just now coming to light. Knowledge about evolution is constructed from both formal and "free-choice" opportunities, like television. Nature programs are commonly considered "educational" by definition, but research indicates the narratives often promote creationist ideas about this important process in biology. I explored how nature programs influenced knowledge construction about evolutionary theory using a combination of qualitative and quantitative approaches. Because misconceptions about evolution are common, I examined how students' conceptual ecologies changed in response to information presented in an example of a particularly poor nature film narrative. Students' held a diversity of misconceptions, proximate conceptions, and evolutionary conceptions simultaneously, and many of their responses were direct reflections of the nature program. As a result, I incorporated the same nature program into an experiment designed to examine the effects of narrative and imagery on evolution understanding. After completing an extensive pre-assessment that addressed attitudes and beliefs about science knowledge, students viewed one of four versions of the nature program that varied in the quality of science and imagery presented. The effect of watching different versions was only vaguely apparent in students with a moderate understanding of evolution. The relationship was much more complex among students with a poor understanding of evolution but suggested a negative effect that was more influenced by public discourses about this "controversial" subject than conceptual understanding. The relationships warranted examining learning from the perspective of the consumers of these programs. I surveyed audience beliefs about the educational value of nature programs and found that an overwhelming majority believed the programs were "educational" and designed to teach about nature. The results were particularly alarming because beliefs about the educational value may strongly impact learning outcomes. An informal survey of nature programs aired during a "sweeps" month indicated that poor presentation of science, and specifically evolutionary theory, was indeed the norm. Indeed, nature programs may be contributing to the "deconstruction" of knowledge about evolution both in and out of the classroom.

Reframing developmental biology and building evolutionary theory's new synthesis.

PubMed

Tauber, Alfred I

2010-01-01

Gilbert and Epel present a new approach to developmental biology: embryogenesis must be understood within the full context of the organism's environment. Instead of an insular embryo following a genetic blueprint, this revised program maintains that embryogenesis is subject to inputs from the environment that generate novel genetic variation with dynamic consequences for development. Beyond allelic variation of structural genes and of regulatory loci, plasticity-derived epigenetic variation completes the triad of the major types of variation required for evolution. Developmental biology and ecology, disciplines that have previously been regarded as distinct, are presented here as fully integrated under the rubric of "eco-devo," and from this perspective, which highlights how the environment not only selects variation, it helps construct it, another synthesis with evolutionary biology must also be made, "eco-evo-devo." This second integration has enormous implications for expanding evolution theory, inasmuch as the Modern Synthesis (Provine 1971), which combined classical genetics and Darwinism in the mid-20th century, did not account for the role of development in evolution. The eco-evo-devo synthesis thus portends a major theoretical inflection in evolutionary biology. Following a description of these scientific developments, comment is offered as to how this new integrated approach might be understood within the larger shifts in contemporary biology.

Evolution of Autonomous Self-Righting Behaviors for Articulated Nanorovers

NASA Technical Reports Server (NTRS)

Tunstel, Edward

1999-01-01

Miniature rovers with articulated mobility mechanisms are being developed for planetary surface exploration on Mars and small solar system bodies. These vehicles are designed to be capable of autonomous recovery from overturning during surface operations. This paper describes a computational means of developing motion behaviors that achieve the autonomous recovery function. It proposes a control software design approach aimed at reducing the effort involved in developing self-righting behaviors. The approach is based on the integration of evolutionary computing with a dynamics simulation environment for evolving and evaluating motion behaviors. The automated behavior design approach is outlined and its underlying genetic programming infrastructure is described.

An evolutionary game approach for determination of the structural conflicts in signed networks

PubMed Central

Tan, Shaolin; Lü, Jinhu

2016-01-01

Social or biochemical networks can often divide into two opposite alliances in response to structural conflicts between positive (friendly, activating) and negative (hostile, inhibiting) interactions. Yet, the underlying dynamics on how the opposite alliances are spontaneously formed to minimize the structural conflicts is still unclear. Here, we demonstrate that evolutionary game dynamics provides a felicitous possible tool to characterize the evolution and formation of alliances in signed networks. Indeed, an evolutionary game dynamics on signed networks is proposed such that each node can adaptively adjust its choice of alliances to maximize its own fitness, which yet leads to a minimization of the structural conflicts in the entire network. Numerical experiments show that the evolutionary game approach is universally efficient in quality and speed to find optimal solutions for all undirected or directed, unweighted or weighted signed networks. Moreover, the evolutionary game approach is inherently distributed. These characteristics thus suggest the evolutionary game dynamic approach as a feasible and effective tool for determining the structural conflicts in large-scale on-line signed networks. PMID:26915581

Adapting legume crops to climate change using genomic approaches.

PubMed

Mousavi-Derazmahalleh, Mahsa; Bayer, Philipp E; Hane, James K; Valliyodan, Babu; Nguyen, Henry T; Nelson, Matthew N; Erskine, William; Varshney, Rajeev K; Papa, Roberto; Edwards, David

2018-03-30

Our agricultural system and hence food security is threatened by combination of events, such as increasing population, the impacts of climate change, and the need to a more sustainable development. Evolutionary adaptation may help some species to overcome environmental changes through new selection pressures driven by climate change. However, success of evolutionary adaptation is dependent on various factors, one of which is the extent of genetic variation available within species. Genomic approaches provide an exceptional opportunity to identify genetic variation that can be employed in crop improvement programs. In this review, we illustrate some of the routinely used genomics-based methods as well as recent breakthroughs, which facilitate assessment of genetic variation and discovery of adaptive genes in legumes. Although additional information is needed, the current utility of selection tools indicate a robust ability to utilize existing variation among legumes to address the challenges of climate uncertainty. © 2018 The Authors. Plant, Cell & Environment Published by John Wiley & Sons Ltd.

Integrated Controls-Structures Design Methodology: Redesign of an Evolutionary Test Structure

NASA Technical Reports Server (NTRS)

Maghami, Peiman G.; Gupta, Sandeep; Elliot, Kenny B.; Joshi, Suresh M.

1997-01-01

An optimization-based integrated controls-structures design methodology for a class of flexible space structures is described, and the phase-0 Controls-Structures-Integration evolutionary model, a laboratory testbed at NASA Langley, is redesigned using this integrated design methodology. The integrated controls-structures design is posed as a nonlinear programming problem to minimize the control effort required to maintain a specified line-of-sight pointing performance, under persistent white noise disturbance. Static and dynamic dissipative control strategies are employed for feedback control, and parameters of these controllers are considered as the control design variables. Sizes of strut elements in various sections of the CEM are used as the structural design variables. Design guides for the struts are developed and employed in the integrated design process, to ensure that the redesigned structure can be effectively fabricated. The superiority of the integrated design methodology over the conventional design approach is demonstrated analytically by observing a significant reduction in the average control power needed to maintain specified pointing performance with the integrated design approach.

Comparing Evolutionary Programs and Evolutionary Pattern Search Algorithms: A Drug Docking Application

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hart, W.E.

1999-02-10

Evolutionary programs (EPs) and evolutionary pattern search algorithms (EPSAS) are two general classes of evolutionary methods for optimizing on continuous domains. The relative performance of these methods has been evaluated on standard global optimization test functions, and these results suggest that EPSAs more robustly converge to near-optimal solutions than EPs. In this paper we evaluate the relative performance of EPSAs and EPs on a real-world application: flexible ligand binding in the Autodock docking software. We compare the performance of these methods on a suite of docking test problems. Our results confirm that EPSAs and EPs have comparable performance, and theymore » suggest that EPSAs may be more robust on larger, more complex problems.« less

IDEA: Interactive Display for Evolutionary Analyses.

PubMed

Egan, Amy; Mahurkar, Anup; Crabtree, Jonathan; Badger, Jonathan H; Carlton, Jane M; Silva, Joana C

2008-12-08

The availability of complete genomic sequences for hundreds of organisms promises to make obtaining genome-wide estimates of substitution rates, selective constraints and other molecular evolution variables of interest an increasingly important approach to addressing broad evolutionary questions. Two of the programs most widely used for this purpose are codeml and baseml, parts of the PAML (Phylogenetic Analysis by Maximum Likelihood) suite. A significant drawback of these programs is their lack of a graphical user interface, which can limit their user base and considerably reduce their efficiency. We have developed IDEA (Interactive Display for Evolutionary Analyses), an intuitive graphical input and output interface which interacts with PHYLIP for phylogeny reconstruction and with codeml and baseml for molecular evolution analyses. IDEA's graphical input and visualization interfaces eliminate the need to edit and parse text input and output files, reducing the likelihood of errors and improving processing time. Further, its interactive output display gives the user immediate access to results. Finally, IDEA can process data in parallel on a local machine or computing grid, allowing genome-wide analyses to be completed quickly. IDEA provides a graphical user interface that allows the user to follow a codeml or baseml analysis from parameter input through to the exploration of results. Novel options streamline the analysis process, and post-analysis visualization of phylogenies, evolutionary rates and selective constraint along protein sequences simplifies the interpretation of results. The integration of these functions into a single tool eliminates the need for lengthy data handling and parsing, significantly expediting access to global patterns in the data.

IDEA: Interactive Display for Evolutionary Analyses

PubMed Central

Egan, Amy; Mahurkar, Anup; Crabtree, Jonathan; Badger, Jonathan H; Carlton, Jane M; Silva, Joana C

2008-01-01

Background The availability of complete genomic sequences for hundreds of organisms promises to make obtaining genome-wide estimates of substitution rates, selective constraints and other molecular evolution variables of interest an increasingly important approach to addressing broad evolutionary questions. Two of the programs most widely used for this purpose are codeml and baseml, parts of the PAML (Phylogenetic Analysis by Maximum Likelihood) suite. A significant drawback of these programs is their lack of a graphical user interface, which can limit their user base and considerably reduce their efficiency. Results We have developed IDEA (Interactive Display for Evolutionary Analyses), an intuitive graphical input and output interface which interacts with PHYLIP for phylogeny reconstruction and with codeml and baseml for molecular evolution analyses. IDEA's graphical input and visualization interfaces eliminate the need to edit and parse text input and output files, reducing the likelihood of errors and improving processing time. Further, its interactive output display gives the user immediate access to results. Finally, IDEA can process data in parallel on a local machine or computing grid, allowing genome-wide analyses to be completed quickly. Conclusion IDEA provides a graphical user interface that allows the user to follow a codeml or baseml analysis from parameter input through to the exploration of results. Novel options streamline the analysis process, and post-analysis visualization of phylogenies, evolutionary rates and selective constraint along protein sequences simplifies the interpretation of results. The integration of these functions into a single tool eliminates the need for lengthy data handling and parsing, significantly expediting access to global patterns in the data. PMID:19061522

EvoBuild: A Quickstart Toolkit for Programming Agent-Based Models of Evolutionary Processes

NASA Astrophysics Data System (ADS)

Wagh, Aditi; Wilensky, Uri

2018-04-01

Extensive research has shown that one of the benefits of programming to learn about scientific phenomena is that it facilitates learning about mechanisms underlying the phenomenon. However, using programming activities in classrooms is associated with costs such as requiring additional time to learn to program or students needing prior experience with programming. This paper presents a class of programming environments that we call quickstart: Environments with a negligible threshold for entry into programming and a modest ceiling. We posit that such environments can provide benefits of programming for learning without incurring associated costs for novice programmers. To make this claim, we present a design-based research study conducted to compare programming models of evolutionary processes with a quickstart toolkit with exploring pre-built models of the same processes. The study was conducted in six seventh grade science classes in two schools. Students in the programming condition used EvoBuild, a quickstart toolkit for programming agent-based models of evolutionary processes, to build their NetLogo models. Students in the exploration condition used pre-built NetLogo models. We demonstrate that although students came from a range of academic backgrounds without prior programming experience, and all students spent the same number of class periods on the activities including the time students took to learn programming in this environment, EvoBuild students showed greater learning about evolutionary mechanisms. We discuss the implications of this work for design research on programming environments in K-12 science education.

Toward autonomous spacecraft

NASA Technical Reports Server (NTRS)

Fogel, L. J.; Calabrese, P. G.; Walsh, M. J.; Owens, A. J.

1982-01-01

Ways in which autonomous behavior of spacecraft can be extended to treat situations wherein a closed loop control by a human may not be appropriate or even possible are explored. Predictive models that minimize mean least squared error and arbitrary cost functions are discussed. A methodology for extracting cyclic components for an arbitrary environment with respect to usual and arbitrary criteria is developed. An approach to prediction and control based on evolutionary programming is outlined. A computer program capable of predicting time series is presented. A design of a control system for a robotic dense with partially unknown physical properties is presented.

Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation.

PubMed

Cornuet, Jean-Marie; Santos, Filipe; Beaumont, Mark A; Robert, Christian P; Marin, Jean-Michel; Balding, David J; Guillemaud, Thomas; Estoup, Arnaud

2008-12-01

Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract part of this information but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIY ABC) for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and population size changes. DIY ABC can be used to compare competing scenarios, estimate parameters for one or more scenarios and compute bias and precision measures for a given scenario and known values of parameters (the current version applies to unlinked microsatellite data). This article describes key methods used in the program and provides its main features. The analysis of one simulated and one real dataset, both with complex evolutionary scenarios, illustrates the main possibilities of DIY ABC. The software DIY ABC is freely available at http://www.montpellier.inra.fr/CBGP/diyabc.

Spatial multiobjective optimization of agricultural conservation practices using a SWAT model and an evolutionary algorithm.

PubMed

Rabotyagov, Sergey; Campbell, Todd; Valcu, Adriana; Gassman, Philip; Jha, Manoj; Schilling, Keith; Wolter, Calvin; Kling, Catherine

2012-12-09

Finding the cost-efficient (i.e., lowest-cost) ways of targeting conservation practice investments for the achievement of specific water quality goals across the landscape is of primary importance in watershed management. Traditional economics methods of finding the lowest-cost solution in the watershed context (e.g.,(5,12,20)) assume that off-site impacts can be accurately described as a proportion of on-site pollution generated. Such approaches are unlikely to be representative of the actual pollution process in a watershed, where the impacts of polluting sources are often determined by complex biophysical processes. The use of modern physically-based, spatially distributed hydrologic simulation models allows for a greater degree of realism in terms of process representation but requires a development of a simulation-optimization framework where the model becomes an integral part of optimization. Evolutionary algorithms appear to be a particularly useful optimization tool, able to deal with the combinatorial nature of a watershed simulation-optimization problem and allowing the use of the full water quality model. Evolutionary algorithms treat a particular spatial allocation of conservation practices in a watershed as a candidate solution and utilize sets (populations) of candidate solutions iteratively applying stochastic operators of selection, recombination, and mutation to find improvements with respect to the optimization objectives. The optimization objectives in this case are to minimize nonpoint-source pollution in the watershed, simultaneously minimizing the cost of conservation practices. A recent and expanding set of research is attempting to use similar methods and integrates water quality models with broadly defined evolutionary optimization methods(3,4,9,10,13-15,17-19,22,23,25). In this application, we demonstrate a program which follows Rabotyagov et al.'s approach and integrates a modern and commonly used SWAT water quality model(7) with a multiobjective evolutionary algorithm SPEA2(26), and user-specified set of conservation practices and their costs to search for the complete tradeoff frontiers between costs of conservation practices and user-specified water quality objectives. The frontiers quantify the tradeoffs faced by the watershed managers by presenting the full range of costs associated with various water quality improvement goals. The program allows for a selection of watershed configurations achieving specified water quality improvement goals and a production of maps of optimized placement of conservation practices.

Islamic Medicine and Evolutionary Medicine: A Comparative Analysis

PubMed Central

Saniotis, Arthur

2012-01-01

The advent of evolutionary medicine in the last two decades has provided new insights into the causes of human disease and possible preventative strategies. One of the strengths of evolutionary medicine is that it follows a multi-disciplinary approach. Such an approach is vital to future biomedicine as it enables for the infiltration of new ideas. Although evolutionary medicine uses Darwinian evolution as a heuristic for understanding human beings’ susceptibility to disease, this is not necessarily in conflict with Islamic medicine. It should be noted that current evolutionary theory was first expounded by various Muslim scientists such as al-Jāḥiẓ, al-Ṭūsī, Ibn Khaldūn and Ibn Maskawayh centuries before Darwin and Wallace. In this way, evolution should not be viewed as being totally antithetical to Islam. This article provides a comparative overview of Islamic medicine and Evolutionary medicine as well as drawing points of comparison between the two approaches which enables their possible future integration. PMID:23864992

Islamic medicine and evolutionary medicine: a comparative analysis.

PubMed

Saniotis, Arthur

2012-01-01

The advent of evolutionary medicine in the last two decades has provided new insights into the causes of human disease and possible preventative strategies. One of the strengths of evolutionary medicine is that it follows a multi-disciplinary approach. Such an approach is vital to future biomedicine as it enables for the infiltration of new ideas. Although evolutionary medicine uses Darwinian evolution as a heuristic for understanding human beings' susceptibility to disease, this is not necessarily in conflict with Islamic medicine. It should be noted that current evolutionary theory was first expounded by various Muslim scientists such as al-Jāḥiẓ, al-Ṭūsī, Ibn Khaldūn and Ibn Maskawayh centuries before Darwin and Wallace. In this way, evolution should not be viewed as being totally antithetical to Islam. This article provides a comparative overview of Islamic medicine and Evolutionary medicine as well as drawing points of comparison between the two approaches which enables their possible future integration.

A novel approach to multiple sequence alignment using hadoop data grids.

PubMed

Sudha Sadasivam, G; Baktavatchalam, G

2010-01-01

Multiple alignment of protein sequences helps to determine evolutionary linkage and to predict molecular structures. The factors to be considered while aligning multiple sequences are speed and accuracy of alignment. Although dynamic programming algorithms produce accurate alignments, they are computation intensive. In this paper we propose a time efficient approach to sequence alignment that also produces quality alignment. The dynamic nature of the algorithm coupled with data and computational parallelism of hadoop data grids improves the accuracy and speed of sequence alignment. The principle of block splitting in hadoop coupled with its scalability facilitates alignment of very large sequences.

Automatic programming via iterated local search for dynamic job shop scheduling.

PubMed

Nguyen, Su; Zhang, Mengjie; Johnston, Mark; Tan, Kay Chen

2015-01-01

Dispatching rules have been commonly used in practice for making sequencing and scheduling decisions. Due to specific characteristics of each manufacturing system, there is no universal dispatching rule that can dominate in all situations. Therefore, it is important to design specialized dispatching rules to enhance the scheduling performance for each manufacturing environment. Evolutionary computation approaches such as tree-based genetic programming (TGP) and gene expression programming (GEP) have been proposed to facilitate the design task through automatic design of dispatching rules. However, these methods are still limited by their high computational cost and low exploitation ability. To overcome this problem, we develop a new approach to automatic programming via iterated local search (APRILS) for dynamic job shop scheduling. The key idea of APRILS is to perform multiple local searches started with programs modified from the best obtained programs so far. The experiments show that APRILS outperforms TGP and GEP in most simulation scenarios in terms of effectiveness and efficiency. The analysis also shows that programs generated by APRILS are more compact than those obtained by genetic programming. An investigation of the behavior of APRILS suggests that the good performance of APRILS comes from the balance between exploration and exploitation in its search mechanism.

Optimal lunar soft landing trajectories using taboo evolutionary programming

NASA Astrophysics Data System (ADS)

Mutyalarao, M.; Raj, M. Xavier James

A safe lunar landing is a key factor to undertake an effective lunar exploration. Lunar lander consists of four phases such as launch phase, the earth-moon transfer phase, circumlunar phase and landing phase. The landing phase can be either hard landing or soft landing. Hard landing means the vehicle lands under the influence of gravity without any deceleration measures. However, soft landing reduces the vertical velocity of the vehicle before landing. Therefore, for the safety of the astronauts as well as the vehicle lunar soft landing with an acceptable velocity is very much essential. So it is important to design the optimal lunar soft landing trajectory with minimum fuel consumption. Optimization of Lunar Soft landing is a complex optimal control problem. In this paper, an analysis related to lunar soft landing from a parking orbit around Moon has been carried out. A two-dimensional trajectory optimization problem is attempted. The problem is complex due to the presence of system constraints. To solve the time-history of control parameters, the problem is converted into two point boundary value problem by using the maximum principle of Pontrygen. Taboo Evolutionary Programming (TEP) technique is a stochastic method developed in recent years and successfully implemented in several fields of research. It combines the features of taboo search and single-point mutation evolutionary programming. Identifying the best unknown parameters of the problem under consideration is the central idea for many space trajectory optimization problems. The TEP technique is used in the present methodology for the best estimation of initial unknown parameters by minimizing objective function interms of fuel requirements. The optimal estimation subsequently results into an optimal trajectory design of a module for soft landing on the Moon from a lunar parking orbit. Numerical simulations demonstrate that the proposed approach is highly efficient and it reduces the minimum fuel consumption. The results are compared with the available results in literature shows that the solution of present algorithm is better than some of the existing algorithms. Keywords: soft landing, trajectory optimization, evolutionary programming, control parameters, Pontrygen principle.

Are hotspots of evolutionary potential adequately protected in southern California?

USGS Publications Warehouse

Vandergast, A.G.; Bohonak, A.J.; Hathaway, S.A.; Boys, J.; Fisher, R.N.

2008-01-01

Reserves are often designed to protect rare habitats, or "typical" exemplars of ecoregions and geomorphic provinces. This approach focuses on current patterns of organismal and ecosystem-level biodiversity, but typically ignores the evolutionary processes that control the gain and loss of biodiversity at these and other levels (e.g., genetic, ecological). In order to include evolutionary processes in conservation planning efforts, their spatial components must first be identified and mapped. We describe a GIS-based approach for explicitly mapping patterns of genetic divergence and diversity for multiple species (a "multi-species genetic landscape"). Using this approach, we analyzed mitochondrial DNA datasets from 21 vertebrate and invertebrate species in southern California to identify areas with common phylogeographic breaks and high intrapopulation diversity. The result is an evolutionary framework for southern California within which patterns of genetic diversity can be analyzed in the context of historical processes, future evolutionary potential and current reserve design. Our multi-species genetic landscapes pinpoint six hotspots where interpopulation genetic divergence is consistently high, five evolutionary hotspots within which genetic connectivity is high, and three hotspots where intrapopulation genetic diversity is high. These 14 hotspots can be grouped into eight geographic areas, of which five largely are unprotected at this time. The multi-species genetic landscape approach may provide an avenue to readily incorporate measures of evolutionary process into GIS-based systematic conservation assessment and land-use planning.

Controlled recovery of phylogenetic communities from an evolutionary model using a network approach

NASA Astrophysics Data System (ADS)

Sousa, Arthur M. Y. R.; Vieira, André P.; Prado, Carmen P. C.; Andrade, Roberto F. S.

2016-04-01

This works reports the use of a complex network approach to produce a phylogenetic classification tree of a simple evolutionary model. This approach has already been used to treat proteomic data of actual extant organisms, but an investigation of its reliability to retrieve a traceable evolutionary history is missing. The used evolutionary model includes key ingredients for the emergence of groups of related organisms by differentiation through random mutations and population growth, but purposefully omits other realistic ingredients that are not strictly necessary to originate an evolutionary history. This choice causes the model to depend only on a small set of parameters, controlling the mutation probability and the population of different species. Our results indicate that for a set of parameter values, the phylogenetic classification produced by the used framework reproduces the actual evolutionary history with a very high average degree of accuracy. This includes parameter values where the species originated by the evolutionary dynamics have modular structures. In the more general context of community identification in complex networks, our model offers a simple setting for evaluating the effects, on the efficiency of community formation and identification, of the underlying dynamics generating the network itself.

An evolutionary algorithm that constructs recurrent neural networks.

PubMed

Angeline, P J; Saunders, G M; Pollack, J B

1994-01-01

Standard methods for simultaneously inducing the structure and weights of recurrent neural networks limit every task to an assumed class of architectures. Such a simplification is necessary since the interactions between network structure and function are not well understood. Evolutionary computations, which include genetic algorithms and evolutionary programming, are population-based search methods that have shown promise in many similarly complex tasks. This paper argues that genetic algorithms are inappropriate for network acquisition and describes an evolutionary program, called GNARL, that simultaneously acquires both the structure and weights for recurrent networks. GNARL's empirical acquisition method allows for the emergence of complex behaviors and topologies that are potentially excluded by the artificial architectural constraints imposed in standard network induction methods.

Conciliation biology: the eco-evolutionary management of permanently invaded biotic systems

PubMed Central

Carroll, Scott P

2011-01-01

Biotic invaders and similar anthropogenic novelties such as domesticates, transgenics, and cancers can alter ecology and evolution in environmental, agricultural, natural resource, public health, and medical systems. The resulting biological changes may either hinder or serve management objectives. For example, biological control and eradication programs are often defeated by unanticipated resistance evolution and by irreversibility of invader impacts. Moreover, eradication may be ill-advised when nonnatives introduce beneficial functions. Thus, contexts that appear to call for eradication may instead demand managed coexistence of natives with nonnatives, and yet applied biologists have not generally considered the need to manage the eco-evolutionary dynamics that commonly result from interactions of natives with nonnatives. Here, I advocate a conciliatory approach to managing systems where novel organisms cannot or should not be eradicated. Conciliatory strategies incorporate benefits of nonnatives to address many practical needs including slowing rates of resistance evolution, promoting evolution of indigenous biological control, cultivating replacement services and novel functions, and managing native–nonnative coevolution. Evolutionary links across disciplines foster cohesion essential for managing the broad impacts of novel biotic systems. Rather than signaling defeat, conciliation biology thus utilizes the predictive power of evolutionary theory to offer diverse and flexible pathways to more sustainable outcomes. PMID:25567967

Evolutionary neural networks for anomaly detection based on the behavior of a program.

PubMed

Han, Sang-Jun; Cho, Sung-Bae

2006-06-01

The process of learning the behavior of a given program by using machine-learning techniques (based on system-call audit data) is effective to detect intrusions. Rule learning, neural networks, statistics, and hidden Markov models (HMMs) are some of the kinds of representative methods for intrusion detection. Among them, neural networks are known for good performance in learning system-call sequences. In order to apply this knowledge to real-world problems successfully, it is important to determine the structures and weights of these call sequences. However, finding the appropriate structures requires very long time periods because there are no suitable analytical solutions. In this paper, a novel intrusion-detection technique based on evolutionary neural networks (ENNs) is proposed. One advantage of using ENNs is that it takes less time to obtain superior neural networks than when using conventional approaches. This is because they discover the structures and weights of the neural networks simultaneously. Experimental results with the 1999 Defense Advanced Research Projects Agency (DARPA) Intrusion Detection Evaluation (IDEVAL) data confirm that ENNs are promising tools for intrusion detection.

Clustering Genes of Common Evolutionary History

PubMed Central

Gori, Kevin; Suchan, Tomasz; Alvarez, Nadir; Goldman, Nick; Dessimoz, Christophe

2016-01-01

Phylogenetic inference can potentially result in a more accurate tree using data from multiple loci. However, if the loci are incongruent—due to events such as incomplete lineage sorting or horizontal gene transfer—it can be misleading to infer a single tree. To address this, many previous contributions have taken a mechanistic approach, by modeling specific processes. Alternatively, one can cluster loci without assuming how these incongruencies might arise. Such “process-agnostic” approaches typically infer a tree for each locus and cluster these. There are, however, many possible combinations of tree distance and clustering methods; their comparative performance in the context of tree incongruence is largely unknown. Furthermore, because standard model selection criteria such as AIC cannot be applied to problems with a variable number of topologies, the issue of inferring the optimal number of clusters is poorly understood. Here, we perform a large-scale simulation study of phylogenetic distances and clustering methods to infer loci of common evolutionary history. We observe that the best-performing combinations are distances accounting for branch lengths followed by spectral clustering or Ward’s method. We also introduce two statistical tests to infer the optimal number of clusters and show that they strongly outperform the silhouette criterion, a general-purpose heuristic. We illustrate the usefulness of the approach by 1) identifying errors in a previous phylogenetic analysis of yeast species and 2) identifying topological incongruence among newly sequenced loci of the globeflower fly genus Chiastocheta. We release treeCl, a new program to cluster genes of common evolutionary history (http://git.io/treeCl). PMID:26893301

Generative Representations for Automated Design of Robots

NASA Technical Reports Server (NTRS)

Homby, Gregory S.; Lipson, Hod; Pollack, Jordan B.

2007-01-01

A method of automated design of complex, modular robots involves an evolutionary process in which generative representations of designs are used. The term generative representations as used here signifies, loosely, representations that consist of or include algorithms, computer programs, and the like, wherein encoded designs can reuse elements of their encoding and thereby evolve toward greater complexity. Automated design of robots through synthetic evolutionary processes has already been demonstrated, but it is not clear whether genetically inspired search algorithms can yield designs that are sufficiently complex for practical engineering. The ultimate success of such algorithms as tools for automation of design depends on the scaling properties of representations of designs. A nongenerative representation (one in which each element of the encoded design is used at most once in translating to the design) scales linearly with the number of elements. Search algorithms that use nongenerative representations quickly become intractable (search times vary approximately exponentially with numbers of design elements), and thus are not amenable to scaling to complex designs. Generative representations are compact representations and were devised as means to circumvent the above-mentioned fundamental restriction on scalability. In the present method, a robot is defined by a compact programmatic form (its generative representation) and the evolutionary variation takes place on this form. The evolutionary process is an iterative one, wherein each cycle consists of the following steps: 1. Generative representations are generated in an evolutionary subprocess. 2. Each generative representation is a program that, when compiled, produces an assembly procedure. 3. In a computational simulation, a constructor executes an assembly procedure to generate a robot. 4. A physical-simulation program tests the performance of a simulated constructed robot, evaluating the performance according to a fitness criterion to yield a figure of merit that is fed back into the evolutionary subprocess of the next iteration. In comparison with prior approaches to automated evolutionary design of robots, the use of generative representations offers two advantages: First, a generative representation enables the reuse of components in regular and hierarchical ways and thereby serves a systematic means of creating more complex modules out of simpler ones. Second, the evolved generative representation may capture intrinsic properties of the design problem, so that variations in the representations move through the design space more effectively than do equivalent variations in a nongenerative representation. This method has been demonstrated by using it to design some robots that move, variously, by walking, rolling, or sliding. Some of the robots were built (see figure). Although these robots are very simple, in comparison with robots designed by humans, their structures are more regular, modular, hierarchical, and complex than are those of evolved designs of comparable functionality synthesized by use of nongenerative representations.

Evolutionary-based approaches for determining the deviatoric stress of calcareous sands

NASA Astrophysics Data System (ADS)

Shahnazari, Habib; Tutunchian, Mohammad A.; Rezvani, Reza; Valizadeh, Fatemeh

2013-01-01

Many hydrocarbon reservoirs are located near oceans which are covered by calcareous deposits. These sediments consist mainly of the remains of marine plants or animals, so calcareous soils can have a wide variety of engineering properties. Due to their local expansion and considerable differences from terrigenous soils, the evaluation of engineering behaviors of calcareous sediments has been a major concern for geotechnical engineers in recent years. Deviatoric stress is one of the most important parameters directly affecting important shearing characteristics of soils. In this study, a dataset of experimental triaxial tests was gathered from two sources. First, the data of previous experimental studies from the literature were gathered. Then, a series of triaxial tests was performed on calcareous sands of the Persian Gulf to develop the dataset. This work resulted in a large database of experimental results on the maximum deviatoric stress of different calcareous sands. To demonstrate the capabilities of evolutionary-based approaches in modeling the deviatoric stress of calcareous sands, two promising variants of genetic programming (GP), multigene genetic programming (MGP) and gene expression programming (GEP), were applied to propose new predictive models. The models' input parameters were the physical and in-situ condition properties of soil and the output was the maximum deviatoric stress (i.e., the axial-deviator stress). The results of statistical analyses indicated the robustness of these models, and a parametric study was also conducted for further verification of the models, in which the resulting trends were consistent with the results of the experimental study. Finally, the proposed models were further simplified by applying a practical geotechnical correlation.

AI-BL1.0: a program for automatic on-line beamline optimization using the evolutionary algorithm.

PubMed

Xi, Shibo; Borgna, Lucas Santiago; Zheng, Lirong; Du, Yonghua; Hu, Tiandou

2017-01-01

In this report, AI-BL1.0, an open-source Labview-based program for automatic on-line beamline optimization, is presented. The optimization algorithms used in the program are Genetic Algorithm and Differential Evolution. Efficiency was improved by use of a strategy known as Observer Mode for Evolutionary Algorithm. The program was constructed and validated at the XAFCA beamline of the Singapore Synchrotron Light Source and 1W1B beamline of the Beijing Synchrotron Radiation Facility.

Active vibration control activities at the LaRC - Present and future

NASA Technical Reports Server (NTRS)

Newsom, J. R.

1990-01-01

The NASA Controls-Structures-Interaction (CSI) program is presented with a description of the ground testing element objectives and approach. The goal of the CSI program is to develop and validate the technology required to design, verify and operate space systems in which the structure and the controls interact beneficially to meet the needs of future NASA missions. The operational Mini-Mast ground testbed and some sample active vibration control experimental results are discussed along with a description of the CSI Evolutionary Model testbed presently under development. Initial results indicate that embedded sensors and actuators are effective in controlling a large truss/reflector structure.

Options for the human settlement of the moon and Mars

NASA Technical Reports Server (NTRS)

Fairchild, Kyle O.; Roberts, Barney B.

1989-01-01

The evolutionary approach to space development is discussed in the framework of three overall strategies encompassing four case studies. The first strategy, human expeditions, places emphasis on highly visible, near-term manned missions to Mars or to one of the two moons of Mars. These expeditions are similar in scope and objectives to the Apollo program, with infrastructure development only conducted to the degree necessary to support one or two short-duration trips. Two such expeditionary scenarios, one to Phobus and the other to the Mars surface, are discussed. The second strategy involves the construction of science outposts, and emphasizes scientific exploration as well as investigation of technologies and operations needed for permanent habitation. A third strategy, evolutionary expansion, would explore and settle the inner solar system in a series of steps, with continued development of technologies, experience, and infrastructure.

Knowledge discovery with classification rules in a cardiovascular dataset.

PubMed

Podgorelec, Vili; Kokol, Peter; Stiglic, Milojka Molan; Hericko, Marjan; Rozman, Ivan

2005-12-01

In this paper we study an evolutionary machine learning approach to data mining and knowledge discovery based on the induction of classification rules. A method for automatic rules induction called AREX using evolutionary induction of decision trees and automatic programming is introduced. The proposed algorithm is applied to a cardiovascular dataset consisting of different groups of attributes which should possibly reveal the presence of some specific cardiovascular problems in young patients. A case study is presented that shows the use of AREX for the classification of patients and for discovering possible new medical knowledge from the dataset. The defined knowledge discovery loop comprises a medical expert's assessment of induced rules to drive the evolution of rule sets towards more appropriate solutions. The final result is the discovery of a possible new medical knowledge in the field of pediatric cardiology.

How Can We Study the Evolution of Animal Minds?

PubMed Central

Cauchoix, Maxime; Chaine, Alexis S.

2016-01-01

During the last 50 years, comparative cognition and neurosciences have improved our understanding of animal minds while evolutionary ecology has revealed how selection acts on traits through evolutionary time. We describe how cognition can be subject to natural selection like any other biological trait and how this evolutionary approach can be used to understand the evolution of animal cognition. We recount how comparative and fitness methods have been used to understand the evolution of cognition and outline how these approaches could extend our understanding of cognition. The fitness approach, in particular, offers unprecedented opportunities to study the evolutionary mechanisms responsible for variation in cognition within species and could allow us to investigate both proximate (i.e., neural and developmental) and ultimate (i.e., ecological and evolutionary) underpinnings of animal cognition together. We highlight recent studies that have successfully shown that cognitive traits can be under selection, in particular by linking individual variation in cognition to fitness. To bridge the gap between cognitive variation and fitness consequences and to better understand why and how selection can occur on cognition, we end this review by proposing a more integrative approach to study contemporary selection on cognitive traits combining socio-ecological data, minimally invasive neuroscience methods and measurement of ecologically relevant behaviors linked to fitness. Our overall goal in this review is to build a bridge between cognitive neuroscientists and evolutionary biologists, illustrate how their research could be complementary, and encourage evolutionary ecologists to include explicit attention to cognitive processes in their studies of behavior. PMID:27014163

Evolutionary impact assessment: accounting for evolutionary consequences of fishing in an ecosystem approach to fisheries management.

PubMed

Laugen, Ane T; Engelhard, Georg H; Whitlock, Rebecca; Arlinghaus, Robert; Dankel, Dorothy J; Dunlop, Erin S; Eikeset, Anne M; Enberg, Katja; Jørgensen, Christian; Matsumura, Shuichi; Nusslé, Sébastien; Urbach, Davnah; Baulier, Loїc; Boukal, David S; Ernande, Bruno; Johnston, Fiona D; Mollet, Fabian; Pardoe, Heidi; Therkildsen, Nina O; Uusi-Heikkilä, Silva; Vainikka, Anssi; Heino, Mikko; Rijnsdorp, Adriaan D; Dieckmann, Ulf

2014-03-01

Managing fisheries resources to maintain healthy ecosystems is one of the main goals of the ecosystem approach to fisheries (EAF). While a number of international treaties call for the implementation of EAF, there are still gaps in the underlying methodology. One aspect that has received substantial scientific attention recently is fisheries-induced evolution (FIE). Increasing evidence indicates that intensive fishing has the potential to exert strong directional selection on life-history traits, behaviour, physiology, and morphology of exploited fish. Of particular concern is that reversing evolutionary responses to fishing can be much more difficult than reversing demographic or phenotypically plastic responses. Furthermore, like climate change, multiple agents cause FIE, with effects accumulating over time. Consequently, FIE may alter the utility derived from fish stocks, which in turn can modify the monetary value living aquatic resources provide to society. Quantifying and predicting the evolutionary effects of fishing is therefore important for both ecological and economic reasons. An important reason this is not happening is the lack of an appropriate assessment framework. We therefore describe the evolutionary impact assessment (EvoIA) as a structured approach for assessing the evolutionary consequences of fishing and evaluating the predicted evolutionary outcomes of alternative management options. EvoIA can contribute to EAF by clarifying how evolution may alter stock properties and ecological relations, support the precautionary approach to fisheries management by addressing a previously overlooked source of uncertainty and risk, and thus contribute to sustainable fisheries.

Evolutionary impact assessment: accounting for evolutionary consequences of fishing in an ecosystem approach to fisheries management

PubMed Central

Laugen, Ane T; Engelhard, Georg H; Whitlock, Rebecca; Arlinghaus, Robert; Dankel, Dorothy J; Dunlop, Erin S; Eikeset, Anne M; Enberg, Katja; Jørgensen, Christian; Matsumura, Shuichi; Nusslé, Sébastien; Urbach, Davnah; Baulier, Loїc; Boukal, David S; Ernande, Bruno; Johnston, Fiona D; Mollet, Fabian; Pardoe, Heidi; Therkildsen, Nina O; Uusi-Heikkilä, Silva; Vainikka, Anssi; Heino, Mikko; Rijnsdorp, Adriaan D; Dieckmann, Ulf

2014-01-01

Managing fisheries resources to maintain healthy ecosystems is one of the main goals of the ecosystem approach to fisheries (EAF). While a number of international treaties call for the implementation of EAF, there are still gaps in the underlying methodology. One aspect that has received substantial scientific attention recently is fisheries-induced evolution (FIE). Increasing evidence indicates that intensive fishing has the potential to exert strong directional selection on life-history traits, behaviour, physiology, and morphology of exploited fish. Of particular concern is that reversing evolutionary responses to fishing can be much more difficult than reversing demographic or phenotypically plastic responses. Furthermore, like climate change, multiple agents cause FIE, with effects accumulating over time. Consequently, FIE may alter the utility derived from fish stocks, which in turn can modify the monetary value living aquatic resources provide to society. Quantifying and predicting the evolutionary effects of fishing is therefore important for both ecological and economic reasons. An important reason this is not happening is the lack of an appropriate assessment framework. We therefore describe the evolutionary impact assessment (EvoIA) as a structured approach for assessing the evolutionary consequences of fishing and evaluating the predicted evolutionary outcomes of alternative management options. EvoIA can contribute to EAF by clarifying how evolution may alter stock properties and ecological relations, support the precautionary approach to fisheries management by addressing a previously overlooked source of uncertainty and risk, and thus contribute to sustainable fisheries. PMID:26430388

Theoretical Analysis of Local Search and Simple Evolutionary Algorithms for the Generalized Travelling Salesperson Problem.

PubMed

Pourhassan, Mojgan; Neumann, Frank

2018-06-22

The generalized travelling salesperson problem is an important NP-hard combinatorial optimization problem for which meta-heuristics, such as local search and evolutionary algorithms, have been used very successfully. Two hierarchical approaches with different neighbourhood structures, namely a Cluster-Based approach and a Node-Based approach, have been proposed by Hu and Raidl (2008) for solving this problem. In this paper, local search algorithms and simple evolutionary algorithms based on these approaches are investigated from a theoretical perspective. For local search algorithms, we point out the complementary abilities of the two approaches by presenting instances where they mutually outperform each other. Afterwards, we introduce an instance which is hard for both approaches when initialized on a particular point of the search space, but where a variable neighbourhood search combining them finds the optimal solution in polynomial time. Then we turn our attention to analysing the behaviour of simple evolutionary algorithms that use these approaches. We show that the Node-Based approach solves the hard instance of the Cluster-Based approach presented in Corus et al. (2016) in polynomial time. Furthermore, we prove an exponential lower bound on the optimization time of the Node-Based approach for a class of Euclidean instances.

Derived heuristics-based consistent optimization of material flow in a gold processing plant

NASA Astrophysics Data System (ADS)

Myburgh, Christie; Deb, Kalyanmoy

2018-01-01

Material flow in a chemical processing plant often follows complicated control laws and involves plant capacity constraints. Importantly, the process involves discrete scenarios which when modelled in a programming format involves if-then-else statements. Therefore, a formulation of an optimization problem of such processes becomes complicated with nonlinear and non-differentiable objective and constraint functions. In handling such problems using classical point-based approaches, users often have to resort to modifications and indirect ways of representing the problem to suit the restrictions associated with classical methods. In a particular gold processing plant optimization problem, these facts are demonstrated by showing results from MATLAB®'s well-known fmincon routine. Thereafter, a customized evolutionary optimization procedure which is capable of handling all complexities offered by the problem is developed. Although the evolutionary approach produced results with comparatively less variance over multiple runs, the performance has been enhanced by introducing derived heuristics associated with the problem. In this article, the development and usage of derived heuristics in a practical problem are presented and their importance in a quick convergence of the overall algorithm is demonstrated.

Transforming Biology Assessment with Machine Learning: Automated Scoring of Written Evolutionary Explanations

ERIC Educational Resources Information Center

Nehm, Ross H.; Ha, Minsu; Mayfield, Elijah

2012-01-01

This study explored the use of machine learning to automatically evaluate the accuracy of students' written explanations of evolutionary change. Performance of the Summarization Integrated Development Environment (SIDE) program was compared to human expert scoring using a corpus of 2,260 evolutionary explanations written by 565 undergraduate…

A variational approach to niche construction.

PubMed

Constant, Axel; Ramstead, Maxwell J D; Veissière, Samuel P L; Campbell, John O; Friston, Karl J

2018-04-01

In evolutionary biology, niche construction is sometimes described as a genuine evolutionary process whereby organisms, through their activities and regulatory mechanisms, modify their environment such as to steer their own evolutionary trajectory, and that of other species. There is ongoing debate, however, on the extent to which niche construction ought to be considered a bona fide evolutionary force, on a par with natural selection. Recent formulations of the variational free-energy principle as applied to the life sciences describe the properties of living systems, and their selection in evolution, in terms of variational inference. We argue that niche construction can be described using a variational approach. We propose new arguments to support the niche construction perspective, and to extend the variational approach to niche construction to current perspectives in various scientific fields. © 2018 The Authors.

A variational approach to niche construction

PubMed Central

Ramstead, Maxwell J. D.; Veissière, Samuel P. L.; Campbell, John O.; Friston, Karl J.

2018-01-01

In evolutionary biology, niche construction is sometimes described as a genuine evolutionary process whereby organisms, through their activities and regulatory mechanisms, modify their environment such as to steer their own evolutionary trajectory, and that of other species. There is ongoing debate, however, on the extent to which niche construction ought to be considered a bona fide evolutionary force, on a par with natural selection. Recent formulations of the variational free-energy principle as applied to the life sciences describe the properties of living systems, and their selection in evolution, in terms of variational inference. We argue that niche construction can be described using a variational approach. We propose new arguments to support the niche construction perspective, and to extend the variational approach to niche construction to current perspectives in various scientific fields. PMID:29643221

Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation

PubMed Central

Cornuet, Jean-Marie; Santos, Filipe; Beaumont, Mark A.; Robert, Christian P.; Marin, Jean-Michel; Balding, David J.; Guillemaud, Thomas; Estoup, Arnaud

2008-01-01

Summary: Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract part of this information but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIY ABC) for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and population size changes. DIY ABC can be used to compare competing scenarios, estimate parameters for one or more scenarios and compute bias and precision measures for a given scenario and known values of parameters (the current version applies to unlinked microsatellite data). This article describes key methods used in the program and provides its main features. The analysis of one simulated and one real dataset, both with complex evolutionary scenarios, illustrates the main possibilities of DIY ABC. Availability: The software DIY ABC is freely available at http://www.montpellier.inra.fr/CBGP/diyabc. Contact: j.cornuet@imperial.ac.uk Supplementary information: Supplementary data are also available at http://www.montpellier.inra.fr/CBGP/diyabc PMID:18842597

An evolutionary medicine approach to understanding factors that contribute to chronic obstructive pulmonary disease.

PubMed

Aoshiba, Kazutetsu; Tsuji, Takao; Itoh, Masayuki; Yamaguchi, Kazuhiro; Nakamura, Hiroyuki

2015-01-01

Although many studies have been published on the causes and mechanisms of chronic obstructive pulmonary disease (COPD), the reason for the existence of COPD and the reasons why COPD develops in humans have hardly been studied. Evolutionary medical approaches are required to explain not only the proximate factors, such as the causes and mechanisms of a disease, but the ultimate (evolutionary) factors as well, such as why the disease is present and why the disease develops in humans. According to the concepts of evolutionary medicine, disease susceptibility is acquired as a result of natural selection during the evolutionary process of traits linked to the genes involved in disease susceptibility. In this paper, we discuss the following six reasons why COPD develops in humans based on current evolutionary medical theories: (1) evolutionary constraints; (2) mismatch between environmental changes and evolution; (3) co-evolution with pathogenic microorganisms; (4) life history trade-off; (5) defenses and their costs, and (6) reproductive success at the expense of health. Our perspective pursues evolutionary answers to the fundamental question, 'Why are humans susceptible to this common disease, COPD, despite their long evolutionary history?' We believe that the perspectives offered by evolutionary medicine are essential for researchers to better understand the significance of their work.

Evolutionary Theory in Undergraduate Biology Programs at Lebanese Universities: A Comparative Study

ERIC Educational Resources Information Center

Vlaardingerbroek, Barend; Hachem-El-Masri, Yasmine

2006-01-01

The purpose of this study was to gauge the profile of evolutionary theory in Lebanese undergraduate biology programs. The research focused mainly on the views of university biology department heads, given that they are the people who exercise the most direct influence over their departments' ethos. An Australasian sample was chosen as a reference…

Evolutionary trade-offs in kidney injury and repair.

PubMed

Lei, Yutian; Anders, Hans-Joachim

2017-11-01

Evolutionary medicine has proven helpful to understand the origin of human disease, e.g. in identifying causal roles of recent environmental changes impacting on human physiology (environment-phenotype mismatch). In contrast, diseases affecting only a limited number of members of a species often originate from evolutionary trade-offs for usually physiologic adaptations assuring reproductive success in the context of extrinsic threats. For example, the G1 and G2 variants of the APOL1 gene supporting control of Trypanosoma infection come with the trade-off that they promote the progression of kidney disease. In this review we extend the concept of evolutionary nephrology by discussing how the physiologic adaptations (danger responses) to tissue injury create evolutionary trade-offs that drive histopathological changes underlying acute and chronic kidney diseases. The evolution of multicellular organisms positively selected a number of danger response programs for their overwhelming benefits in assuring survival such as clotting, inflammation, epithelial healing and mesenchymal healing, i.e. fibrosis and sclerosis. Upon kidney injury these danger programs often present as pathomechanisms driving persistent nephron loss and renal failure. We explore how classic kidney disease entities involve insufficient or overshooting activation of these danger response programs for which the underlying genetic basis remains largely to be defined. Dissecting the causative and hierarchical relationships between danger programs should help to identify molecular targets to control kidney injury and to improve disease outcomes.

Evolutionary systems biology: historical and philosophical perspectives on an emerging synthesis.

PubMed

O'Malley, Maureen A

2012-01-01

Systems biology (SB) is at least a decade old now and maturing rapidly. A more recent field, evolutionary systems biology (ESB), is in the process of further developing system-level approaches through the expansion of their explanatory and potentially predictive scope. This chapter will outline the varieties of ESB existing today by tracing the diverse roots and fusions that make up this integrative project. My approach is philosophical and historical. As well as examining the recent origins of ESB, I will reflect on its central features and the different clusters of research it comprises. In its broadest interpretation, ESB consists of five overlapping approaches: comparative and correlational ESB; network architecture ESB; network property ESB; population genetics ESB; and finally, standard evolutionary questions answered with SB methods. After outlining each approach with examples, I will examine some strong general claims about ESB, particularly that it can be viewed as the next step toward a fuller modern synthesis of evolutionary biology (EB), and that it is also the way forward for evolutionary and systems medicine. I will conclude with a discussion of whether the emerging field of ESB has the capacity to combine an even broader scope of research aims and efforts than it presently does.

A Bell-Curved Based Algorithm for Mixed Continuous and Discrete Structural Optimization

NASA Technical Reports Server (NTRS)

Kincaid, Rex K.; Weber, Michael; Sobieszczanski-Sobieski, Jaroslaw

2001-01-01

An evolutionary based strategy utilizing two normal distributions to generate children is developed to solve mixed integer nonlinear programming problems. This Bell-Curve Based (BCB) evolutionary algorithm is similar in spirit to (mu + mu) evolutionary strategies and evolutionary programs but with fewer parameters to adjust and no mechanism for self adaptation. First, a new version of BCB to solve purely discrete optimization problems is described and its performance tested against a tabu search code for an actuator placement problem. Next, the performance of a combined version of discrete and continuous BCB is tested on 2-dimensional shape problems and on a minimum weight hub design problem. In the latter case the discrete portion is the choice of the underlying beam shape (I, triangular, circular, rectangular, or U).

On the path to genetic novelties: insights from programmed DNA elimination and RNA splicing.

PubMed

Catania, Francesco; Schmitz, Jürgen

2015-01-01

Understanding how genetic novelties arise is a central goal of evolutionary biology. To this end, programmed DNA elimination and RNA splicing deserve special consideration. While programmed DNA elimination reshapes genomes by eliminating chromatin during organismal development, RNA splicing rearranges genetic messages by removing intronic regions during transcription. Small RNAs help to mediate this class of sequence reorganization, which is not error-free. It is this imperfection that makes programmed DNA elimination and RNA splicing excellent candidates for generating evolutionary novelties. Leveraging a number of these two processes' mechanistic and evolutionary properties, which have been uncovered over the past years, we present recently proposed models and empirical evidence for how splicing can shape the structure of protein-coding genes in eukaryotes. We also chronicle a number of intriguing similarities between the processes of programmed DNA elimination and RNA splicing, and highlight the role that the variation in the population-genetic environment may play in shaping their target sequences. © 2015 Wiley Periodicals, Inc.

Honey bee-inspired algorithms for SNP haplotype reconstruction problem

NASA Astrophysics Data System (ADS)

PourkamaliAnaraki, Maryam; Sadeghi, Mehdi

2016-03-01

Reconstructing haplotypes from SNP fragments is an important problem in computational biology. There have been a lot of interests in this field because haplotypes have been shown to contain promising data for disease association research. It is proved that haplotype reconstruction in Minimum Error Correction model is an NP-hard problem. Therefore, several methods such as clustering techniques, evolutionary algorithms, neural networks and swarm intelligence approaches have been proposed in order to solve this problem in appropriate time. In this paper, we have focused on various evolutionary clustering techniques and try to find an efficient technique for solving haplotype reconstruction problem. It can be referred from our experiments that the clustering methods relying on the behaviour of honey bee colony in nature, specifically bees algorithm and artificial bee colony methods, are expected to result in more efficient solutions. An application program of the methods is available at the following link. http://www.bioinf.cs.ipm.ir/software/haprs/

Using Evolved Fuzzy Neural Networks for Injury Detection from Isokinetic Curves

NASA Astrophysics Data System (ADS)

Couchet, Jorge; Font, José María; Manrique, Daniel

In this paper we propose an evolutionary fuzzy neural networks system for extracting knowledge from a set of time series containing medical information. The series represent isokinetic curves obtained from a group of patients exercising the knee joint on an isokinetic dynamometer. The system has two parts: i) it analyses the time series input in order generate a simplified model of an isokinetic curve; ii) it applies a grammar-guided genetic program to obtain a knowledge base represented by a fuzzy neural network. Once the knowledge base has been generated, the system is able to perform knee injuries detection. The results suggest that evolved fuzzy neural networks perform better than non-evolutionary approaches and have a high accuracy rate during both the training and testing phases. Additionally, they are robust, as the system is able to self-adapt to changes in the problem without human intervention.

On the origin of biological construction, with a focus on multicellularity.

PubMed

van Gestel, Jordi; Tarnita, Corina E

2017-10-17

Biology is marked by a hierarchical organization: all life consists of cells; in some cases, these cells assemble into groups, such as endosymbionts or multicellular organisms; in turn, multicellular organisms sometimes assemble into yet other groups, such as primate societies or ant colonies. The construction of new organizational layers results from hierarchical evolutionary transitions, in which biological units (e.g., cells) form groups that evolve into new units of biological organization (e.g., multicellular organisms). Despite considerable advances, there is no bottom-up, dynamical account of how, starting from the solitary ancestor, the first groups originate and subsequently evolve the organizing principles that qualify them as new units. Guided by six central questions, we propose an integrative bottom-up approach for studying the dynamics underlying hierarchical evolutionary transitions, which builds on and synthesizes existing knowledge. This approach highlights the crucial role of the ecology and development of the solitary ancestor in the emergence and subsequent evolution of groups, and it stresses the paramount importance of the life cycle: only by evaluating groups in the context of their life cycle can we unravel the evolutionary trajectory of hierarchical transitions. These insights also provide a starting point for understanding the types of subsequent organizational complexity. The central research questions outlined here naturally link existing research programs on biological construction (e.g., on cooperation, multilevel selection, self-organization, and development) and thereby help integrate knowledge stemming from diverse fields of biology.

Evolutionary medicine: its scope, interest and potential

PubMed Central

Stearns, Stephen C.

2012-01-01

This review is aimed at readers seeking an introductory overview, teaching courses and interested in visionary ideas. It first describes the range of topics covered by evolutionary medicine, which include human genetic variation, mismatches to modernity, reproductive medicine, degenerative disease, host–pathogen interactions and insights from comparisons with other species. It then discusses priorities for translational research, basic research and health management. Its conclusions are that evolutionary thinking should not displace other approaches to medical science, such as molecular medicine and cell and developmental biology, but that evolutionary insights can combine with and complement established approaches to reduce suffering and save lives. Because we are on the cusp of so much new research and innovative insights, it is hard to estimate how much impact evolutionary thinking will have on medicine, but it is already clear that its potential is enormous. PMID:22933370

Evolutionary medicine: its scope, interest and potential.

PubMed

Stearns, Stephen C

2012-11-07

This review is aimed at readers seeking an introductory overview, teaching courses and interested in visionary ideas. It first describes the range of topics covered by evolutionary medicine, which include human genetic variation, mismatches to modernity, reproductive medicine, degenerative disease, host-pathogen interactions and insights from comparisons with other species. It then discusses priorities for translational research, basic research and health management. Its conclusions are that evolutionary thinking should not displace other approaches to medical science, such as molecular medicine and cell and developmental biology, but that evolutionary insights can combine with and complement established approaches to reduce suffering and save lives. Because we are on the cusp of so much new research and innovative insights, it is hard to estimate how much impact evolutionary thinking will have on medicine, but it is already clear that its potential is enormous.

Evolutionary psychology in the modern world: applications, perspectives, and strategies.

PubMed

Roberts, S Craig; van Vugt, Mark; Dunbar, Robin I M

2012-12-20

An evolutionary approach is a powerful framework which can bring new perspectives on any aspect of human behavior, to inform and complement those from other disciplines, from psychology and anthropology to economics and politics. Here we argue that insights from evolutionary psychology may be increasingly applied to address practical issues and help alleviate social problems. We outline the promise of this endeavor, and some of the challenges it faces. In doing so, we draw parallels between an applied evolutionary psychology and recent developments in Darwinian medicine, which similarly has the potential to complement conventional approaches. Finally, we describe some promising new directions which are developed in the associated papers accompanying this article.

Evolutionary origins of the endosperm in flowering plants

PubMed Central

Baroux, Célia; Spillane, Charles; Grossniklaus, Ueli

2002-01-01

The evolutionary origin of double fertilization and the resultant endosperm tissue in flowering plants remains a puzzle, despite over a century of research. The recent resurgence of approaches to evolutionary developmental biology combining comparative biology with phylogenetics provides new understanding of endosperm origins. PMID:12225592

How conservative are evolutionary anthropologists?: a survey of political attitudes.

PubMed

Lyle, Henry F; Smith, Eric A

2012-09-01

The application of evolutionary theory to human behavior has elicited a variety of critiques, some of which charge that this approach expresses or encourages conservative or reactionary political agendas. In a survey of graduate students in psychology, Tybur, Miller, and Gangestad (Human Nature, 18, 313-328, 2007) found that the political attitudes of those who use an evolutionary approach did not differ from those of other psychology grad students. Here, we present results from a directed online survey of a broad sample of graduate students in anthropology that assays political views. We found that evolutionary anthropology graduate students were very liberal in their political beliefs, overwhelmingly voted for a liberal U.S. presidential candidate in the 2008 election, and identified with liberal political parties; in this, they were almost indistinguishable from non-evolutionary anthropology students. Our results contradict the view that evolutionary anthropologists hold conservative or reactionary political views. We discuss some possible reasons for the persistence of this view in terms of the sociology of science.

Assembling networks of microbial genomes using linear programming.

PubMed

Holloway, Catherine; Beiko, Robert G

2010-11-20

Microbial genomes exhibit complex sets of genetic affinities due to lateral genetic transfer. Assessing the relative contributions of parent-to-offspring inheritance and gene sharing is a vital step in understanding the evolutionary origins and modern-day function of an organism, but recovering and showing these relationships is a challenging problem. We have developed a new approach that uses linear programming to find between-genome relationships, by treating tables of genetic affinities (here, represented by transformed BLAST e-values) as an optimization problem. Validation trials on simulated data demonstrate the effectiveness of the approach in recovering and representing vertical and lateral relationships among genomes. Application of the technique to a set comprising Aquifex aeolicus and 75 other thermophiles showed an important role for large genomes as 'hubs' in the gene sharing network, and suggested that genes are preferentially shared between organisms with similar optimal growth temperatures. We were also able to discover distinct and common genetic contributors to each sequenced representative of genus Pseudomonas. The linear programming approach we have developed can serve as an effective inference tool in its own right, and can be an efficient first step in a more-intensive phylogenomic analysis.

Using Human Evolution to Teach Evolutionary Theory

ERIC Educational Resources Information Center

Besterman, Hugo; La Velle, Linda Baggott

2007-01-01

This paper discusses some traditional approaches to the teaching of evolutionary theory at pre-university level, criticising in particular some of the more commonly used models and exemplars. Curricular demands are described and an alternative approach is suggested, using the emerging story of human evolution. Recent discoveries help to illustrate…

A comparative study of corrugated horn design by evolutionary techniques

NASA Technical Reports Server (NTRS)

Hoorfar, A.

2003-01-01

Here an evolutionary programming algorithm is used to optimize the pattern of a corrugated circular horn subject to various constraints on return loss, antenna beamwidth, pattern circularity, and low cross polarization.

Cancer: shift of the paradigm.

PubMed

Lichtenstein, Anatoly V

2008-12-01

Cancer is usually considered to be a by-product of design limitations of a multicellular organism and its intrinsic fallibility. However, recent data prompt a revision of some established notions about carcinogenesis and form a new paradigm of carcinogenesis as a highly conserved biological phenomenon - a programmed death of an organism. This altruistic program, which is unleashed when mutagenesis surpasses a certain critical threshold, gives a population the important benefit acting as a guardian of the gene pool against the spread of certain mutant genes. A growing body of evidence supports this point of view: (i) epigenetic changes leading to cancer arise early, simultaneously in many cells and look like deterministic regulation; (ii) concept of cancer stem cell suggests a view of carcinogenesis not as vague transformation but as well known differentiation; (iii) tumor/host relations usually perceived as antagonistic are, in reality, synergistic; (iv) death of an individual from cancer is predetermined and results apparently from a specific activity (killer function) of cancer cell and (v) evolutionary conservation indicates that cancer comes with a general advantage that explains its evolutionary success. A holistic approach to carcinogenesis suggests new avenues of research and new therapeutic strategy.

Application of evolutionary computation in ECAD problems

NASA Astrophysics Data System (ADS)

Lee, Dae-Hyun; Hwang, Seung H.

1998-10-01

Design of modern electronic system is a complicated task which demands the use of computer- aided design (CAD) tools. Since a lot of problems in ECAD are combinatorial optimization problems, evolutionary computations such as genetic algorithms and evolutionary programming have been widely employed to solve those problems. We have applied evolutionary computation techniques to solve ECAD problems such as technology mapping, microcode-bit optimization, data path ordering and peak power estimation, where their benefits are well observed. This paper presents experiences and discusses issues in those applications.

Ecology and evolution of plant–pollinator interactions

PubMed Central

Mitchell, Randall J.; Irwin, Rebecca E.; Flanagan, Rebecca J.; Karron, Jeffrey D.

2009-01-01

Background Some of the most exciting advances in pollination biology have resulted from interdisciplinary research combining ecological and evolutionary perspectives. For example, these two approaches have been essential for understanding the functional ecology of floral traits, the dynamics of pollen transport, competition for pollinator services, and patterns of specialization and generalization in plant–pollinator interactions. However, as research in these and other areas has progressed, many pollination biologists have become more specialized in their research interests, focusing their attention on either evolutionary or ecological questions. We believe that the continuing vigour of a synthetic and interdisciplinary field like pollination biology depends on renewed connections between ecological and evolutionary approaches. Scope In this Viewpoint paper we highlight the application of ecological and evolutionary approaches to two themes in pollination biology: (1) links between pollinator behaviour and plant mating systems, and (2) generalization and specialization in pollination systems. We also describe how mathematical models and synthetic analyses have broadened our understanding of pollination biology, especially in human-modified landscapes. We conclude with several suggestions that we hope will stimulate future research. This Viewpoint also serves as the introduction to this Special Issue on the Ecology and Evolution of Plant–Pollinator Interactions. These papers provide inspiring examples of the synergy between evolutionary and ecological approaches, and offer glimpses of great accomplishments yet to come. PMID:19482881

Ecology and evolution of plant-pollinator interactions.

PubMed

Mitchell, Randall J; Irwin, Rebecca E; Flanagan, Rebecca J; Karron, Jeffrey D

2009-06-01

Some of the most exciting advances in pollination biology have resulted from interdisciplinary research combining ecological and evolutionary perspectives. For example, these two approaches have been essential for understanding the functional ecology of floral traits, the dynamics of pollen transport, competition for pollinator services, and patterns of specialization and generalization in plant-pollinator interactions. However, as research in these and other areas has progressed, many pollination biologists have become more specialized in their research interests, focusing their attention on either evolutionary or ecological questions. We believe that the continuing vigour of a synthetic and interdisciplinary field like pollination biology depends on renewed connections between ecological and evolutionary approaches. In this Viewpoint paper we highlight the application of ecological and evolutionary approaches to two themes in pollination biology: (1) links between pollinator behaviour and plant mating systems, and (2) generalization and specialization in pollination systems. We also describe how mathematical models and synthetic analyses have broadened our understanding of pollination biology, especially in human-modified landscapes. We conclude with several suggestions that we hope will stimulate future research. This Viewpoint also serves as the introduction to this Special Issue on the Ecology and Evolution of Plant-Pollinator Interactions. These papers provide inspiring examples of the synergy between evolutionary and ecological approaches, and offer glimpses of great accomplishments yet to come.

Systems metabolic engineering strategies for the production of amino acids.

PubMed

Ma, Qian; Zhang, Quanwei; Xu, Qingyang; Zhang, Chenglin; Li, Yanjun; Fan, Xiaoguang; Xie, Xixian; Chen, Ning

2017-06-01

Systems metabolic engineering is a multidisciplinary area that integrates systems biology, synthetic biology and evolutionary engineering. It is an efficient approach for strain improvement and process optimization, and has been successfully applied in the microbial production of various chemicals including amino acids. In this review, systems metabolic engineering strategies including pathway-focused approaches, systems biology-based approaches, evolutionary approaches and their applications in two major amino acid producing microorganisms: Corynebacterium glutamicum and Escherichia coli, are summarized.

A Philosophical Perspective on Evolutionary Systems Biology

PubMed Central

Soyer, Orkun S.; Siegal, Mark L.

2015-01-01

Evolutionary systems biology (ESB) is an emerging hybrid approach that integrates methods, models, and data from evolutionary and systems biology. Drawing on themes that arose at a cross-disciplinary meeting on ESB in 2013, we discuss in detail some of the explanatory friction that arises in the interaction between evolutionary and systems biology. These tensions appear because of different modeling approaches, diverse explanatory aims and strategies, and divergent views about the scope of the evolutionary synthesis. We locate these discussions in the context of long-running philosophical deliberations on explanation, modeling, and theoretical synthesis. We show how many of the issues central to ESB’s progress can be understood as general philosophical problems. The benefits of addressing these philosophical issues feed back into philosophy too, because ESB provides excellent examples of scientific practice for the development of philosophy of science and philosophy of biology. PMID:26085823

NASA Space Rocket Logistics Challenges

NASA Technical Reports Server (NTRS)

Neeley, James R.; Jones, James V.; Watson, Michael D.; Bramon, Christopher J.; Inman, Sharon K.; Tuttle, Loraine

2014-01-01

The Space Launch System (SLS) is the new NASA heavy lift launch vehicle and is scheduled for its first mission in 2017. The goal of the first mission, which will be uncrewed, is to demonstrate the integrated system performance of the SLS rocket and spacecraft before a crewed flight in 2021. SLS has many of the same logistics challenges as any other large scale program. Common logistics concerns for SLS include integration of discreet programs geographically separated, multiple prime contractors with distinct and different goals, schedule pressures and funding constraints. However, SLS also faces unique challenges. The new program is a confluence of new hardware and heritage, with heritage hardware constituting seventy-five percent of the program. This unique approach to design makes logistics concerns such as commonality especially problematic. Additionally, a very low manifest rate of one flight every four years makes logistics comparatively expensive. That, along with the SLS architecture being developed using a block upgrade evolutionary approach, exacerbates long-range planning for supportability considerations. These common and unique logistics challenges must be clearly identified and tackled to allow SLS to have a successful program. This paper will address the common and unique challenges facing the SLS programs, along with the analysis and decisions the NASA Logistics engineers are making to mitigate the threats posed by each.

Understanding the mind from an evolutionary perspective: an overview of evolutionary psychology.

PubMed

Shackelford, Todd K; Liddle, James R

2014-05-01

The theory of evolution by natural selection provides the only scientific explanation for the existence of complex adaptations. The design features of the brain, like any organ, are the result of selection pressures operating over deep time. Evolutionary psychology posits that the human brain comprises a multitude of evolved psychological mechanisms, adaptations to specific and recurrent problems of survival and reproduction faced over human evolutionary history. Although some mistakenly view evolutionary psychology as promoting genetic determinism, evolutionary psychologists appreciate and emphasize the interactions between genes and environments. This approach to psychology has led to a richer understanding of a variety of psychological phenomena, and has provided a powerful foundation for generating novel hypotheses. Critics argue that evolutionary psychologists resort to storytelling, but as with any branch of science, empirical testing is a vital component of the field, with hypotheses standing or falling with the weight of the evidence. Evolutionary psychology is uniquely suited to provide a unifying theoretical framework for the disparate subdisciplines of psychology. An evolutionary perspective has provided insights into several subdisciplines of psychology, while simultaneously demonstrating the arbitrary nature of dividing psychological science into such subdisciplines. Evolutionary psychologists have amassed a substantial empirical and theoretical literature, but as a relatively new approach to psychology, many questions remain, with several promising directions for future research. For further resources related to this article, please visit the WIREs website. The authors have declared no conflicts of interest for this article. © 2014 John Wiley & Sons, Ltd.

Multi Sensor Fusion Using Fitness Adaptive Differential Evolution

NASA Astrophysics Data System (ADS)

Giri, Ritwik; Ghosh, Arnob; Chowdhury, Aritra; Das, Swagatam

The rising popularity of multi-source, multi-sensor networks supports real-life applications calls for an efficient and intelligent approach to information fusion. Traditional optimization techniques often fail to meet the demands. The evolutionary approach provides a valuable alternative due to its inherent parallel nature and its ability to deal with difficult problems. We present a new evolutionary approach based on a modified version of Differential Evolution (DE), called Fitness Adaptive Differential Evolution (FiADE). FiADE treats sensors in the network as distributed intelligent agents with various degrees of autonomy. Existing approaches based on intelligent agents cannot completely answer the question of how their agents could coordinate their decisions in a complex environment. The proposed approach is formulated to produce good result for the problems that are high-dimensional, highly nonlinear, and random. The proposed approach gives better result in case of optimal allocation of sensors. The performance of the proposed approach is compared with an evolutionary algorithm coordination generalized particle model (C-GPM).

Gender approaches to evolutionary multi-objective optimization using pre-selection of criteria

NASA Astrophysics Data System (ADS)

Kowalczuk, Zdzisław; Białaszewski, Tomasz

2018-01-01

A novel idea to perform evolutionary computations (ECs) for solving highly dimensional multi-objective optimization (MOO) problems is proposed. Following the general idea of evolution, it is proposed that information about gender is used to distinguish between various groups of objectives and identify the (aggregate) nature of optimality of individuals (solutions). This identification is drawn out of the fitness of individuals and applied during parental crossover in the processes of evolutionary multi-objective optimization (EMOO). The article introduces the principles of the genetic-gender approach (GGA) and virtual gender approach (VGA), which are not just evolutionary techniques, but constitute a completely new rule (philosophy) for use in solving MOO tasks. The proposed approaches are validated against principal representatives of the EMOO algorithms of the state of the art in solving benchmark problems in the light of recognized EC performance criteria. The research shows the superiority of the gender approach in terms of effectiveness, reliability, transparency, intelligibility and MOO problem simplification, resulting in the great usefulness and practicability of GGA and VGA. Moreover, an important feature of GGA and VGA is that they alleviate the 'curse' of dimensionality typical of many engineering designs.

MultiSeq: unifying sequence and structure data for evolutionary analysis

PubMed Central

Roberts, Elijah; Eargle, John; Wright, Dan; Luthey-Schulten, Zaida

2006-01-01

Background Since the publication of the first draft of the human genome in 2000, bioinformatic data have been accumulating at an overwhelming pace. Currently, more than 3 million sequences and 35 thousand structures of proteins and nucleic acids are available in public databases. Finding correlations in and between these data to answer critical research questions is extremely challenging. This problem needs to be approached from several directions: information science to organize and search the data; information visualization to assist in recognizing correlations; mathematics to formulate statistical inferences; and biology to analyze chemical and physical properties in terms of sequence and structure changes. Results Here we present MultiSeq, a unified bioinformatics analysis environment that allows one to organize, display, align and analyze both sequence and structure data for proteins and nucleic acids. While special emphasis is placed on analyzing the data within the framework of evolutionary biology, the environment is also flexible enough to accommodate other usage patterns. The evolutionary approach is supported by the use of predefined metadata, adherence to standard ontological mappings, and the ability for the user to adjust these classifications using an electronic notebook. MultiSeq contains a new algorithm to generate complete evolutionary profiles that represent the topology of the molecular phylogenetic tree of a homologous group of distantly related proteins. The method, based on the multidimensional QR factorization of multiple sequence and structure alignments, removes redundancy from the alignments and orders the protein sequences by increasing linear dependence, resulting in the identification of a minimal basis set of sequences that spans the evolutionary space of the homologous group of proteins. Conclusion MultiSeq is a major extension of the Multiple Alignment tool that is provided as part of VMD, a structural visualization program for analyzing molecular dynamics simulations. Both are freely distributed by the NIH Resource for Macromolecular Modeling and Bioinformatics and MultiSeq is included with VMD starting with version 1.8.5. The MultiSeq website has details on how to download and use the software: PMID:16914055

[Evolutionary medicine: A new look on health and disease].

PubMed

Bauduer, F

2017-03-01

Evolutionary medicine represents an innovative approach deriving from evolutionary biology. It includes the initial Darwin's view, its actualization in the light of progresses in genetics and also dissident theories (i.e. non gene-based) particularly epigenetics. This approach enables us to reconsider the pathophysiology of numerous diseases, as for instance, infection, and our so-called diseases of civilization especially obesity, type 2 diabetes, allergy or cancer. Evolutionary medicine may also improve our knowledge regarding inter-individual variation in susceptibility to disease or drugs. Furthermore, it points out the impact of our behaviors and environment on the genesis of a series of diseases. Copyright © 2016 Société Nationale Française de Médecine Interne (SNFMI). Published by Elsevier SAS. All rights reserved.

A Novel Handwritten Letter Recognizer Using Enhanced Evolutionary Neural Network

NASA Astrophysics Data System (ADS)

Mahmoudi, Fariborz; Mirzashaeri, Mohsen; Shahamatnia, Ehsan; Faridnia, Saed

This paper introduces a novel design for handwritten letter recognition by employing a hybrid back-propagation neural network with an enhanced evolutionary algorithm. Feeding the neural network consists of a new approach which is invariant to translation, rotation, and scaling of input letters. Evolutionary algorithm is used for the global search of the search space and the back-propagation algorithm is used for the local search. The results have been computed by implementing this approach for recognizing 26 English capital letters in the handwritings of different people. The computational results show that the neural network reaches very satisfying results with relatively scarce input data and a promising performance improvement in convergence of the hybrid evolutionary back-propagation algorithms is exhibited.

Inherit the Policy: A Sociocultural Approach to Understanding Evolutionary Biology Policy in South Carolina

ERIC Educational Resources Information Center

Moore, Gregory D.

2012-01-01

South Carolina biology Indicator 5.6 calls for students to "Summarize ways that scientists use data from a variety of sources to investigate and critically analyze aspects of evolutionary theory" (South Carolina Department of Education, 2006). Levinson and Sutton (2001) offered a sociocultural approach to policy that considers cultural…

Underlying Principles of Natural Selection in Network Evolution: Systems Biology Approach

PubMed Central

Chen, Bor-Sen; Wu, Wei-Sheng

2007-01-01

Systems biology is a rapidly expanding field that integrates diverse areas of science such as physics, engineering, computer science, mathematics, and biology toward the goal of elucidating the underlying principles of hierarchical metabolic and regulatory systems in the cell, and ultimately leading to predictive understanding of cellular response to perturbations. Because post-genomics research is taking place throughout the tree of life, comparative approaches offer a way for combining data from many organisms to shed light on the evolution and function of biological networks from the gene to the organismal level. Therefore, systems biology can build on decades of theoretical work in evolutionary biology, and at the same time evolutionary biology can use the systems biology approach to go in new uncharted directions. In this study, we present a review of how the post-genomics era is adopting comparative approaches and dynamic system methods to understand the underlying design principles of network evolution and to shape the nascent field of evolutionary systems biology. Finally, the application of evolutionary systems biology to robust biological network designs is also discussed from the synthetic biology perspective. PMID:19468310

Bell-Curve Based Evolutionary Strategies for Structural Optimization

NASA Technical Reports Server (NTRS)

Kincaid, Rex K.

2001-01-01

Evolutionary methods are exceedingly popular with practitioners of many fields; more so than perhaps any optimization tool in existence. Historically Genetic Algorithms (GAs) led the way in practitioner popularity. However, in the last ten years Evolutionary Strategies (ESs) and Evolutionary Programs (EPS) have gained a significant foothold. One partial explanation for this shift is the interest in using GAs to solve continuous optimization problems. The typical GA relies upon a cumbersome binary representation of the design variables. An ES or EP, however, works directly with the real-valued design variables. For detailed references on evolutionary methods in general and ES or EP in specific see Back and Dasgupta and Michalesicz. We call our evolutionary algorithm BCB (bell curve based) since it is based upon two normal distributions.

Are attractors 'strange', or is life more complicated than the simple laws of physics?

PubMed

Pogun, S

2001-01-01

Interesting and intriguing questions involve complex systems whose properties cannot be explained fully by reductionist approaches. Last century was dominated by physics, and applying the simple laws of physics to biology appeared to be a practical solution to understand living organisms. However, although some attributes of living organisms involve physico-chemical properties, the genetic program and evolutionary history of complex biological systems make them unique and unpredictable. Furthermore, there are and will be 'unobservable' phenomena in biology which have to be accounted for.

A Tale of Four Stories: Soil Ecology, Theory, Evolution and the Publication System

PubMed Central

Barot, Sébastien; Blouin, Manuel; Fontaine, Sébastien; Jouquet, Pascal; Lata, Jean-Christophe; Mathieu, Jérôme

2007-01-01

Background Soil ecology has produced a huge corpus of results on relations between soil organisms, ecosystem processes controlled by these organisms and links between belowground and aboveground processes. However, some soil scientists think that soil ecology is short of modelling and evolutionary approaches and has developed too independently from general ecology. We have tested quantitatively these hypotheses through a bibliographic study (about 23000 articles) comparing soil ecology journals, generalist ecology journals, evolutionary ecology journals and theoretical ecology journals. Findings We have shown that soil ecology is not well represented in generalist ecology journals and that soil ecologists poorly use modelling and evolutionary approaches. Moreover, the articles published by a typical soil ecology journal (Soil Biology and Biochemistry) are cited by and cite low percentages of articles published in generalist ecology journals, evolutionary ecology journals and theoretical ecology journals. Conclusion This confirms our hypotheses and suggests that soil ecology would benefit from an effort towards modelling and evolutionary approaches. This effort should promote the building of a general conceptual framework for soil ecology and bridges between soil ecology and general ecology. We give some historical reasons for the parsimonious use of modelling and evolutionary approaches by soil ecologists. We finally suggest that a publication system that classifies journals according to their Impact Factors and their level of generality is probably inadequate to integrate “particularity” (empirical observations) and “generality” (general theories), which is the goal of all natural sciences. Such a system might also be particularly detrimental to the development of a science such as ecology that is intrinsically multidisciplinary. PMID:18043755

Evolutionary Creation: Moving beyond the Evolution versus Creation Debate

ERIC Educational Resources Information Center

Lamoureux, Denis O.

2010-01-01

Evolutionary creation offers a conservative Christian approach to evolution. It explores biblical faith and evolutionary science through a Two Divine Books model and proposes a complementary relationship between Scripture and science. The Book of God's Words discloses the spiritual character of the world, while the Book of God's Works reveals the…

Using Evolutionary Data in Developing Phylogenetic Trees: A Scaffolded Approach with Authentic Data

ERIC Educational Resources Information Center

Davenport, K. D.; Milks, Kirstin Jane; Van Tassell, Rebecca

2015-01-01

Analyzing evolutionary relationships requires that students have a thorough understanding of evidence and of how scientists use evidence to develop these relationships. In this lesson sequence, students work in groups to process many different lines of evidence of evolutionary relationships between ungulates, then construct a scientific argument…

Predicting evolutionary responses to climate change in the sea.

PubMed

Munday, Philip L; Warner, Robert R; Monro, Keyne; Pandolfi, John M; Marshall, Dustin J

2013-12-01

An increasing number of short-term experimental studies show significant effects of projected ocean warming and ocean acidification on the performance on marine organisms. Yet, it remains unclear if we can reliably predict the impact of climate change on marine populations and ecosystems, because we lack sufficient understanding of the capacity for marine organisms to adapt to rapid climate change. In this review, we emphasise why an evolutionary perspective is crucial to understanding climate change impacts in the sea and examine the approaches that may be useful for addressing this challenge. We first consider what the geological record and present-day analogues of future climate conditions can tell us about the potential for adaptation to climate change. We also examine evidence that phenotypic plasticity may assist marine species to persist in a rapidly changing climate. We then outline the various experimental approaches that can be used to estimate evolutionary potential, focusing on molecular tools, quantitative genetics, and experimental evolution, and we describe the benefits of combining different approaches to gain a deeper understanding of evolutionary potential. Our goal is to provide a platform for future research addressing the evolutionary potential for marine organisms to cope with climate change. © 2013 John Wiley & Sons Ltd/CNRS.

Pattern and Process in the Comparative Study of Convergent Evolution.

PubMed

Mahler, D Luke; Weber, Marjorie G; Wagner, Catherine E; Ingram, Travis

2017-08-01

Understanding processes that have shaped broad-scale biodiversity patterns is a fundamental goal in evolutionary biology. The development of phylogenetic comparative methods has yielded a tool kit for analyzing contemporary patterns by explicitly modeling processes of change in the past, providing neontologists tools for asking questions previously accessible only for select taxa via the fossil record or laboratory experimentation. The comparative approach, however, differs operationally from alternative approaches to studying convergence in that, for studies of only extant species, convergence must be inferred using evolutionary process models rather than being directly measured. As a result, investigation of evolutionary pattern and process cannot be decoupled in comparative studies of convergence, even though such a decoupling could in theory guard against adaptationist bias. Assumptions about evolutionary process underlying comparative tools can shape the inference of convergent pattern in sometimes profound ways and can color interpretation of such patterns. We discuss these issues and other limitations common to most phylogenetic comparative approaches and suggest ways that they can be avoided in practice. We conclude by promoting a multipronged approach to studying convergence that integrates comparative methods with complementary tests of evolutionary mechanisms and includes ecological and biogeographical perspectives. Carefully employed, the comparative method remains a powerful tool for enriching our understanding of convergence in macroevolution, especially for investigation of why convergence occurs in some settings but not others.

TARGETED CAPTURE IN EVOLUTIONARY AND ECOLOGICAL GENOMICS

PubMed Central

Jones, Matthew R.; Good, Jeffrey M.

2016-01-01

The rapid expansion of next-generation sequencing has yielded a powerful array of tools to address fundamental biological questions at a scale that was inconceivable just a few years ago. Various genome partitioning strategies to sequence select subsets of the genome have emerged as powerful alternatives to whole genome sequencing in ecological and evolutionary genomic studies. High throughput targeted capture is one such strategy that involves the parallel enrichment of pre-selected genomic regions of interest. The growing use of targeted capture demonstrates its potential power to address a range of research questions, yet these approaches have yet to expand broadly across labs focused on evolutionary and ecological genomics. In part, the use of targeted capture has been hindered by the logistics of capture design and implementation in species without established reference genomes. Here we aim to 1) increase the accessibility of targeted capture to researchers working in non-model taxa by discussing capture methods that circumvent the need of a reference genome, 2) highlight the evolutionary and ecological applications where this approach is emerging as a powerful sequencing strategy, and 3) discuss the future of targeted capture and other genome partitioning approaches in light of the increasing accessibility of whole genome sequencing. Given the practical advantages and increasing feasibility of high-throughput targeted capture, we anticipate an ongoing expansion of capture-based approaches in evolutionary and ecological research, synergistic with an expansion of whole genome sequencing. PMID:26137993

How can we estimate natural selection on endocrine traits? Lessons from evolutionary biology

PubMed Central

2016-01-01

An evolutionary perspective can enrich almost any endeavour in biology, providing a deeper understanding of the variation we see in nature. To this end, evolutionary endocrinologists seek to describe the fitness consequences of variation in endocrine traits. Much of the recent work in our field, however, follows a flawed approach to the study of how selection shapes endocrine traits. Briefly, this approach relies on among-individual correlations between endocrine phenotypes (often circulating hormone levels) and fitness metrics to estimate selection on those endocrine traits. Adaptive plasticity in both endocrine and fitness-related traits can drive these correlations, generating patterns that do not accurately reflect natural selection. We illustrate why this approach to studying selection on endocrine traits is problematic, referring to work from evolutionary biologists who, decades ago, described this problem as it relates to a variety of other plastic traits. We extend these arguments to evolutionary endocrinology, where the likelihood that this flaw generates bias in estimates of selection is unusually high due to the exceptional responsiveness of hormones to environmental conditions, and their function to induce adaptive life-history responses to environmental variation. We end with a review of productive approaches for investigating the fitness consequences of variation in endocrine traits that we expect will generate exciting advances in our understanding of endocrine system evolution. PMID:27881753

Using traveling salesman problem algorithms for evolutionary tree construction.

PubMed

Korostensky, C; Gonnet, G H

2000-07-01

The construction of evolutionary trees is one of the major problems in computational biology, mainly due to its complexity. We present a new tree construction method that constructs a tree with minimum score for a given set of sequences, where the score is the amount of evolution measured in PAM distances. To do this, the problem of tree construction is reduced to the Traveling Salesman Problem (TSP). The input for the TSP algorithm are the pairwise distances of the sequences and the output is a circular tour through the optimal, unknown tree plus the minimum score of the tree. The circular order and the score can be used to construct the topology of the optimal tree. Our method can be used for any scoring function that correlates to the amount of changes along the branches of an evolutionary tree, for instance it could also be used for parsimony scores, but it cannot be used for least squares fit of distances. A TSP solution reduces the space of all possible trees to 2n. Using this order, we can guarantee that we reconstruct a correct evolutionary tree if the absolute value of the error for each distance measurement is smaller than f2.gif" BORDER="0">, where f3.gif" BORDER="0">is the length of the shortest edge in the tree. For data sets with large errors, a dynamic programming approach is used to reconstruct the tree. Finally simulations and experiments with real data are shown.

LEGEND, a LEO-to-GEO Environment Debris Model

NASA Technical Reports Server (NTRS)

Liou, Jer Chyi; Hall, Doyle T.

2013-01-01

LEGEND (LEO-to-GEO Environment Debris model) is a three-dimensional orbital debris evolutionary model that is capable of simulating the historical and future debris populations in the near-Earth environment. The historical component in LEGEND adopts a deterministic approach to mimic the known historical populations. Launched rocket bodies, spacecraft, and mission-related debris (rings, bolts, etc.) are added to the simulated environment. Known historical breakup events are reproduced, and fragments down to 1 mm in size are created. The LEGEND future projection component adopts a Monte Carlo approach and uses an innovative pair-wise collision probability evaluation algorithm to simulate the future breakups and the growth of the debris populations. This algorithm is based on a new "random sampling in time" approach that preserves characteristics of the traditional approach and captures the rapidly changing nature of the orbital debris environment. LEGEND is a Fortran 90-based numerical simulation program. It operates in a UNIX/Linux environment.

Developing of the future: scaffolded Darwinism in societal evolution.

PubMed

Andersson, Claes; Törnberg, Anton; Törnberg, Petter

2014-08-01

We sympathize with the project of a synthetic approach for devising a "theory of intentional change" and agree that Darwinism should be central in such a theory. But Darwinism is not the only process of evolution that needs to be included. Evolutionary biology itself has taken such a turn recently, with the emergence of developmental evolutionary approaches.

Evolutionary change in physiological phenotypes along the human lineage

PubMed Central

Vining, Alexander Q.; Nunn, Charles L.

2016-01-01

Background and Objectives: Research in evolutionary medicine provides many examples of how evolution has shaped human susceptibility to disease. Traits undergoing rapid evolutionary change may result in associated costs or reduce the energy available to other traits. We hypothesize that humans have experienced more such changes than other primates as a result of major evolutionary change along the human lineage. We investigated 41 physiological traits across 50 primate species to identify traits that have undergone marked evolutionary change along the human lineage. Methodology: We analysed the data using two Bayesian phylogenetic comparative methods. One approach models trait covariation in non-human primates and predicts human phenotypes to identify whether humans are evolutionary outliers. The other approach models adaptive shifts under an Ornstein-Uhlenbeck model of evolution to assess whether inferred shifts are more common on the human branch than on other primate lineages. Results: We identified four traits with strong evidence for an evolutionary increase on the human lineage (amylase, haematocrit, phosphorus and monocytes) and one trait with strong evidence for decrease (neutrophilic bands). Humans exhibited more cases of distinct evolutionary change than other primates. Conclusions and Implications: Human physiology has undergone increased evolutionary change compared to other primates. Long distance running may have contributed to increases in haematocrit and mean corpuscular haemoglobin concentration, while dietary changes are likely related to increases in amylase. In accordance with the pathogen load hypothesis, human monocyte levels were increased, but many other immune-related measures were not. Determining the mechanisms underlying conspicuous evolutionary change in these traits may provide new insights into human disease. PMID:27615376

Bistability of Evolutionary Stable Vaccination Strategies in the Reinfection SIRI Model.

PubMed

Martins, José; Pinto, Alberto

2017-04-01

We use the reinfection SIRI epidemiological model to analyze the impact of education programs and vaccine scares on individuals decisions to vaccinate or not. The presence of the reinfection provokes the novelty of the existence of three Nash equilibria for the same level of the morbidity relative risk instead of a single Nash equilibrium as occurs in the SIR model studied by Bauch and Earn (PNAS 101:13391-13394, 2004). The existence of three Nash equilibria, with two of them being evolutionary stable, introduces two scenarios with relevant and opposite features for the same level of the morbidity relative risk: the low-vaccination scenario corresponding to the evolutionary stable vaccination strategy, where individuals will vaccinate with a low probability; and the high-vaccination scenario corresponding to the evolutionary stable vaccination strategy, where individuals will vaccinate with a high probability. We introduce the evolutionary vaccination dynamics for the SIRI model and we prove that it is bistable. The bistability of the evolutionary dynamics indicates that the damage provoked by false scares on the vaccination perceived morbidity risks can be much higher and much more persistent than in the SIR model. Furthermore, the vaccination education programs to be efficient they need to implement a mechanism to suddenly increase the vaccination coverage level.

Bell-Curve Based Evolutionary Strategies for Structural Optimization

NASA Technical Reports Server (NTRS)

Kincaid, Rex K.

2000-01-01

Evolutionary methods are exceedingly popular with practitioners of many fields; more so than perhaps any optimization tool in existence. Historically Genetic Algorithms (GAs) led the way in practitioner popularity (Reeves 1997). However, in the last ten years Evolutionary Strategies (ESs) and Evolutionary Programs (EPS) have gained a significant foothold (Glover 1998). One partial explanation for this shift is the interest in using GAs to solve continuous optimization problems. The typical GA relies upon a cumber-some binary representation of the design variables. An ES or EP, however, works directly with the real-valued design variables. For detailed references on evolutionary methods in general and ES or EP in specific see Back (1996) and Dasgupta and Michalesicz (1997). We call our evolutionary algorithm BCB (bell curve based) since it is based upon two normal distributions.

Solution of the Generalized Noah's Ark Problem.

PubMed

Billionnet, Alain

2013-01-01

The phylogenetic diversity (PD) of a set of species is a measure of the evolutionary distance among the species in the collection, based on a phylogenetic tree. Such a tree is composed of a root, internal nodes, and leaves that correspond to the set of taxa under study. With each edge of the tree is associated a non-negative branch length (evolutionary distance). If a particular survival probability is associated with each taxon, the PD measure becomes the expected PD measure. In the Noah's Ark Problem (NAP) introduced by Weitzman (1998), these survival probabilities can be increased at some cost. The problem is to determine how best to allocate a limited amount of resources to maximize the expected PD of the considered species. It is easy to formulate the NAP as a (difficult) nonlinear 0-1 programming problem. The aim of this article is to show that a general version of the NAP (GNAP) can be solved simply and efficiently with any set of edge weights and any set of survival probabilities by using standard mixed-integer linear programming software. The crucial point to move from a nonlinear program in binary variables to a mixed-integer linear program, is to approximate the logarithmic function by the lower envelope of a set of tangents to the curve. Solving the obtained mixed-integer linear program provides not only a near-optimal solution but also an upper bound on the value of the optimal solution. We also applied this approach to a generalization of the nature reserve problem (GNRP) that consists of selecting a set of regions to be conserved so that the expected PD of the set of species present in these regions is maximized. In this case, the survival probabilities of different taxa are not independent of each other. Computational results are presented to illustrate potentialities of the approach. Near-optimal solutions with hypothetical phylogenetic trees comprising about 4000 taxa are obtained in a few seconds or minutes of computing time for the GNAP, and in about 30 min for the GNRP. In all the cases the average guarantee varies from 0% to 1.20%.

A theoretical comparison of evolutionary algorithms and simulated annealing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hart, W.E.

1995-08-28

This paper theoretically compares the performance of simulated annealing and evolutionary algorithms. Our main result is that under mild conditions a wide variety of evolutionary algorithms can be shown to have greater performance than simulated annealing after a sufficiently large number of function evaluations. This class of EAs includes variants of evolutionary strategie and evolutionary programming, the canonical genetic algorithm, as well as a variety of genetic algorithms that have been applied to combinatorial optimization problems. The proof of this result is based on a performance analysis of a very general class of stochastic optimization algorithms, which has implications formore » the performance of a variety of other optimization algorithm.« less

Sex, acceleration, brain imaging, and rhesus monkeys: Converging evidence for an evolutionary bias for looming auditory motion

NASA Astrophysics Data System (ADS)

Neuhoff, John G.

2003-04-01

Increasing acoustic intensity is a primary cue to looming auditory motion. Perceptual overestimation of increasing intensity could provide an evolutionary selective advantage by specifying that an approaching sound source is closer than actual, thus affording advanced warning and more time than expected to prepare for the arrival of the source. Here, multiple lines of converging evidence for this evolutionary hypothesis are presented. First, it is shown that intensity change specifying accelerating source approach changes in loudness more than equivalent intensity change specifying decelerating source approach. Second, consistent with evolutionary hunter-gatherer theories of sex-specific spatial abilities, it is shown that females have a significantly larger bias for rising intensity than males. Third, using functional magnetic resonance imaging in conjunction with approaching and receding auditory motion, it is shown that approaching sources preferentially activate a specific neural network responsible for attention allocation, motor planning, and translating perception into action. Finally, it is shown that rhesus monkeys also exhibit a rising intensity bias by orienting longer to looming tones than to receding tones. Together these results illustrate an adaptive perceptual bias that has evolved because it provides a selective advantage in processing looming acoustic sources. [Work supported by NSF and CDC.

Neo-Darwinists and Neo-Aristotelians: how to talk about natural purpose.

PubMed

Woodford, Peter

2016-12-01

This paper examines the points of disagreement between Neo-Darwinian and recent Neo-Aristotelian discussions of the status of purposive language in biology. I discuss recent Neo-Darwinian "evolutionary" treatments and distinguish three ways to deal with the philosophical status of teleological language of purpose: teleological error theory, methodological teleology, and Darwinian teleological realism. I then show how "non-evolutionary" Neo-Aristotelian approaches in the work of Michael Thompson and Philippa Foot differ from these by offering a view of purposiveness grounded in life-cycle patterns, rather than in long-term evolutionary processes or natural selection. Finally, I argue that the crucial difference between Neo-Darwinian and Neo-Aristotelian approaches regards the question of whether or not reproduction deserves the status of an "ultimate" aim of organisms. I offer reasons to reject the concept of an "ultimate" aim in evolutionary biology and to reject the notion that reproduction serves a purpose. I argue that evolutionary biology is not in the position to determine what the "ultimate" explanation of natural purpose is.

Phylogenetic Paleoecology: Tree-Thinking and Ecology in Deep Time.

PubMed

Lamsdell, James C; Congreve, Curtis R; Hopkins, Melanie J; Krug, Andrew Z; Patzkowsky, Mark E

2017-06-01

The new and emerging field of phylogenetic paleoecology leverages the evolutionary relationships among species to explain temporal and spatial changes in species diversity, abundance, and distribution in deep time. This field is poised for rapid progress as knowledge of the evolutionary relationships among fossil species continues to expand. In particular, this approach will lend new insights to many of the longstanding questions in evolutionary biology, such as: the relationships among character change, ecology, and evolutionary rates; the processes that determine the evolutionary relationships among species within communities and along environmental gradients; and the phylogenetic signal underlying ecological selectivity in background and mass extinctions and in major evolutionary radiations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Divergent gene expression in the conserved dauer stage of the nematodes Pristionchus pacificus and Caenorhabditis elegans.

PubMed

Sinha, Amit; Sommer, Ralf J; Dieterich, Christoph

2012-06-19

An organism can respond to changing environmental conditions by adjusting gene regulation and by forming alternative phenotypes. In nematodes, these mechanisms are coupled because many species will form dauer larvae, a stress-resistant and non-aging developmental stage, when exposed to unfavorable environmental conditions, and execute gene expression programs that have been selected for the survival of the animal in the wild. These dauer larvae represent an environmentally induced, homologous developmental stage across many nematode species, sharing conserved morphological and physiological properties. Hence it can be expected that some core components of the associated transcriptional program would be conserved across species, while others might diverge over the course of evolution. However, transcriptional and metabolic analysis of dauer development has been largely restricted to Caenorhabditis elegans. Here, we use a transcriptomic approach to compare the dauer stage in the evolutionary model system Pristionchus pacificus with the dauer stage in C. elegans. We have employed Agilent microarrays, which represent 20,446 P. pacificus and 20,143 C. elegans genes to show an unexpected divergence in the expression profiles of these two nematodes in dauer and dauer exit samples. P. pacificus and C. elegans differ in the dynamics and function of genes that are differentially expressed. We find that only a small number of orthologous gene pairs show similar expression pattern in the dauers of the two species, while the non-orthologous fraction of genes is a major contributor to the active transcriptome in dauers. Interestingly, many of the genes acquired by horizontal gene transfer and orphan genes in P. pacificus, are differentially expressed suggesting that these genes are of evolutionary and functional importance. Our data set provides a catalog for future functional investigations and indicates novel insight into evolutionary mechanisms. We discuss the limited conservation of core developmental and transcriptional programs as a common aspect of animal evolution.

Divergent gene expression in the conserved dauer stage of the nematodes Pristionchus pacificus and Caenorhabditis elegans

PubMed Central

2012-01-01

Background An organism can respond to changing environmental conditions by adjusting gene regulation and by forming alternative phenotypes. In nematodes, these mechanisms are coupled because many species will form dauer larvae, a stress-resistant and non-aging developmental stage, when exposed to unfavorable environmental conditions, and execute gene expression programs that have been selected for the survival of the animal in the wild. These dauer larvae represent an environmentally induced, homologous developmental stage across many nematode species, sharing conserved morphological and physiological properties. Hence it can be expected that some core components of the associated transcriptional program would be conserved across species, while others might diverge over the course of evolution. However, transcriptional and metabolic analysis of dauer development has been largely restricted to Caenorhabditis elegans. Here, we use a transcriptomic approach to compare the dauer stage in the evolutionary model system Pristionchus pacificus with the dauer stage in C. elegans. Results We have employed Agilent microarrays, which represent 20,446 P. pacificus and 20,143 C. elegans genes to show an unexpected divergence in the expression profiles of these two nematodes in dauer and dauer exit samples. P. pacificus and C. elegans differ in the dynamics and function of genes that are differentially expressed. We find that only a small number of orthologous gene pairs show similar expression pattern in the dauers of the two species, while the non-orthologous fraction of genes is a major contributor to the active transcriptome in dauers. Interestingly, many of the genes acquired by horizontal gene transfer and orphan genes in P. pacificus, are differentially expressed suggesting that these genes are of evolutionary and functional importance. Conclusion Our data set provides a catalog for future functional investigations and indicates novel insight into evolutionary mechanisms. We discuss the limited conservation of core developmental and transcriptional programs as a common aspect of animal evolution. PMID:22712530

The role of evolutionary biology in research and control of liver flukes in Southeast Asia.

PubMed

Echaubard, Pierre; Sripa, Banchob; Mallory, Frank F; Wilcox, Bruce A

2016-09-01

Stimulated largely by the availability of new technology, biomedical research at the molecular-level and chemical-based control approaches arguably dominate the field of infectious diseases. Along with this, the proximate view of disease etiology predominates to the exclusion of the ultimate, evolutionary biology-based, causation perspective. Yet, historically and up to today, research in evolutionary biology has provided much of the foundation for understanding the mechanisms underlying disease transmission dynamics, virulence, and the design of effective integrated control strategies. Here we review the state of knowledge regarding the biology of Asian liver Fluke-host relationship, parasitology, phylodynamics, drug-based interventions and liver Fluke-related cancer etiology from an evolutionary biology perspective. We consider how evolutionary principles, mechanisms and research methods could help refine our understanding of clinical disease associated with infection by Liver Flukes as well as their transmission dynamics. We identify a series of questions for an evolutionary biology research agenda for the liver Fluke that should contribute to an increased understanding of liver Fluke-associated diseases. Finally, we describe an integrative evolutionary medicine approach to liver Fluke prevention and control highlighting the need to better contextualize interventions within a broader human health and sustainable development framework. Copyright © 2016 Elsevier B.V. All rights reserved.

The Role of Evolutionary Biology in Research and Control of Liver Flukes in Southeast Asia

PubMed Central

Echaubard, Pierre; Sripa, Banchob; Mallory, Frank F.; Wilcox, Bruce A.

2016-01-01

Stimulated largely by the availability of new technology, biomedical research at the molecular-level and chemical-based control approaches arguably dominate the field of infectious diseases. Along with this, the proximate view of disease etiology predominates to the exclusion of the ultimate, evolutionary biology-based, causation perspective. Yet, historically and up to today, research in evolutionary biology has provided much of the foundation for understanding the mechanisms underlying disease transmission dynamics, virulence, and the design of effective integrated control strategies. Here we review the state of knowledge regarding the biology of Asian liver Fluke-host relationship, parasitology, phylodynamics, drug-based interventions and liver Fluke-related cancer etiology from an evolutionary biology perspective. We consider how evolutionary principles, mechanisms and research methods could help refine our understanding of clinical disease associated with infection by Liver Flukes as well as their transmission dynamics. We identify a series of questions for an evolutionary biology research agenda for the liver Fluke that should contribute to an increased understanding of liver Fluke-associated diseases. Finally, we describe an integrative evolutionary medicine approach to liver Fluke prevention and control highlighting the need to better contextualize interventions within a broader human health and sustainable development framework. PMID:27197053

Evolution of the INMARSAT aeronautical system: Service, system, and business considerations

NASA Technical Reports Server (NTRS)

Sengupta, Jay R.

1995-01-01

A market-driven approach was adopted to develop enhancements to the Inmarsat-Aeronautical system, to address the requirements of potential new market segments. An evolutionary approach and well differentiated product/service portfolio was required, to minimize system upgrade costs and market penetration, respectively. The evolved system definition serves to minimize equipment cost/size/mass for short/medium range aircraft, by reducing the antenna gain requirement and relaxing the performance requirements for non safety-related communications. A validation program involving simulation, laboratory tests, over-satellite tests and flight trials is being conducted to confirm the system definition. Extensive market research has been conducted to determine user requirements and to quantify market demand for future Inmarsat Aero-1 AES, using sophisticated computer assisted survey techniques.

Genetic Network Programming with Reconstructed Individuals

NASA Astrophysics Data System (ADS)

Ye, Fengming; Mabu, Shingo; Wang, Lutao; Eto, Shinji; Hirasawa, Kotaro

A lot of research on evolutionary computation has been done and some significant classical methods such as Genetic Algorithm (GA), Genetic Programming (GP), Evolutionary Programming (EP), and Evolution Strategies (ES) have been studied. Recently, a new approach named Genetic Network Programming (GNP) has been proposed. GNP can evolve itself and find the optimal solution. It is based on the idea of Genetic Algorithm and uses the data structure of directed graphs. Many papers have demonstrated that GNP can deal with complex problems in the dynamic environments very efficiently and effectively. As a result, recently, GNP is getting more and more attentions and is used in many different areas such as data mining, extracting trading rules of stock markets, elevator supervised control systems, etc., and GNP has obtained some outstanding results. Focusing on the GNP's distinguished expression ability of the graph structure, this paper proposes a method named Genetic Network Programming with Reconstructed Individuals (GNP-RI). The aim of GNP-RI is to balance the exploitation and exploration of GNP, that is, to strengthen the exploitation ability by using the exploited information extensively during the evolution process of GNP and finally obtain better performances than that of GNP. In the proposed method, the worse individuals are reconstructed and enhanced by the elite information before undergoing genetic operations (mutation and crossover). The enhancement of worse individuals mimics the maturing phenomenon in nature, where bad individuals can become smarter after receiving a good education. In this paper, GNP-RI is applied to the tile-world problem which is an excellent bench mark for evaluating the proposed architecture. The performance of GNP-RI is compared with that of the conventional GNP. The simulation results show some advantages of GNP-RI demonstrating its superiority over the conventional GNPs.

XTALOPT: An open-source evolutionary algorithm for crystal structure prediction

NASA Astrophysics Data System (ADS)

Lonie, David C.; Zurek, Eva

2011-02-01

The implementation and testing of XTALOPT, an evolutionary algorithm for crystal structure prediction, is outlined. We present our new periodic displacement (ripple) operator which is ideally suited to extended systems. It is demonstrated that hybrid operators, which combine two pure operators, reduce the number of duplicate structures in the search. This allows for better exploration of the potential energy surface of the system in question, while simultaneously zooming in on the most promising regions. A continuous workflow, which makes better use of computational resources as compared to traditional generation based algorithms, is employed. Various parameters in XTALOPT are optimized using a novel benchmarking scheme. XTALOPT is available under the GNU Public License, has been interfaced with various codes commonly used to study extended systems, and has an easy to use, intuitive graphical interface. Program summaryProgram title:XTALOPT Catalogue identifier: AEGX_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEGX_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GPL v2.1 or later [1] No. of lines in distributed program, including test data, etc.: 36 849 No. of bytes in distributed program, including test data, etc.: 1 149 399 Distribution format: tar.gz Programming language: C++ Computer: PCs, workstations, or clusters Operating system: Linux Classification: 7.7 External routines: QT [2], OpenBabel [3], AVOGADRO [4], SPGLIB [8] and one of: VASP [5], PWSCF [6], GULP [7]. Nature of problem: Predicting the crystal structure of a system from its stoichiometry alone remains a grand challenge in computational materials science, chemistry, and physics. Solution method: Evolutionary algorithms are stochastic search techniques which use concepts from biological evolution in order to locate the global minimum on their potential energy surface. Our evolutionary algorithm, XTALOPT, is freely available to the scientific community for use and collaboration under the GNU Public License. Running time: User dependent. The program runs until stopped by the user.

Evolutionary Medicine: The Ongoing Evolution of Human Physiology and Metabolism.

PubMed

Rühli, Frank; van Schaik, Katherine; Henneberg, Maciej

2016-11-01

The field of evolutionary medicine uses evolutionary principles to understand changes in human anatomy and physiology that have occurred over time in response to environmental changes. Through this evolutionary-based approach, we can understand disease as a consequence of anatomical and physiological "trade-offs" that develop to facilitate survival and reproduction. We demonstrate how diachronic study of human anatomy and physiology is fundamental for an increased understanding of human health and disease. ©2016 Int. Union Physiol. Sci./Am. Physiol. Soc.

Evolutionary computation in zoology and ecology.

PubMed

Boone, Randall B

2017-12-01

Evolutionary computational methods have adopted attributes of natural selection and evolution to solve problems in computer science, engineering, and other fields. The method is growing in use in zoology and ecology. Evolutionary principles may be merged with an agent-based modeling perspective to have individual animals or other agents compete. Four main categories are discussed: genetic algorithms, evolutionary programming, genetic programming, and evolutionary strategies. In evolutionary computation, a population is represented in a way that allows for an objective function to be assessed that is relevant to the problem of interest. The poorest performing members are removed from the population, and remaining members reproduce and may be mutated. The fitness of the members is again assessed, and the cycle continues until a stopping condition is met. Case studies include optimizing: egg shape given different clutch sizes, mate selection, migration of wildebeest, birds, and elk, vulture foraging behavior, algal bloom prediction, and species richness given energy constraints. Other case studies simulate the evolution of species and a means to project shifts in species ranges in response to a changing climate that includes competition and phenotypic plasticity. This introduction concludes by citing other uses of evolutionary computation and a review of the flexibility of the methods. For example, representing species' niche spaces subject to selective pressure allows studies on cladistics, the taxon cycle, neutral versus niche paradigms, fundamental versus realized niches, community structure and order of colonization, invasiveness, and responses to a changing climate.

Evolutionary computation in zoology and ecology

PubMed Central

2017-01-01

Abstract Evolutionary computational methods have adopted attributes of natural selection and evolution to solve problems in computer science, engineering, and other fields. The method is growing in use in zoology and ecology. Evolutionary principles may be merged with an agent-based modeling perspective to have individual animals or other agents compete. Four main categories are discussed: genetic algorithms, evolutionary programming, genetic programming, and evolutionary strategies. In evolutionary computation, a population is represented in a way that allows for an objective function to be assessed that is relevant to the problem of interest. The poorest performing members are removed from the population, and remaining members reproduce and may be mutated. The fitness of the members is again assessed, and the cycle continues until a stopping condition is met. Case studies include optimizing: egg shape given different clutch sizes, mate selection, migration of wildebeest, birds, and elk, vulture foraging behavior, algal bloom prediction, and species richness given energy constraints. Other case studies simulate the evolution of species and a means to project shifts in species ranges in response to a changing climate that includes competition and phenotypic plasticity. This introduction concludes by citing other uses of evolutionary computation and a review of the flexibility of the methods. For example, representing species’ niche spaces subject to selective pressure allows studies on cladistics, the taxon cycle, neutral versus niche paradigms, fundamental versus realized niches, community structure and order of colonization, invasiveness, and responses to a changing climate. PMID:29492029

Evolutionary explanations in medicine: how do they differ and how to benefit from them.

PubMed

Lozano, George A

2010-04-01

Evolutionary explanations, many of which have appeared on the pages of this journal, are becoming more pervasive and influential in medicine, so it is becoming more important to understand how these types of explanations differ from the proximate approach that is more common in medicine, and how the evolutionary approach can contribute to medicine. Understanding of any biological phenomenon can occur at four levels: (1) ontogeny (2) causation, (3) function and (4) evolution. These approaches are not mutually exclusive, and whereas the first two are more common in medical practice, a complete explanation requires all four levels of analysis. Two major differences among these approaches are the apparent degree of immediacy associated with them, and the extent to which they apply to individuals rather than populations. Criticisms of adaptive explanations often arise from a failure to understand the complementary nature of these four types of explanations. Other unwarranted criticisms result from a failure to appreciate that adaptive explanations often apply to populations, not individuals. A third type of criticism is driven by the mistaken belief that adaptive explanations somehow justify morally reprehensible behaviours. Finally, evolutionary explanations sometimes face the criticism of "personal incredulity". Adaptive explanations must be consistent with basic evolutionary concepts and must adhere to the physical reality of the phenomenon in question. Their value, however, comes not in devising a seemingly rational explanation, but in their predictions. Testable predictions must be explicitly stated and clearly articulated. They must differ from those of arising from other hypotheses and must not only be interesting to evolutionary biologists, but also useful to medical practitioners. Integration of the proximate and the ultimate approaches is possible and potentially beneficial to both evolutionists and physicians, but it requires some basic understanding of our differences and a desire to co-operate. (c) 2009 Elsevier Ltd. All rights reserved.

Classifying the Progression of Ductal Carcinoma from Single-Cell Sampled Data via Integer Linear Programming: A Case Study

PubMed Central

Catanzaro, Daniele; Schäffer, Alejandro A.; Schwartz, Russell

2016-01-01

Ductal Carcinoma In Situ (DCIS) is a precursor lesion of Invasive Ductal Carcinoma (IDC) of the breast. Investigating its temporal progression could provide fundamental new insights for the development of better diagnostic tools to predict which cases of DCIS will progress to IDC. We investigate the problem of reconstructing a plausible progression from single-cell sampled data of an individual with Synchronous DCIS and IDC. Specifically, by using a number of assumptions derived from the observation of cellular atypia occurring in IDC, we design a possible predictive model using integer linear programming (ILP). Computational experiments carried out on a preexisting data set of 13 patients with simultaneous DCIS and IDC show that the corresponding predicted progression models are classifiable into categories having specific evolutionary characteristics. The approach provides new insights into mechanisms of clonal progression in breast cancers and helps illustrate the power of the ILP approach for similar problems in reconstructing tumor evolution scenarios under complex sets of constraints. PMID:26353381

Classifying the Progression of Ductal Carcinoma from Single-Cell Sampled Data via Integer Linear Programming: A Case Study.

PubMed

Catanzaro, Daniele; Shackney, Stanley E; Schaffer, Alejandro A; Schwartz, Russell

2016-01-01

Ductal Carcinoma In Situ (DCIS) is a precursor lesion of Invasive Ductal Carcinoma (IDC) of the breast. Investigating its temporal progression could provide fundamental new insights for the development of better diagnostic tools to predict which cases of DCIS will progress to IDC. We investigate the problem of reconstructing a plausible progression from single-cell sampled data of an individual with synchronous DCIS and IDC. Specifically, by using a number of assumptions derived from the observation of cellular atypia occurring in IDC, we design a possible predictive model using integer linear programming (ILP). Computational experiments carried out on a preexisting data set of 13 patients with simultaneous DCIS and IDC show that the corresponding predicted progression models are classifiable into categories having specific evolutionary characteristics. The approach provides new insights into mechanisms of clonal progression in breast cancers and helps illustrate the power of the ILP approach for similar problems in reconstructing tumor evolution scenarios under complex sets of constraints.

Open system magnetic evolution of the taos plateau volcanic field, Northern New Mexico. I - The petrology and geochemistry of the servilleta basalt

NASA Technical Reports Server (NTRS)

Dungan, M. A.; Lindstrom, M. M.; Mcmillan, N. J.; Moorbath, S.; Hoefs, J.

1986-01-01

MULTIFIT, an embodiment of the conceptual structure needed in modeling multisource and multiprocess magmatic systems, is described. This program, which uses familiar materials balance methodology and the equilibrium form of the Rayleigh equations, links evolutionary arrays, which is turn collectively relate the starting and final compositions of a given magmatic system. Moreover, MULTIFIT incorporates variations within major element data arrays; the linkage between them can be tested using an extension of the least squares algorithm, which selects the best branch point according to the minimum-sum-of-squared-residuals criterion. Advantages and disadvantages of the materials balance approach used in this program are discussed, an example is provided, and equations utilized by MULTIFIT are summarized. While MULTIFIT may not be the best approach for poorly constrained models involving partial melting for complex mixing, it may ultimately prove useful for ascertaining trace element partition coefficients in magnetic systems.

Evolutionary principles and their practical application

PubMed Central

Hendry, Andrew P; Kinnison, Michael T; Heino, Mikko; Day, Troy; Smith, Thomas B; Fitt, Gary; Bergstrom, Carl T; Oakeshott, John; Jørgensen, Peter S; Zalucki, Myron P; Gilchrist, George; Southerton, Simon; Sih, Andrew; Strauss, Sharon; Denison, Robert F; Carroll, Scott P

2011-01-01

Evolutionary principles are now routinely incorporated into medicine and agriculture. Examples include the design of treatments that slow the evolution of resistance by weeds, pests, and pathogens, and the design of breeding programs that maximize crop yield or quality. Evolutionary principles are also increasingly incorporated into conservation biology, natural resource management, and environmental science. Examples include the protection of small and isolated populations from inbreeding depression, the identification of key traits involved in adaptation to climate change, the design of harvesting regimes that minimize unwanted life-history evolution, and the setting of conservation priorities based on populations, species, or communities that harbor the greatest evolutionary diversity and potential. The adoption of evolutionary principles has proceeded somewhat independently in these different fields, even though the underlying fundamental concepts are the same. We explore these fundamental concepts under four main themes: variation, selection, connectivity, and eco-evolutionary dynamics. Within each theme, we present several key evolutionary principles and illustrate their use in addressing applied problems. We hope that the resulting primer of evolutionary concepts and their practical utility helps to advance a unified multidisciplinary field of applied evolutionary biology. PMID:25567966

Evolutionary principles and their practical application.

PubMed

Hendry, Andrew P; Kinnison, Michael T; Heino, Mikko; Day, Troy; Smith, Thomas B; Fitt, Gary; Bergstrom, Carl T; Oakeshott, John; Jørgensen, Peter S; Zalucki, Myron P; Gilchrist, George; Southerton, Simon; Sih, Andrew; Strauss, Sharon; Denison, Robert F; Carroll, Scott P

2011-03-01

Evolutionary principles are now routinely incorporated into medicine and agriculture. Examples include the design of treatments that slow the evolution of resistance by weeds, pests, and pathogens, and the design of breeding programs that maximize crop yield or quality. Evolutionary principles are also increasingly incorporated into conservation biology, natural resource management, and environmental science. Examples include the protection of small and isolated populations from inbreeding depression, the identification of key traits involved in adaptation to climate change, the design of harvesting regimes that minimize unwanted life-history evolution, and the setting of conservation priorities based on populations, species, or communities that harbor the greatest evolutionary diversity and potential. The adoption of evolutionary principles has proceeded somewhat independently in these different fields, even though the underlying fundamental concepts are the same. We explore these fundamental concepts under four main themes: variation, selection, connectivity, and eco-evolutionary dynamics. Within each theme, we present several key evolutionary principles and illustrate their use in addressing applied problems. We hope that the resulting primer of evolutionary concepts and their practical utility helps to advance a unified multidisciplinary field of applied evolutionary biology.

Evolutionary change in physiological phenotypes along the human lineage.

PubMed

Vining, Alexander Q; Nunn, Charles L

2016-01-01

Research in evolutionary medicine provides many examples of how evolution has shaped human susceptibility to disease. Traits undergoing rapid evolutionary change may result in associated costs or reduce the energy available to other traits. We hypothesize that humans have experienced more such changes than other primates as a result of major evolutionary change along the human lineage. We investigated 41 physiological traits across 50 primate species to identify traits that have undergone marked evolutionary change along the human lineage. We analysed the data using two Bayesian phylogenetic comparative methods. One approach models trait covariation in non-human primates and predicts human phenotypes to identify whether humans are evolutionary outliers. The other approach models adaptive shifts under an Ornstein-Uhlenbeck model of evolution to assess whether inferred shifts are more common on the human branch than on other primate lineages. We identified four traits with strong evidence for an evolutionary increase on the human lineage (amylase, haematocrit, phosphorus and monocytes) and one trait with strong evidence for decrease (neutrophilic bands). Humans exhibited more cases of distinct evolutionary change than other primates. Human physiology has undergone increased evolutionary change compared to other primates. Long distance running may have contributed to increases in haematocrit and mean corpuscular haemoglobin concentration, while dietary changes are likely related to increases in amylase. In accordance with the pathogen load hypothesis, human monocyte levels were increased, but many other immune-related measures were not. Determining the mechanisms underlying conspicuous evolutionary change in these traits may provide new insights into human disease. The Author(s) 2016. Published by Oxford University Press on behalf of the Foundation for Evolution, Medicine, and Public Health.

Evolutionary contributions to the study of human fertility.

PubMed

Sear, Rebecca

2015-01-01

Demography, lacking an overarching theoretical framework of its own, has drawn on theories in many other social sciences to inform its analyses. The aim of this paper is to bring to the demographic community's attention research in the evolutionary sciences on fertility, and to demonstrate that evolutionary theory can be another useful tool in the demographer's toolkit. I first dispel some myths which impede the incorporation of evolutionary theory into demography: I make it clear that evolutionary explanations do not assume that all human behaviour is hardwired and functions to maximize genetic fitness; that they are able to explain variation in human behaviour; and that they are not necessarily alternatives to social science explanations. I then describe the diversity of work on fertility by evolutionary researchers, particularly human evolutionary ecologists and cultural evolutionists, and illustrate the usefulness of the evolutionary approach with examples of its application to age at first birth and the fertility transition.

Evolutionary domestication in Drosophila subobscura.

PubMed

Simões, P; Rose, M R; Duarte, A; Gonçalves, R; Matos, M

2007-03-01

The domestication of plants and animals is historically one of the most important topics in evolutionary biology. The evolutionary genetic changes arising from human cultivation are complex because of the effects of such varied processes as continuing natural selection, artificial selection, deliberate inbreeding, genetic drift and hybridization of different lineages. Despite the interest of domestication as an evolutionary process, few studies of multicellular sexual species have approached this topic using well-replicated experiments. Here we present a comprehensive study in which replicated evolutionary trajectories from several Drosophila subobscura populations provide a detailed view of the evolutionary dynamics of domestication in an outbreeding animal species. Our results show a clear evolutionary response in fecundity traits, but no clear pattern for adult starvation resistance and juvenile traits such as development time and viability. These results supply new perspectives on the confounding of adaptation with other evolutionary mechanisms in the process of domestication.

A sense of life: computational and experimental investigations with models of biochemical and evolutionary processes.

PubMed

Mishra, Bud; Daruwala, Raoul-Sam; Zhou, Yi; Ugel, Nadia; Policriti, Alberto; Antoniotti, Marco; Paxia, Salvatore; Rejali, Marc; Rudra, Archisman; Cherepinsky, Vera; Silver, Naomi; Casey, William; Piazza, Carla; Simeoni, Marta; Barbano, Paolo; Spivak, Marina; Feng, Jiawu; Gill, Ofer; Venkatesh, Mysore; Cheng, Fang; Sun, Bing; Ioniata, Iuliana; Anantharaman, Thomas; Hubbard, E Jane Albert; Pnueli, Amir; Harel, David; Chandru, Vijay; Hariharan, Ramesh; Wigler, Michael; Park, Frank; Lin, Shih-Chieh; Lazebnik, Yuri; Winkler, Franz; Cantor, Charles R; Carbone, Alessandra; Gromov, Mikhael

2003-01-01

We collaborate in a research program aimed at creating a rigorous framework, experimental infrastructure, and computational environment for understanding, experimenting with, manipulating, and modifying a diverse set of fundamental biological processes at multiple scales and spatio-temporal modes. The novelty of our research is based on an approach that (i) requires coevolution of experimental science and theoretical techniques and (ii) exploits a certain universality in biology guided by a parsimonious model of evolutionary mechanisms operating at the genomic level and manifesting at the proteomic, transcriptomic, phylogenic, and other higher levels. Our current program in "systems biology" endeavors to marry large-scale biological experiments with the tools to ponder and reason about large, complex, and subtle natural systems. To achieve this ambitious goal, ideas and concepts are combined from many different fields: biological experimentation, applied mathematical modeling, computational reasoning schemes, and large-scale numerical and symbolic simulations. From a biological viewpoint, the basic issues are many: (i) understanding common and shared structural motifs among biological processes; (ii) modeling biological noise due to interactions among a small number of key molecules or loss of synchrony; (iii) explaining the robustness of these systems in spite of such noise; and (iv) cataloging multistatic behavior and adaptation exhibited by many biological processes.

Object-oriented programming for the biosciences.

PubMed

Wiechert, W; Joksch, B; Wittig, R; Hartbrich, A; Höner, T; Möllney, M

1995-10-01

The development of software systems for the biosciences is always closely connected to experimental practice. Programs must be able to handle the inherent complexity and heterogeneous structure of biological systems in combination with the measuring equipment. Moreover, a high degree of flexibility is required to treat rapidly changing experimental conditions. Object-oriented methodology seems to be well suited for this purpose. It enables an evolutionary approach to software development that still maintains a high degree of modularity. This paper presents experience with object-oriented technology gathered during several years of programming in the fields of bioprocess development and metabolic engineering. It concentrates on the aspects of experimental support, data analysis, interaction and visualization. Several examples are presented and discussed in the general context of the experimental cycle of knowledge acquisition, thus pointing out the benefits and problems of object-oriented technology in the specific application field of the biosciences. Finally, some strategies for future development are described.

From computers to cultivation: reconceptualizing evolutionary psychology.

PubMed

Barrett, Louise; Pollet, Thomas V; Stulp, Gert

2014-01-01

Does evolutionary theorizing have a role in psychology? This is a more contentious issue than one might imagine, given that, as evolved creatures, the answer must surely be yes. The contested nature of evolutionary psychology lies not in our status as evolved beings, but in the extent to which evolutionary ideas add value to studies of human behavior, and the rigor with which these ideas are tested. This, in turn, is linked to the framework in which particular evolutionary ideas are situated. While the framing of the current research topic places the brain-as-computer metaphor in opposition to evolutionary psychology, the most prominent school of thought in this field (born out of cognitive psychology, and often known as the Santa Barbara school) is entirely wedded to the computational theory of mind as an explanatory framework. Its unique aspect is to argue that the mind consists of a large number of functionally specialized (i.e., domain-specific) computational mechanisms, or modules (the massive modularity hypothesis). Far from offering an alternative to, or an improvement on, the current perspective, we argue that evolutionary psychology is a mainstream computational theory, and that its arguments for domain-specificity often rest on shaky premises. We then go on to suggest that the various forms of e-cognition (i.e., embodied, embedded, enactive) represent a true alternative to standard computational approaches, with an emphasis on "cognitive integration" or the "extended mind hypothesis" in particular. We feel this offers the most promise for human psychology because it incorporates the social and historical processes that are crucial to human "mind-making" within an evolutionarily informed framework. In addition to linking to other research areas in psychology, this approach is more likely to form productive links to other disciplines within the social sciences, not least by encouraging a healthy pluralism in approach.

Emerging Concepts of Data Integration in Pathogen Phylodynamics.

PubMed

Baele, Guy; Suchard, Marc A; Rambaut, Andrew; Lemey, Philippe

2017-01-01

Phylodynamics has become an increasingly popular statistical framework to extract evolutionary and epidemiological information from pathogen genomes. By harnessing such information, epidemiologists aim to shed light on the spatio-temporal patterns of spread and to test hypotheses about the underlying interaction of evolutionary and ecological dynamics in pathogen populations. Although the field has witnessed a rich development of statistical inference tools with increasing levels of sophistication, these tools initially focused on sequences as their sole primary data source. Integrating various sources of information, however, promises to deliver more precise insights in infectious diseases and to increase opportunities for statistical hypothesis testing. Here, we review how the emerging concept of data integration is stimulating new advances in Bayesian evolutionary inference methodology which formalize a marriage of statistical thinking and evolutionary biology. These approaches include connecting sequence to trait evolution, such as for host, phenotypic and geographic sampling information, but also the incorporation of covariates of evolutionary and epidemic processes in the reconstruction procedures. We highlight how a full Bayesian approach to covariate modeling and testing can generate further insights into sequence evolution, trait evolution, and population dynamics in pathogen populations. Specific examples demonstrate how such approaches can be used to test the impact of host on rabies and HIV evolutionary rates, to identify the drivers of influenza dispersal as well as the determinants of rabies cross-species transmissions, and to quantify the evolutionary dynamics of influenza antigenicity. Finally, we briefly discuss how data integration is now also permeating through the inference of transmission dynamics, leading to novel insights into tree-generative processes and detailed reconstructions of transmission trees. [Bayesian inference; birth–death models; coalescent models; continuous trait evolution; covariates; data integration; discrete trait evolution; pathogen phylodynamics.

Emerging Concepts of Data Integration in Pathogen Phylodynamics

PubMed Central

Baele, Guy; Suchard, Marc A.; Rambaut, Andrew; Lemey, Philippe

2017-01-01

Phylodynamics has become an increasingly popular statistical framework to extract evolutionary and epidemiological information from pathogen genomes. By harnessing such information, epidemiologists aim to shed light on the spatio-temporal patterns of spread and to test hypotheses about the underlying interaction of evolutionary and ecological dynamics in pathogen populations. Although the field has witnessed a rich development of statistical inference tools with increasing levels of sophistication, these tools initially focused on sequences as their sole primary data source. Integrating various sources of information, however, promises to deliver more precise insights in infectious diseases and to increase opportunities for statistical hypothesis testing. Here, we review how the emerging concept of data integration is stimulating new advances in Bayesian evolutionary inference methodology which formalize a marriage of statistical thinking and evolutionary biology. These approaches include connecting sequence to trait evolution, such as for host, phenotypic and geographic sampling information, but also the incorporation of covariates of evolutionary and epidemic processes in the reconstruction procedures. We highlight how a full Bayesian approach to covariate modeling and testing can generate further insights into sequence evolution, trait evolution, and population dynamics in pathogen populations. Specific examples demonstrate how such approaches can be used to test the impact of host on rabies and HIV evolutionary rates, to identify the drivers of influenza dispersal as well as the determinants of rabies cross-species transmissions, and to quantify the evolutionary dynamics of influenza antigenicity. Finally, we briefly discuss how data integration is now also permeating through the inference of transmission dynamics, leading to novel insights into tree-generative processes and detailed reconstructions of transmission trees. [Bayesian inference; birth–death models; coalescent models; continuous trait evolution; covariates; data integration; discrete trait evolution; pathogen phylodynamics. PMID:28173504

A Conserved Core of Programmed Cell Death Indicator Genes Discriminates Developmentally and Environmentally Induced Programmed Cell Death in Plants.

PubMed

Olvera-Carrillo, Yadira; Van Bel, Michiel; Van Hautegem, Tom; Fendrych, Matyáš; Huysmans, Marlies; Simaskova, Maria; van Durme, Matthias; Buscaill, Pierre; Rivas, Susana; Coll, Nuria S.; Coppens, Frederik; Maere, Steven; Nowack, Moritz K.

2015-12-01

A plethora of diverse programmed cell death (PCD) processes has been described in living organisms. In animals and plants, different forms of PCD play crucial roles in development, immunity, and responses to the environment. While the molecular control of some animal PCD forms such as apoptosis is known in great detail, we still know comparatively little about the regulation of the diverse types of plant PCD. In part, this deficiency in molecular understanding is caused by the lack of reliable reporters to detect PCD processes. Here, we addressed this issue by using a combination of bioinformatics approaches to identify commonly regulated genes during diverse plant PCD processes in Arabidopsis (Arabidopsis thaliana). Our results indicate that the transcriptional signatures of developmentally controlled cell death are largely distinct from the ones associated with environmentally induced cell death. Moreover, different cases of developmental PCD share a set of cell death-associated genes. Most of these genes are evolutionary conserved within the green plant lineage, arguing for an evolutionary conserved core machinery of developmental PCD. Based on this information, we established an array of specific promoter-reporter lines for developmental PCD in Arabidopsis. These PCD indicators represent a powerful resource that can be used in addition to established morphological and biochemical methods to detect and analyze PCD processes in vivo and in planta. © 2015 American Society of Plant Biologists. All Rights Reserved.

Sublgacial Antarctic Lake Environments (SALE)

NASA Astrophysics Data System (ADS)

Kennicutt, M. C.; Bell, R. E.; Priscu, J. C.

2004-12-01

Subglacial Antarctic lake environments are emerging as one of the new frontiers targeted for exploration during the IPY 2007-2009. Several campaigns by various nations are in the early stages of planning and implementation with timelines that will coincide with the IPY. The ambitious interdisciplinary objectives will best be realized by multiple exploration programs investigating diverse subglacial environments continent-wide over the next decade or more. A concerted, multi-target approach wil be taken to advance our understanding of the range of possible lake evolutionary histories; the character of the physical, chemical, and biological niches; the interconnectivity of subglacial lake environments; the coupling of the ice sheet, climate and the evolution of life under the ice; the tectonic settings; and the interplay of biogeochemical cycles. Research and exploration programs spanning the continent will investigate subglacial lake environments of differing ages, evolutionary histories, and biogeochemical settings. The combined efforts will provide a holistic view of these environments over millions of years and under changing climatic conditions. The IPY will provide an opportunity for an intense period of initial exploration that will advance scientific discoveries in glaciology, biogeochemistry, paleoclimate, biology, geology and tectonics, and ecology. While early discoveries and exciting findings are expected during the IPY 2007-2009, a long term sustained program of research and exploration will continue far beyond the IPY. Within the five year period that spans the IPY, specific accomplishments will be targeted, accelerating the research agenda and setting a framework for follow-on studies. Four phases of exploration and discovery are envisioned.

Tinbergen's "four questions" provides a formal framework for a more complete understanding of prosocial biases in favour of attractive people.

PubMed

Stephen, Ian D; Burke, Darren; Sulikowski, Danielle

2017-01-01

We adopt Tinbergen's (1963) "four questions" approach to strengthen the criticism by Maestripieri et al. of the non-evolutionary accounts of favouritism toward attractive individuals, by showing which levels of explanation are lacking in these accounts. We also use this approach to propose ways in which the evolutionary account may be extended and strengthened.

Space industrialization. Volume 1: Executive summary

NASA Technical Reports Server (NTRS)

1978-01-01

Potential goals for space industrialization were identified, and evolutionary program options for the realization of those goals were developed and assessed. Program support demands were defined, and recommendations were made in relation to program implementation.

Understanding Evolutionary Change within the Framework of Geological Time

ERIC Educational Resources Information Center

Dodick, Jeff

2007-01-01

This paper focuses on a learning strategy designed to overcome students' difficulty in understanding evolutionary change within the framework of geological time. Incorporated into the learning program "From Dinosaurs to Darwin: Evolution from the Perspective of Time," this strategy consists of four scaffolded investigations in which…

Evolutionary programming for goal-driven dynamic planning

NASA Astrophysics Data System (ADS)

Vaccaro, James M.; Guest, Clark C.; Ross, David O.

2002-03-01

Many complex artificial intelligence (IA) problems are goal- driven in nature and the opportunity exists to realize the benefits of a goal-oriented solution. In many cases, such as in command and control, a goal-oriented approach may be the only option. One of many appropriate applications for such an approach is War Gaming. War Gaming is an important tool for command and control because it provides a set of alternative courses of actions so that military leaders can contemplate their next move in the battlefield. For instance, when making decisions that save lives, it is necessary to completely understand the consequences of a given order. A goal-oriented approach provides a slowly evolving tractably reasoned solution that inherently follows one of the principles of war: namely concentration on the objective. Future decision-making will depend not only on the battlefield, but also on a virtual world where military leaders can wage wars and determine their options by playing computer war games much like the real world. The problem with these games is that the built-in AI does not learn nor adapt and many times cheats, because the intelligent player has access to all the information, while the user has access to limited information provided on a display. These games are written for the purpose of entertainment and actions are calculated a priori and off-line, and are made prior or during their development. With these games getting more sophisticated in structure and less domain specific in scope, there needs to be a more general intelligent player that can adapt and learn in case the battlefield situations or the rules of engagement change. One such war game that might be considered is Risk. Risk incorporates the principles of war, is a top-down scalable model, and provides a good application for testing a variety of goal- oriented AI approaches. By integrating a goal-oriented hybrid approach, one can develop a program that plays the Risk game effectively and move one step closer to solving more difficult real-world AI problems. Using a hybrid approach that includes adaptation via evolutionary computation for the intelligent planning of a Risk player's turn provides better dynamic intelligent planning than more uniform approaches.

Incorporating evolution of transcription factor binding sites into annotated alignments.

PubMed

Bais, Abha S; Grossmann, Stefen; Vingron, Martin

2007-08-01

Identifying transcription factor binding sites (TFBSs) is essential to elucidate putative regulatory mechanisms. A common strategy is to combine cross-species conservation with single sequence TFBS annotation to yield "conserved TFBSs". Most current methods in this field adopt a multi-step approach that segregates the two aspects. Again, it is widely accepted that the evolutionary dynamics of binding sites differ from those of the surrounding sequence. Hence, it is desirable to have an approach that explicitly takes this factor into account. Although a plethora of approaches have been proposed for the prediction of conserved TFBSs, very few explicitly model TFBS evolutionary properties, while additionally being multi-step. Recently, we introduced a novel approach to simultaneously align and annotate conserved TFBSs in a pair of sequences. Building upon the standard Smith-Waterman algorithm for local alignments, SimAnn introduces additional states for profiles to output extended alignments or annotated alignments. That is, alignments with parts annotated as gaplessly aligned TFBSs (pair-profile hits)are generated. Moreover,the pair- profile related parameters are derived in a sound statistical framework. In this article, we extend this approach to explicitly incorporate evolution of binding sites in the SimAnn framework. We demonstrate the extension in the theoretical derivations through two position-specific evolutionary models, previously used for modelling TFBS evolution. In a simulated setting, we provide a proof of concept that the approach works given the underlying assumptions,as compared to the original work. Finally, using a real dataset of experimentally verified binding sites in human-mouse sequence pairs,we compare the new approach (eSimAnn) to an existing multi-step tool that also considers TFBS evolution. Although it is widely accepted that binding sites evolve differently from the surrounding sequences, most comparative TFBS identification methods do not explicitly consider this.Additionally, prediction of conserved binding sites is carried out in a multi-step approach that segregates alignment from TFBS annotation. In this paper, we demonstrate how the simultaneous alignment and annotation approach of SimAnn can be further extended to incorporate TFBS evolutionary relationships. We study how alignments and binding site predictions interplay at varying evolutionary distances and for various profile qualities.

Environmental Effect on Evolutionary Cyclic Plasticity Material Parameters of 316 Stainless Steel: An Experimental & Material Modeling Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mohanty, Subhasish; Soppet, William K.; Majumdar, Saurin

2014-09-20

This report provides an update on an earlier assessment of environmentally assisted fatigue for light water reactor (LWR) materials under extended service conditions. This report is a deliverable under the work package for environmentally assisted fatigue in the Light Water Reactor Sustainability (LWRS) program. The overall objective of this LWRS project is to assess the degradation by environmentally assisted cracking/fatigue of LWR materials such as various alloy base metals and their welds used in reactor coolant system piping. This effort is to support the Department of Energy LWRS program for developing tools to understand the aging/failure mechanism and to predictmore » the remaining life of LWR components for anticipated 60-80 year operation.« less

Isolating Escherichia coli strains for recombinant protein production.

PubMed

Schlegel, Susan; Genevaux, Pierre; de Gier, Jan-Willem

2017-03-01

Escherichia coli has been widely used for the production of recombinant proteins. To improve protein production yields in E. coli, directed engineering approaches have been commonly used. However, there are only few reported examples of the isolation of E. coli protein production strains using evolutionary approaches. Here, we first give an introduction to bacterial evolution and mutagenesis to set the stage for discussing how so far selection- and screening-based approaches have been used to isolate E. coli protein production strains. Finally, we discuss how evolutionary approaches may be used in the future to isolate E. coli strains with improved protein production characteristics.

The Modern Synthesis in the Light of Microbial Genomics.

PubMed

Booth, Austin; Mariscal, Carlos; Doolittle, W Ford

2016-09-08

We review the theoretical implications of findings in genomics for evolutionary biology since the Modern Synthesis. We examine the ways in which microbial genomics has influenced our understanding of the last universal common ancestor, the tree of life, species, lineages, and evolutionary transitions. We conclude by advocating a piecemeal toolkit approach to evolutionary biology, in lieu of any grand unified theory updated to include microbial genomics.

In Darwin's Footsteps: An On and Off-Campus Approach to Teaching Evolutionary Theory and Animal Behavior

ERIC Educational Resources Information Center

Gillie, Lynn; Bizub, Anne L.

2012-01-01

The study of evolutionary theory and fieldwork in animal behavior is enriched when students leave the classroom so they may test their abilities to think and act like scientists. This article describes a course on evolutionary theory and animal behavior that blended on campus learning with field experience in the United States and in Ecuador and…

Inherit the policy: A sociocultural approach to understanding evolutionary biology policy in South Carolina

NASA Astrophysics Data System (ADS)

Moore, Gregory D.

South Carolina biology Indicator 5.6 calls for students to "Summarize ways that scientists use data from a variety of sources to investigate and critically analyze aspects of evolutionary theory" (South Carolina Department of Education, 2006). Levinson and Sutton (2001) offered a sociocultural approach to policy that considers cultural and historical influences at all levels of the policy process. Lipsky (1980/2010) and others have identified teachers as de facto policy makers, exercising broad discretion in the execution of their work. This study looks to Ajzen's Theory of Planned Behavior as an initial framework to inform how evolutionary biology policy in South Carolina is conceptualized and understood at different levels of the policy process. The results of this study indicate that actors in the state's evolutionary biology policy process draw upon a myriad of Discourses (Gee, 1999/2005). These Discourses shape cultural dynamics and the agency of the policy actors as they navigate conflicting messages between testing mandates and evolutionary biology policy. There indeed exist gaps between how evolutionary biology policy in South Carolina is conceptualized and understood at the different levels of the policy process. Evidence from this study suggests that appropriation-level policy actors must be brought into the Discourse related to the critical analysis of evolutionary biology and academic freedom legislation must be enacted if South Carolina biology Indicator 5.6 is to realize practical significance in educational policy.

Evolution in agriculture: the application of evolutionary approaches to the management of biotic interactions in agro-ecosystems

PubMed Central

Thrall, Peter H; Oakeshott, John G; Fitt, Gary; Southerton, Simon; Burdon, Jeremy J; Sheppard, Andy; Russell, Robyn J; Zalucki, Myron; Heino, Mikko; Ford Denison, R

2011-01-01

Anthropogenic impacts increasingly drive ecological and evolutionary processes at many spatio-temporal scales, demanding greater capacity to predict and manage their consequences. This is particularly true for agro-ecosystems, which not only comprise a significant proportion of land use, but which also involve conflicting imperatives to expand or intensify production while simultaneously reducing environmental impacts. These imperatives reinforce the likelihood of further major changes in agriculture over the next 30–40 years. Key transformations include genetic technologies as well as changes in land use. The use of evolutionary principles is not new in agriculture (e.g. crop breeding, domestication of animals, management of selection for pest resistance), but given land-use trends and other transformative processes in production landscapes, ecological and evolutionary research in agro-ecosystems must consider such issues in a broader systems context. Here, we focus on biotic interactions involving pests and pathogens as exemplars of situations where integration of agronomic, ecological and evolutionary perspectives has practical value. Although their presence in agro-ecosystems may be new, many traits involved in these associations evolved in natural settings. We advocate the use of predictive frameworks based on evolutionary models as pre-emptive management tools and identify some specific research opportunities to facilitate this. We conclude with a brief discussion of multidisciplinary approaches in applied evolutionary problems. PMID:25567968

An evolutionary morphological approach for software development cost estimation.

PubMed

Araújo, Ricardo de A; Oliveira, Adriano L I; Soares, Sergio; Meira, Silvio

2012-08-01

In this work we present an evolutionary morphological approach to solve the software development cost estimation (SDCE) problem. The proposed approach consists of a hybrid artificial neuron based on framework of mathematical morphology (MM) with algebraic foundations in the complete lattice theory (CLT), referred to as dilation-erosion perceptron (DEP). Also, we present an evolutionary learning process, called DEP(MGA), using a modified genetic algorithm (MGA) to design the DEP model, because a drawback arises from the gradient estimation of morphological operators in the classical learning process of the DEP, since they are not differentiable in the usual way. Furthermore, an experimental analysis is conducted with the proposed model using five complex SDCE problems and three well-known performance metrics, demonstrating good performance of the DEP model to solve SDCE problems. Copyright © 2012 Elsevier Ltd. All rights reserved.

Evolutionary and differential psychology: conceptual conflicts and the path to integration

PubMed Central

Marsh, Tim; Boag, Simon

2013-01-01

Evolutionary psychology has seen the majority of its success exploring adaptive features of the mind believed to be ubiquitous across our species. This has given rise to the belief that the adaptationist approach has little to offer the field of differential psychology, which concerns itself exclusively with the ways in which individuals systematically differ. By framing the historical origins of both disciplines, and exploring the means through which they each address the unique challenges of psychological description and explanation, the present article identifies the conceptual and theoretical problems that have kept differential psychology isolated not only from evolutionary psychology, but from explanatory approaches in general. Paying special attention to these conceptual problems, the authors review how these difficulties are being overcome by contemporary evolutionary research, and offer instructive suggestions concerning how differential researchers (and others) can best build upon these innovations. PMID:24065949

Introducing survival ethics into engineering education and practice.

PubMed

Verharen, C; Tharakan, J; Middendorf, G; Castro-Sitiriche, M; Kadoda, G

2013-06-01

Given the possibilities of synthetic biology, weapons of mass destruction and global climate change, humans may achieve the capacity globally to alter life. This crisis calls for an ethics that furnishes effective motives to take global action necessary for survival. We propose a research program for understanding why ethical principles change across time and culture. We also propose provisional motives and methods for reaching global consensus on engineering field ethics. Current interdisciplinary research in ethics, psychology, neuroscience and evolutionary theory grounds these proposals. Experimental ethics, the application of scientific principles to ethical studies, provides a model for developing policies to advance solutions. A growing literature proposes evolutionary explanations for moral development. Connecting these approaches necessitates an experimental or scientific ethics that deliberately examines theories of morality for reliability. To illustrate how such an approach works, we cover three areas. The first section analyzes cross-cultural ethical systems in light of evolutionary theory. While such research is in its early stages, its assumptions entail consequences for engineering education. The second section discusses Howard University and University of Puerto Rico/Mayagüez (UPRM) courses that bring ethicists together with scientists and engineers to unite ethical theory and practice. We include a syllabus for engineering and STEM (Science, Technology, Engineering and Mathematics) ethics courses and a checklist model for translating educational theory and practice into community action. The model is based on aviation, medicine and engineering practice. The third and concluding section illustrates Howard University and UPRM efforts to translate engineering educational theory into community action. Multidisciplinary teams of engineering students and instructors take their expertise from the classroom to global communities to examine further the ethicality of prospective technologies and the decision-making processes that lead to them.

Literary study and evolutionary theory : A review essay.

PubMed

Carroll, J

1998-09-01

Several recent books have claimed to integrate literary study with evolutionary biology. All of the books here considered, except Robert Storey's, adopt conceptions of evolutionary theory that are in some way marginal to the Darwinian adaptationist program. All the works attempt to connect evolutionary study with various other disciplines or methodologies: for example, with cultural anthropology, cognitive psychology, the psychology of emotion, neurobiology, chaos theory, or structuralist linguistics. No empirical paradigm has yet been established for this field, but important steps have been taken, especially by Storey, in formulating basic principles, identifying appropriate disciplinary connections, and marking out lines of inquiry. Reciprocal efforts are needed from biologists and social scientists.

First steps in experimental cancer evolution

PubMed Central

Taylor, Tiffany B; Johnson, Louise J; Jackson, Robert W; Brockhurst, Michael A; Dash, Philip R

2013-01-01

Evolutionary processes play a central role in the development, progression and response to treatment of cancers. The current challenge facing researchers is to harness evolutionary theory to further our understanding of the clinical progression of cancers. Central to this endeavour will be the development of experimental systems and approaches by which theories of cancer evolution can be effectively tested. We argue here that the experimental evolution approach – whereby evolution is observed in real time and which has typically employed microorganisms – can be usefully applied to cancer. This approach allows us to disentangle the ecological causes of natural selection, identify the genetic basis of evolutionary changes and determine their repeatability. Cell cultures used in cancer research share many of the desirable traits that make microorganisms ideal for studying evolution. As such, experimental cancer evolution is feasible and likely to give great insight into the selective pressures driving the evolution of clinically destructive cancer traits. We highlight three areas of evolutionary theory with importance to cancer biology that are amenable to experimental evolution: drug resistance, social evolution and resource competition. Understanding the diversity, persistence and evolution of cancers is vital for treatment and drug development, and an experimental evolution approach could provide strategic directions and focus for future research. PMID:23745144

Office of Nuclear Energy Knowledge Management Program Situational Analysis Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kimberlyn C. Mousseau

2011-12-01

Knowledge management (KM) has been a high priority for the Department of Energy (DOE) Office of Nuclear Energy (NE) for the past several years. NE Programs are moving toward well-established knowledge management practices and a formal knowledge management program has been established. Knowledge management is being practiced to some level within each of the NE programs. Although it continues to evolve as NE programs evolve, a formal strategic plan that guides the implementation of KM has been developed. Despite the acceptance of KM within DOE NE, more work is necessary before the NE KM program can be considered fully successful.more » Per Dr. David J. Skyrme[1], an organization typically moves through the following evolutionary phases: (1) Ad-hoc - KM is being practiced to some level in some parts of the organization; (2) Formal - KM is established as a formal project or program; (3) Expanding - the use of KM as a discipline grows in practice across different parts of the organization; (4) Cohesive - there is a degree of coordination of KM; (5) Integrated - there are formal standards and approaches that give every individual access to most organizational knowledge through common interfaces; and (6) Embedded - KM is part-and-parcel of everyday tasks; it blends seamlessly into the background. According to the evolutionary phases, the NE KM program is operating at the two lower levels, Ad-hoc and Formal. Although KM is being practiced to some level, it is not being practiced in a consistent manner across the NE programs. To be fully successful, more emphasis must be placed on establishing KM standards and processes for collecting, organizing, sharing and accessing NE knowledge. Existing knowledge needs to be prioritized and gathered on a routine basis, its existence formally recorded in a knowledge inventory. Governance to ensure the quality of the knowledge being used must also be considered. For easy retrieval, knowledge must be organized according to a taxonomy that mimics nuclear energy programs. Technologies need to be established to make accessing the knowledge easier for the user. Finally, knowledge needs to be used as part of a well defined work process.« less

The challenges and benefits of lunar exploration

NASA Technical Reports Server (NTRS)

Cohen, Aaron

1992-01-01

Three decades into the Space Age, the United States is experiencing a fundamental shift in space policy with the adoption of a broad national goal to expand human presence and activity beyond Earth orbit and out into the Solar System. These plans mark a turning point in American space exploration, for they entail a shift away from singular forays to a long-term, evolutionary program of exploration and utilization of space. No longer limited to the technical and operational specifics of any one vehicle or any one mission plan, this new approach will involve a fleet of spacecraft and a stable of off-planet research laboratories, industrial facilities, and exploration programs. The challenges inherent in this program are immense, but so too are the benefits. Central to this new space architecture is the concept of using a lunar base for in-situ resource utilization, and for the development of planetary surface exploration systems, applicable to the Moon, Mars, and other planetary bodies in the Solar System. This paper discusses the technical, economic, and political challenges involved in this new approach, and details the latest thinking on the benefits that could come from bold new endeavors on the final frontier.

NASA's Orbital Space Plane Risk Reduction Strategy

NASA Technical Reports Server (NTRS)

Dumbacher, Dan

2003-01-01

This paper documents the transformation of NASA s Space Launch Initiative (SLI) Second Generation Reusable Launch Vehicle Program under the revised Integrated Space Transportation Plan, announced November 2002. Outlining the technology development approach followed by the original SLI, this paper gives insight into the current risk-reduction strategy that will enable confident development of the Nation s first orbital space plane (OSP). The OSP will perform an astronaut and contingency cargo transportation function, with an early crew rescue capability, thus enabling increased crew size and enhanced science operations aboard the International Space Station. The OSP design chosen for full-scale development will take advantage of the latest innovations American industry has to offer. The OSP Program identifies critical technologies that must be advanced to field a safe, reliable, affordable space transportation system for U.S. access to the Station and low-Earth orbit. OSP flight demonstrators will test crew safety features, validate autonomous operations, and mature thermal protection systems. Additional enabling technologies may be identified during the OSP design process as part of an overall risk-management strategy. The OSP Program uses a comprehensive and evolutionary systems acquisition approach, while applying appropriate lessons learned.

Evolutionary dynamics with fluctuating population sizes and strong mutualism.

PubMed

Chotibut, Thiparat; Nelson, David R

2015-08-01

Game theory ideas provide a useful framework for studying evolutionary dynamics in a well-mixed environment. This approach, however, typically enforces a strictly fixed overall population size, deemphasizing natural growth processes. We study a competitive Lotka-Volterra model, with number fluctuations, that accounts for natural population growth and encompasses interaction scenarios typical of evolutionary games. We show that, in an appropriate limit, the model describes standard evolutionary games with both genetic drift and overall population size fluctuations. However, there are also regimes where a varying population size can strongly influence the evolutionary dynamics. We focus on the strong mutualism scenario and demonstrate that standard evolutionary game theory fails to describe our simulation results. We then analytically and numerically determine fixation probabilities as well as mean fixation times using matched asymptotic expansions, taking into account the population size degree of freedom. These results elucidate the interplay between population dynamics and evolutionary dynamics in well-mixed systems.

Evolutionary dynamics with fluctuating population sizes and strong mutualism

NASA Astrophysics Data System (ADS)

Chotibut, Thiparat; Nelson, David R.

2015-08-01

Game theory ideas provide a useful framework for studying evolutionary dynamics in a well-mixed environment. This approach, however, typically enforces a strictly fixed overall population size, deemphasizing natural growth processes. We study a competitive Lotka-Volterra model, with number fluctuations, that accounts for natural population growth and encompasses interaction scenarios typical of evolutionary games. We show that, in an appropriate limit, the model describes standard evolutionary games with both genetic drift and overall population size fluctuations. However, there are also regimes where a varying population size can strongly influence the evolutionary dynamics. We focus on the strong mutualism scenario and demonstrate that standard evolutionary game theory fails to describe our simulation results. We then analytically and numerically determine fixation probabilities as well as mean fixation times using matched asymptotic expansions, taking into account the population size degree of freedom. These results elucidate the interplay between population dynamics and evolutionary dynamics in well-mixed systems.

Hybrid zone studies: An interdisciplinary approach for the analysis of evolutionary processes

USGS Publications Warehouse

Scribner, Kim T.

1994-01-01

There has been considerable debate in the ecological and evolutionary literature over the relative importance and rate by which microevolutionary processes operating at the population level result in separation and differentiation of lineages and populations, and ultimately in speciation. Our understanding of evolutionary processes have need greatly enhances through the study of hybridization and hybrid zones. Indeed, hybrid zones have been described as “natural laboratories” (Barton, N. H., and G .M. Hewitt, 189. Adaptation, speciation, and hybrid zones. Nature 341:497-503) or as “windows on the evolutionary processes” (Harrison, R. G. 1990. Hybrid zones: windows on the evolutionary process. Oxford Surveys in Evolutionary Biology 7:69-128). Hybrid zones greatly facilitate analyses of evolutionary dynamics because differences in factors such as mating preference, fertility, and viability are likely to be magnified, making the consequences easier to document over short periods of time.

A systemic approach for modeling biological evolution using Parallel DEVS.

PubMed

Heredia, Daniel; Sanz, Victorino; Urquia, Alfonso; Sandín, Máximo

2015-08-01

A new model for studying the evolution of living organisms is proposed in this manuscript. The proposed model is based on a non-neodarwinian systemic approach. The model is focused on considering several controversies and open discussions about modern evolutionary biology. Additionally, a simplification of the proposed model, named EvoDEVS, has been mathematically described using the Parallel DEVS formalism and implemented as a computer program using the DEVSLib Modelica library. EvoDEVS serves as an experimental platform to study different conditions and scenarios by means of computer simulations. Two preliminary case studies are presented to illustrate the behavior of the model and validate its results. EvoDEVS is freely available at http://www.euclides.dia.uned.es. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Strategic approaches to planetary base development

NASA Technical Reports Server (NTRS)

Roberts, Barney B.

1992-01-01

The evolutionary development of a planetary expansionary outpost is considered in the light of both technical and economic issues. The outline of a partnering taxonomy is set forth which encompasses both institutional and temporal issues related to establishing shared interests and investments. The purely technical issues are discussed in terms of the program components which include nonaerospace technologies such as construction engineering. Five models are proposed in which partnership and autonomy for participants are approached in different ways including: (1) the standard customer/provider relationship; (2) a service-provider scenario; (3) the joint venture; (4) a technology joint-development model; and (5) a redundancy model for reduced costs. Based on the assumed characteristics of planetary surface systems the cooperative private/public models are championed with coordinated design by NASA to facilitate outside cooperation.

Group adaptation, formal darwinism and contextual analysis.

PubMed

Okasha, S; Paternotte, C

2012-06-01

We consider the question: under what circumstances can the concept of adaptation be applied to groups, rather than individuals? Gardner and Grafen (2009, J. Evol. Biol.22: 659-671) develop a novel approach to this question, building on Grafen's 'formal Darwinism' project, which defines adaptation in terms of links between evolutionary dynamics and optimization. They conclude that only clonal groups, and to a lesser extent groups in which reproductive competition is repressed, can be considered as adaptive units. We re-examine the conditions under which the selection-optimization links hold at the group level. We focus on an important distinction between two ways of understanding the links, which have different implications regarding group adaptationism. We show how the formal Darwinism approach can be reconciled with G.C. Williams' famous analysis of group adaptation, and we consider the relationships between group adaptation, the Price equation approach to multi-level selection, and the alternative approach based on contextual analysis. © 2012 The Authors. Journal of Evolutionary Biology © 2012 European Society For Evolutionary Biology.

Quantitative genetic models of sexual conflict based on interacting phenotypes.

PubMed

Moore, Allen J; Pizzari, Tommaso

2005-05-01

Evolutionary conflict arises between reproductive partners when alternative reproductive opportunities are available. Sexual conflict can generate sexually antagonistic selection, which mediates sexual selection and intersexual coevolution. However, despite intense interest, the evolutionary implications of sexual conflict remain unresolved. We propose a novel theoretical approach to study the evolution of sexually antagonistic phenotypes based on quantitative genetics and the measure of social selection arising from male-female interactions. We consider the phenotype of one sex as both a genetically influenced evolving trait as well as the (evolving) social environment in which the phenotype of the opposite sex evolves. Several important points emerge from our analysis, including the relationship between direct selection on one sex and indirect effects through selection on the opposite sex. We suggest that the proposed approach may be a valuable tool to complement other theoretical approaches currently used to study sexual conflict. Most importantly, our approach highlights areas where additional empirical data can help clarify the role of sexual conflict in the evolutionary process.

Optimizing a realistic large-scale frequency assignment problem using a new parallel evolutionary approach

NASA Astrophysics Data System (ADS)

Chaves-González, José M.; Vega-Rodríguez, Miguel A.; Gómez-Pulido, Juan A.; Sánchez-Pérez, Juan M.

2011-08-01

This article analyses the use of a novel parallel evolutionary strategy to solve complex optimization problems. The work developed here has been focused on a relevant real-world problem from the telecommunication domain to verify the effectiveness of the approach. The problem, known as frequency assignment problem (FAP), basically consists of assigning a very small number of frequencies to a very large set of transceivers used in a cellular phone network. Real data FAP instances are very difficult to solve due to the NP-hard nature of the problem, therefore using an efficient parallel approach which makes the most of different evolutionary strategies can be considered as a good way to obtain high-quality solutions in short periods of time. Specifically, a parallel hyper-heuristic based on several meta-heuristics has been developed. After a complete experimental evaluation, results prove that the proposed approach obtains very high-quality solutions for the FAP and beats any other result published.

Requirements Definition for Force Level Command and Control in the Tactical Air Control System: An Evolutionary Approach Toward Meeting Near Term and Future Operational Needs.

DTIC Science & Technology

1985-01-01

numerous major exercises, such as WINTEX- CIMEX , REFORGER, CRESTED EAGLE, and BRIGHT STAR. USAFE is now actively planning an evolutionary approach toward C2...during WINTEX- CIMEX 85, we have been investigating a number of approaches to enhancing joint air-ground operations and providing a means for better...throughout the ground battle elements. The USAREUR Distributed Decision Aid System (UD[1AS) was initially deployed in Exercise WINTEX- CIMEX 84. During

Discovery radiomics via evolutionary deep radiomic sequencer discovery for pathologically proven lung cancer detection.

PubMed

Shafiee, Mohammad Javad; Chung, Audrey G; Khalvati, Farzad; Haider, Masoom A; Wong, Alexander

2017-10-01

While lung cancer is the second most diagnosed form of cancer in men and women, a sufficiently early diagnosis can be pivotal in patient survival rates. Imaging-based, or radiomics-driven, detection methods have been developed to aid diagnosticians, but largely rely on hand-crafted features that may not fully encapsulate the differences between cancerous and healthy tissue. Recently, the concept of discovery radiomics was introduced, where custom abstract features are discovered from readily available imaging data. We propose an evolutionary deep radiomic sequencer discovery approach based on evolutionary deep intelligence. Motivated by patient privacy concerns and the idea of operational artificial intelligence, the evolutionary deep radiomic sequencer discovery approach organically evolves increasingly more efficient deep radiomic sequencers that produce significantly more compact yet similarly descriptive radiomic sequences over multiple generations. As a result, this framework improves operational efficiency and enables diagnosis to be run locally at the radiologist's computer while maintaining detection accuracy. We evaluated the evolved deep radiomic sequencer (EDRS) discovered via the proposed evolutionary deep radiomic sequencer discovery framework against state-of-the-art radiomics-driven and discovery radiomics methods using clinical lung CT data with pathologically proven diagnostic data from the LIDC-IDRI dataset. The EDRS shows improved sensitivity (93.42%), specificity (82.39%), and diagnostic accuracy (88.78%) relative to previous radiomics approaches.

Integrating genomics into evolutionary medicine.

PubMed

Rodríguez, Juan Antonio; Marigorta, Urko M; Navarro, Arcadi

2014-12-01

The application of the principles of evolutionary biology into medicine was suggested long ago and is already providing insight into the ultimate causes of disease. However, a full systematic integration of medical genomics and evolutionary medicine is still missing. Here, we briefly review some cases where the combination of the two fields has proven profitable and highlight two of the main issues hindering the development of evolutionary genomic medicine as a mature field, namely the dissociation between fitness and health and the still considerable difficulties in predicting phenotypes from genotypes. We use publicly available data to illustrate both problems and conclude that new approaches are needed for evolutionary genomic medicine to overcome these obstacles. Copyright © 2014 Elsevier Ltd. All rights reserved.

Fitness consequences of maternal and embryonic responses to environmental variation: using reptiles as models for studies of developmental plasticity.

PubMed

Warner, Daniel A

2014-11-01

Environmental factors strongly influence phenotypic variation within populations. The environment contributes to this variation in two ways: (1) by acting as a determinant of phenotypic variation (i.e., plastic responses) and (2) as an agent of selection that "chooses" among existing phenotypes. Understanding how these two environmental forces contribute to phenotypic variation is a major goal in the field of evolutionary biology and a primary objective of my research program. The objective of this article is to provide a framework to guide studies of environmental sources of phenotypic variation (specifically, developmental plasticity and maternal effects, and their adaptive significance). Two case studies from my research on reptiles are used to illustrate the general approaches I have taken to address these conceptual topics. Some key points for advancing our understanding of environmental influences on phenotypic variation include (1) merging laboratory-based research that identifies specific environmental effects with field studies to validate ecological relevance; (2) using controlled experimental approaches that mimic complex environments found in nature; (3) integrating data across biological fields (e.g., genetics, morphology, physiology, behavior, and ecology) under an evolutionary framework to provide novel insights into the underlying mechanisms that generate phenotypic variation; (4) assessing fitness consequences using measurements of survival and/or reproductive success across ontogeny (from embryos to adults) and under multiple ecologically-meaningful contexts; and (5) quantifying the strength and form of natural selection in multiple populations over multiple periods of time to understand the spatial and temporal consistency of phenotypic selection. Research programs that focus on organisms that are amenable to these approaches will provide the most promise for advancing our understanding of the environmental factors that generate the remarkable phenotypic diversity observed within populations. © The Author 2014. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Evolutionary public health: introducing the concept.

PubMed

Wells, Jonathan C K; Nesse, Randolph M; Sear, Rebecca; Johnstone, Rufus A; Stearns, Stephen C

2017-07-29

The emerging discipline of evolutionary medicine is breaking new ground in understanding why people become ill. However, the value of evolutionary analyses of human physiology and behaviour is only beginning to be recognised in the field of public health. Core principles come from life history theory, which analyses the allocation of finite amounts of energy between four competing functions-maintenance, growth, reproduction, and defence. A central tenet of evolutionary theory is that organisms are selected to allocate energy and time to maximise reproductive success, rather than health or longevity. Ecological interactions that influence mortality risk, nutrient availability, and pathogen burden shape energy allocation strategies throughout the life course, thereby affecting diverse health outcomes. Public health interventions could improve their own effectiveness by incorporating an evolutionary perspective. In particular, evolutionary approaches offer new opportunities to address the complex challenges of global health, in which populations are differentially exposed to the metabolic consequences of poverty, high fertility, infectious diseases, and rapid changes in nutrition and lifestyle. The effect of specific interventions is predicted to depend on broader factors shaping life expectancy. Among the important tools in this approach are mathematical models, which can explore probable benefits and limitations of interventions in silico, before their implementation in human populations. Copyright © 2017 Elsevier Ltd. All rights reserved.

The major synthetic evolutionary transitions.

PubMed

Solé, Ricard

2016-08-19

Evolution is marked by well-defined events involving profound innovations that are known as 'major evolutionary transitions'. They involve the integration of autonomous elements into a new, higher-level organization whereby the former isolated units interact in novel ways, losing their original autonomy. All major transitions, which include the origin of life, cells, multicellular systems, societies or language (among other examples), took place millions of years ago. Are these transitions unique, rare events? Have they instead universal traits that make them almost inevitable when the right pieces are in place? Are there general laws of evolutionary innovation? In order to approach this problem under a novel perspective, we argue that a parallel class of evolutionary transitions can be explored involving the use of artificial evolutionary experiments where alternative paths to innovation can be explored. These 'synthetic' transitions include, for example, the artificial evolution of multicellular systems or the emergence of language in evolved communicating robots. These alternative scenarios could help us to understand the underlying laws that predate the rise of major innovations and the possibility for general laws of evolved complexity. Several key examples and theoretical approaches are summarized and future challenges are outlined.This article is part of the themed issue 'The major synthetic evolutionary transitions'. © 2016 The Author(s).

The major synthetic evolutionary transitions

PubMed Central

Solé, Ricard

2016-01-01

Evolution is marked by well-defined events involving profound innovations that are known as ‘major evolutionary transitions'. They involve the integration of autonomous elements into a new, higher-level organization whereby the former isolated units interact in novel ways, losing their original autonomy. All major transitions, which include the origin of life, cells, multicellular systems, societies or language (among other examples), took place millions of years ago. Are these transitions unique, rare events? Have they instead universal traits that make them almost inevitable when the right pieces are in place? Are there general laws of evolutionary innovation? In order to approach this problem under a novel perspective, we argue that a parallel class of evolutionary transitions can be explored involving the use of artificial evolutionary experiments where alternative paths to innovation can be explored. These ‘synthetic’ transitions include, for example, the artificial evolution of multicellular systems or the emergence of language in evolved communicating robots. These alternative scenarios could help us to understand the underlying laws that predate the rise of major innovations and the possibility for general laws of evolved complexity. Several key examples and theoretical approaches are summarized and future challenges are outlined. This article is part of the themed issue ‘The major synthetic evolutionary transitions’. PMID:27431528

A novel approach for supercapacitors degradation characterization

NASA Astrophysics Data System (ADS)

Oz, Alon; Gelman, Danny; Goren, Emanuelle; Shomrat, Neta; Baltianski, Sioma; Tsur, Yoed

2017-07-01

A novel approach to analyze electrochemical impedance spectroscopy (EIS), based on evolutionary programming, has been utilized to characterize supercapacitors operation mechanism and degradation processes. This approach poses the ability of achieving a comprehensive study of supercapacitors via solely AC measurements. Commercial supercapacitors were examined during accelerated degradation. The microstructure of the electrode-electrolyte interface changes upon degradation; electrolyte parasitic reactions yield the formation of precipitates on the porous surface, which limit the access of the electrolyte ions to the active area and thus reduces performance. EIS analysis using Impedance Spectroscopy Genetic Programming (ISGP) technique enables identifying how the changing microstructure is affecting the operation mechanism of supercapacitors, in terms of each process effective capacitance and time constant. The most affected process is the transport of electrolyte ions at the porous electrode. Their access to the whole active area is hindered, which is shown in our analysis by the decrease of the capacitance gained in the transport and the longer time it takes to penetrate the entire pores depth. Early failure detection is also demonstrated, in a way not readily possible via conventional indicators. ISGP advanced analysis method has been verified using conventional and proven techniques: cyclic voltammetry and post mortem measurements.

Open Issues in Evolutionary Robotics.

PubMed

Silva, Fernando; Duarte, Miguel; Correia, Luís; Oliveira, Sancho Moura; Christensen, Anders Lyhne

2016-01-01

One of the long-term goals in evolutionary robotics is to be able to automatically synthesize controllers for real autonomous robots based only on a task specification. While a number of studies have shown the applicability of evolutionary robotics techniques for the synthesis of behavioral control, researchers have consistently been faced with a number of issues preventing the widespread adoption of evolutionary robotics for engineering purposes. In this article, we review and discuss the open issues in evolutionary robotics. First, we analyze the benefits and challenges of simulation-based evolution and subsequent deployment of controllers versus evolution on real robotic hardware. Second, we discuss specific evolutionary computation issues that have plagued evolutionary robotics: (1) the bootstrap problem, (2) deception, and (3) the role of genomic encoding and genotype-phenotype mapping in the evolution of controllers for complex tasks. Finally, we address the absence of standard research practices in the field. We also discuss promising avenues of research. Our underlying motivation is the reduction of the current gap between evolutionary robotics and mainstream robotics, and the establishment of evolutionary robotics as a canonical approach for the engineering of autonomous robots.

Assessing the evolutionary rate of positional orthologous genes in prokaryotes using synteny data

PubMed Central

Lemoine, Frédéric; Lespinet, Olivier; Labedan, Bernard

2007-01-01

Background Comparison of completely sequenced microbial genomes has revealed how fluid these genomes are. Detecting synteny blocks requires reliable methods to determining the orthologs among the whole set of homologs detected by exhaustive comparisons between each pair of completely sequenced genomes. This is a complex and difficult problem in the field of comparative genomics but will help to better understand the way prokaryotic genomes are evolving. Results We have developed a suite of programs that automate three essential steps to study conservation of gene order, and validated them with a set of 107 bacteria and archaea that cover the majority of the prokaryotic taxonomic space. We identified the whole set of shared homologs between two or more species and computed the evolutionary distance separating each pair of homologs. We applied two strategies to extract from the set of homologs a collection of valid orthologs shared by at least two genomes. The first computes the Reciprocal Smallest Distance (RSD) using the PAM distances separating pairs of homologs. The second method groups homologs in families and reconstructs each family's evolutionary tree, distinguishing bona fide orthologs as well as paralogs created after the last speciation event. Although the phylogenetic tree method often succeeds where RSD fails, the reverse could occasionally be true. Accordingly, we used the data obtained with either methods or their intersection to number the orthologs that are adjacent in for each pair of genomes, the Positional Orthologous Genes (POGs), and to further study their properties. Once all these synteny blocks have been detected, we showed that POGs are subject to more evolutionary constraints than orthologs outside synteny groups, whichever the taxonomic distance separating the compared organisms. Conclusion The suite of programs described in this paper allows a reliable detection of orthologs and is useful for evaluating gene order conservation in prokaryotes whichever their taxonomic distance. Thus, our approach will make easy the rapid identification of POGS in the next few years as we are expecting to be inundated with thousands of completely sequenced microbial genomes. PMID:18047665

MOCASSIN-prot: A multi-objective clustering approach for protein similarity networks

USDA-ARS?s Scientific Manuscript database

Motivation: Proteins often include multiple conserved domains. Various evolutionary events including duplication and loss of domains, domain shuffling, as well as sequence divergence contribute to generating complexities in protein structures, and consequently, in their functions. The evolutionary h...

From prompt gamma distribution to dose: a novel approach combining an evolutionary algorithm and filtering based on Gaussian-powerlaw convolutions.

PubMed

Schumann, A; Priegnitz, M; Schoene, S; Enghardt, W; Rohling, H; Fiedler, F

2016-10-07

Range verification and dose monitoring in proton therapy is considered as highly desirable. Different methods have been developed worldwide, like particle therapy positron emission tomography (PT-PET) and prompt gamma imaging (PGI). In general, these methods allow for a verification of the proton range. However, quantification of the dose from these measurements remains challenging. For the first time, we present an approach for estimating the dose from prompt γ-ray emission profiles. It combines a filtering procedure based on Gaussian-powerlaw convolution with an evolutionary algorithm. By means of convolving depth dose profiles with an appropriate filter kernel, prompt γ-ray depth profiles are obtained. In order to reverse this step, the evolutionary algorithm is applied. The feasibility of this approach is demonstrated for a spread-out Bragg-peak in a water target.

Evolutionary Steps in the Emergence of Life Deduced from the Bottom-Up Approach and GADV Hypothesis (Top-Down Approach)

PubMed Central

Ikehara, Kenji

2016-01-01

It is no doubt quite difficult to solve the riddle of the origin of life. So, firstly, I would like to point out the kinds of obstacles there are in solving this riddle and how we should tackle these difficult problems, reviewing the studies that have been conducted so far. After that, I will propose that the consecutive evolutionary steps in a timeline can be rationally deduced by using a common event as a juncture, which is obtained by two counter-directional approaches: one is the bottom-up approach through which many researchers have studied the origin of life, and the other is the top-down approach, through which I established the [GADV]-protein world hypothesis or GADV hypothesis on the origin of life starting from a study on the formation of entirely new genes in extant microorganisms. Last, I will describe the probable evolutionary process from the formation of Earth to the emergence of life, which was deduced by using a common event—the establishment of the first genetic code encoding [GADV]-amino acids—as a juncture for the results obtained from the two approaches. PMID:26821048

Evolutionary Steps in the Emergence of Life Deduced from the Bottom-Up Approach and GADV Hypothesis (Top-Down Approach).

PubMed

Ikehara, Kenji

2016-01-26

It is no doubt quite difficult to solve the riddle of the origin of life. So, firstly, I would like to point out the kinds of obstacles there are in solving this riddle and how we should tackle these difficult problems, reviewing the studies that have been conducted so far. After that, I will propose that the consecutive evolutionary steps in a timeline can be rationally deduced by using a common event as a juncture, which is obtained by two counter-directional approaches: one is the bottom-up approach through which many researchers have studied the origin of life, and the other is the top-down approach, through which I established the [GADV]-protein world hypothesis or GADV hypothesis on the origin of life starting from a study on the formation of entirely new genes in extant microorganisms. Last, I will describe the probable evolutionary process from the formation of Earth to the emergence of life, which was deduced by using a common event-the establishment of the first genetic code encoding [GADV]-amino acids-as a juncture for the results obtained from the two approaches.

Effective Technology Insertion: The Key to Evolutionary Acquisition Program

DTIC Science & Technology

2004-05-03

Army War College, 7 April 2003. 47Orazia A. Di Marca ; Rejto, Stephen B. Rejto and Thomas Gomez, “ Open System Design and Evolutionary Acquisition...to Military Applications-Report No. D-2002-107. 14 June 2002. Di Marca , Orazia A.; Rejto, StephenB., and Gomez, Thomas, “ Open System Design and

EvoluCode: Evolutionary Barcodes as a Unifying Framework for Multilevel Evolutionary Data.

PubMed

Linard, Benjamin; Nguyen, Ngoc Hoan; Prosdocimi, Francisco; Poch, Olivier; Thompson, Julie D

2012-01-01

Evolutionary systems biology aims to uncover the general trends and principles governing the evolution of biological networks. An essential part of this process is the reconstruction and analysis of the evolutionary histories of these complex, dynamic networks. Unfortunately, the methodologies for representing and exploiting such complex evolutionary histories in large scale studies are currently limited. Here, we propose a new formalism, called EvoluCode (Evolutionary barCode), which allows the integration of different evolutionary parameters (eg, sequence conservation, orthology, synteny …) in a unifying format and facilitates the multilevel analysis and visualization of complex evolutionary histories at the genome scale. The advantages of the approach are demonstrated by constructing barcodes representing the evolution of the complete human proteome. Two large-scale studies are then described: (i) the mapping and visualization of the barcodes on the human chromosomes and (ii) automatic clustering of the barcodes to highlight protein subsets sharing similar evolutionary histories and their functional analysis. The methodologies developed here open the way to the efficient application of other data mining and knowledge extraction techniques in evolutionary systems biology studies. A database containing all EvoluCode data is available at: http://lbgi.igbmc.fr/barcodes.

Evolutionary psychology and evolutionary developmental psychology: understanding the evolution of human behavior and development.

PubMed

Hernández Blasi, Carlos; Causey, Kayla

2010-02-01

This is an introduction to this special issue on evolutionary psychology (EP) and evolutionary developmental psychology (EDP). We suggest here that, contrary to some common assumptions, mainstream psychology continues to be essentially non Darwinian and that EP and EDP are new approaches that can potentially help us to change this situation. We then present the organization of the special issue (composed of six papers). We conclude that evolution is certainly not the final consideration in psychology, but emphasize its importance as the basis upon which all modern behaviors and development are built.

From evolutionary computation to the evolution of things.

PubMed

Eiben, Agoston E; Smith, Jim

2015-05-28

Evolution has provided a source of inspiration for algorithm designers since the birth of computers. The resulting field, evolutionary computation, has been successful in solving engineering tasks ranging in outlook from the molecular to the astronomical. Today, the field is entering a new phase as evolutionary algorithms that take place in hardware are developed, opening up new avenues towards autonomous machines that can adapt to their environment. We discuss how evolutionary computation compares with natural evolution and what its benefits are relative to other computing approaches, and we introduce the emerging area of artificial evolution in physical systems.

Applications of genetic programming in cancer research.

PubMed

Worzel, William P; Yu, Jianjun; Almal, Arpit A; Chinnaiyan, Arul M

2009-02-01

The theory of Darwinian evolution is the fundamental keystones of modern biology. Late in the last century, computer scientists began adapting its principles, in particular natural selection, to complex computational challenges, leading to the emergence of evolutionary algorithms. The conceptual model of selective pressure and recombination in evolutionary algorithms allow scientists to efficiently search high dimensional space for solutions to complex problems. In the last decade, genetic programming has been developed and extensively applied for analysis of molecular data to classify cancer subtypes and characterize the mechanisms of cancer pathogenesis and development. This article reviews current successes using genetic programming and discusses its potential impact in cancer research and treatment in the near future.

Pathways to cognitive design.

PubMed

Wertz, Annie E; Moya, Cristina

2018-05-30

Despite a shared recognition that the design of the human mind and the design of human culture are tightly linked, researchers in the evolutionary social sciences tend to specialize in understanding one at the expense of the other. The disciplinary boundaries roughly correspond to research traditions that focus more on natural selection and those that focus more on cultural evolution. In this paper, we articulate how two research traditions within the evolutionary social sciences-evolutionary psychology and cultural evolution-approach the study of design. We focus our analysis on the design of cognitive mechanisms that are the result of the interplay of genetic and cultural evolution. We aim to show how the approaches of these two research traditions can complement each other, and provide a framework for developing a wider range of testable hypotheses about cognitive design. To do so, we provide concrete illustrations of how this integrated approach can be used to interrogate cognitive design using examples from our own work on plant and symbolic group boundary cognition. We hope this recognition of different pathways to design will broaden the hypothesis space in the evolutionary social sciences and encourage methodological pluralism in the investigation of the mind. Copyright © 2018 Elsevier B.V. All rights reserved.

Evolutionary space platform concept study. Volume 1: Executive summary

NASA Technical Reports Server (NTRS)

1982-01-01

The Evolutionary Space Platform Concept Study encompassed a 10 month effort to define, evaluate and compare approaches and concepts for evolving unmanned and manned capability platforms beyond the current Space Platform concepts to an evolutionary goal of establishing a permanent manned presence in space. Areas addressed included: special emphasis trade studies on the current unmanned concept, assessment of manned platform concepts, and utility analysis of a manned platform for defense related missions.

Evolutionary perspectives on human personality. Comment on "Personality from a cognitive-biological perspective" by Y. Neuman

NASA Astrophysics Data System (ADS)

Southard, Ashton C.; Zeigler-Hill, Virgil; Shackelford, Todd K.

2014-12-01

Yair Neuman [6] presents many provocative ideas in his interdisciplinary approach to human personality. In this commentary, we focus on his ideas regarding (1) the evolutionary basis of personality and (2) human sperm competition.

The Evolution of Ion Pumps.

ERIC Educational Resources Information Center

Maloney, Peter C.; Wilson, T. Hastings

1985-01-01

Constructs an evolutionary sequence to account for the diversity of ion pumps found today. Explanations include primary ion pumps in bacteria, features and distribution of ATP-driven pumps, preference for cation transport, and proton pump reversal. The integrated evolutionary hypothesis should encourage new experimental approaches. (DH)

[Morphogenetic foundations for increased evolutionary complexity in the organization of thecate hydroids shoots (Cnidaria, Hydroidomedusa, Leptomedusae)].

PubMed

Kosevich, I A

2012-01-01

The morphogenetic approach is applied to analyze the diversity of spatial organization of shoots in thecate hydroids (Cnidaria, Hydroidomedusa, Leptomedusae). The main tendencies and constraints of increased evolutionary complexity in thecate hydroids colonies are uncovered.

Understanding Evolutionary Potential in Virtual CPU Instruction Set Architectures

PubMed Central

Bryson, David M.; Ofria, Charles

2013-01-01

We investigate fundamental decisions in the design of instruction set architectures for linear genetic programs that are used as both model systems in evolutionary biology and underlying solution representations in evolutionary computation. We subjected digital organisms with each tested architecture to seven different computational environments designed to present a range of evolutionary challenges. Our goal was to engineer a general purpose architecture that would be effective under a broad range of evolutionary conditions. We evaluated six different types of architectural features for the virtual CPUs: (1) genetic flexibility: we allowed digital organisms to more precisely modify the function of genetic instructions, (2) memory: we provided an increased number of registers in the virtual CPUs, (3) decoupled sensors and actuators: we separated input and output operations to enable greater control over data flow. We also tested a variety of methods to regulate expression: (4) explicit labels that allow programs to dynamically refer to specific genome positions, (5) position-relative search instructions, and (6) multiple new flow control instructions, including conditionals and jumps. Each of these features also adds complication to the instruction set and risks slowing evolution due to epistatic interactions. Two features (multiple argument specification and separated I/O) demonstrated substantial improvements in the majority of test environments, along with versions of each of the remaining architecture modifications that show significant improvements in multiple environments. However, some tested modifications were detrimental, though most exhibit no systematic effects on evolutionary potential, highlighting the robustness of digital evolution. Combined, these observations enhance our understanding of how instruction architecture impacts evolutionary potential, enabling the creation of architectures that support more rapid evolution of complex solutions to a broad range of challenges. PMID:24376669

Adaptive elastic segmentation of brain MRI via shape-model-guided evolutionary programming.

PubMed

Pitiot, Alain; Toga, Arthur W; Thompson, Paul M

2002-08-01

This paper presents a fully automated segmentation method for medical images. The goal is to localize and parameterize a variety of types of structure in these images for subsequent quantitative analysis. We propose a new hybrid strategy that combines a general elastic template matching approach and an evolutionary heuristic. The evolutionary algorithm uses prior statistical information about the shape of the target structure to control the behavior of a number of deformable templates. Each template, modeled in the form of a B-spline, is warped in a potential field which is itself dynamically adapted. Such a hybrid scheme proves to be promising: by maintaining a population of templates, we cover a large domain of the solution space under the global guidance of the evolutionary heuristic, and thoroughly explore interesting areas. We address key issues of automated image segmentation systems. The potential fields are initially designed based on the spatial features of the edges in the input image, and are subjected to spatially adaptive diffusion to guarantee the deformation of the template. This also improves its global consistency and convergence speed. The deformation algorithm can modify the internal structure of the templates to allow a better match. We investigate in detail the preprocessing phase that the images undergo before they can be used more effectively in the iterative elastic matching procedure: a texture classifier, trained via linear discriminant analysis of a learning set, is used to enhance the contrast of the target structure with respect to surrounding tissues. We show how these techniques interact within a statistically driven evolutionary scheme to achieve a better tradeoff between template flexibility and sensitivity to noise and outliers. We focus on understanding the features of template matching that are most beneficial in terms of the achieved match. Examples from simulated and real image data are discussed, with considerations of algorithmic efficiency.

From computers to cultivation: reconceptualizing evolutionary psychology

PubMed Central

Barrett, Louise; Pollet, Thomas V.; Stulp, Gert

2014-01-01

Does evolutionary theorizing have a role in psychology? This is a more contentious issue than one might imagine, given that, as evolved creatures, the answer must surely be yes. The contested nature of evolutionary psychology lies not in our status as evolved beings, but in the extent to which evolutionary ideas add value to studies of human behavior, and the rigor with which these ideas are tested. This, in turn, is linked to the framework in which particular evolutionary ideas are situated. While the framing of the current research topic places the brain-as-computer metaphor in opposition to evolutionary psychology, the most prominent school of thought in this field (born out of cognitive psychology, and often known as the Santa Barbara school) is entirely wedded to the computational theory of mind as an explanatory framework. Its unique aspect is to argue that the mind consists of a large number of functionally specialized (i.e., domain-specific) computational mechanisms, or modules (the massive modularity hypothesis). Far from offering an alternative to, or an improvement on, the current perspective, we argue that evolutionary psychology is a mainstream computational theory, and that its arguments for domain-specificity often rest on shaky premises. We then go on to suggest that the various forms of e-cognition (i.e., embodied, embedded, enactive) represent a true alternative to standard computational approaches, with an emphasis on “cognitive integration” or the “extended mind hypothesis” in particular. We feel this offers the most promise for human psychology because it incorporates the social and historical processes that are crucial to human “mind-making” within an evolutionarily informed framework. In addition to linking to other research areas in psychology, this approach is more likely to form productive links to other disciplines within the social sciences, not least by encouraging a healthy pluralism in approach. PMID:25161633

Merging molecular mechanism and evolution: theory and computation at the interface of biophysics and evolutionary population genetics

PubMed Central

Serohijos, Adrian W.R.; Shakhnovich, Eugene I.

2014-01-01

The variation among sequences and structures in nature is both determined by physical laws and by evolutionary history. However, these two factors are traditionally investigated by disciplines with different emphasis and philosophy—molecular biophysics on one hand and evolutionary population genetics in another. Here, we review recent theoretical and computational approaches that address the critical need to integrate these two disciplines. We first articulate the elements of these integrated approaches. Then, we survey their contribution to our mechanistic understanding of molecular evolution, the polymorphisms in coding region, the distribution of fitness effects (DFE) of mutations, the observed folding stability of proteins in nature, and the distribution of protein folds in genomes. PMID:24952216

Merging molecular mechanism and evolution: theory and computation at the interface of biophysics and evolutionary population genetics.

PubMed

Serohijos, Adrian W R; Shakhnovich, Eugene I

2014-06-01

The variation among sequences and structures in nature is both determined by physical laws and by evolutionary history. However, these two factors are traditionally investigated by disciplines with different emphasis and philosophy-molecular biophysics on one hand and evolutionary population genetics in another. Here, we review recent theoretical and computational approaches that address the crucial need to integrate these two disciplines. We first articulate the elements of these approaches. Then, we survey their contribution to our mechanistic understanding of molecular evolution, the polymorphisms in coding region, the distribution of fitness effects (DFE) of mutations, the observed folding stability of proteins in nature, and the distribution of protein folds in genomes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Deontic reasoning with emotional content: evolutionary psychology or decision theory?

PubMed

Perham, Nick; Oaksford, Mike

2005-09-10

Three experiments investigated the contrasting predictions of the evolutionary and decision-theoretic approaches to deontic reasoning. Two experiments embedded a hazard management (HM) rule in a social contract scenario that should lead to competition between innate modules. A 3rd experiment used a pure HM task. Threatening material was also introduced into the antecedent, p, of a deontic rule, if p then must q. According to the evolutionary approach, more HM responses (Cosmides & Tooby, 2000) are predicted when p is threatening, whereas decision theory predicts fewer. All 3 experiments were consistent with decision theory. Other theories are discussed, and it is concluded that they cannot account for the behavior observed in these experiments. 2005 Lawrence Erlbaum Associates, Inc.

Toward Evolvable Hardware Chips: Experiments with a Programmable Transistor Array

NASA Technical Reports Server (NTRS)

Stoica, Adrian

1998-01-01

Evolvable Hardware is reconfigurable hardware that self-configures under the control of an evolutionary algorithm. We search for a hardware configuration can be performed using software models or, faster and more accurate, directly in reconfigurable hardware. Several experiments have demonstrated the possibility to automatically synthesize both digital and analog circuits. The paper introduces an approach to automated synthesis of CMOS circuits, based on evolution on a Programmable Transistor Array (PTA). The approach is illustrated with a software experiment showing evolutionary synthesis of a circuit with a desired DC characteristic. A hardware implementation of a test PTA chip is then described, and the same evolutionary experiment is performed on the chip demonstrating circuit synthesis/self-configuration directly in hardware.

Mean-field approximations of fixation time distributions of evolutionary game dynamics on graphs

NASA Astrophysics Data System (ADS)

Ying, Li-Min; Zhou, Jie; Tang, Ming; Guan, Shu-Guang; Zou, Yong

2018-02-01

The mean fixation time is often not accurate for describing the timescales of fixation probabilities of evolutionary games taking place on complex networks. We simulate the game dynamics on top of complex network topologies and approximate the fixation time distributions using a mean-field approach. We assume that there are two absorbing states. Numerically, we show that the mean fixation time is sufficient in characterizing the evolutionary timescales when network structures are close to the well-mixing condition. In contrast, the mean fixation time shows large inaccuracies when networks become sparse. The approximation accuracy is determined by the network structure, and hence by the suitability of the mean-field approach. The numerical results show good agreement with the theoretical predictions.

Cancer Evolution: Mathematical Models and Computational Inference

PubMed Central

Beerenwinkel, Niko; Schwarz, Roland F.; Gerstung, Moritz; Markowetz, Florian

2015-01-01

Cancer is a somatic evolutionary process characterized by the accumulation of mutations, which contribute to tumor growth, clinical progression, immune escape, and drug resistance development. Evolutionary theory can be used to analyze the dynamics of tumor cell populations and to make inference about the evolutionary history of a tumor from molecular data. We review recent approaches to modeling the evolution of cancer, including population dynamics models of tumor initiation and progression, phylogenetic methods to model the evolutionary relationship between tumor subclones, and probabilistic graphical models to describe dependencies among mutations. Evolutionary modeling helps to understand how tumors arise and will also play an increasingly important prognostic role in predicting disease progression and the outcome of medical interventions, such as targeted therapy. PMID:25293804

An Improved Evolutionary Programming with Voting and Elitist Dispersal Scheme

NASA Astrophysics Data System (ADS)

Maity, Sayan; Gunjan, Kumar; Das, Swagatam

Although initially conceived for evolving finite state machines, Evolutionary Programming (EP), in its present form, is largely used as a powerful real parameter optimizer. For function optimization, EP mainly relies on its mutation operators. Over past few years several mutation operators have been proposed to improve the performance of EP on a wide variety of numerical benchmarks. However, unlike real-coded GAs, there has been no fitness-induced bias in parent selection for mutation in EP. That means the i-th population member is selected deterministically for mutation and creation of the i-th offspring in each generation. In this article we present an improved EP variant called Evolutionary Programming with Voting and Elitist Dispersal (EPVE). The scheme encompasses a voting process which not only gives importance to best solutions but also consider those solutions which are converging fast. By introducing Elitist Dispersal Scheme we maintain the elitism by keeping the potential solutions intact and other solutions are perturbed accordingly, so that those come out of the local minima. By applying these two techniques we can be able to explore those regions which have not been explored so far that may contain optima. Comparison with the recent and best-known versions of EP over 25 benchmark functions from the CEC (Congress on Evolutionary Computation) 2005 test-suite for real parameter optimization reflects the superiority of the new scheme in terms of final accuracy, speed, and robustness.

DiscML: an R package for estimating evolutionary rates of discrete characters using maximum likelihood.

PubMed

Kim, Tane; Hao, Weilong

2014-09-27

The study of discrete characters is crucial for the understanding of evolutionary processes. Even though great advances have been made in the analysis of nucleotide sequences, computer programs for non-DNA discrete characters are often dedicated to specific analyses and lack flexibility. Discrete characters often have different transition rate matrices, variable rates among sites and sometimes contain unobservable states. To obtain the ability to accurately estimate a variety of discrete characters, programs with sophisticated methodologies and flexible settings are desired. DiscML performs maximum likelihood estimation for evolutionary rates of discrete characters on a provided phylogeny with the options that correct for unobservable data, rate variations, and unknown prior root probabilities from the empirical data. It gives users options to customize the instantaneous transition rate matrices, or to choose pre-determined matrices from models such as birth-and-death (BD), birth-death-and-innovation (BDI), equal rates (ER), symmetric (SYM), general time-reversible (GTR) and all rates different (ARD). Moreover, we show application examples of DiscML on gene family data and on intron presence/absence data. DiscML was developed as a unified R program for estimating evolutionary rates of discrete characters with no restriction on the number of character states, and with flexibility to use different transition models. DiscML is ideal for the analyses of binary (1s/0s) patterns, multi-gene families, and multistate discrete morphological characteristics.

Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach.

PubMed

Liu, Li; Shao, Ling; Li, Xuelong; Lu, Ke

2016-01-01

Extracting discriminative and robust features from video sequences is the first and most critical step in human action recognition. In this paper, instead of using handcrafted features, we automatically learn spatio-temporal motion features for action recognition. This is achieved via an evolutionary method, i.e., genetic programming (GP), which evolves the motion feature descriptor on a population of primitive 3D operators (e.g., 3D-Gabor and wavelet). In this way, the scale and shift invariant features can be effectively extracted from both color and optical flow sequences. We intend to learn data adaptive descriptors for different datasets with multiple layers, which makes fully use of the knowledge to mimic the physical structure of the human visual cortex for action recognition and simultaneously reduce the GP searching space to effectively accelerate the convergence of optimal solutions. In our evolutionary architecture, the average cross-validation classification error, which is calculated by an support-vector-machine classifier on the training set, is adopted as the evaluation criterion for the GP fitness function. After the entire evolution procedure finishes, the best-so-far solution selected by GP is regarded as the (near-)optimal action descriptor obtained. The GP-evolving feature extraction method is evaluated on four popular action datasets, namely KTH, HMDB51, UCF YouTube, and Hollywood2. Experimental results show that our method significantly outperforms other types of features, either hand-designed or machine-learned.

Establishment of the mathematical model for diagnosing the engine valve faults by genetic programming

NASA Astrophysics Data System (ADS)

Yang, Wen-Xian

2006-05-01

Available machine fault diagnostic methods show unsatisfactory performances on both on-line and intelligent analyses because their operations involve intensive calculations and are labour intensive. Aiming at improving this situation, this paper describes the development of an intelligent approach by using the Genetic Programming (abbreviated as GP) method. Attributed to the simple calculation of the mathematical model being constructed, different kinds of machine faults may be diagnosed correctly and quickly. Moreover, human input is significantly reduced in the process of fault diagnosis. The effectiveness of the proposed strategy is validated by an illustrative example, in which three kinds of valve states inherent in a six-cylinders/four-stroke cycle diesel engine, i.e. normal condition, valve-tappet clearance and gas leakage faults, are identified. In the example, 22 mathematical functions have been specially designed and 8 easily obtained signal features are used to construct the diagnostic model. Different from existing GPs, the diagnostic tree used in the algorithm is constructed in an intelligent way by applying a power-weight coefficient to each feature. The power-weight coefficients vary adaptively between 0 and 1 during the evolutionary process. Moreover, different evolutionary strategies are employed, respectively for selecting the diagnostic features and functions, so that the mathematical functions are sufficiently utilized and in the meantime, the repeated use of signal features may be fully avoided. The experimental results are illustrated diagrammatically in the following sections.

Disease Dynamics in Ants: A Critical Review of the Ecological Relevance of Using Generalist Fungi to Study Infections in Insect Societies.

PubMed

Loreto, R G; Hughes, D P

2016-01-01

It is assumed that social life can lead to the rapid spread of infectious diseases and outbreaks. In ants, disease outbreaks are rare and the expression of collective behaviors is invoked to explain the absence of epidemics in natural populations. Here, we address the ecological approach employed by many studies that have notably focused (89% of the studies) on two genera of generalist fungal parasites (Beauveria and Metarhizium). We ask whether these are the most representative models to study the evolutionary ecology of ant-fungal parasite interactions. To assess this, we critically examine the literature on ants and their interactions with fungal parasites from the past 114years (1900-2014). We discuss how current evolutionary ecology approaches emerged from studies focused on the biological control of pest ants. We also analyzed the ecological relevance of the laboratory protocols used in evolutionary ecology studies employing generalist parasites, as well as the rare natural occurrence of these parasites on ants. After a detailed consideration of all the publications, we suggest that using generalist pathogens such as Beauveria and Metarhizium is not an optimal approach if the goal is to study the evolutionary ecology of disease in ants. We conclude by advocating for approaches that incorporate greater realism. Copyright © 2016 Elsevier Inc. All rights reserved.

The Evolutionary Psychology of Envy and Jealousy

PubMed Central

Ramachandran, Vilayanur S.; Jalal, Baland

2017-01-01

The old dogma has always been that the most complex aspects of human emotions are driven by culture; Germans and English are thought to be straight-laced whereas Italians and Indians are effusive. Yet in the last two decades there has been a growing realization that even though culture plays a major role in the final expression of human nature, there must be a basic scaffolding specified by genes. While this is recognized to be true for simple emotions like anger, fear, and joy, the relevance of evolutionary arguments for more complex nuances of emotion have been inadequately explored. In this paper, we consider envy or jealousy as an example; the feeling evoked when someone is better off than you. Our approach is broadly consistent with traditional evolutionary psychology (EP) approaches, but takes it further by exploring the complexity and functional logic of the emotion – and the precise social triggers that elicit them – by using deliberately farfetched, and contrived “thought experiments” that the subject is asked to participate in. When common sense (e.g., we should be jealous of Bill Gates – not of our slightly richer neighbor) appears to contradict observed behavior (i.e., we are more envious of our neighbor) the paradox can often be resolved by evolutionary considerations which h predict the latter. Many – but not all – EP approaches fail because evolution and common sense do not make contradictory predictions. Finally, we briefly raise the possibility that gaining deeper insight into the evolutionary origins of certain undesirable emotions or behaviors can help shake them off, and may therefore have therapeutic utility. Such an approach would complement current therapies (such as cognitive behavior therapies, psychoanalysis, psychopharmacologies, and hypnotherapy), rather than negate them. PMID:28970815

On joint subtree distributions under two evolutionary models.

PubMed

Wu, Taoyang; Choi, Kwok Pui

2016-04-01

In population and evolutionary biology, hypotheses about micro-evolutionary and macro-evolutionary processes are commonly tested by comparing the shape indices of empirical evolutionary trees with those predicted by neutral models. A key ingredient in this approach is the ability to compute and quantify distributions of various tree shape indices under random models of interest. As a step to meet this challenge, in this paper we investigate the joint distribution of cherries and pitchforks (that is, subtrees with two and three leaves) under two widely used null models: the Yule-Harding-Kingman (YHK) model and the proportional to distinguishable arrangements (PDA) model. Based on two novel recursive formulae, we propose a dynamic approach to numerically compute the exact joint distribution (and hence the marginal distributions) for trees of any size. We also obtained insights into the statistical properties of trees generated under these two models, including a constant correlation between the cherry and the pitchfork distributions under the YHK model, and the log-concavity and unimodality of the cherry distributions under both models. In addition, we show that there exists a unique change point for the cherry distributions between these two models. Copyright © 2015 Elsevier Inc. All rights reserved.

The sociobiology of genes: the gene's eye view as a unifying behavioural-ecological framework for biological evolution.

PubMed

De Tiège, Alexis; Van de Peer, Yves; Braeckman, Johan; Tanghe, Koen B

2017-11-22

Although classical evolutionary theory, i.e., population genetics and the Modern Synthesis, was already implicitly 'gene-centred', the organism was, in practice, still generally regarded as the individual unit of which a population is composed. The gene-centred approach to evolution only reached a logical conclusion with the advent of the gene-selectionist or gene's eye view in the 1960s and 1970s. Whereas classical evolutionary theory can only work with (genotypically represented) fitness differences between individual organisms, gene-selectionism is capable of working with fitness differences among genes within the same organism and genome. Here, we explore the explanatory potential of 'intra-organismic' and 'intra-genomic' gene-selectionism, i.e., of a behavioural-ecological 'gene's eye view' on genetic, genomic and organismal evolution. First, we give a general outline of the framework and how it complements the-to some extent-still 'organism-centred' approach of classical evolutionary theory. Secondly, we give a more in-depth assessment of its explanatory potential for biological evolution, i.e., for Darwin's 'common descent with modification' or, more specifically, for 'historical continuity or homology with modular evolutionary change' as it has been studied by evolutionary developmental biology (evo-devo) during the last few decades. In contrast with classical evolutionary theory, evo-devo focuses on 'within-organism' developmental processes. Given the capacity of gene-selectionism to adopt an intra-organismal gene's eye view, we outline the relevance of the latter model for evo-devo. Overall, we aim for the conceptual integration between the gene's eye view on the one hand, and more organism-centred evolutionary models (both classical evolutionary theory and evo-devo) on the other.

Howling about Trophic Cascades

ERIC Educational Resources Information Center

Kowalewski, David

2012-01-01

Following evolutionary theory and an agriculture model, ecosystem research has stressed bottom-up dynamics, implying that top wild predators are epiphenomenal effects of more basic causes. As such, they are assumed expendable. A more modern co-evolutionary and wilderness approach--trophic cascades--instead suggests that top predators, whose…

Evolution and Vaccination of Influenza Virus.

PubMed

Lam, Ham Ching; Bi, Xuan; Sreevatsan, Srinand; Boley, Daniel

2017-08-01

In this study, we present an application paradigm in which an unsupervised machine learning approach is applied to the high-dimensional influenza genetic sequences to investigate whether vaccine is a driving force to the evolution of influenza virus. We first used a visualization approach to visualize the evolutionary paths of vaccine-controlled and non-vaccine-controlled influenza viruses in a low-dimensional space. We then quantified the evolutionary differences between their evolutionary trajectories through the use of within- and between-scatter matrices computation to provide the statistical confidence to support the visualization results. We used the influenza surface Hemagglutinin (HA) gene for this study as the HA gene is the major target of the immune system. The visualization is achieved without using any clustering methods or prior information about the influenza sequences. Our results clearly showed that the evolutionary trajectories between vaccine-controlled and non-vaccine-controlled influenza viruses are different and vaccine as an evolution driving force cannot be completely eliminated.

Theoretical Foundation of the RelTime Method for Estimating Divergence Times from Variable Evolutionary Rates

PubMed Central

Tamura, Koichiro; Tao, Qiqing; Kumar, Sudhir

2018-01-01

Abstract RelTime estimates divergence times by relaxing the assumption of a strict molecular clock in a phylogeny. It shows excellent performance in estimating divergence times for both simulated and empirical molecular sequence data sets in which evolutionary rates varied extensively throughout the tree. RelTime is computationally efficient and scales well with increasing size of data sets. Until now, however, RelTime has not had a formal mathematical foundation. Here, we show that the basis of the RelTime approach is a relative rate framework (RRF) that combines comparisons of evolutionary rates in sister lineages with the principle of minimum rate change between evolutionary lineages and their respective descendants. We present analytical solutions for estimating relative lineage rates and divergence times under RRF. We also discuss the relationship of RRF with other approaches, including the Bayesian framework. We conclude that RelTime will be useful for phylogenies with branch lengths derived not only from molecular data, but also morphological and biochemical traits. PMID:29893954

Structural technology challenges for evolutionary growth of Space Station Freedom

NASA Technical Reports Server (NTRS)

Doiron, Harold H.

1990-01-01

A proposed evolutionary growth scenario for Space Station Freedom was defined recently by a NASA task force created to study requirements for a Human Exploration Initiative. The study was an initial response to President Bush's July 20, 1989 proposal to begin a long range program of human exploration of space including a permanently manned lunar base and a manned mission to Mars. This growth scenario evolves Freedom into a critical transportation node to support lunar and Mars missions. The growth scenario begins with the Assembly Complete configuration and adds structure, power, and facilities to support a Lunar Transfer Vehicle (LTV) verification flight. Evolutionary growth continues to support expendable, then reusable LTV operations, and finally, LTV and Mars Transfer Vehicle (MTV) operations. The significant structural growth and additional operations creating new loading conditions will present new technological and structural design challenges in addition to the considerable technology requirements of the baseline Space Station Freedom program. Several structural design and technology issues of the baseline program are reviewed and related technology development required by the growth scenario is identified.

Growth requirements for multidiscipline research and development on the evolutionary space station

NASA Technical Reports Server (NTRS)

Meredith, Barry; Ahlf, Peter; Saucillo, Rudy; Eakman, David

1988-01-01

The NASA Space Station Freedom is being designed to facilitate on-orbit evolution and growth to accommodate changing user needs and future options for U.S. space exploration. In support of the Space Station Freedom Program Preliminary Requirements Review, The Langley Space Station Office has identified a set of resource requirements for Station growth which is deemed adequate for the various evolution options. As part of that effort, analysis was performed to scope requirements for Space Station as an expanding, multidiscipline facility for scientific research, technology development and commercial production. This report describes the assumptions, approach and results of the study.

Applying molecular genetic tools to the conservation and action plan for the critically endangered Far Eastern leopard (Panthera pardus orientalis).

PubMed

Uphyrkina, Olga; O'Brien, Stephen J

2003-08-01

A role for molecular genetic approaches in conservation of endangered taxa is now commonly recognized. Because conservation genetic analyses provide essential insights on taxonomic status, recent evolutionary history and current health of endangered taxa, they are considered in nearly all conservation programs. Genetic analyses of the critically endangered Far Eastern, or Amur leopard, Panthera pardus orientalis, have been done recently to address all of these questions and develop strategies for survival of the leopard in the wild. The genetic status and implication for conservation management of the Far Eastern leopard subspecies are discussed.

Management Practices and Tools: 2000-2004

NASA Technical Reports Server (NTRS)

2004-01-01

This custom bibliography from the NASA Scientific and Technical Information Program lists a sampling of records found in the NASA Aeronautics and Space Database. The scope of this topic is divided into four parts and covers the adoption of proven personnel and management reforms to implement the national space exploration vision, including the use of "system-of-systems" approach; policies of spiral, evolutionary development; reliance upon lead systems integrators; and independent technical and cost assessments. This area of focus is one of the enabling technologies as defined by NASA s Report of the President s Commission on Implementation of United States Space Exploration Policy, published in June 2004.

Beyond the pleistocene: using phylogeny and constraint to inform the evolutionary psychology of human mating.

PubMed

Eastwick, Paul W

2009-09-01

Evolutionary psychologists explore the adaptive function of traits and behaviors that characterize modern Homo sapiens. However, evolutionary psychologists have yet to incorporate the phylogenetic relationship between modern Homo sapiens and humans' hominid and pongid relatives (both living and extinct) into their theorizing. By considering the specific timing of evolutionary events and the role of evolutionary constraint, researchers using the phylogenetic approach can generate new predictions regarding mating phenomena and derive new explanations for existing evolutionary psychological findings. Especially useful is the concept of the adaptive workaround-an adaptation that manages the maladaptive elements of a pre-existing evolutionary constraint. The current review organizes 7 features of human mating into their phylogenetic context and presents evidence that 2 adaptive workarounds played a critical role as Homo sapiens's mating psychology evolved. These adaptive workarounds function in part to mute or refocus the effects of older, previously evolved adaptations and highlight the layered nature of humans' mating psychology. (c) 2009 APA, all rights reserved.

Marine Dispersal Scales Are Congruent over Evolutionary and Ecological Time.

PubMed

Pinsky, Malin L; Saenz-Agudelo, Pablo; Salles, Océane C; Almany, Glenn R; Bode, Michael; Berumen, Michael L; Andréfouët, Serge; Thorrold, Simon R; Jones, Geoffrey P; Planes, Serge

2017-01-09

The degree to which offspring remain near their parents or disperse widely is critical for understanding population dynamics, evolution, and biogeography, and for designing conservation actions. In the ocean, most estimates suggesting short-distance dispersal are based on direct ecological observations of dispersing individuals, while indirect evolutionary estimates often suggest substantially greater homogeneity among populations. Reconciling these two approaches and their seemingly competing perspectives on dispersal has been a major challenge. Here we show for the first time that evolutionary and ecological measures of larval dispersal can closely agree by using both to estimate the distribution of dispersal distances. In orange clownfish (Amphiprion percula) populations in Kimbe Bay, Papua New Guinea, we found that evolutionary dispersal kernels were 17 km (95% confidence interval: 12-24 km) wide, while an exhaustive set of direct larval dispersal observations suggested kernel widths of 27 km (19-36 km) or 19 km (15-27 km) across two years. The similarity between these two approaches suggests that ecological and evolutionary dispersal kernels can be equivalent, and that the apparent disagreement between direct and indirect measurements can be overcome. Our results suggest that carefully applied evolutionary methods, which are often less expensive, can be broadly relevant for understanding ecological dispersal across the tree of life. Copyright © 2017 Elsevier Ltd. All rights reserved.

Parallel evolutionary computation in bioinformatics applications.

PubMed

Pinho, Jorge; Sobral, João Luis; Rocha, Miguel

2013-05-01

A large number of optimization problems within the field of Bioinformatics require methods able to handle its inherent complexity (e.g. NP-hard problems) and also demand increased computational efforts. In this context, the use of parallel architectures is a necessity. In this work, we propose ParJECoLi, a Java based library that offers a large set of metaheuristic methods (such as Evolutionary Algorithms) and also addresses the issue of its efficient execution on a wide range of parallel architectures. The proposed approach focuses on the easiness of use, making the adaptation to distinct parallel environments (multicore, cluster, grid) transparent to the user. Indeed, this work shows how the development of the optimization library can proceed independently of its adaptation for several architectures, making use of Aspect-Oriented Programming. The pluggable nature of parallelism related modules allows the user to easily configure its environment, adding parallelism modules to the base source code when needed. The performance of the platform is validated with two case studies within biological model optimization. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Can-Evo-Ens: Classifier stacking based evolutionary ensemble system for prediction of human breast cancer using amino acid sequences.

PubMed

Ali, Safdar; Majid, Abdul

2015-04-01

The diagnostic of human breast cancer is an intricate process and specific indicators may produce negative results. In order to avoid misleading results, accurate and reliable diagnostic system for breast cancer is indispensable. Recently, several interesting machine-learning (ML) approaches are proposed for prediction of breast cancer. To this end, we developed a novel classifier stacking based evolutionary ensemble system "Can-Evo-Ens" for predicting amino acid sequences associated with breast cancer. In this paper, first, we selected four diverse-type of ML algorithms of Naïve Bayes, K-Nearest Neighbor, Support Vector Machines, and Random Forest as base-level classifiers. These classifiers are trained individually in different feature spaces using physicochemical properties of amino acids. In order to exploit the decision spaces, the preliminary predictions of base-level classifiers are stacked. Genetic programming (GP) is then employed to develop a meta-classifier that optimal combine the predictions of the base classifiers. The most suitable threshold value of the best-evolved predictor is computed using Particle Swarm Optimization technique. Our experiments have demonstrated the robustness of Can-Evo-Ens system for independent validation dataset. The proposed system has achieved the highest value of Area Under Curve (AUC) of ROC Curve of 99.95% for cancer prediction. The comparative results revealed that proposed approach is better than individual ML approaches and conventional ensemble approaches of AdaBoostM1, Bagging, GentleBoost, and Random Subspace. It is expected that the proposed novel system would have a major impact on the fields of Biomedical, Genomics, Proteomics, Bioinformatics, and Drug Development. Copyright © 2015 Elsevier Inc. All rights reserved.

The Evolutionary History of Protein Domains Viewed by Species Phylogeny

PubMed Central

Yang, Song; Bourne, Philip E.

2009-01-01

Background Protein structural domains are evolutionary units whose relationships can be detected over long evolutionary distances. The evolutionary history of protein domains, including the origin of protein domains, the identification of domain loss, transfer, duplication and combination with other domains to form new proteins, and the formation of the entire protein domain repertoire, are of great interest. Methodology/Principal Findings A methodology is presented for providing a parsimonious domain history based on gain, loss, vertical and horizontal transfer derived from the complete genomic domain assignments of 1015 organisms across the tree of life. When mapped to species trees the evolutionary history of domains and domain combinations is revealed, and the general evolutionary trend of domain and combination is analyzed. Conclusions/Significance We show that this approach provides a powerful tool to study how new proteins and functions emerged and to study such processes as horizontal gene transfer among more distant species. PMID:20041107

Evolutionary biology: a basic science for medicine in the 21st century.

PubMed

Perlman, Robert L

2011-01-01

Evolutionary biology was a poorly developed discipline at the time of the Flexner Report and was not included in Flexner's recommendations for premedical or medical education. Since that time, however, the value of an evolutionary approach to medicine has become increasingly recognized. There are several ways in which an evolutionary perspective can enrich medical education and improve medical practice. Evolutionary considerations rationalize our continued susceptibility or vulnerability to disease; they call attention to the idea that the signs and symptoms of disease may be adaptations that prevent or limit the severity of disease; they help us understand the ways in which our interventions may affect the evolution of microbial pathogens and of cancer cells; and they provide a framework for thinking about population variation and risk factors for disease. Evolutionary biology should become a foundational science for the medical education of the future.

Polymorphic Evolutionary Games.

PubMed

Fishman, Michael A

2016-06-07

In this paper, I present an analytical framework for polymorphic evolutionary games suitable for explicitly modeling evolutionary processes in diploid populations with sexual reproduction. The principal aspect of the proposed approach is adding diploid genetics cum sexual recombination to a traditional evolutionary game, and switching from phenotypes to haplotypes as the new game׳s pure strategies. Here, the relevant pure strategy׳s payoffs derived by summing the payoffs of all the phenotypes capable of producing gametes containing that particular haplotype weighted by the pertinent probabilities. The resulting game is structurally identical to the familiar Evolutionary Games with non-linear pure strategy payoffs (Hofbauer and Sigmund, 1998. Cambridge University Press), and can be analyzed in terms of an established analytical framework for such games. And these results can be translated into the terms of genotypic, and whence, phenotypic evolutionary stability pertinent to the original game. Copyright © 2016 Elsevier Ltd. All rights reserved.

Research traditions and evolutionary explanations in medicine.

PubMed

Méthot, Pierre-Olivier

2011-02-01

In this article, I argue that distinguishing 'evolutionary' from 'Darwinian' medicine will help us assess the variety of roles that evolutionary explanations can play in a number of medical contexts. Because the boundaries of evolutionary and Darwinian medicine overlap to some extent, however, they are best described as distinct 'research traditions' rather than as competing paradigms. But while evolutionary medicine does not stand out as a new scientific field of its own, Darwinian medicine is united by a number of distinctive theoretical and methodological claims. For example, evolutionary medicine and Darwinian medicine can be distinguished with respect to the styles of evolutionary explanations they employ. While the former primarily involves 'forward looking' explanations, the latter depends mostly on 'backward looking' explanations. A forward looking explanation tries to predict the effects of ongoing evolutionary processes on human health and disease in contemporary environments (e.g., hospitals). In contrast, a backward looking explanation typically applies evolutionary principles from the vantage point of humans' distant biological past in order to assess present states of health and disease. Both approaches, however, are concerned with the prevention and control of human diseases. In conclusion, I raise some concerns about the claim that 'nothing in medicine makes sense except in the light of evolution'.

Artificial Bee Colony Optimization for Short-Term Hydrothermal Scheduling

NASA Astrophysics Data System (ADS)

Basu, M.

2014-12-01

Artificial bee colony optimization is applied to determine the optimal hourly schedule of power generation in a hydrothermal system. Artificial bee colony optimization is a swarm-based algorithm inspired by the food foraging behavior of honey bees. The algorithm is tested on a multi-reservoir cascaded hydroelectric system having prohibited operating zones and thermal units with valve point loading. The ramp-rate limits of thermal generators are taken into consideration. The transmission losses are also accounted for through the use of loss coefficients. The algorithm is tested on two hydrothermal multi-reservoir cascaded hydroelectric test systems. The results of the proposed approach are compared with those of differential evolution, evolutionary programming and particle swarm optimization. From numerical results, it is found that the proposed artificial bee colony optimization based approach is able to provide better solution.

Analysis of Students' Arguments on Evolutionary Theory

ERIC Educational Resources Information Center

Basel, Nicolai; Harms, Ute; Prechtl, Helmut

2013-01-01

A qualitative exploratory study was conducted to reveal students' argumentation skills in the context of the topic of evolution. Transcripts from problem-centred interviews on secondary students' beliefs about evolutionary processes of adaptation were analysed using a content analysis approach. For this purpose two categorical systems were…

Evolutionary Multiobjective Design Targeting a Field Programmable Transistor Array

NASA Technical Reports Server (NTRS)

Aguirre, Arturo Hernandez; Zebulum, Ricardo S.; Coello, Carlos Coello

2004-01-01

This paper introduces the ISPAES algorithm for circuit design targeting a Field Programmable Transistor Array (FPTA). The use of evolutionary algorithms is common in circuit design problems, where a single fitness function drives the evolution process. Frequently, the design problem is subject to several goals or operating constraints, thus, designing a suitable fitness function catching all requirements becomes an issue. Such a problem is amenable for multi-objective optimization, however, evolutionary algorithms lack an inherent mechanism for constraint handling. This paper introduces ISPAES, an evolutionary optimization algorithm enhanced with a constraint handling technique. Several design problems targeting a FPTA show the potential of our approach.

Segmenting healthcare terminology users: a strategic approach to large scale evolutionary development.

PubMed

Price, C; Briggs, K; Brown, P J

1999-01-01

Healthcare terminologies have become larger and more complex, aiming to support a diverse range of functions across the whole spectrum of healthcare activity. Prioritization of development, implementation and evaluation can be achieved by regarding the "terminology" as an integrated system of content-based and functional components. Matching these components to target segments within the healthcare community, supports a strategic approach to evolutionary development and provides essential product differentiation to enable terminology providers and systems suppliers to focus on end-user requirements.

Achieving sustainable plant disease management through evolutionary principles.

PubMed

Zhan, Jiasui; Thrall, Peter H; Burdon, Jeremy J

2014-09-01

Plants and their pathogens are engaged in continuous evolutionary battles and sustainable disease management requires novel systems to create environments conducive for short-term and long-term disease control. In this opinion article, we argue that knowledge of the fundamental factors that drive host-pathogen coevolution in wild systems can provide new insights into disease development in agriculture. Such evolutionary principles can be used to guide the formulation of sustainable disease management strategies which can minimize disease epidemics while simultaneously reducing pressure on pathogens to evolve increased infectivity and aggressiveness. To ensure agricultural sustainability, disease management programs that reflect the dynamism of pathogen population structure are essential and evolutionary biologists should play an increasing role in their design. Copyright © 2014 Elsevier Ltd. All rights reserved.

Evolutionary and mechanistic theories of aging.

PubMed

Hughes, Kimberly A; Reynolds, Rose M

2005-01-01

Senescence (aging) is defined as a decline in performance and fitness with advancing age. Senescence is a nearly universal feature of multicellular organisms, and understanding why it occurs is a long-standing problem in biology. Here we present a concise review of both evolutionary and mechanistic theories of aging. We describe the development of the general evolutionary theory, along with the mutation accumulation, antagonistic pleiotropy, and disposable soma versions of the evolutionary model. The review of the mechanistic theories focuses on the oxidative stress resistance, cellular signaling, and dietary control mechanisms of life span extension. We close with a discussion of how an approach that makes use of both evolutionary and molecular analyses can address a critical question: Which of the mechanisms that can cause variation in aging actually do cause variation in natural populations?

Evolutionary and ecological approaches to the study of personality

PubMed Central

Réale, Denis; Dingemanse, Niels J.; Kazem, Anahita J. N.; Wright, Jonathan

2010-01-01

This introduction to the themed issue on Evolutionary and ecological approaches to the study of personality provides an overview of conceptual, theoretical and methodological progress in research on animal personalities over the last decade, and places the contributions to this volume in context. The issue has three main goals. First, we aimed to bring together theoreticians to contribute to the development of models providing adaptive explanations for animal personality that could guide empiricists, and stimulate exchange of ideas between the two groups of researchers. Second, we aimed to stimulate cross-fertilization between different scientific fields that study personality, namely behavioural ecology, psychology, genomics, quantitative genetics, neuroendocrinology and developmental biology. Third, we aimed to foster the application of an evolutionary framework to the study of personality. PMID:21078646

An adaptive paradigm for human space settlement

NASA Astrophysics Data System (ADS)

Smith, Cameron M.

2016-02-01

Because permanent space settlement will be multigenerational it will have to be viable on ecological timescales so far unfamiliar to those planning space exploration. Long-term viability will require evolutionary and adaptive planning. Adaptations in the natural world provide many lessons for such planning, but implementing these lessons will require a new, evolutionary paradigm for envisioning and carrying out Earth-independent space settlement. I describe some of these adaptive lessons and propose some cognitive shifts required to implement them in a genuinely evolutionary approach to human space settlement.

EvoBuild: A Quickstart Toolkit for Programming Agent-Based Models of Evolutionary Processes

ERIC Educational Resources Information Center

Wagh, Aditi; Wilensky, Uri

2018-01-01

Extensive research has shown that one of the benefits of programming to learn about scientific phenomena is that it facilitates learning about mechanisms underlying the phenomenon. However, using programming activities in classrooms is associated with costs such as requiring additional time to learn to program or students needing prior experience…

An Hypothesis-Driven, Molecular Phylogenetics Exercise for College Biology Students

ERIC Educational Resources Information Center

Parker, Joel D.; Ziemba, Robert E.; Cahan, Sara Helms; Rissing, Steven W.

2004-01-01

This hypothesis-driven laboratory exercise teaches how DNA evidence can be used to investigate an organism's evolutionary history while providing practical modeling of the fundamental processes of gene transcription and translation. We used an inquiry-based approach to construct a laboratory around a nontrivial, open-ended evolutionary question…

A Strategic Approach to Joint Officer Management: Analysis and Modeling Results

DTIC Science & Technology

2009-01-01

rules. 5 Johnson and Wichern, 2002, p. 643. 6 Sullivan and Perry, 2004, p. 370. 7 Francesco Mola and Raffaele Miele, “Evolutionary Algorithms for...in Military Affairs, Newport, R.I.: Center for Naval Warfare Studies, 2003. Mola , Francesco, and Raffaele Miele, “Evolutionary Algorithms for

Attachment in Middle Childhood: An Evolutionary-Developmental Perspective

ERIC Educational Resources Information Center

Del Giudice, Marco

2015-01-01

Middle childhood is a key transitional stage in the development of attachment processes and representations. Here I discuss the middle childhood transition from an evolutionary-developmental perspective and show how this approach offers fresh insight into the function and organization of attachment in this life stage. I begin by presenting an…

Evolutionary Developmental Psychology: Contributions from Comparative Research with Nonhuman Primates

ERIC Educational Resources Information Center

Maestripieri, Dario; Roney, James R.

2006-01-01

Evolutionary developmental psychology is a discipline that has the potential to integrate conceptual approaches to the study of behavioral development derived from psychology and biology as well as empirical data from humans and animals. Comparative research with animals, and especially with nonhuman primates, can provide evidence of adaptation in…

Bridging Developmental Systems Theory and Evolutionary Psychology Using Dynamic Optimization

ERIC Educational Resources Information Center

Frankenhuis, Willem E.; Panchanathan, Karthik; Clark Barrett, H.

2013-01-01

Interactions between evolutionary psychologists and developmental systems theorists have been largely antagonistic. This is unfortunate because potential synergies between the two approaches remain unexplored. This article presents a method that may help to bridge the divide, and that has proven fruitful in biology: dynamic optimization. Dynamic…

Analysis of evolutionary patterns of genes in campylobacter jejuni and C. coli

USDA-ARS?s Scientific Manuscript database

Background: In order to investigate the population genetics structure of thermophilic Campylobacter spp., we extracted a set of 1029 core gene families (CGF) from 25 sequenced genomes of C. jejuni, C. coli and C. lari. Based on these CGFs we employed different approaches to reveal the evolutionary ...

Optimal Wavelengths Selection Using Hierarchical Evolutionary Algorithm for Prediction of Firmness and Soluble Solids Content in Apples

USDA-ARS?s Scientific Manuscript database

Hyperspectral scattering is a promising technique for rapid and noninvasive measurement of multiple quality attributes of apple fruit. A hierarchical evolutionary algorithm (HEA) approach, in combination with subspace decomposition and partial least squares (PLS) regression, was proposed to select o...

Manager’s Guide to Technology Transition in an Evolutionary Acquisition Environment

DTIC Science & Technology

2005-06-01

program managers, product managers, staffs, and organizations that manage the development , procurement, production, and fielding of systems...rapidly advancing technologies. Technology transitions can occur during the development of systems, or even after a system has been in the field ...Documentation Evolutionary acquisition is an acquisition strategy that defines, develops , produces or acquires, and fields an initial hardware or software

A systems approach to physiologic evolution: From micelles to consciousness.

PubMed

Torday, John S; Miller, William B

2018-01-01

A systems approach to evolutionary biology offers the promise of an improved understanding of the fundamental principles of life through the effective integration of many biologic disciplines. It is presented that any critical integrative approach to evolutionary development involves a paradigmatic shift in perspective, more than just the engagement of a large number of disciplines. Critical to this differing viewpoint is the recognition that all biological processes originate from the unicellular state and remain permanently anchored to that phase throughout evolutionary development despite their macroscopic appearances. Multicellular eukaryotic development can, therefore, be viewed as a series of connected responses to epiphenomena that proceeds from that base in continuous iterative maintenance of collective cellular homeostatic equipoise juxtaposed against an ever-changing and challenging environment. By following this trajectory of multicellular eukaryotic evolution from within unicellular First Principles of Physiology forward, the mechanistic nature of complex physiology can be identified through a step-wise analysis of a continuous arc of vertebrate evolution based upon serial exaptations. © 2017 Wiley Periodicals, Inc.

Local Geometry and Evolutionary Conservation of Protein Surfaces Reveal the Multiple Recognition Patches in Protein-Protein Interactions

PubMed Central

Laine, Elodie; Carbone, Alessandra

2015-01-01

Protein-protein interactions (PPIs) are essential to all biological processes and they represent increasingly important therapeutic targets. Here, we present a new method for accurately predicting protein-protein interfaces, understanding their properties, origins and binding to multiple partners. Contrary to machine learning approaches, our method combines in a rational and very straightforward way three sequence- and structure-based descriptors of protein residues: evolutionary conservation, physico-chemical properties and local geometry. The implemented strategy yields very precise predictions for a wide range of protein-protein interfaces and discriminates them from small-molecule binding sites. Beyond its predictive power, the approach permits to dissect interaction surfaces and unravel their complexity. We show how the analysis of the predicted patches can foster new strategies for PPIs modulation and interaction surface redesign. The approach is implemented in JET2, an automated tool based on the Joint Evolutionary Trees (JET) method for sequence-based protein interface prediction. JET2 is freely available at www.lcqb.upmc.fr/JET2. PMID:26690684

Interactive optimization approach for optimal impulsive rendezvous using primer vector and evolutionary algorithms

NASA Astrophysics Data System (ADS)

Luo, Ya-Zhong; Zhang, Jin; Li, Hai-yang; Tang, Guo-Jin

2010-08-01

In this paper, a new optimization approach combining primer vector theory and evolutionary algorithms for fuel-optimal non-linear impulsive rendezvous is proposed. The optimization approach is designed to seek the optimal number of impulses as well as the optimal impulse vectors. In this optimization approach, adding a midcourse impulse is determined by an interactive method, i.e. observing the primer-magnitude time history. An improved version of simulated annealing is employed to optimize the rendezvous trajectory with the fixed-number of impulses. This interactive approach is evaluated by three test cases: coplanar circle-to-circle rendezvous, same-circle rendezvous and non-coplanar rendezvous. The results show that the interactive approach is effective and efficient in fuel-optimal non-linear rendezvous design. It can guarantee solutions, which satisfy the Lawden's necessary optimality conditions.

Behavioral Genetic Toolkits: Toward the Evolutionary Origins of Complex Phenotypes.

PubMed

Rittschof, C C; Robinson, G E

2016-01-01

The discovery of toolkit genes, which are highly conserved genes that consistently regulate the development of similar morphological phenotypes across diverse species, is one of the most well-known observations in the field of evolutionary developmental biology. Surprisingly, this phenomenon is also relevant for a wide array of behavioral phenotypes, despite the fact that these phenotypes are highly complex and regulated by many genes operating in diverse tissues. In this chapter, we review the use of the toolkit concept in the context of behavior, noting the challenges of comparing behaviors and genes across diverse species, but emphasizing the successes in identifying genetic toolkits for behavior; these successes are largely attributable to the creative research approaches fueled by advances in behavioral genomics. We have two general goals: (1) to acknowledge the groundbreaking progress in this field, which offers new approaches to the difficult but exciting challenge of understanding the evolutionary genetic basis of behaviors, some of the most complex phenotypes known, and (2) to provide a theoretical framework that encompasses the scope of behavioral genetic toolkit studies in order to clearly articulate the research questions relevant to the toolkit concept. We emphasize areas for growth and highlight the emerging approaches that are being used to drive the field forward. Behavioral genetic toolkit research has elevated the use of integrative and comparative approaches in the study of behavior, with potentially broad implications for evolutionary biologists and behavioral ecologists alike. © 2016 Elsevier Inc. All rights reserved.

Using evolutionary computations to understand the design and evolution of gene and cell regulatory networks.

PubMed

Spirov, Alexander; Holloway, David

2013-07-15

This paper surveys modeling approaches for studying the evolution of gene regulatory networks (GRNs). Modeling of the design or 'wiring' of GRNs has become increasingly common in developmental and medical biology, as a means of quantifying gene-gene interactions, the response to perturbations, and the overall dynamic motifs of networks. Drawing from developments in GRN 'design' modeling, a number of groups are now using simulations to study how GRNs evolve, both for comparative genomics and to uncover general principles of evolutionary processes. Such work can generally be termed evolution in silico. Complementary to these biologically-focused approaches, a now well-established field of computer science is Evolutionary Computations (ECs), in which highly efficient optimization techniques are inspired from evolutionary principles. In surveying biological simulation approaches, we discuss the considerations that must be taken with respect to: (a) the precision and completeness of the data (e.g. are the simulations for very close matches to anatomical data, or are they for more general exploration of evolutionary principles); (b) the level of detail to model (we proceed from 'coarse-grained' evolution of simple gene-gene interactions to 'fine-grained' evolution at the DNA sequence level); (c) to what degree is it important to include the genome's cellular context; and (d) the efficiency of computation. With respect to the latter, we argue that developments in computer science EC offer the means to perform more complete simulation searches, and will lead to more comprehensive biological predictions. Copyright © 2013 Elsevier Inc. All rights reserved.

Simultaneously estimating evolutionary history and repeated traits phylogenetic signal: applications to viral and host phenotypic evolution

PubMed Central

Vrancken, Bram; Lemey, Philippe; Rambaut, Andrew; Bedford, Trevor; Longdon, Ben; Günthard, Huldrych F.; Suchard, Marc A.

2014-01-01

Phylogenetic signal quantifies the degree to which resemblance in continuously-valued traits reflects phylogenetic relatedness. Measures of phylogenetic signal are widely used in ecological and evolutionary research, and are recently gaining traction in viral evolutionary studies. Standard estimators of phylogenetic signal frequently condition on data summary statistics of the repeated trait observations and fixed phylogenetics trees, resulting in information loss and potential bias. To incorporate the observation process and phylogenetic uncertainty in a model-based approach, we develop a novel Bayesian inference method to simultaneously estimate the evolutionary history and phylogenetic signal from molecular sequence data and repeated multivariate traits. Our approach builds upon a phylogenetic diffusion framework that model continuous trait evolution as a Brownian motion process and incorporates Pagel’s λ transformation parameter to estimate dependence among traits. We provide a computationally efficient inference implementation in the BEAST software package. We evaluate the synthetic performance of the Bayesian estimator of phylogenetic signal against standard estimators, and demonstrate the use of our coherent framework to address several virus-host evolutionary questions, including virulence heritability for HIV, antigenic evolution in influenza and HIV, and Drosophila sensitivity to sigma virus infection. Finally, we discuss model extensions that will make useful contributions to our flexible framework for simultaneously studying sequence and trait evolution. PMID:25780554

Multi-objective evolutionary optimization for constructing neural networks for virtual reality visual data mining: application to geophysical prospecting.

PubMed

Valdés, Julio J; Barton, Alan J

2007-05-01

A method for the construction of virtual reality spaces for visual data mining using multi-objective optimization with genetic algorithms on nonlinear discriminant (NDA) neural networks is presented. Two neural network layers (the output and the last hidden) are used for the construction of simultaneous solutions for: (i) a supervised classification of data patterns and (ii) an unsupervised similarity structure preservation between the original data matrix and its image in the new space. A set of spaces are constructed from selected solutions along the Pareto front. This strategy represents a conceptual improvement over spaces computed by single-objective optimization. In addition, genetic programming (in particular gene expression programming) is used for finding analytic representations of the complex mappings generating the spaces (a composition of NDA and orthogonal principal components). The presented approach is domain independent and is illustrated via application to the geophysical prospecting of caves.

Critical thinking skills of basic baccalaureate and Accelerated second-degree nursing students.

PubMed

Newton, Sarah E; Moore, Gary

2013-01-01

The purpose of this study was to describe the critical thinking (CT) skills of basic baccalaureate (basic-BSN) and accelerated second-degree (ASD) nursing students at nursing program entry. Many authors propose that CT in nursing should be viewed as a developmental process that increases as students' experiences with it change. However, there is a dearth of literature that describes basic-BSN and ASD students' CT skills from an evolutionary perspective. The study design was exploratory descriptive. The results indicated thatASD students had higher CT scores on a quantitative critical thinking assessment at program entry than basic-BSN students. CT data are needed across the nursing curriculum from basic-BSN and ASD students in order for nurse educators to develop cohort-specific pedagogical approaches that facilitate critical thinking in nursing and produce nurses with good CT skills for the future.

A Generalized National Planning Approach for Admission Capacity in Higher Education: A Nonlinear Integer Goal Programming Model with a Novel Differential Evolution Algorithm

PubMed Central

El-Qulity, Said Ali; Mohamed, Ali Wagdy

2016-01-01

This paper proposes a nonlinear integer goal programming model (NIGPM) for solving the general problem of admission capacity planning in a country as a whole. The work aims to satisfy most of the required key objectives of a country related to the enrollment problem for higher education. The system general outlines are developed along with the solution methodology for application to the time horizon in a given plan. The up-to-date data for Saudi Arabia is used as a case study and a novel evolutionary algorithm based on modified differential evolution (DE) algorithm is used to solve the complexity of the NIGPM generated for different goal priorities. The experimental results presented in this paper show their effectiveness in solving the admission capacity for higher education in terms of final solution quality and robustness. PMID:26819583

A Generalized National Planning Approach for Admission Capacity in Higher Education: A Nonlinear Integer Goal Programming Model with a Novel Differential Evolution Algorithm.

PubMed

El-Qulity, Said Ali; Mohamed, Ali Wagdy

2016-01-01

This paper proposes a nonlinear integer goal programming model (NIGPM) for solving the general problem of admission capacity planning in a country as a whole. The work aims to satisfy most of the required key objectives of a country related to the enrollment problem for higher education. The system general outlines are developed along with the solution methodology for application to the time horizon in a given plan. The up-to-date data for Saudi Arabia is used as a case study and a novel evolutionary algorithm based on modified differential evolution (DE) algorithm is used to solve the complexity of the NIGPM generated for different goal priorities. The experimental results presented in this paper show their effectiveness in solving the admission capacity for higher education in terms of final solution quality and robustness.

Texture segmentation by genetic programming.

PubMed

Song, Andy; Ciesielski, Vic

2008-01-01

This paper describes a texture segmentation method using genetic programming (GP), which is one of the most powerful evolutionary computation algorithms. By choosing an appropriate representation texture, classifiers can be evolved without computing texture features. Due to the absence of time-consuming feature extraction, the evolved classifiers enable the development of the proposed texture segmentation algorithm. This GP based method can achieve a segmentation speed that is significantly higher than that of conventional methods. This method does not require a human expert to manually construct models for texture feature extraction. In an analysis of the evolved classifiers, it can be seen that these GP classifiers are not arbitrary. Certain textural regularities are captured by these classifiers to discriminate different textures. GP has been shown in this study as a feasible and a powerful approach for texture classification and segmentation, which are generally considered as complex vision tasks.

New Insight into the Colonization Processes of Common Voles: Inferences from Molecular and Fossil Evidence

PubMed Central

Tougard, Christelle; Renvoisé, Elodie; Petitjean, Amélie; Quéré, Jean-Pierre

2008-01-01

Elucidating the colonization processes associated with Quaternary climatic cycles is important in order to understand the distribution of biodiversity and the evolutionary potential of temperate plant and animal species. In Europe, general evolutionary scenarios have been defined from genetic evidence. Recently, these scenarios have been challenged with genetic as well as fossil data. The origins of the modern distributions of most temperate plant and animal species could predate the Last Glacial Maximum. The glacial survival of such populations may have occurred in either southern (Mediterranean regions) and/or northern (Carpathians) refugia. Here, a phylogeographic analysis of a widespread European small mammal (Microtus arvalis) is conducted with a multidisciplinary approach. Genetic, fossil and ecological traits are used to assess the evolutionary history of this vole. Regardless of whether the European distribution of the five previously identified evolutionary lineages is corroborated, this combined analysis brings to light several colonization processes of M. arvalis. The species' dispersal was relatively gradual with glacial survival in small favourable habitats in Western Europe (from Germany to Spain) while in the rest of Europe, because of periglacial conditions, dispersal was less regular with bottleneck events followed by postglacial expansions. Our study demonstrates that the evolutionary history of European temperate small mammals is indeed much more complex than previously suggested. Species can experience heterogeneous evolutionary histories over their geographic range. Multidisciplinary approaches should therefore be preferentially chosen in prospective studies, the better to understand the impact of climatic change on past and present biodiversity. PMID:18958287

The Evolution of Different Forms of Sociality: Behavioral Mechanisms and Eco-Evolutionary Feedback

PubMed Central

van der Post, Daniel J.; Verbrugge, Rineke; Hemelrijk, Charlotte K.

2015-01-01

Different forms of sociality have evolved via unique evolutionary trajectories. However, it remains unknown to what extent trajectories of social evolution depend on the specific characteristics of different species. Our approach to studying such trajectories is to use evolutionary case-studies, so that we can investigate how grouping co-evolves with a multitude of individual characteristics. Here we focus on anti-predator vigilance and foraging. We use an individual-based model, where behavioral mechanisms are specified, and costs and benefits are not predefined. We show that evolutionary changes in grouping alter selection pressures on vigilance, and vice versa. This eco-evolutionary feedback generates an evolutionary progression from “leader-follower” societies to “fission-fusion” societies, where cooperative vigilance in groups is maintained via a balance between within- and between-group selection. Group-level selection is generated from an assortment that arises spontaneously when vigilant and non-vigilant foragers have different grouping tendencies. The evolutionary maintenance of small groups, and cooperative vigilance in those groups, is therefore achieved simultaneously. The evolutionary phases, and the transitions between them, depend strongly on behavioral mechanisms. Thus, integrating behavioral mechanisms and eco-evolutionary feedback is critical for understanding what kinds of intermediate stages are involved during the evolution of particular forms of sociality. PMID:25629313

The evolution of different forms of sociality: behavioral mechanisms and eco-evolutionary feedback.

PubMed

van der Post, Daniel J; Verbrugge, Rineke; Hemelrijk, Charlotte K

2015-01-01

Different forms of sociality have evolved via unique evolutionary trajectories. However, it remains unknown to what extent trajectories of social evolution depend on the specific characteristics of different species. Our approach to studying such trajectories is to use evolutionary case-studies, so that we can investigate how grouping co-evolves with a multitude of individual characteristics. Here we focus on anti-predator vigilance and foraging. We use an individual-based model, where behavioral mechanisms are specified, and costs and benefits are not predefined. We show that evolutionary changes in grouping alter selection pressures on vigilance, and vice versa. This eco-evolutionary feedback generates an evolutionary progression from "leader-follower" societies to "fission-fusion" societies, where cooperative vigilance in groups is maintained via a balance between within- and between-group selection. Group-level selection is generated from an assortment that arises spontaneously when vigilant and non-vigilant foragers have different grouping tendencies. The evolutionary maintenance of small groups, and cooperative vigilance in those groups, is therefore achieved simultaneously. The evolutionary phases, and the transitions between them, depend strongly on behavioral mechanisms. Thus, integrating behavioral mechanisms and eco-evolutionary feedback is critical for understanding what kinds of intermediate stages are involved during the evolution of particular forms of sociality.

Buried treasure: evolutionary perspectives on microbial iron piracy

PubMed Central

Barber, Matthew F.; Elde, Nels C.

2015-01-01

Host-pathogen interactions provide valuable systems for the study of evolutionary genetics and natural selection. The sequestration of essential iron has emerged as a critical innate defense system termed nutritional immunity, leading pathogens to evolve mechanisms of `iron piracy' to scavenge this metal from host proteins. This battle for iron carries numerous consequences not only for host-pathogen evolution, but also microbial community interactions. Here we highlight recent and potential future areas of investigation on the evolutionary implications of microbial iron piracy in relation to molecular arms races, host range, competition, and virulence. Applying evolutionary genetic approaches to the study of microbial iron acquisition could also provide new inroads for understanding and combating infectious disease. PMID:26431675

A Genetic Representation for Evolutionary Fault Recovery in Virtex FPGAs

NASA Technical Reports Server (NTRS)

Lohn, Jason; Larchev, Greg; DeMara, Ronald; Korsmeyer, David (Technical Monitor)

2003-01-01

Most evolutionary approaches to fault recovery in FPGAs focus on evolving alternative logic configurations as opposed to evolving the intra-cell routing. Since the majority of transistors in a typical FPGA are dedicated to interconnect, nearly 80% according to one estimate, evolutionary fault-recovery systems should benefit hy accommodating routing. In this paper, we propose an evolutionary fault-recovery system employing a genetic representation that takes into account both logic and routing configurations. Experiments were run using a software model of the Xilinx Virtex FPGA. We report that using four Virtex combinational logic blocks, we were able to evolve a 100% accurate quadrature decoder finite state machine in the presence of a stuck-at-zero fault.

Implementation of a longitudinal mentored scholarly project: an approach at two medical schools.

PubMed

Boninger, Michael; Troen, Philip; Green, Emily; Borkan, Jeffrey; Lance-Jones, Cynthia; Humphrey, Allen; Gruppuso, Philip; Kant, Peter; McGee, James; Willochell, Michael; Schor, Nina; Kanter, Steven L; Levine, Arthur S

2010-03-01

An increasing number of medical schools have implemented or are considering implementing scholarly activity programs as part of their undergraduate medical curricula. The goal of these programs is to foster students' analytical skills, enhance their self-directed learning and their oral and written communication skills, and ultimately to train better physicians. In this article, the authors describe the approach to implementing scholarly activities at a school that requires this activity and at a school where it is elective. Both programs have dealt with significant challenges including orienting students to a complex activity that is fundamentally different than traditional medical school courses and clerkships, helping both students and their mentors understand how to "stay on track" and complete work, especially during the third and fourth years, and educating students and mentors about the responsible conduct of research, especially involving human participants. Both schools have found the implementation process to be evolutionary, requiring experience before faculty could significantly improve processes. A required scholarly activity has highlighted the need for information technology (IT) support, including Web-based document storage and student updates, as well as automatic e-mails alerting supervisory individuals to student activity. Directors of the elective program have found difficulty with both ensuring uniform outcomes across different areas of study and leadership changes in a process that has been largely student-driven. Both programs have found that teamwork, regular meetings, and close communication have helped with implementation. Schools considering the establishment of a scholarly activity should consider these factors when designing programs.

Cancer evolution: mathematical models and computational inference.

PubMed

Beerenwinkel, Niko; Schwarz, Roland F; Gerstung, Moritz; Markowetz, Florian

2015-01-01

Cancer is a somatic evolutionary process characterized by the accumulation of mutations, which contribute to tumor growth, clinical progression, immune escape, and drug resistance development. Evolutionary theory can be used to analyze the dynamics of tumor cell populations and to make inference about the evolutionary history of a tumor from molecular data. We review recent approaches to modeling the evolution of cancer, including population dynamics models of tumor initiation and progression, phylogenetic methods to model the evolutionary relationship between tumor subclones, and probabilistic graphical models to describe dependencies among mutations. Evolutionary modeling helps to understand how tumors arise and will also play an increasingly important prognostic role in predicting disease progression and the outcome of medical interventions, such as targeted therapy. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society of Systematic Biologists.

Selecting the Best: Evolutionary Engineering of Chemical Production in Microbes.

PubMed

Shepelin, Denis; Hansen, Anne Sofie Lærke; Lennen, Rebecca; Luo, Hao; Herrgård, Markus J

2018-05-11

Microbial cell factories have proven to be an economical means of production for many bulk, specialty, and fine chemical products. However, we still lack both a holistic understanding of organism physiology and the ability to predictively tune enzyme activities in vivo, thus slowing down rational engineering of industrially relevant strains. An alternative concept to rational engineering is to use evolution as the driving force to select for desired changes, an approach often described as evolutionary engineering. In evolutionary engineering, in vivo selections for a desired phenotype are combined with either generation of spontaneous mutations or some form of targeted or random mutagenesis. Evolutionary engineering has been used to successfully engineer easily selectable phenotypes, such as utilization of a suboptimal nutrient source or tolerance to inhibitory substrates or products. In this review, we focus primarily on a more challenging problem-the use of evolutionary engineering for improving the production of chemicals in microbes directly. We describe recent developments in evolutionary engineering strategies, in general, and discuss, in detail, case studies where production of a chemical has been successfully achieved through evolutionary engineering by coupling production to cellular growth.

Evolutionary adaptations: theoretical and practical implications for visual ergonomics.

PubMed

Fostervold, Knut Inge; Watten, Reidulf G; Volden, Frode

2014-01-01

The literature discussing visual ergonomics often mention that human vision is adapted to light emitted by the sun. However, theoretical and practical implications of this viewpoint is seldom discussed or taken into account. The paper discusses some of the main theoretical implications of an evolutionary approach to visual ergonomics. Based on interactional theory and ideas from ecological psychology an evolutionary stress model is proposed as a theoretical framework for future research in ergonomics and human factors. The model stresses the importance of developing work environments that fits with our evolutionary adaptations. In accordance with evolutionary psychology, the environment of evolutionary adaptedness (EEA) and evolutionarily-novel environments (EN) are used as key concepts. Using work with visual display units (VDU) as an example, the paper discusses how this knowledge can be utilized in an ergonomic analysis of risk factors in the work environment. The paper emphasises the importance of incorporating evolutionary theory in the field of ergonomics. Further, the paper encourages scientific practices that further our understanding of any phenomena beyond the borders of traditional proximal explanations.

Niche construction theory: a practical guide for ecologists.

PubMed

Odling-Smee, John; Erwin, Douglas H; Palkovacs, Eric P; Feldman, Marcus W; Laland, Kevin N

2013-03-01

Niche construction theory (NCT) explicitly recognizes environmental modication by organisms ("niche construction") and their legacy overtime ("ecological inheritance") to be evolutionary processes in their own right. Here we illustrate how niche construction theory provides usedl conceptual tools and theoretical insights for integrating ecosystem ecology and evolutionary theory. We begin by briefly describing NCT, and illustrating how it deifers from conventional evolutionary approaches. We then distinguish between two aspects ofniche construction--environment alteration and subsequent evolution in response to constructed environments--equating the first of these with "ecosystem engineering." We describe some of the ecological and evolutionary impacts on ecosystems of niche construction, ecosystem engineering and ecological inheritance, and illustrate how these processes trigger ecological and evolutionary feedbacks and leave detectable ecological signatures that are open to investigation. FIinally, we provide a practical guide to how NCT could be deployed by ecologists and evolutionary biologists to aeplore ecoeoolutionay dynamics. We suggest that, by highlighting the ecological and evolutionay ramifications of changes that organisms bring about in ecosystems, NCT helps link ecosystem ecology to evolutionary biology, potentially leading to a deeper understanding of how ecosystems change over time.

The Evolution of Cartography Graduate Programs and the Development of New Graduate Programs in Cartography: An Assessment of Models.

ERIC Educational Resources Information Center

Steinke, Theodore R.

This paper traces the historical development of cartography graduate programs, establishes an evolutionary model, and evaluates the model to determine if it has some utility today for the development of programs capable of producing highly skilled cartographers. Cartography is defined to include traditional cartography, computer cartography,…

Unraveling the Tangled Skein: The Evolution of Transcriptional Regulatory Networks in Development.

PubMed

Rebeiz, Mark; Patel, Nipam H; Hinman, Veronica F

2015-01-01

The molecular and genetic basis for the evolution of anatomical diversity is a major question that has inspired evolutionary and developmental biologists for decades. Because morphology takes form during development, a true comprehension of how anatomical structures evolve requires an understanding of the evolutionary events that alter developmental genetic programs. Vast gene regulatory networks (GRNs) that connect transcription factors to their target regulatory sequences control gene expression in time and space and therefore determine the tissue-specific genetic programs that shape morphological structures. In recent years, many new examples have greatly advanced our understanding of the genetic alterations that modify GRNs to generate newly evolved morphologies. Here, we review several aspects of GRN evolution, including their deep preservation, their mechanisms of alteration, and how they originate to generate novel developmental programs.

What to expect from an evolutionary hypothesis for a human disease: The case of type 2 diabetes.

PubMed

Watve, Milind; Diwekar-Joshi, Manawa

2016-10-01

Evolutionary medicine has a promise to bring in a conceptual revolution in medicine. However, as yet the field does not have the same theoretical rigour as that of many other fields in evolutionary studies. We discuss here with reference to type 2 diabetes mellitus (T2DM) what role an evolutionary hypothesis should play in the development of thinking in medicine. Starting with the thrifty gene hypothesis, evolutionary thinking in T2DM has undergone several transitions, modifications and refinements of the thrift family of hypotheses. In addition alternative hypotheses independent of thrift are also suggested. However, most hypotheses look at partial pictures; make selective use of supportive data ignoring inconvenient truths. Most hypotheses look at a superficial picture and avoid getting into the intricacies of underlying molecular, neuronal and physiological processes. Very few hypotheses have suggested clinical implications and none of them have been tested with randomized clinical trials. In the meanwhile the concepts in the pathophysiology of T2DM are undergoing radical changes and evolutionary hypotheses need to take them into account. We suggest an approach and a set of criteria to evaluate the relative merits of the alternative hypotheses. A number of hypotheses are likely to fail when critically evaluated against these criteria. It is possible that more than one selective process are at work in the evolution of propensity to T2DM, but the intercompatibility of the alternative selective forces and their relative contribution needs to be examined. The approach we describe could potentially lead to a sound evolutionary theory that is clinically useful and testable by randomized controlled clinical trials. Copyright © 2016 Elsevier GmbH. All rights reserved.

A framework for evolutionary systems biology

PubMed Central

Loewe, Laurence

2009-01-01

Background Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects. Results Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions in silico. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism. Conclusion EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications. PMID:19239699

Space Station

NASA Image and Video Library

1982-01-01

McDornel Douglas performed an Evolutionary Space Platform Concept Study for the Marshall Space Flight Center in the early 1980's. The 10-month study was designed to define, evaluate, and compare approaches and concepts for evolving unmanned and manned capability platforms beyond the then current space platform concepts to an evolutionary goal of establishing a permanent-manned presence in space.

Approaches to understanding the impact of life-history features on plant-pathogen co-evolutionary dynamics

Treesearch

Jeremy J. Burdon; Peter H. Thrall; Adnane Nemri

2012-01-01

Natural plant-pathogen associations are complex interactions in which the interplay of environment, host, and pathogen factors results in spatially heterogeneous ecological and epidemiological dynamics. The evolutionary patterns that result from the interaction of these factors are still relatively poorly understood. Recently, integration of the appropriate spatial and...

Deontic Reasoning with Emotional Content: Evolutionary Psychology or Decision Theory?

ERIC Educational Resources Information Center

Perham, Nick; Oaksford, Mike

2005-01-01

Three experiments investigated the contrasting predictions of the evolutionary and decision-theoretic approaches to deontic reasoning. Two experiments embedded a hazard management (HM) rule in a social contract scenario that should lead to competition between innate modules. A 3rd experiment used a pure HM task. Threatening material was also…

Questioning Clerkship: Applying Popper's Evolutionary Analysis of Learning to Medical Student Training

ERIC Educational Resources Information Center

Chitpin, Jeremy Sebastian; Chitpin, Stephanie

2017-01-01

Purpose: Through a series of critical discussions on Karl Popper's evolutionary analysis of learning and the non-authoritarian values it promotes, the purpose of this paper is to advocate a Popperian approach for building medical student knowledge. Specifically, it challenges positivist assumptions that permeate the design and management of many…

Preschoolers' Social Dominance, Moral Cognition, and Moral Behavior: An Evolutionary Perspective

ERIC Educational Resources Information Center

Hawley, Patricia H.; Geldhof, G. John

2012-01-01

Various aspects of moral functioning, aggression, and positive peer regard were assessed in 153 preschool children. Our hypotheses were inspired by an evolutionary approach to morality that construes moral norms as tools of the social elite. Accordingly, children were also rated for social dominance and strategies for its attainment. We predicted…

Evolutionary computing for the design search and optimization of space vehicle power subsystems

NASA Technical Reports Server (NTRS)

Kordon, M.; Klimeck, G.; Hanks, D.

2004-01-01

Evolutionary computing has proven to be a straightforward and robust approach for optimizing a wide range of difficult analysis and design problems. This paper discusses the application of these techniques to an existing space vehicle power subsystem resource and performance analysis simulation in a parallel processing environment.

Finding a common path: predicting gene function using inferred evolutionary trees.

PubMed

Reynolds, Kimberly A

2014-07-14

Reporting in Cell, Li and colleagues (2014) describe an innovative method to functionally classify genes using evolutionary information. This approach demonstrates broad utility for eukaryotic gene annotation and suggests an intriguing new decomposition of pathways and complexes into evolutionarily conserved modules. Copyright © 2014 Elsevier Inc. All rights reserved.

The Evolution of Altruistic Preferences: Mothers versus Fathers.

PubMed

Alger, Ingela; Cox, Donald

2013-09-01

What can evolutionary biology tell us about male-female differences in preferences concerning family matters? Might mothers be more solicitous toward offspring than fathers, for example? The economics literature has documented gender differences-children benefit more from money put in the hands of mothers rather than fathers, for example-and these differences are thought to be partly due to preferences. Yet for good reason family economics is mostly concerned with how prices and incomes affect behavior against a backdrop of exogenous preferences. Evolutionary biology complements this approach by treating preferences as the outcome of natural selection. We mine the well-developed biological literature to make a prima facie case for evolutionary roots of parental preferences. We consider the most rudimentary of traits-sex differences in gamete size and internal fertilization-and explain how they have been thought to generate male-female differences in altruism toward children and other preferences related to family behavior. The evolutionary approach to the family illuminates connections between issues typically thought distinct in family economics, such as parental care and marriage markets.

Spatial evolutionary epidemiology of spreading epidemics

PubMed Central

2016-01-01

Most spatial models of host–parasite interactions either neglect the possibility of pathogen evolution or consider that this process is slow enough for epidemiological dynamics to reach an equilibrium on a fast timescale. Here, we propose a novel approach to jointly model the epidemiological and evolutionary dynamics of spatially structured host and pathogen populations. Starting from a multi-strain epidemiological model, we use a combination of spatial moment equations and quantitative genetics to analyse the dynamics of mean transmission and virulence in the population. A key insight of our approach is that, even in the absence of long-term evolutionary consequences, spatial structure can affect the short-term evolution of pathogens because of the build-up of spatial differentiation in mean virulence. We show that spatial differentiation is driven by a balance between epidemiological and genetic effects, and this quantity is related to the effect of kin competition discussed in previous studies of parasite evolution in spatially structured host populations. Our analysis can be used to understand and predict the transient evolutionary dynamics of pathogens and the emergence of spatial patterns of phenotypic variation. PMID:27798295

Spatial evolutionary epidemiology of spreading epidemics.

PubMed

Lion, S; Gandon, S

2016-10-26

Most spatial models of host-parasite interactions either neglect the possibility of pathogen evolution or consider that this process is slow enough for epidemiological dynamics to reach an equilibrium on a fast timescale. Here, we propose a novel approach to jointly model the epidemiological and evolutionary dynamics of spatially structured host and pathogen populations. Starting from a multi-strain epidemiological model, we use a combination of spatial moment equations and quantitative genetics to analyse the dynamics of mean transmission and virulence in the population. A key insight of our approach is that, even in the absence of long-term evolutionary consequences, spatial structure can affect the short-term evolution of pathogens because of the build-up of spatial differentiation in mean virulence. We show that spatial differentiation is driven by a balance between epidemiological and genetic effects, and this quantity is related to the effect of kin competition discussed in previous studies of parasite evolution in spatially structured host populations. Our analysis can be used to understand and predict the transient evolutionary dynamics of pathogens and the emergence of spatial patterns of phenotypic variation. © 2016 The Author(s).

The Evolution of Altruistic Preferences: Mothers versus Fathers

PubMed Central

Alger, Ingela; Cox, Donald

2013-01-01

What can evolutionary biology tell us about male-female differences in preferences concerning family matters? Might mothers be more solicitous toward offspring than fathers, for example? The economics literature has documented gender differences—children benefit more from money put in the hands of mothers rather than fathers, for example—and these differences are thought to be partly due to preferences. Yet for good reason family economics is mostly concerned with how prices and incomes affect behavior against a backdrop of exogenous preferences. Evolutionary biology complements this approach by treating preferences as the outcome of natural selection. We mine the well-developed biological literature to make a prima facie case for evolutionary roots of parental preferences. We consider the most rudimentary of traits—sex differences in gamete size and internal fertilization—and explain how they have been thought to generate male-female differences in altruism toward children and other preferences related to family behavior. The evolutionary approach to the family illuminates connections between issues typically thought distinct in family economics, such as parental care and marriage markets. PMID:23976890

Decentralized diagnostics based on a distributed micro-genetic algorithm for transducer networks monitoring large experimental systems.

PubMed

Arpaia, P; Cimmino, P; Girone, M; La Commara, G; Maisto, D; Manna, C; Pezzetti, M

2014-09-01

Evolutionary approach to centralized multiple-faults diagnostics is extended to distributed transducer networks monitoring large experimental systems. Given a set of anomalies detected by the transducers, each instance of the multiple-fault problem is formulated as several parallel communicating sub-tasks running on different transducers, and thus solved one-by-one on spatially separated parallel processes. A micro-genetic algorithm merges evaluation time efficiency, arising from a small-size population distributed on parallel-synchronized processors, with the effectiveness of centralized evolutionary techniques due to optimal mix of exploitation and exploration. In this way, holistic view and effectiveness advantages of evolutionary global diagnostics are combined with reliability and efficiency benefits of distributed parallel architectures. The proposed approach was validated both (i) by simulation at CERN, on a case study of a cold box for enhancing the cryogeny diagnostics of the Large Hadron Collider, and (ii) by experiments, under the framework of the industrial research project MONDIEVOB (Building Remote Monitoring and Evolutionary Diagnostics), co-funded by EU and the company Del Bo srl, Napoli, Italy.

An evolutionary approach to financial history.

PubMed

Ferguson, N

2009-01-01

Financial history is not conventionally thought of in evolutionary terms, but it should be. Traditional ways of thinking about finance, dating back to Hilferding, emphasize the importance of concentration and economies of scale. But these approaches overlook the rich "biodiversity" that characterizes the financial world. They also overlook the role of natural selection. To be sure, natural selection in the financial world is not exactly analogous to the processes first described by Darwin and elaborated on by modern biologists. There is conscious adaptation as well as random mutation. Moreover, there is something resembling "intelligent design" in finance, whereby regulators and legislators act in a quasidivine capacity, putting dinosaurs on life support. The danger is that such interventions in the natural processes of the market may ultimately distort the evolutionary process, by getting in the way of Schumpeter's "creative destruction."

Applying Evolutionary Anthropology

PubMed Central

Gibson, Mhairi A; Lawson, David W

2015-01-01

Evolutionary anthropology provides a powerful theoretical framework for understanding how both current environments and legacies of past selection shape human behavioral diversity. This integrative and pluralistic field, combining ethnographic, demographic, and sociological methods, has provided new insights into the ultimate forces and proximate pathways that guide human adaptation and variation. Here, we present the argument that evolutionary anthropological studies of human behavior also hold great, largely untapped, potential to guide the design, implementation, and evaluation of social and public health policy. Focusing on the key anthropological themes of reproduction, production, and distribution we highlight classic and recent research demonstrating the value of an evolutionary perspective to improving human well-being. The challenge now comes in transforming relevance into action and, for that, evolutionary behavioral anthropologists will need to forge deeper connections with other applied social scientists and policy-makers. We are hopeful that these developments are underway and that, with the current tide of enthusiasm for evidence-based approaches to policy, evolutionary anthropology is well positioned to make a strong contribution. PMID:25684561

Applying evolutionary anthropology.

PubMed

Gibson, Mhairi A; Lawson, David W

2015-01-01

Evolutionary anthropology provides a powerful theoretical framework for understanding how both current environments and legacies of past selection shape human behavioral diversity. This integrative and pluralistic field, combining ethnographic, demographic, and sociological methods, has provided new insights into the ultimate forces and proximate pathways that guide human adaptation and variation. Here, we present the argument that evolutionary anthropological studies of human behavior also hold great, largely untapped, potential to guide the design, implementation, and evaluation of social and public health policy. Focusing on the key anthropological themes of reproduction, production, and distribution we highlight classic and recent research demonstrating the value of an evolutionary perspective to improving human well-being. The challenge now comes in transforming relevance into action and, for that, evolutionary behavioral anthropologists will need to forge deeper connections with other applied social scientists and policy-makers. We are hopeful that these developments are underway and that, with the current tide of enthusiasm for evidence-based approaches to policy, evolutionary anthropology is well positioned to make a strong contribution. © 2015 Wiley Periodicals, Inc.

Nemo: an evolutionary and population genetics programming framework.

PubMed

Guillaume, Frédéric; Rougemont, Jacques

2006-10-15

Nemo is an individual-based, genetically explicit and stochastic population computer program for the simulation of population genetics and life-history trait evolution in a metapopulation context. It comes as both a C++ programming framework and an executable program file. Its object-oriented programming design gives it the flexibility and extensibility needed to implement a large variety of forward-time evolutionary models. It provides developers with abstract models allowing them to implement their own life-history traits and life-cycle events. Nemo offers a large panel of population models, from the Island model to lattice models with demographic or environmental stochasticity and a variety of already implemented traits (deleterious mutations, neutral markers and more), life-cycle events (mating, dispersal, aging, selection, etc.) and output operators for saving data and statistics. It runs on all major computer platforms including parallel computing environments. The source code, binaries and documentation are available under the GNU General Public License at http://nemo2.sourceforge.net.

Evolutionary Local Search of Fuzzy Rules through a novel Neuro-Fuzzy encoding method.

PubMed

Carrascal, A; Manrique, D; Ríos, J; Rossi, C

2003-01-01

This paper proposes a new approach for constructing fuzzy knowledge bases using evolutionary methods. We have designed a genetic algorithm that automatically builds neuro-fuzzy architectures based on a new indirect encoding method. The neuro-fuzzy architecture represents the fuzzy knowledge base that solves a given problem; the search for this architecture takes advantage of a local search procedure that improves the chromosomes at each generation. Experiments conducted both on artificially generated and real world problems confirm the effectiveness of the proposed approach.

Learning, epigenetics, and computation: An extension on Fitch's proposal. Comment on “Toward a computational framework for cognitive biology: Unifying approaches from cognitive neuroscience and comparative cognition” by W. Tecumseh Fitch

NASA Astrophysics Data System (ADS)

Okanoya, Kazuo

2014-09-01

The comparative computational approach of Fitch [1] attempts to renew the classical David Marr paradigm of computation, algorithm, and implementation, by introducing evolutionary view of the relationship between neural architecture and cognition. This comparative evolutionary view provides constraints useful in narrowing down the problem space for both cognition and neural mechanisms. I will provide two examples from our own studies that reinforce and extend Fitch's proposal.

Evolutionary space platform concept study. Volume 2, part A: SASP special emphasis trade studies

NASA Technical Reports Server (NTRS)

1982-01-01

Efforts are in progress to define an approach to provide a simple and cost effective solution to the problem of long duration space flight. This approach involves a Space Platform in low Earth orbit, which can be tended by the Space Shuttle and which will provide, for extended periods of time, stability, utilities and access for a variety of replaceable payloads. The feasibility of an evolutionary space system which would cost effectively support unmanned payloads in groups, using a Space Platform which provides centralized basic subsystems is addressed.

Reconstructing Networks from Profit Sequences in Evolutionary Games via a Multiobjective Optimization Approach with Lasso Initialization

PubMed Central

Wu, Kai; Liu, Jing; Wang, Shuai

2016-01-01

Evolutionary games (EG) model a common type of interactions in various complex, networked, natural and social systems. Given such a system with only profit sequences being available, reconstructing the interacting structure of EG networks is fundamental to understand and control its collective dynamics. Existing approaches used to handle this problem, such as the lasso, a convex optimization method, need a user-defined constant to control the tradeoff between the natural sparsity of networks and measurement error (the difference between observed data and simulated data). However, a shortcoming of these approaches is that it is not easy to determine these key parameters which can maximize the performance. In contrast to these approaches, we first model the EG network reconstruction problem as a multiobjective optimization problem (MOP), and then develop a framework which involves multiobjective evolutionary algorithm (MOEA), followed by solution selection based on knee regions, termed as MOEANet, to solve this MOP. We also design an effective initialization operator based on the lasso for MOEA. We apply the proposed method to reconstruct various types of synthetic and real-world networks, and the results show that our approach is effective to avoid the above parameter selecting problem and can reconstruct EG networks with high accuracy. PMID:27886244

Reconstructing Networks from Profit Sequences in Evolutionary Games via a Multiobjective Optimization Approach with Lasso Initialization

NASA Astrophysics Data System (ADS)

Wu, Kai; Liu, Jing; Wang, Shuai

2016-11-01

Evolutionary games (EG) model a common type of interactions in various complex, networked, natural and social systems. Given such a system with only profit sequences being available, reconstructing the interacting structure of EG networks is fundamental to understand and control its collective dynamics. Existing approaches used to handle this problem, such as the lasso, a convex optimization method, need a user-defined constant to control the tradeoff between the natural sparsity of networks and measurement error (the difference between observed data and simulated data). However, a shortcoming of these approaches is that it is not easy to determine these key parameters which can maximize the performance. In contrast to these approaches, we first model the EG network reconstruction problem as a multiobjective optimization problem (MOP), and then develop a framework which involves multiobjective evolutionary algorithm (MOEA), followed by solution selection based on knee regions, termed as MOEANet, to solve this MOP. We also design an effective initialization operator based on the lasso for MOEA. We apply the proposed method to reconstruct various types of synthetic and real-world networks, and the results show that our approach is effective to avoid the above parameter selecting problem and can reconstruct EG networks with high accuracy.

Breast tumor malignancy modelling using evolutionary neural logic networks.

PubMed

Tsakonas, Athanasios; Dounias, Georgios; Panagi, Georgia; Panourgias, Evangelia

2006-01-01

The present work proposes a computer assisted methodology for the effective modelling of the diagnostic decision for breast tumor malignancy. The suggested approach is based on innovative hybrid computational intelligence algorithms properly applied in related cytological data contained in past medical records. The experimental data used in this study were gathered in the early 1990s in the University of Wisconsin, based in post diagnostic cytological observations performed by expert medical staff. Data were properly encoded in a computer database and accordingly, various alternative modelling techniques were applied on them, in an attempt to form diagnostic models. Previous methods included standard optimisation techniques, as well as artificial intelligence approaches, in a way that a variety of related publications exists in modern literature on the subject. In this report, a hybrid computational intelligence approach is suggested, which effectively combines modern mathematical logic principles, neural computation and genetic programming in an effective manner. The approach proves promising either in terms of diagnostic accuracy and generalization capabilities, or in terms of comprehensibility and practical importance for the related medical staff.

Cui bono? A review of breaking the spell: religion as a natural phenomenon by Daniel C. Dennett.

PubMed

Rachlin, Howard

2007-01-01

The three requirements for a Darwinian evolutionary process are replication, variation and selection. Dennett (2006) discusses various theories of how these three processes, especially selection, may have operated in the evolution of religion. He believes that the origins of religion, like the origins of language and music, may be approached scientifically. He hopes that such investigations will open a dialog between science and religion leading to moderation of current religious extremism. One problem with Dennett's program, illustrating the difficulty of breaking away from creationist thinking, is Dennett's own failure to consider how Darwinian methods may be used to study evolution of behavioral patterns over the lifetime of individual organisms.

A Comprehensive Review of Swarm Optimization Algorithms

PubMed Central

2015-01-01

Many swarm optimization algorithms have been introduced since the early 60’s, Evolutionary Programming to the most recent, Grey Wolf Optimization. All of these algorithms have demonstrated their potential to solve many optimization problems. This paper provides an in-depth survey of well-known optimization algorithms. Selected algorithms are briefly explained and compared with each other comprehensively through experiments conducted using thirty well-known benchmark functions. Their advantages and disadvantages are also discussed. A number of statistical tests are then carried out to determine the significant performances. The results indicate the overall advantage of Differential Evolution (DE) and is closely followed by Particle Swarm Optimization (PSO), compared with other considered approaches. PMID:25992655

Racial classification in the evolutionary sciences: a comparative analysis.

PubMed

Billinger, Michael S

2007-01-01

Human racial classification has long been a problem for the discipline of anthropology, but much of the criticism of the race concept has focused on its social and political connotations. The central argument of this paper is that race is not a specifically human problem, but one that exists in evolutionary thought in general. This paper looks at various disciplinary approaches to racial or subspecies classification, extending its focus beyond the anthropological race concept by providing a comparative analysis of the use of racial classification in evolutionary biology, genetics, and anthropology.

Goal-based dictator game

NASA Astrophysics Data System (ADS)

Zaibidi, Nerda Zura; Ibrahim, Adyda; Abidin, Norhaslinda Zainal

2014-12-01

A considerable number of studies have been conducted to study fairness issues using two-player game. Dictator Game is one of the two-player games that receive much attention. In this paper, we develop an evolutionary approach to the Dictator Game by using Goal programming to build a model of human decision-making for cooperation. The model is formulated based on the theories of cognitive neuroscience that is capable in capturing a more realistic fairness concerns between players in the games. We show that fairness will evolve by taking into account players' aspirations and preferences explicitly in terms of profit and fairness concerns. The model is then simulated to investigate any possible effective strategy for people in economics to deal with fairness coalition. Parallels are drawn between the approach and concepts of human decision making from the field of cognitive neuroscience and psychology. The proposed model is also able to help decision makers to plan or enhance the effective strategies for business purposes.

Evolutionary pattern search algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hart, W.E.

1995-09-19

This paper defines a class of evolutionary algorithms called evolutionary pattern search algorithms (EPSAs) and analyzes their convergence properties. This class of algorithms is closely related to evolutionary programming, evolutionary strategie and real-coded genetic algorithms. EPSAs are self-adapting systems that modify the step size of the mutation operator in response to the success of previous optimization steps. The rule used to adapt the step size can be used to provide a stationary point convergence theory for EPSAs on any continuous function. This convergence theory is based on an extension of the convergence theory for generalized pattern search methods. An experimentalmore » analysis of the performance of EPSAs demonstrates that these algorithms can perform a level of global search that is comparable to that of canonical EAs. We also describe a stopping rule for EPSAs, which reliably terminated near stationary points in our experiments. This is the first stopping rule for any class of EAs that can terminate at a given distance from stationary points.« less

Ecological theatre and the evolutionary game: how environmental and demographic factors determine payoffs in evolutionary games.

PubMed

Argasinski, K; Broom, M

2013-10-01

In the standard approach to evolutionary games and replicator dynamics, differences in fitness can be interpreted as an excess from the mean Malthusian growth rate in the population. In the underlying reasoning, related to an analysis of "costs" and "benefits", there is a silent assumption that fitness can be described in some type of units. However, in most cases these units of measure are not explicitly specified. Then the question arises: are these theories testable? How can we measure "benefit" or "cost"? A natural language, useful for describing and justifying comparisons of strategic "cost" versus "benefits", is the terminology of demography, because the basic events that shape the outcome of natural selection are births and deaths. In this paper, we present the consequences of an explicit analysis of births and deaths in an evolutionary game theoretic framework. We will investigate different types of mortality pressures, their combinations and the possibility of trade-offs between mortality and fertility. We will show that within this new approach it is possible to model how strictly ecological factors such as density dependence and additive background fitness, which seem neutral in classical theory, can affect the outcomes of the game. We consider the example of the Hawk-Dove game, and show that when reformulated in terms of our new approach new details and new biological predictions are produced.

Evolutionary genetics of plant adaptation.

PubMed

Anderson, Jill T; Willis, John H; Mitchell-Olds, Thomas

2011-07-01

Plants provide unique opportunities to study the mechanistic basis and evolutionary processes of adaptation to diverse environmental conditions. Complementary laboratory and field experiments are important for testing hypotheses reflecting long-term ecological and evolutionary history. For example, these approaches can infer whether local adaptation results from genetic tradeoffs (antagonistic pleiotropy), where native alleles are best adapted to local conditions, or if local adaptation is caused by conditional neutrality at many loci, where alleles show fitness differences in one environment, but not in a contrasting environment. Ecological genetics in natural populations of perennial or outcrossing plants can also differ substantially from model systems. In this review of the evolutionary genetics of plant adaptation, we emphasize the importance of field studies for understanding the evolutionary dynamics of model and nonmodel systems, highlight a key life history trait (flowering time) and discuss emerging conservation issues. Copyright © 2011 Elsevier Ltd. All rights reserved.

Inspection planning development: An evolutionary approach using reliability engineering as a tool

NASA Technical Reports Server (NTRS)

Graf, David A.; Huang, Zhaofeng

1994-01-01

This paper proposes an evolutionary approach for inspection planning which introduces various reliability engineering tools into the process and assess system trade-offs among reliability, engineering requirement, manufacturing capability and inspection cost to establish an optimal inspection plan. The examples presented in the paper illustrate some advantages and benefits of the new approach. Through the analysis, reliability and engineering impacts due to manufacturing process capability and inspection uncertainty are clearly understood; the most cost effective and efficient inspection plan can be established and associated risks are well controlled; some inspection reductions and relaxations are well justified; and design feedbacks and changes may be initiated from the analysis conclusion to further enhance reliability and reduce cost. The approach is particularly promising as global competitions and customer quality improvement expectations are rapidly increasing.

Conservation and canalization of gene expression during angiosperm diversification accompany the origin and evolution of the flower

PubMed Central

Chanderbali, André S.; Yoo, Mi-Jeong; Zahn, Laura M.; Brockington, Samuel F.; Wall, P. Kerr; Gitzendanner, Matthew A.; Albert, Victor A.; Leebens-Mack, James; Altman, Naomi S.; Ma, Hong; dePamphilis, Claude W.; Soltis, Douglas E.; Soltis, Pamela S.

2010-01-01

The origin and rapid diversification of the angiosperms (Darwin's “Abominable Mystery”) has engaged generations of researchers. Here, we examine the floral genetic programs of phylogenetically pivotal angiosperms (water lily, avocado, California poppy, and Arabidopsis) and a nonflowering seed plant (a cycad) to obtain insight into the origin and subsequent evolution of the flower. Transcriptional cascades with broadly overlapping spatial domains, resembling the hypothesized ancestral gymnosperm program, are deployed across morphologically intergrading organs in water lily and avocado flowers. In contrast, spatially discrete transcriptional programs in distinct floral organs characterize the more recently derived angiosperm lineages represented by California poppy and Arabidopsis. Deep evolutionary conservation in the genetic programs of putatively homologous floral organs traces to those operating in gymnosperm reproductive cones. Female gymnosperm cones and angiosperm carpels share conserved genetic features, which may be associated with the ovule developmental program common to both organs. However, male gymnosperm cones share genetic features with both perianth (sterile attractive and protective) organs and stamens, supporting the evolutionary origin of the floral perianth from the male genetic program of seed plants. PMID:21149731

Conservation and canalization of gene expression during angiosperm diversification accompany the origin and evolution of the flower.

PubMed

Chanderbali, André S; Yoo, Mi-Jeong; Zahn, Laura M; Brockington, Samuel F; Wall, P Kerr; Gitzendanner, Matthew A; Albert, Victor A; Leebens-Mack, James; Altman, Naomi S; Ma, Hong; dePamphilis, Claude W; Soltis, Douglas E; Soltis, Pamela S

2010-12-28

The origin and rapid diversification of the angiosperms (Darwin's "Abominable Mystery") has engaged generations of researchers. Here, we examine the floral genetic programs of phylogenetically pivotal angiosperms (water lily, avocado, California poppy, and Arabidopsis) and a nonflowering seed plant (a cycad) to obtain insight into the origin and subsequent evolution of the flower. Transcriptional cascades with broadly overlapping spatial domains, resembling the hypothesized ancestral gymnosperm program, are deployed across morphologically intergrading organs in water lily and avocado flowers. In contrast, spatially discrete transcriptional programs in distinct floral organs characterize the more recently derived angiosperm lineages represented by California poppy and Arabidopsis. Deep evolutionary conservation in the genetic programs of putatively homologous floral organs traces to those operating in gymnosperm reproductive cones. Female gymnosperm cones and angiosperm carpels share conserved genetic features, which may be associated with the ovule developmental program common to both organs. However, male gymnosperm cones share genetic features with both perianth (sterile attractive and protective) organs and stamens, supporting the evolutionary origin of the floral perianth from the male genetic program of seed plants.

Biology Teachers' Conceptions of the Diversity of Life and the Historical Development of Evolutionary Concepts

ERIC Educational Resources Information Center

da Silva, Paloma Rodrigues; de Andrade, Mariana A. Bologna Soares; de Andrade Caldeira, Ana Maria

2015-01-01

Biology is a science that involves study of the diversity of living organisms. This diversity has always generated questions and has motivated cultures to seek plausible explanations for the differences and similarities between types of organisms. In biology teaching, these issues are addressed by adopting an evolutionary approach. The aim of this…

Scheduling Earth Observing Fleets Using Evolutionary Algorithms: Problem Description and Approach

NASA Technical Reports Server (NTRS)

Globus, Al; Crawford, James; Lohn, Jason; Morris, Robert; Clancy, Daniel (Technical Monitor)

2002-01-01

We describe work in progress concerning multi-instrument, multi-satellite scheduling. Most, although not all, Earth observing instruments currently in orbit are unique. In the relatively near future, however, we expect to see fleets of Earth observing spacecraft, many carrying nearly identical instruments. This presents a substantially new scheduling challenge. Inspired by successful commercial applications of evolutionary algorithms in scheduling domains, this paper presents work in progress regarding the use of evolutionary algorithms to solve a set of Earth observing related model problems. Both the model problems and the software are described. Since the larger problems will require substantial computation and evolutionary algorithms are embarrassingly parallel, we discuss our parallelization techniques using dedicated and cycle-scavenged workstations.

A Penalized Likelihood Framework For High-Dimensional Phylogenetic Comparative Methods And An Application To New-World Monkeys Brain Evolution.

PubMed

Julien, Clavel; Leandro, Aristide; Hélène, Morlon

2018-06-19

Working with high-dimensional phylogenetic comparative datasets is challenging because likelihood-based multivariate methods suffer from low statistical performances as the number of traits p approaches the number of species n and because some computational complications occur when p exceeds n. Alternative phylogenetic comparative methods have recently been proposed to deal with the large p small n scenario but their use and performances are limited. Here we develop a penalized likelihood framework to deal with high-dimensional comparative datasets. We propose various penalizations and methods for selecting the intensity of the penalties. We apply this general framework to the estimation of parameters (the evolutionary trait covariance matrix and parameters of the evolutionary model) and model comparison for the high-dimensional multivariate Brownian (BM), Early-burst (EB), Ornstein-Uhlenbeck (OU) and Pagel's lambda models. We show using simulations that our penalized likelihood approach dramatically improves the estimation of evolutionary trait covariance matrices and model parameters when p approaches n, and allows for their accurate estimation when p equals or exceeds n. In addition, we show that penalized likelihood models can be efficiently compared using Generalized Information Criterion (GIC). We implement these methods, as well as the related estimation of ancestral states and the computation of phylogenetic PCA in the R package RPANDA and mvMORPH. Finally, we illustrate the utility of the new proposed framework by evaluating evolutionary models fit, analyzing integration patterns, and reconstructing evolutionary trajectories for a high-dimensional 3-D dataset of brain shape in the New World monkeys. We find a clear support for an Early-burst model suggesting an early diversification of brain morphology during the ecological radiation of the clade. Penalized likelihood offers an efficient way to deal with high-dimensional multivariate comparative data.

Inference of Evolutionary Jumps in Large Phylogenies using Lévy Processes

PubMed Central

Duchen, Pablo; Leuenberger, Christoph; Szilágyi, Sándor M.; Harmon, Luke; Eastman, Jonathan; Schweizer, Manuel

2017-01-01

Abstract Although it is now widely accepted that the rate of phenotypic evolution may not necessarily be constant across large phylogenies, the frequency and phylogenetic position of periods of rapid evolution remain unclear. In his highly influential view of evolution, G. G. Simpson supposed that such evolutionary jumps occur when organisms transition into so-called new adaptive zones, for instance after dispersal into a new geographic area, after rapid climatic changes, or following the appearance of an evolutionary novelty. Only recently, large, accurate and well calibrated phylogenies have become available that allow testing this hypothesis directly, yet inferring evolutionary jumps remains computationally very challenging. Here, we develop a computationally highly efficient algorithm to accurately infer the rate and strength of evolutionary jumps as well as their phylogenetic location. Following previous work we model evolutionary jumps as a compound process, but introduce a novel approach to sample jump configurations that does not require matrix inversions and thus naturally scales to large trees. We then make use of this development to infer evolutionary jumps in Anolis lizards and Loriinii parrots where we find strong signal for such jumps at the basis of clades that transitioned into new adaptive zones, just as postulated by Simpson’s hypothesis. [evolutionary jump; Lévy process; phenotypic evolution; punctuated equilibrium; quantitative traits. PMID:28204787

Ecological and evolutionary genomics of marine photosynthetic organisms.

PubMed

Coelho, Susana M; Simon, Nathalie; Ahmed, Sophia; Cock, J Mark; Partensky, Frédéric

2013-02-01

Environmental (ecological) genomics aims to understand the genetic basis of relationships between organisms and their abiotic and biotic environments. It is a rapidly progressing field of research largely due to recent advances in the speed and volume of genomic data being produced by next generation sequencing (NGS) technologies. Building on information generated by NGS-based approaches, functional genomic methodologies are being applied to identify and characterize genes and gene systems of both environmental and evolutionary relevance. Marine photosynthetic organisms (MPOs) were poorly represented amongst the early genomic models, but this situation is changing rapidly. Here we provide an overview of the recent advances in the application of ecological genomic approaches to both prokaryotic and eukaryotic MPOs. We describe how these approaches are being used to explore the biology and ecology of marine cyanobacteria and algae, particularly with regard to their functions in a broad range of marine ecosystems. Specifically, we review the ecological and evolutionary insights gained from whole genome and transcriptome sequencing projects applied to MPOs and illustrate how their genomes are yielding information on the specific features of these organisms. © 2012 Blackwell Publishing Ltd.

Mechanisms of bacterial morphogenesis: evolutionary cell biology approaches provide new insights.

PubMed

Jiang, Chao; Caccamo, Paul D; Brun, Yves V

2015-04-01

How Darwin's "endless forms most beautiful" have evolved remains one of the most exciting questions in biology. The significant variety of bacterial shapes is most likely due to the specific advantages they confer with respect to the diverse environments they occupy. While our understanding of the mechanisms generating relatively simple shapes has improved tremendously in the last few years, the molecular mechanisms underlying the generation of complex shapes and the evolution of shape diversity are largely unknown. The emerging field of bacterial evolutionary cell biology provides a novel strategy to answer this question in a comparative phylogenetic framework. This relatively novel approach provides hypotheses and insights into cell biological mechanisms, such as morphogenesis, and their evolution that would have been difficult to obtain by studying only model organisms. We discuss the necessary steps, challenges, and impact of integrating "evolutionary thinking" into bacterial cell biology in the genomic era. © 2015 WILEY Periodicals, Inc.

Impressions of Danger Influence Impressions of People: An Evolutionary Perspective on Individual and Collective Cognition

PubMed Central

Schaller, Mark; Faulkner, Jason; Park, Justin H.; Neuberg, Steven L.; Kenrick, Douglas T.

2011-01-01

An evolutionary approach to social cognition yields novel hypotheses about the perception of people belonging to specific kinds of social categories. These implications are illustrated by empirical results linking the perceived threat of physical injury to stereotypical impressions of outgroups. We review a set of studies revealing several ways in which threat-connoting cues influence perceptions of ethnic outgroups and the individuals who belong to those outgroups. We also present new results that suggest additional implications of evolved danger-avoidance mechanisms on interpersonal communication and the persistence of cultural-level stereotypes about ethnic outgroups. The conceptual utility of an evolutionary approach is further illustrated by a parallel line of research linking the threat of disease to additional kinds of social perceptions and behaviors. Evolved danger-avoidance mechanisms appear to contribute in diverse ways to individual-level cognitive processes, as well as to culturally-shared collective beliefs. PMID:21874126

The Price Equation, Gradient Dynamics, and Continuous Trait Game Theory.

PubMed

Lehtonen, Jussi

2018-01-01

A recent article convincingly nominated the Price equation as the fundamental theorem of evolution and used it as a foundation to derive several other theorems. A major section of evolutionary theory that was not addressed is that of game theory and gradient dynamics of continuous traits with frequency-dependent fitness. Deriving fundamental results in these fields under the unifying framework of the Price equation illuminates similarities and differences between approaches and allows a simple, unified view of game-theoretical and dynamic concepts. Using Taylor polynomials and the Price equation, I derive a dynamic measure of evolutionary change, a condition for singular points, the convergence stability criterion, and an alternative interpretation of evolutionary stability. Furthermore, by applying the Price equation to a multivariable Taylor polynomial, the direct fitness approach to kin selection emerges. Finally, I compare these results to the mean gradient equation of quantitative genetics and the canonical equation of adaptive dynamics.

A survey on evolutionary algorithm based hybrid intelligence in bioinformatics.

PubMed

Li, Shan; Kang, Liying; Zhao, Xing-Ming

2014-01-01

With the rapid advance in genomics, proteomics, metabolomics, and other types of omics technologies during the past decades, a tremendous amount of data related to molecular biology has been produced. It is becoming a big challenge for the bioinformatists to analyze and interpret these data with conventional intelligent techniques, for example, support vector machines. Recently, the hybrid intelligent methods, which integrate several standard intelligent approaches, are becoming more and more popular due to their robustness and efficiency. Specifically, the hybrid intelligent approaches based on evolutionary algorithms (EAs) are widely used in various fields due to the efficiency and robustness of EAs. In this review, we give an introduction about the applications of hybrid intelligent methods, in particular those based on evolutionary algorithm, in bioinformatics. In particular, we focus on their applications to three common problems that arise in bioinformatics, that is, feature selection, parameter estimation, and reconstruction of biological networks.

Development of Collaborative Research Initiatives to Advance the Aerospace Sciences-via the Communications, Electronics, Information Systems Focus Group

NASA Technical Reports Server (NTRS)

Knasel, T. Michael

1996-01-01

The primary goal of the Adaptive Vision Laboratory Research project was to develop advanced computer vision systems for automatic target recognition. The approach used in this effort combined several machine learning paradigms including evolutionary learning algorithms, neural networks, and adaptive clustering techniques to develop the E-MOR.PH system. This system is capable of generating pattern recognition systems to solve a wide variety of complex recognition tasks. A series of simulation experiments were conducted using E-MORPH to solve problems in OCR, military target recognition, industrial inspection, and medical image analysis. The bulk of the funds provided through this grant were used to purchase computer hardware and software to support these computationally intensive simulations. The payoff from this effort is the reduced need for human involvement in the design and implementation of recognition systems. We have shown that the techniques used in E-MORPH are generic and readily transition to other problem domains. Specifically, E-MORPH is multi-phase evolutionary leaming system that evolves cooperative sets of features detectors and combines their response using an adaptive classifier to form a complete pattern recognition system. The system can operate on binary or grayscale images. In our most recent experiments, we used multi-resolution images that are formed by applying a Gabor wavelet transform to a set of grayscale input images. To begin the leaming process, candidate chips are extracted from the multi-resolution images to form a training set and a test set. A population of detector sets is randomly initialized to start the evolutionary process. Using a combination of evolutionary programming and genetic algorithms, the feature detectors are enhanced to solve a recognition problem. The design of E-MORPH and recognition results for a complex problem in medical image analysis are described at the end of this report. The specific task involves the identification of vertebrae in x-ray images of human spinal columns. This problem is extremely challenging because the individual vertebra exhibit variation in shape, scale, orientation, and contrast. E-MORPH generated several accurate recognition systems to solve this task. This dual use of this ATR technology clearly demonstrates the flexibility and power of our approach.

Self-management support in chronic illness care: a concept analysis.

PubMed

Kawi, Jennifer

2012-01-01

This article reports on the concept analysis of self-management support (SMS) to provide clarity for systematic implementation in practice. SMS is a concept in its early phase of development. It is increasingly evident in literature on chronic illness care. However, the definition has been simplified or vague leading to variable SMS programs and inconsistent outcomes. Elucidation of SMS is necessary in chronic illness care to facilitate clear understanding and implementation. Rodgers' evolutionary concept analysis method was used to examine SMS. Data sources included systematic multidisciplinary searches of multiple search engines. SMS refers to comprehensive sustaining approaches toward improving chronic illness outcomes consisting of patient-centered attributes (involving patients as partners; providing diverse, innovative educational modalities specific to patients' needs; individualizing patient care), provider attributes (possessing adequate knowledge, skills, attitudes in providing care), and organizational attributes (putting an organized system of care in place, having multidisciplinary team approach, using tangible and social support). A well-clarified SMS concept is important in theory development. The attributes offer necessary components in SMS programs for systematic implementation, evaluation, and research. There is great potential that SMS can help improve outcomes of chronic illness care.

The Environmental Control and Life Support System (ECLSS) advanced automation project

NASA Technical Reports Server (NTRS)

Dewberry, Brandon S.; Carnes, Ray

1990-01-01

The objective of the environmental control and life support system (ECLSS) Advanced Automation Project is to influence the design of the initial and evolutionary Space Station Freedom Program (SSFP) ECLSS toward a man-made closed environment in which minimal flight and ground manpower is needed. Another objective includes capturing ECLSS design and development knowledge future missions. Our approach has been to (1) analyze the SSFP ECLSS, (2) envision as our goal a fully automated evolutionary environmental control system - an augmentation of the baseline, and (3) document the advanced software systems, hooks, and scars which will be necessary to achieve this goal. From this analysis, prototype software is being developed, and will be tested using air and water recovery simulations and hardware subsystems. In addition, the advanced software is being designed, developed, and tested using automation software management plan and lifecycle tools. Automated knowledge acquisition, engineering, verification and testing tools are being used to develop the software. In this way, we can capture ECLSS development knowledge for future use develop more robust and complex software, provide feedback to the knowledge based system tool community, and ensure proper visibility of our efforts.

Genomic sequencing of Pleistocene cave bears

DOE Office of Scientific and Technical Information (OSTI.GOV)

Noonan, James P.; Hofreiter, Michael; Smith, Doug

2005-04-01

Despite the information content of genomic DNA, ancient DNA studies to date have largely been limited to amplification of mitochondrial DNA due to technical hurdles such as contamination and degradation of ancient DNAs. In this study, we describe two metagenomic libraries constructed using unamplified DNA extracted from the bones of two 40,000-year-old extinct cave bears. Analysis of {approx}1 Mb of sequence from each library showed that, despite significant microbial contamination, 5.8 percent and 1.1 percent of clones in the libraries contain cave bear inserts, yielding 26,861 bp of cave bear genome sequence. Alignment of this sequence to the dog genome,more » the closest sequenced genome to cave bear in terms of evolutionary distance, revealed roughly the expected ratio of cave bear exons, repeats and conserved noncoding sequences. Only 0.04 percent of all clones sequenced were derived from contamination with modern human DNA. Comparison of cave bear with orthologous sequences from several modern bear species revealed the evolutionary relationship of these lineages. Using the metagenomic approach described here, we have recovered substantial quantities of mammalian genomic sequence more than twice as old as any previously reported, establishing the feasibility of ancient DNA genomic sequencing programs.« less

Hidden relationships between metalloproteins unveiled by structural comparison of their metal sites

NASA Astrophysics Data System (ADS)

Valasatava, Yana; Andreini, Claudia; Rosato, Antonio

2015-03-01

Metalloproteins account for a substantial fraction of all proteins. They incorporate metal atoms, which are required for their structure and/or function. Here we describe a new computational protocol to systematically compare and classify metal-binding sites on the basis of their structural similarity. These sites are extracted from the MetalPDB database of minimal functional sites (MFSs) in metal-binding biological macromolecules. Structural similarity is measured by the scoring function of the available MetalS2 program. Hierarchical clustering was used to organize MFSs into clusters, for each of which a representative MFS was identified. The comparison of all representative MFSs provided a thorough structure-based classification of the sites analyzed. As examples, the application of the proposed computational protocol to all heme-binding proteins and zinc-binding proteins of known structure highlighted the existence of structural subtypes, validated known evolutionary links and shed new light on the occurrence of similar sites in systems at different evolutionary distances. The present approach thus makes available an innovative viewpoint on metalloproteins, where the functionally crucial metal sites effectively lead the discovery of structural and functional relationships in a largely protein-independent manner.

The niche reduction approach: an opportunity for optimal control of infectious diseases in low-income countries?

PubMed

Roche, Benjamin; Broutin, Hélène; Choisy, Marc; Godreuil, Sylvain; de Magny, Guillaume Constantin; Chevaleyre, Yann; Zucker, Jean-Daniel; Breban, Romulus; Cazelles, Bernard; Simard, Frédéric

2014-07-25

During the last century, WHO led public health interventions that resulted in spectacular achievements such as the worldwide eradication of smallpox and the elimination of malaria from the Western world. However, besides major successes achieved worldwide in infectious diseases control, most elimination/control programs remain frustrating in many tropical countries where specific biological and socio-economical features prevented implementation of disease control over broad spatial and temporal scales. Emblematic examples include malaria, yellow fever, measles and HIV. There is consequently an urgent need to develop affordable and sustainable disease control strategies that can target the core of infectious diseases transmission in highly endemic areas. Meanwhile, although most pathogens appear so difficult to eradicate, it is surprising to realize that human activities are major drivers of the current high rate of extinction among upper organisms through alteration of their ecology and evolution, i.e., their "niche". During the last decades, the accumulation of ecological and evolutionary studies focused on infectious diseases has shown that the niche of a pathogen holds more dimensions than just the immune system targeted by vaccination and treatment. Indeed, it is situated at various intra- and inter- host levels involved on very different spatial and temporal scales. After developing a precise definition of the niche of a pathogen, we detail how major advances in the field of ecology and evolutionary biology of infectious diseases can enlighten the planning and implementation of infectious diseases control in tropical countries with challenging economic constraints. We develop how the approach could translate into applied cases, explore its expected benefits and constraints, and we conclude on the necessity of such approach for pathogen control in low-income countries.

Women, behavior, and evolution: understanding the debate between feminist evolutionists and evolutionary psychologists.

PubMed

Liesen, Laurette T

2007-03-01

Often since the early 1990s, feminist evolutionists have criticized evolutionary psychologists, finding fault in their analyses of human male and female reproductive behavior. Feminist evolutionists have criticized various evolutionary psychologists for perpetuating gender stereotypes, using questionable methodology, and exhibiting a chill toward feminism. Though these criticisms have been raised many times, the conflict itself has not been fully analyzed. Therefore, I reconsider this conflict, both in its origins and its implications. I find that the approaches and perspectives of feminist evolutionists and evolutionary psychologists are distinctly different, leading many of the former to work in behavioral ecology, primatology, and evolutionary biology. Invitingly to feminist evolutionists, these three fields emphasize social behavior and the influences of environmental variables; in contrast, evolutionary psychology has come to rely on assumptions deemphasizing the pliability of psychological mechanisms and the flexibility of human behavior. In behavioral ecology, primatology, and evolutionary biology, feminist evolutionists have found old biases easy to correct and new hypotheses practical to test, offering new insights into male and female behavior, explaining the emergence and persistence of patriarchy, and potentially bringing closer a prime feminist goal, sexual equality.

A combined NLP-differential evolution algorithm approach for the optimization of looped water distribution systems

NASA Astrophysics Data System (ADS)

Zheng, Feifei; Simpson, Angus R.; Zecchin, Aaron C.

2011-08-01

This paper proposes a novel optimization approach for the least cost design of looped water distribution systems (WDSs). Three distinct steps are involved in the proposed optimization approach. In the first step, the shortest-distance tree within the looped network is identified using the Dijkstra graph theory algorithm, for which an extension is proposed to find the shortest-distance tree for multisource WDSs. In the second step, a nonlinear programming (NLP) solver is employed to optimize the pipe diameters for the shortest-distance tree (chords of the shortest-distance tree are allocated the minimum allowable pipe sizes). Finally, in the third step, the original looped water network is optimized using a differential evolution (DE) algorithm seeded with diameters in the proximity of the continuous pipe sizes obtained in step two. As such, the proposed optimization approach combines the traditional deterministic optimization technique of NLP with the emerging evolutionary algorithm DE via the proposed network decomposition. The proposed methodology has been tested on four looped WDSs with the number of decision variables ranging from 21 to 454. Results obtained show the proposed approach is able to find optimal solutions with significantly less computational effort than other optimization techniques.

Evolutionary computing for the design search and optimization of space vehicle power subsystems

NASA Technical Reports Server (NTRS)

Kordon, Mark; Klimeck, Gerhard; Hanks, David; Hua, Hook

2004-01-01

Evolutionary computing has proven to be a straightforward and robust approach for optimizing a wide range of difficult analysis and design problems. This paper discusses the application of these techniques to an existing space vehicle power subsystem resource and performance analysis simulation in a parallel processing environment. Out preliminary results demonstrate that this approach has the potential to improve the space system trade study process by allowing engineers to statistically weight subsystem goals of mass, cost and performance then automatically size power elements based on anticipated performance of the subsystem rather than on worst-case estimates.

On the design of neuro-controllers for individual and social learning behaviour in autonomous robots: an evolutionary approach

NASA Astrophysics Data System (ADS)

Pini, Giovanni; Tuci, Elio

2008-06-01

In biology/psychology, the capability of natural organisms to learn from the observation/interaction with conspecifics is referred to as social learning. Roboticists have recently developed an interest in social learning, since it might represent an effective strategy to enhance the adaptivity of a team of autonomous robots. In this study, we show that a methodological approach based on artifcial neural networks shaped by evolutionary computation techniques can be successfully employed to synthesise the individual and social learning mechanisms for robots required to learn a desired action (i.e. phototaxis or antiphototaxis).

Evolutionary history of the little fire ant Wasmannia auropunctata before global invasion: inferring dispersal patterns, niche requirements, and past and present distribution within its native range

USDA-ARS?s Scientific Manuscript database

The evolutionary history of invasive species within their native range may involve key processes that allow them to colonize new habitats. We integrated classic and Bayesian phylogeographic methods with a paleodistribution modeling approach to study the demographic patterns that shaped the distribut...

Evolution of Enzyme Superfamilies: Comprehensive Exploration of Sequence-Function Relationships.

PubMed

Baier, F; Copp, J N; Tokuriki, N

2016-11-22

The sequence and functional diversity of enzyme superfamilies have expanded through billions of years of evolution from a common ancestor. Understanding how protein sequence and functional "space" have expanded, at both the evolutionary and molecular level, is central to biochemistry, molecular biology, and evolutionary biology. Integrative approaches that examine protein sequence, structure, and function have begun to provide comprehensive views of the functional diversity and evolutionary relationships within enzyme superfamilies. In this review, we outline the recent advances in our understanding of enzyme evolution and superfamily functional diversity. We describe the tools that have been used to comprehensively analyze sequence relationships and to characterize sequence and function relationships. We also highlight recent large-scale experimental approaches that systematically determine the activity profiles across enzyme superfamilies. We identify several intriguing insights from this recent body of work. First, promiscuous activities are prevalent among extant enzymes. Second, many divergent proteins retain "function connectivity" via enzyme promiscuity, which can be used to probe the evolutionary potential and history of enzyme superfamilies. Finally, we discuss open questions regarding the intricacies of enzyme divergence, as well as potential research directions that will deepen our understanding of enzyme superfamily evolution.

Mode and tempo in the evolution of socio-political organization: reconciling 'Darwinian' and 'Spencerian' evolutionary approaches in anthropology.

PubMed

Currie, Thomas E; Mace, Ruth

2011-04-12

Traditional investigations of the evolution of human social and political institutions trace their ancestry back to nineteenth century social scientists such as Herbert Spencer, and have concentrated on the increase in socio-political complexity over time. More recent studies of cultural evolution have been explicitly informed by Darwinian evolutionary theory and focus on the transmission of cultural traits between individuals. These two approaches to investigating cultural change are often seen as incompatible. However, we argue that many of the defining features and assumptions of 'Spencerian' cultural evolutionary theory represent testable hypotheses that can and should be tackled within a broader 'Darwinian' framework. In this paper we apply phylogenetic comparative techniques to data from Austronesian-speaking societies of Island South-East Asia and the Pacific to test hypotheses about the mode and tempo of human socio-political evolution. We find support for three ideas often associated with Spencerian cultural evolutionary theory: (i) political organization has evolved through a regular sequence of forms, (ii) increases in hierarchical political complexity have been more common than decreases, and (iii) political organization has co-evolved with the wider presence of hereditary social stratification.

Evolutionary dynamics of imatinib-treated leukemic cells by stochastic approach

NASA Astrophysics Data System (ADS)

Pizzolato, Nicola; Valenti, Davide; Adorno, Dominique Persano; Spagnolo, Bernardo

2009-09-01

The evolutionary dynamics of a system of cancerous cells in a model of chronic myeloid leukemia (CML) is investigated by a statistical approach. Cancer progression is explored by applying a Monte Carlo method to simulate the stochastic behavior of cell reproduction and death in a population of blood cells which can experience genetic mutations. In CML front line therapy is represented by the tyrosine kinase inhibitor imatinib which strongly affects the reproduction of leukemic cells only. In this work, we analyze the effects of a targeted therapy on the evolutionary dynamics of normal, first-mutant and cancerous cell populations. Several scenarios of the evolutionary dynamics of imatinib-treated leukemic cells are described as a consequence of the efficacy of the different modelled therapies. We show how the patient response to the therapy changes when a high value of the mutation rate from healthy to cancerous cells is present. Our results are in agreement with clinical observations. Unfortunately, development of resistance to imatinib is observed in a fraction of patients, whose blood cells are characterized by an increasing number of genetic alterations. We find that the occurrence of resistance to the therapy can be related to a progressive increase of deleterious mutations.

Mode and tempo in the evolution of socio-political organization: reconciling ‘Darwinian’ and ‘Spencerian’ evolutionary approaches in anthropology

PubMed Central

Currie, Thomas E.; Mace, Ruth

2011-01-01

Traditional investigations of the evolution of human social and political institutions trace their ancestry back to nineteenth century social scientists such as Herbert Spencer, and have concentrated on the increase in socio-political complexity over time. More recent studies of cultural evolution have been explicitly informed by Darwinian evolutionary theory and focus on the transmission of cultural traits between individuals. These two approaches to investigating cultural change are often seen as incompatible. However, we argue that many of the defining features and assumptions of ‘Spencerian’ cultural evolutionary theory represent testable hypotheses that can and should be tackled within a broader ‘Darwinian’ framework. In this paper we apply phylogenetic comparative techniques to data from Austronesian-speaking societies of Island South-East Asia and the Pacific to test hypotheses about the mode and tempo of human socio-political evolution. We find support for three ideas often associated with Spencerian cultural evolutionary theory: (i) political organization has evolved through a regular sequence of forms, (ii) increases in hierarchical political complexity have been more common than decreases, and (iii) political organization has co-evolved with the wider presence of hereditary social stratification. PMID:21357233

[Narcissism in the world of Facebook. An evolutionary psychopathological interpretation].

PubMed

Szekeres, Adám; Tisljár, Roland

2013-01-01

In the last few decades there has been a considerable increase in the levels of narcissism among the population of individualistic, western cultures. The phenomena of narcissism induced a large number of psychological researches, some of which approaches the issue from changes in environmental factors. The modern environment of these days is substantially different from the one to which our ancestors have adapted over millions of years of evolution. The research results of narcissism from the perspective of evolutionary psychopathology approach have yet to integrate.The present review focuses on two studies and empirical findings induced by them in which an attempt is made to explore the evolutionary origins of narcissism. Relating to these studies we present the main mechanisms by which evolution may have played a role in the development and maintenance of narcissism. One of the significant elements of the current, changing social environment allowing virtual contacts is the social networking site called Facebook. Following the presentation of the main features of the site we discuss research results in connection with narcissistic traits and Facebook usage. Finally an attempt is made to integrate these findings into an evolutionary psychopathological framework.

Sum-of-squares-based fuzzy controller design using quantum-inspired evolutionary algorithm

NASA Astrophysics Data System (ADS)

Yu, Gwo-Ruey; Huang, Yu-Chia; Cheng, Chih-Yung

2016-07-01

In the field of fuzzy control, control gains are obtained by solving stabilisation conditions in linear-matrix-inequality-based Takagi-Sugeno fuzzy control method and sum-of-squares-based polynomial fuzzy control method. However, the optimal performance requirements are not considered under those stabilisation conditions. In order to handle specific performance problems, this paper proposes a novel design procedure with regard to polynomial fuzzy controllers using quantum-inspired evolutionary algorithms. The first contribution of this paper is a combination of polynomial fuzzy control and quantum-inspired evolutionary algorithms to undertake an optimal performance controller design. The second contribution is the proposed stability condition derived from the polynomial Lyapunov function. The proposed design approach is dissimilar to the traditional approach, in which control gains are obtained by solving the stabilisation conditions. The first step of the controller design uses the quantum-inspired evolutionary algorithms to determine the control gains with the best performance. Then, the stability of the closed-loop system is analysed under the proposed stability conditions. To illustrate effectiveness and validity, the problem of balancing and the up-swing of an inverted pendulum on a cart is used.

Embedding Agile Practices within a Plan-Driven Hierarchical Project Life Cycle

DOE Office of Scientific and Technical Information (OSTI.GOV)

Millard, W. David; Johnson, Daniel M.; Henderson, John M.

2014-07-28

Organizations use structured, plan-driven approaches to provide continuity, direction, and control to large, multi-year programs. Projects within these programs vary greatly in size, complexity, level of maturity, technical risk, and clarity of the development objectives. Organizations that perform exploratory research, evolutionary development, and other R&D activities can obtain the benefits of Agile practices without losing the benefits of their program’s overarching plan-driven structure. This paper describes application of Agile development methods on a large plan-driven sensor integration program. While the client employed plan-driven, requirements flow-down methodologies, tight project schedules and complex interfaces called for frequent end-to-end demonstrations to provide feedbackmore » during system development. The development process maintained the many benefits of plan-driven project execution with the rapid prototyping, integration, demonstration, and client feedback possible through Agile development methods. This paper also describes some of the tools and implementing mechanisms used to transition between and take advantage of each methodology, and presents lessons learned from the project management, system engineering, and developer’s perspectives.« less

Evolutionary accounts of human behavioural diversity

PubMed Central

Brown, Gillian R.; Dickins, Thomas E.; Sear, Rebecca; Laland, Kevin N.

2011-01-01

Human beings persist in an extraordinary range of ecological settings, in the process exhibiting enormous behavioural diversity, both within and between populations. People vary in their social, mating and parental behaviour and have diverse and elaborate beliefs, traditions, norms and institutions. The aim of this theme issue is to ask whether, and how, evolutionary theory can help us to understand this diversity. In this introductory article, we provide a background to the debate surrounding how best to understand behavioural diversity using evolutionary models of human behaviour. In particular, we examine how diversity has been viewed by the main subdisciplines within the human evolutionary behavioural sciences, focusing in particular on the human behavioural ecology, evolutionary psychology and cultural evolution approaches. In addition to differences in focus and methodology, these subdisciplines have traditionally varied in the emphasis placed on human universals, ecological factors and socially learned behaviour, and on how they have addressed the issue of genetic variation. We reaffirm that evolutionary theory provides an essential framework for understanding behavioural diversity within and between human populations, but argue that greater integration between the subfields is critical to developing a satisfactory understanding of diversity. PMID:21199836

Comparison of Evolutionary (Genetic) Algorithm and Adjoint Methods for Multi-Objective Viscous Airfoil Optimizations

NASA Technical Reports Server (NTRS)

Pulliam, T. H.; Nemec, M.; Holst, T.; Zingg, D. W.; Kwak, Dochan (Technical Monitor)

2002-01-01

A comparison between an Evolutionary Algorithm (EA) and an Adjoint-Gradient (AG) Method applied to a two-dimensional Navier-Stokes code for airfoil design is presented. Both approaches use a common function evaluation code, the steady-state explicit part of the code,ARC2D. The parameterization of the design space is a common B-spline approach for an airfoil surface, which together with a common griding approach, restricts the AG and EA to the same design space. Results are presented for a class of viscous transonic airfoils in which the optimization tradeoff between drag minimization as one objective and lift maximization as another, produces the multi-objective design space. Comparisons are made for efficiency, accuracy and design consistency.

Advances in computer simulation of genome evolution: toward more realistic evolutionary genomics analysis by approximate bayesian computation.

PubMed

Arenas, Miguel

2015-04-01

NGS technologies present a fast and cheap generation of genomic data. Nevertheless, ancestral genome inference is not so straightforward due to complex evolutionary processes acting on this material such as inversions, translocations, and other genome rearrangements that, in addition to their implicit complexity, can co-occur and confound ancestral inferences. Recently, models of genome evolution that accommodate such complex genomic events are emerging. This letter explores these novel evolutionary models and proposes their incorporation into robust statistical approaches based on computer simulations, such as approximate Bayesian computation, that may produce a more realistic evolutionary analysis of genomic data. Advantages and pitfalls in using these analytical methods are discussed. Potential applications of these ancestral genomic inferences are also pointed out.

Comparison of multiobjective evolutionary algorithms: empirical results.

PubMed

Zitzler, E; Deb, K; Thiele, L

2000-01-01

In this paper, we provide a systematic comparison of various evolutionary approaches to multiobjective optimization using six carefully chosen test functions. Each test function involves a particular feature that is known to cause difficulty in the evolutionary optimization process, mainly in converging to the Pareto-optimal front (e.g., multimodality and deception). By investigating these different problem features separately, it is possible to predict the kind of problems to which a certain technique is or is not well suited. However, in contrast to what was suspected beforehand, the experimental results indicate a hierarchy of the algorithms under consideration. Furthermore, the emerging effects are evidence that the suggested test functions provide sufficient complexity to compare multiobjective optimizers. Finally, elitism is shown to be an important factor for improving evolutionary multiobjective search.

Beyond the EDGE with EDAM: Prioritising British Plant Species According to Evolutionary Distinctiveness, and Accuracy and Magnitude of Decline

PubMed Central

Pearse, William D.; Chase, Mark W.; Crawley, Michael J.; Dolphin, Konrad; Fay, Michael F.; Joseph, Jeffrey A.; Powney, Gary; Preston, Chris D.; Rapacciuolo, Giovanni; Roy, David B.; Purvis, Andy

2015-01-01

Conservation biologists have only finite resources, and so must prioritise some species over others. The EDGE-listing approach ranks species according to their combined evolutionary distinctiveness and degree of threat, but ignores the uncertainty surrounding both threat and evolutionary distinctiveness. We develop a new family of measures for species, which we name EDAM, that incorporates evolutionary distinctiveness, the magnitude of decline, and the accuracy with which decline can be predicted. Further, we show how the method can be extended to explore phyogenetic uncertainty. Using the vascular plants of Britain as a case study, we find that the various EDAM measures emphasise different species and parts of Britain, and that phylogenetic uncertainty can strongly affect the prioritisation scores of some species. PMID:26018568

Evolutionary psychology and intelligence research.

PubMed

Kanazawa, Satoshi

2010-01-01

This article seeks to unify two subfields of psychology that have hitherto stood separately: evolutionary psychology and intelligence research/differential psychology. I suggest that general intelligence may simultaneously be an evolved adaptation and an individual-difference variable. Tooby and Cosmides's (1990a) notion of random quantitative variation on a monomorphic design allows us to incorporate heritable individual differences in evolved adaptations. The Savanna-IQ Interaction Hypothesis, which is one consequence of the integration of evolutionary psychology and intelligence research, can potentially explain why less intelligent individuals enjoy TV more, why liberals are more intelligent than conservatives, and why night owls are more intelligent than morning larks, among many other findings. The general approach proposed here will allow us to integrate evolutionary psychology with any other aspect of differential psychology. Copyright 2010 APA, all rights reserved.

Individual-based modeling of ecological and evolutionary processes

USGS Publications Warehouse

DeAngelis, Donald L.; Mooij, Wolf M.

2005-01-01

Individual-based models (IBMs) allow the explicit inclusion of individual variation in greater detail than do classical differential-equation and difference-equation models. Inclusion of such variation is important for continued progress in ecological and evolutionary theory. We provide a conceptual basis for IBMs by describing five major types of individual variation in IBMs: spatial, ontogenetic, phenotypic, cognitive, and genetic. IBMs are now used in almost all subfields of ecology and evolutionary biology. We map those subfields and look more closely at selected key papers on fish recruitment, forest dynamics, sympatric speciation, metapopulation dynamics, maintenance of diversity, and species conservation. Theorists are currently divided on whether IBMs represent only a practical tool for extending classical theory to more complex situations, or whether individual-based theory represents a radically new research program. We feel that the tension between these two poles of thinking can be a source of creativity in ecology and evolutionary theory.

Sex in a test tube: testing the benefits of in vitro recombination.

PubMed

Pesce, Diego; Lehman, Niles; de Visser, J Arjan G M

2016-10-19

The origin and evolution of sex, and the associated role of recombination, present a major problem in biology. Sex typically involves recombination of closely related DNA or RNA sequences, which is fundamentally a random process that creates but also breaks up beneficial allele combinations. Directed evolution experiments, which combine in vitro mutation and recombination protocols with in vitro or in vivo selection, have proved to be an effective approach for improving functionality of nucleic acids and enzymes. As this approach allows extreme control over evolutionary conditions and parameters, it also facilitates the detection of small or position-specific recombination benefits and benefits associated with recombination between highly divergent genotypes. Yet, in vitro approaches have been largely exploratory and motivated by obtaining improved end products rather than testing hypotheses of recombination benefits. Here, we review the various experimental systems and approaches used by in vitro studies of recombination, discuss what they say about the evolutionary role of recombination, and sketch their potential for addressing extant questions about the evolutionary role of sex and recombination, in particular on complex fitness landscapes. We also review recent insights into the role of 'extracellular recombination' during the origin of life.This article is part of the themed issue 'Weird sex: the underappreciated diversity of sexual reproduction'. © 2016 The Author(s).

The Exercise–Affect–Adherence Pathway: An Evolutionary Perspective

PubMed Central

Lee, Harold H.; Emerson, Jessica A.; Williams, David M.

2016-01-01

The low rates of regular exercise and overall physical activity (PA) in the general population represent a significant public health challenge. Previous research suggests that, for many people, exercise leads to a negative affective response and, in turn, reduced likelihood of future exercise. The purpose of this paper is to examine this exercise–affect–adherence relationship from an evolutionary perspective. Specifically, we argue that low rates of physical exercise in the general population are a function of the evolved human tendency to avoid unnecessary physical exertion. This innate tendency evolved because it allowed our evolutionary ancestors to conserve energy for physical activities that had immediate adaptive utility such as pursuing prey, escaping predators, and engaging in social and reproductive behaviors. The commonly observed negative affective response to exercise is an evolved proximate psychological mechanism through which humans avoid unnecessary energy expenditure. The fact that the human tendencies toward negative affective response to and avoidance of unnecessary physical activities are innate does not mean that they are unchangeable. Indeed, it is only because of human-engineered changes in our environmental conditions (i.e., it is no longer necessary for us to work for our food) that our predisposition to avoid unnecessary physical exertion has become a liability. Thus, it is well within our capabilities to reengineer our environments to once again make PA necessary or, at least, to serve an immediate functional purpose. We propose a two-pronged approach to PA promotion based on this evolutionary functional perspective: first, to promote exercise and other physical activities that are perceived to have an immediate purpose, and second, to instill greater perceived purpose for a wider range of physical activities. We posit that these strategies are more likely to result in more positive (or less negative) affective responses to exercise, better adherence to exercise programs, and higher rates of overall PA. PMID:27610096

Evolutionary history of barley cultivation in Europe revealed by genetic analysis of extant landraces

PubMed Central

2011-01-01

Background Understanding the evolution of cultivated barley is important for two reasons. First, the evolutionary relationships between different landraces might provide information on the spread and subsequent development of barley cultivation, including the adaptation of the crop to new environments and its response to human selection. Second, evolutionary information would enable landraces with similar traits but different genetic backgrounds to be identified, providing alternative strategies for the introduction of these traits into modern germplasm. Results The evolutionary relationships between 651 barley landraces were inferred from the genotypes for 24 microsatellites. The landraces could be divided into nine populations, each with a different geographical distribution. Comparisons with ear row number, caryopsis structure, seasonal growth habit and flowering time revealed a degree of association between population structure and phenotype, and analysis of climate variables indicated that the landraces are adapted, at least to some extent, to their environment. Human selection and/or environmental adaptation may therefore have played a role in the origin and/or maintenance of one or more of the barley landrace populations. There was also evidence that at least some of the population structure derived from geographical partitioning set up during the initial spread of barley cultivation into Europe, or reflected the later introduction of novel varieties. In particular, three closely-related populations were made up almost entirely of plants with the daylength nonresponsive version of the photoperiod response gene PPD-H1, conferring adaptation to the long annual growth season of northern Europe. These three populations probably originated in the eastern Fertile Crescent and entered Europe after the initial spread of agriculture. Conclusions The discovery of population structure, combined with knowledge of associated phenotypes and environmental adaptations, enables a rational approach to identification of landraces that might be used as sources of germplasm for breeding programs. The population structure also enables hypotheses concerning the prehistoric spread and development of agriculture to be addressed. PMID:22047039

Capturing neutral and adaptive genetic diversity for conservation in a highly structured tree species.

PubMed

Rodríguez-Quilón, Isabel; Santos-Del-Blanco, Luis; Serra-Varela, María Jesús; Koskela, Jarkko; González-Martínez, Santiago C; Alía, Ricardo

2016-10-01

Preserving intraspecific genetic diversity is essential for long-term forest sustainability in a climate change scenario. Despite that, genetic information is largely neglected in conservation planning, and how conservation units should be defined is still heatedly debated. Here, we use maritime pine (Pinus pinaster Ait.), an outcrossing long-lived tree with a highly fragmented distribution in the Mediterranean biodiversity hotspot, to prove the importance of accounting for genetic variation, of both neutral molecular markers and quantitative traits, to define useful conservation units. Six gene pools associated to distinct evolutionary histories were identified within the species using 12 microsatellites and 266 single nucleotide polymorphisms (SNPs). In addition, height and survival standing variation, their genetic control, and plasticity were assessed in a multisite clonal common garden experiment (16 544 trees). We found high levels of quantitative genetic differentiation within previously defined neutral gene pools. Subsequent cluster analysis and post hoc trait distribution comparisons allowed us to define 10 genetically homogeneous population groups with high evolutionary potential. They constitute the minimum number of units to be represented in a maritime pine dynamic conservation program. Our results uphold that the identification of conservation units below the species level should account for key neutral and adaptive components of genetic diversity, especially in species with strong population structure and complex evolutionary histories. The environmental zonation approach currently used by the pan-European genetic conservation strategy for forest trees would be largely improved by gradually integrating molecular and quantitative trait information, as data become available. © 2016 by the Ecological Society of America.

A genetic programming approach for Burkholderia Pseudomallei diagnostic pattern discovery

PubMed Central

Yang, Zheng Rong; Lertmemongkolchai, Ganjana; Tan, Gladys; Felgner, Philip L.; Titball, Richard

2009-01-01

Motivation: Finding diagnostic patterns for fighting diseases like Burkholderia pseudomallei using biomarkers involves two key issues. First, exhausting all subsets of testable biomarkers (antigens in this context) to find a best one is computationally infeasible. Therefore, a proper optimization approach like evolutionary computation should be investigated. Second, a properly selected function of the antigens as the diagnostic pattern which is commonly unknown is a key to the diagnostic accuracy and the diagnostic effectiveness in clinical use. Results: A conversion function is proposed to convert serum tests of antigens on patients to binary values based on which Boolean functions as the diagnostic patterns are developed. A genetic programming approach is designed for optimizing the diagnostic patterns in terms of their accuracy and effectiveness. During optimization, it is aimed to maximize the coverage (the rate of positive response to antigens) in the infected patients and minimize the coverage in the non-infected patients while maintaining the fewest number of testable antigens used in the Boolean functions as possible. The final coverage in the infected patients is 96.55% using 17 of 215 (7.4%) antigens with zero coverage in the non-infected patients. Among these 17 antigens, BPSL2697 is the most frequently selected one for the diagnosis of Burkholderia Pseudomallei. The approach has been evaluated using both the cross-validation and the Jack–knife simulation methods with the prediction accuracy as 93% and 92%, respectively. A novel approach is also proposed in this study to evaluate a model with binary data using ROC analysis. Contact: z.r.yang@ex.ac.uk PMID:19561021

A Program for At-Risk High School Students Informed by Evolutionary Science

PubMed Central

Wilson, David Sloan; Kauffman, Richard A.; Purdy, Miriam S.

2011-01-01

Improving the academic performance of at-risk high school students has proven difficult, often calling for an extended day, extended school year, and other expensive measures. Here we report the results of a program for at-risk 9th and 10th graders in Binghamton, New York, called the Regents Academy that takes place during the normal school day and year. The design of the program is informed by the evolutionary dynamics of cooperation and learning, in general and for our species as a unique product of biocultural evolution. Not only did the Regents Academy students outperform their comparison group in a randomized control design, but they performed on a par with the average high school student in Binghamton on state-mandated exams. All students can benefit from the social environment provided for at-risk students at the Regents Academy, which is within the reach of most public school districts. PMID:22114703

Inference of Evolutionary Jumps in Large Phylogenies using Lévy Processes.

PubMed

Duchen, Pablo; Leuenberger, Christoph; Szilágyi, Sándor M; Harmon, Luke; Eastman, Jonathan; Schweizer, Manuel; Wegmann, Daniel

2017-11-01

Although it is now widely accepted that the rate of phenotypic evolution may not necessarily be constant across large phylogenies, the frequency and phylogenetic position of periods of rapid evolution remain unclear. In his highly influential view of evolution, G. G. Simpson supposed that such evolutionary jumps occur when organisms transition into so-called new adaptive zones, for instance after dispersal into a new geographic area, after rapid climatic changes, or following the appearance of an evolutionary novelty. Only recently, large, accurate and well calibrated phylogenies have become available that allow testing this hypothesis directly, yet inferring evolutionary jumps remains computationally very challenging. Here, we develop a computationally highly efficient algorithm to accurately infer the rate and strength of evolutionary jumps as well as their phylogenetic location. Following previous work we model evolutionary jumps as a compound process, but introduce a novel approach to sample jump configurations that does not require matrix inversions and thus naturally scales to large trees. We then make use of this development to infer evolutionary jumps in Anolis lizards and Loriinii parrots where we find strong signal for such jumps at the basis of clades that transitioned into new adaptive zones, just as postulated by Simpson's hypothesis. [evolutionary jump; Lévy process; phenotypic evolution; punctuated equilibrium; quantitative traits. The Author(s) 2017. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.

Evolutionary dynamics from a variational principle.

PubMed

Klimek, Peter; Thurner, Stefan; Hanel, Rudolf

2010-07-01

We demonstrate with a thought experiment that fitness-based population dynamical approaches to evolution are not able to make quantitative, falsifiable predictions about the long-term behavior of some evolutionary systems. A key characteristic of evolutionary systems is the ongoing endogenous production of new species. These novel entities change the conditions for already existing species. Even Darwin's Demon, a hypothetical entity with exact knowledge of the abundance of all species and their fitness functions at a given time, could not prestate the impact of these novelties on established populations. We argue that fitness is always a posteriori knowledge--it measures but does not explain why a species has reproductive success or not. To overcome these conceptual limitations, a variational principle is proposed in a spin-model-like setup of evolutionary systems. We derive a functional which is minimized under the most general evolutionary formulation of a dynamical system, i.e., evolutionary trajectories causally emerge as a minimization of a functional. This functional allows the derivation of analytic solutions of the asymptotic diversity for stochastic evolutionary systems within a mean-field approximation. We test these approximations by numerical simulations of the corresponding model and find good agreement in the position of phase transitions in diversity curves. The model is further able to reproduce stylized facts of timeseries from several man-made and natural evolutionary systems. Light will be thrown on how species and their fitness landscapes dynamically coevolve.

Social evolution and genetic interactions in the short and long term.

PubMed

Van Cleve, Jeremy

2015-08-01

The evolution of social traits remains one of the most fascinating and feisty topics in evolutionary biology even after half a century of theoretical research. W.D. Hamilton shaped much of the field initially with his 1964 papers that laid out the foundation for understanding the effect of genetic relatedness on the evolution of social behavior. Early theoretical investigations revealed two critical assumptions required for Hamilton's rule to hold in dynamical models: weak selection and additive genetic interactions. However, only recently have analytical approaches from population genetics and evolutionary game theory developed sufficiently so that social evolution can be studied under the joint action of selection, mutation, and genetic drift. We review how these approaches suggest two timescales for evolution under weak mutation: (i) a short-term timescale where evolution occurs between a finite set of alleles, and (ii) a long-term timescale where a continuum of alleles are possible and populations evolve continuously from one monomorphic trait to another. We show how Hamilton's rule emerges from the short-term analysis under additivity and how non-additive genetic interactions can be accounted for more generally. This short-term approach reproduces, synthesizes, and generalizes many previous results including the one-third law from evolutionary game theory and risk dominance from economic game theory. Using the long-term approach, we illustrate how trait evolution can be described with a diffusion equation that is a stochastic analogue of the canonical equation of adaptive dynamics. Peaks in the stationary distribution of the diffusion capture classic notions of convergence stability from evolutionary game theory and generally depend on the additive genetic interactions inherent in Hamilton's rule. Surprisingly, the peaks of the long-term stationary distribution can predict the effects of simple kinds of non-additive interactions. Additionally, the peaks capture both weak and strong effects of social payoffs in a manner difficult to replicate with the short-term approach. Together, the results from the short and long-term approaches suggest both how Hamilton's insight may be robust in unexpected ways and how current analytical approaches can expand our understanding of social evolution far beyond Hamilton's original work. Copyright © 2015 Elsevier Inc. All rights reserved.

A Multifaceted Approach to Modernizing NASA's Advanced Multi-Mission Operations System (AMMOS) System Architecture

NASA Technical Reports Server (NTRS)

Estefan, Jeff A.; Giovannoni, Brian J.

2014-01-01

The Advanced Multi-Mission Operations Systems (AMMOS) is NASA's premier space mission operations product line offering for use in deep-space robotic and astrophysics missions. The general approach to AMMOS modernization over the course of its 29-year history exemplifies a continual, evolutionary approach with periods of sponsor investment peaks and valleys in between. Today, the Multimission Ground Systems and Services (MGSS) office-the program office that manages the AMMOS for NASA-actively pursues modernization initiatives and continues to evolve the AMMOS by incorporating enhanced capabilities and newer technologies into its end-user tool and service offerings. Despite the myriad of modernization investments that have been made over the evolutionary course of the AMMOS, pain points remain. These pain points, based on interviews with numerous flight project mission operations personnel, can be classified principally into two major categories: 1) information-related issues, and 2) process-related issues. By information-related issues, we mean pain points associated with the management and flow of MOS data across the various system interfaces. By process-related issues, we mean pain points associated with the MOS activities performed by mission operators (i.e., humans) and supporting software infrastructure used in support of those activities. In this paper, three foundational concepts-Timeline, Closed Loop Control, and Separation of Concerns-collectively form the basis for expressing a set of core architectural tenets that provides a multifaceted approach to AMMOS system architecture modernization intended to address the information- and process-related issues. Each of these architectural tenets will be further explored in this paper. Ultimately, we envision the application of these core tenets resulting in a unified vision of a future-state architecture for the AMMOS-one that is intended to result in a highly adaptable, highly efficient, and highly cost-effective set of multimission MOS products and services.

Bayesian estimation and use of high-throughput remote sensing indices for quantitative genetic analyses of leaf growth.

PubMed

Baker, Robert L; Leong, Wen Fung; An, Nan; Brock, Marcus T; Rubin, Matthew J; Welch, Stephen; Weinig, Cynthia

2018-02-01

We develop Bayesian function-valued trait models that mathematically isolate genetic mechanisms underlying leaf growth trajectories by factoring out genotype-specific differences in photosynthesis. Remote sensing data can be used instead of leaf-level physiological measurements. Characterizing the genetic basis of traits that vary during ontogeny and affect plant performance is a major goal in evolutionary biology and agronomy. Describing genetic programs that specifically regulate morphological traits can be complicated by genotypic differences in physiological traits. We describe the growth trajectories of leaves using novel Bayesian function-valued trait (FVT) modeling approaches in Brassica rapa recombinant inbred lines raised in heterogeneous field settings. While frequentist approaches estimate parameter values by treating each experimental replicate discretely, Bayesian models can utilize information in the global dataset, potentially leading to more robust trait estimation. We illustrate this principle by estimating growth asymptotes in the face of missing data and comparing heritabilities of growth trajectory parameters estimated by Bayesian and frequentist approaches. Using pseudo-Bayes factors, we compare the performance of an initial Bayesian logistic growth model and a model that incorporates carbon assimilation (A max ) as a cofactor, thus statistically accounting for genotypic differences in carbon resources. We further evaluate two remotely sensed spectroradiometric indices, photochemical reflectance (pri2) and MERIS Terrestrial Chlorophyll Index (mtci) as covariates in lieu of A max , because these two indices were genetically correlated with A max across years and treatments yet allow much higher throughput compared to direct leaf-level gas-exchange measurements. For leaf lengths in uncrowded settings, including A max improves model fit over the initial model. The mtci and pri2 indices also outperform direct A max measurements. Of particular importance for evolutionary biologists and plant breeders, hierarchical Bayesian models estimating FVT parameters improve heritabilities compared to frequentist approaches.

The scope and strength of sex-specific selection in genome evolution.

PubMed

Wright, A E; Mank, J E

2013-09-01

Males and females share the vast majority of their genomes and yet are often subject to different, even conflicting, selection. Genomic and transcriptomic developments have made it possible to assess sex-specific selection at the molecular level, and it is clear that sex-specific selection shapes the evolutionary properties of several genomic characteristics, including transcription, post-transcriptional regulation, imprinting, genome structure and gene sequence. Sex-specific selection is strongly influenced by mating system, which also causes neutral evolutionary changes that affect different regions of the genome in different ways. Here, we synthesize theoretical and molecular work in order to provide a cohesive view of the role of sex-specific selection and mating system in genome evolution. We also highlight the need for a combined approach, incorporating both genomic data and experimental phenotypic studies, in order to understand precisely how sex-specific selection drives evolutionary change across the genome. © 2013 The Authors. Journal of Evolutionary Biology © 2013 European Society For Evolutionary Biology.

Treatment resistance in urothelial carcinoma: an evolutionary perspective.

PubMed

Vlachostergios, Panagiotis J; Faltas, Bishoy M

2018-05-02

The emergence of treatment-resistant clones is a critical barrier to cure in patients with urothelial carcinoma. Setting the stage for the evolution of resistance, urothelial carcinoma is characterized by extensive mutational heterogeneity, which is detectable even in patients with early stage disease. Chemotherapy and immunotherapy both act as selective pressures that shape the evolutionary trajectory of urothelial carcinoma throughout the course of the disease. A detailed understanding of the dynamics of evolutionary drivers is required for the rational development of curative therapies. Herein, we describe the molecular basis of the clonal evolution of urothelial carcinomas and the use of genomic approaches to predict treatment responses. We discuss various mechanisms of resistance to chemotherapy with a focus on the mutagenic effects of the DNA dC->dU-editing enzymes APOBEC3 family of proteins. We also review the evolutionary mechanisms underlying resistance to immunotherapy, such as the loss of clonal tumour neoantigens. By dissecting treatment resistance through an evolutionary lens, the field will advance towards true precision medicine for urothelial carcinoma.

Asynchronous spatial evolutionary games.

PubMed

Newth, David; Cornforth, David

2009-02-01

Over the past 50 years, much attention has been given to the Prisoner's Dilemma as a metaphor for problems surrounding the evolution and maintenance of cooperative and altruistic behavior. The bulk of this work has dealt with the successfulness and robustness of various strategies. Nowak and May (1992) considered an alternative approach to studying evolutionary games. They assumed that players were distributed across a two-dimensional (2D) lattice, interactions between players occurred locally, rather than at long range as in the well mixed situation. The resulting spatial evolutionary games display dynamics not seen in their well-mixed counterparts. An assumption underlying much of the work on spatial evolutionary games is that the state of all players is updated in unison or in synchrony. Using the framework outlined in Nowak and May (1992), we examine the effect of various asynchronous updating schemes on the dynamics of spatial evolutionary games. There are potential implications for the dynamics of a wide variety of spatially extended systems in biology, physics and chemistry.

A dynamic eco-evolutionary model predicts slow response of alpine plants to climate warming.

PubMed

Cotto, Olivier; Wessely, Johannes; Georges, Damien; Klonner, Günther; Schmid, Max; Dullinger, Stefan; Thuiller, Wilfried; Guillaume, Frédéric

2017-05-05

Withstanding extinction while facing rapid climate change depends on a species' ability to track its ecological niche or to evolve a new one. Current methods that predict climate-driven species' range shifts use ecological modelling without eco-evolutionary dynamics. Here we present an eco-evolutionary forecasting framework that combines niche modelling with individual-based demographic and genetic simulations. Applying our approach to four endemic perennial plant species of the Austrian Alps, we show that accounting for eco-evolutionary dynamics when predicting species' responses to climate change is crucial. Perennial species persist in unsuitable habitats longer than predicted by niche modelling, causing delayed range losses; however, their evolutionary responses are constrained because long-lived adults produce increasingly maladapted offspring. Decreasing population size due to maladaptation occurs faster than the contraction of the species range, especially for the most abundant species. Monitoring of species' local abundance rather than their range may likely better inform on species' extinction risks under climate change.

Testing inferences in developmental evolution: the forensic evidence principle.

PubMed

Larsson, Hans C E; Wagner, Günter P

2012-09-01

Developmental evolution (DE) examines the influence of developmental mechanisms on biological evolution. Here we consider the question: "what is the evidence that allows us to decide whether a certain developmental scenario for an evolutionary change is in fact "correct" or at least falsifiable?" We argue that the comparative method linked with what we call the "forensic evidence principle" (FEP) is sufficient to conduct rigorous tests of DE scenarios. The FEP states that different genetically mediated developmental causes of an evolutionary transformation will leave different signatures in the development of the derived character. Although similar inference rules have been used in practically every empirical science, we expand this approach here in two ways: (1) we justify the validity of this principle with reference to a well-known result from mathematical physics, known as the symmetry principle, and (2) propose a specific form of the FEP for DE: given two or more developmental explanations for a certain evolutionary event, say an evolutionary novelty, then the evidence discriminating between these hypotheses will be found in the most proximal internal drivers of the derived character. Hence, a detailed description of the ancestral and derived states, and their most proximal developmental drivers are necessary to discriminate between various evolutionary developmental hypotheses. We discuss how this stepwise order of testing is necessary, establishes a formal test, and how skipping this order of examination may violate a more accurate examination of DE. We illustrate the approach with an example from avian digit evolution. © 2012 Wiley Periodicals, Inc.

Development of a population of cancer cells: Observation and modeling by a Mixed Spatial Evolutionary Games approach.

PubMed

Świerniak, Andrzej; Krześlak, Michał; Student, Sebastian; Rzeszowska-Wolny, Joanna

2016-09-21

Living cells, like whole living organisms during evolution, communicate with their neighbors, interact with the environment, divide, change their phenotypes, and eventually die. The development of specific ways of communication (through signaling molecules and receptors) allows some cellular subpopulations to survive better, to coordinate their physiological status, and during embryonal development to create tissues and organs or in some conditions to become tumors. Populations of cells cultured in vitro interact similarly, also competing for space and nutrients and stimulating each other to better survive or to die. The results of these intercellular interactions of different types seem to be good examples of biological evolutionary games, and have been the subjects of simulations by the methods of evolutionary game theory where individual cells are treated as players. Here we present examples of intercellular contacts in a population of living human cancer HeLa cells cultured in vitro and propose an evolutionary game theory approach to model the development of such populations. We propose a new technique termed Mixed Spatial Evolutionary Games (MSEG) which are played on multiple lattices corresponding to the possible cellular phenotypes which gives the possibility of simulating and investigating the effects of heterogeneity at the cellular level in addition to the population level. Analyses performed with MSEG suggested different ways in which cellular populations develop in the case of cells communicating directly and through factors released to the environment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Applying evolutionary concepts to wildlife disease ecology and management

PubMed Central

Vander Wal, Eric; Garant, Dany; Calmé, Sophie; Chapman, Colin A; Festa-Bianchet, Marco; Millien, Virginie; Rioux-Paquette, Sébastien; Pelletier, Fanie

2014-01-01

Existing and emerging infectious diseases are among the most pressing global threats to biodiversity, food safety and human health. The complex interplay between host, pathogen and environment creates a challenge for conserving species, communities and ecosystem functions, while mediating the many known ecological and socio-economic negative effects of disease. Despite the clear ecological and evolutionary contexts of host–pathogen dynamics, approaches to managing wildlife disease remain predominantly reactionary, focusing on surveillance and some attempts at eradication. A few exceptional studies have heeded recent calls for better integration of ecological concepts in the study and management of wildlife disease; however, evolutionary concepts remain underused. Applied evolution consists of four principles: evolutionary history, genetic and phenotypic variation, selection and eco-evolutionary dynamics. In this article, we first update a classical framework for understanding wildlife disease to integrate better these principles. Within this framework, we explore the evolutionary implications of environment–disease interactions. Subsequently, we synthesize areas where applied evolution can be employed in wildlife disease management. Finally, we discuss some future directions and challenges. Here, we underscore that despite some evolutionary principles currently playing an important role in our understanding of disease in wild animals, considerable opportunities remain for fostering the practice of evolutionarily enlightened wildlife disease management. PMID:25469163

An evolutionary critique of cultural analysis in sociology.

PubMed

Crippen, T

1992-12-01

A noteworthy development that has transpired in American sociology in the past quarter century has been the increasingly sophisticated interest in the analysis of human cultural systems. Sadly, however, these analyses reveal that social scientists rarely appreciate the profoundly evolutionary aspects of human culture. The chief purpose of this essay is to address this shortcoming and to offer some tentative suggestions toward its rectification. The essay begins by briefly reviewing recent developments in the analysis of cultural systems, primarily by reference to the influential work of Wuthnow. Second, a common flaw in these approaches is addressed-namely, the absence of any recognition of the value of grounding sociocultural theory in an informed evolutionary framework-and the case is made that this shortcoming is avoidable, even within the context of the intellectual traditions of the social sciences. Third, the evolutionary foundations of human cultural behavior are explored in terms of an analysis of relevant theoretical and empirical developments in the evolutionary neurosciences. Fourth, the value of these insights is illustrated by reference to an evolutionary critique of a recent and thought-provoking contribution to the study of modern political culture-Douglas and Wildavsky's analysis ofRisk and Culture. Finally, the article concludes by emphasizing the value of and the necessity for incorporating evolutionary reasoning into the domain of sociocultural theory.

Applying evolutionary concepts to wildlife disease ecology and management.

PubMed

Vander Wal, Eric; Garant, Dany; Calmé, Sophie; Chapman, Colin A; Festa-Bianchet, Marco; Millien, Virginie; Rioux-Paquette, Sébastien; Pelletier, Fanie

2014-08-01

Existing and emerging infectious diseases are among the most pressing global threats to biodiversity, food safety and human health. The complex interplay between host, pathogen and environment creates a challenge for conserving species, communities and ecosystem functions, while mediating the many known ecological and socio-economic negative effects of disease. Despite the clear ecological and evolutionary contexts of host-pathogen dynamics, approaches to managing wildlife disease remain predominantly reactionary, focusing on surveillance and some attempts at eradication. A few exceptional studies have heeded recent calls for better integration of ecological concepts in the study and management of wildlife disease; however, evolutionary concepts remain underused. Applied evolution consists of four principles: evolutionary history, genetic and phenotypic variation, selection and eco-evolutionary dynamics. In this article, we first update a classical framework for understanding wildlife disease to integrate better these principles. Within this framework, we explore the evolutionary implications of environment-disease interactions. Subsequently, we synthesize areas where applied evolution can be employed in wildlife disease management. Finally, we discuss some future directions and challenges. Here, we underscore that despite some evolutionary principles currently playing an important role in our understanding of disease in wild animals, considerable opportunities remain for fostering the practice of evolutionarily enlightened wildlife disease management.

Prediction of Layer Thickness in Molten Borax Bath with Genetic Evolutionary Programming

NASA Astrophysics Data System (ADS)

Taylan, Fatih

2011-04-01

In this study, the vanadium carbide coating in molten borax bath process is modeled by evolutionary genetic programming (GEP) with bath composition (borax percentage, ferro vanadium (Fe-V) percentage, boric acid percentage), bath temperature, immersion time, and layer thickness data. Five inputs and one output data exist in the model. The percentage of borax, Fe-V, and boric acid, temperature, and immersion time parameters are used as input data and the layer thickness value is used as output data. For selected bath components, immersion time, and temperature variables, the layer thicknesses are derived from the mathematical expression. The results of the mathematical expressions are compared to that of experimental data; it is determined that the derived mathematical expression has an accuracy of 89%.

Constraints in Genetic Programming

NASA Technical Reports Server (NTRS)

Janikow, Cezary Z.

1996-01-01

Genetic programming refers to a class of genetic algorithms utilizing generic representation in the form of program trees. For a particular application, one needs to provide the set of functions, whose compositions determine the space of program structures being evolved, and the set of terminals, which determine the space of specific instances of those programs. The algorithm searches the space for the best program for a given problem, applying evolutionary mechanisms borrowed from nature. Genetic algorithms have shown great capabilities in approximately solving optimization problems which could not be approximated or solved with other methods. Genetic programming extends their capabilities to deal with a broader variety of problems. However, it also extends the size of the search space, which often becomes too large to be effectively searched even by evolutionary methods. Therefore, our objective is to utilize problem constraints, if such can be identified, to restrict this space. In this publication, we propose a generic constraint specification language, powerful enough for a broad class of problem constraints. This language has two elements -- one reduces only the number of program instances, the other reduces both the space of program structures as well as their instances. With this language, we define the minimal set of complete constraints, and a set of operators guaranteeing offspring validity from valid parents. We also show that these operators are not less efficient than the standard genetic programming operators if one preprocesses the constraints - the necessary mechanisms are identified.

A method for inferring the rate of evolution of homologous characters that can potentially improve phylogenetic inference, resolve deep divergence and correct systematic biases.

PubMed

Cummins, Carla A; McInerney, James O

2011-12-01

Current phylogenetic methods attempt to account for evolutionary rate variation across characters in a matrix. This is generally achieved by the use of sophisticated evolutionary models, combined with dense sampling of large numbers of characters. However, systematic biases and superimposed substitutions make this task very difficult. Model adequacy can sometimes be achieved at the cost of adding large numbers of free parameters, with each parameter being optimized according to some criterion, resulting in increased computation times and large variances in the model estimates. In this study, we develop a simple approach that estimates the relative evolutionary rate of each homologous character. The method that we describe uses the similarity between characters as a proxy for evolutionary rate. In this article, we work on the premise that if the character-state distribution of a homologous character is similar to many other characters, then this character is likely to be relatively slowly evolving. If the character-state distribution of a homologous character is not similar to many or any of the rest of the characters in a data set, then it is likely to be the result of rapid evolution. We show that in some test cases, at least, the premise can hold and the inferences are robust. Importantly, the method does not use a "starting tree" to make the inference and therefore is tree independent. We demonstrate that this approach can work as well as a maximum likelihood (ML) approach, though the ML method needs to have a known phylogeny, or at least a very good estimate of that phylogeny. We then demonstrate some uses for this method of analysis, including the improvement in phylogeny reconstruction for both deep-level and recent relationships and overcoming systematic biases such as base composition bias. Furthermore, we compare this approach to two well-established methods for reweighting or removing characters. These other methods are tree-based and we show that they can be systematically biased. We feel this method can be useful for phylogeny reconstruction, understanding evolutionary rate variation, and for understanding selection variation on different characters.

Group-level traits can be studied with standard evolutionary theory.

PubMed

Scott-Phillips, Thomas C; Dickins, Thomas E

2014-06-01

Smaldino's target article draws on and seeks to add to a literature that has partially rejected orthodox, gene-centric evolutionary theory. However, orthodox theory has much to say about group-level traits. The target article does not reference or refute these views, and provides no explicit arguments for this narrow approach. In this commentary we: (i) give two examples of topics that the target article might and probably should have discussed (cultural epidemiology and the psychology of individual differences); and (ii) argue that the orthodox approach has much more to say about the emergence of group-level traits than the target article recognises, or gives credit for.

Maximizing ecological and evolutionary insight in bisulfite sequencing data sets

PubMed Central

Lea, Amanda J.; Vilgalys, Tauras P.; Durst, Paul A.P.; Tung, Jenny

2017-01-01

Preface Genome-scale bisulfite sequencing approaches have opened the door to ecological and evolutionary studies of DNA methylation in many organisms. These approaches can be powerful. However, they introduce new methodological and statistical considerations, some of which are particularly relevant to non-model systems. Here, we highlight how these considerations influence a study’s power to link methylation variation with a predictor variable of interest. Relative to current practice, we argue that sample sizes will need to increase to provide robust insights. We also provide recommendations for overcoming common challenges and an R Shiny app to aid in study design. PMID:29046582

Back to the future: Rational maps for exploring acetylcholine receptor space and time.

PubMed

Tessier, Christian J G; Emlaw, Johnathon R; Cao, Zhuo Qian; Pérez-Areales, F Javier; Salameh, Jean-Paul J; Prinston, Jethro E; McNulty, Melissa S; daCosta, Corrie J B

2017-11-01

Global functions of nicotinic acetylcholine receptors, such as subunit cooperativity and compatibility, likely emerge from a network of amino acid residues distributed across the entire pentameric complex. Identification of such networks has stymied traditional approaches to acetylcholine receptor structure and function, likely due to the cryptic interdependency of their underlying amino acid residues. An emerging evolutionary biochemistry approach, which traces the evolutionary history of acetylcholine receptor subunits, allows for rational mapping of acetylcholine receptor sequence space, and offers new hope for uncovering the amino acid origins of these enigmatic properties. Copyright © 2017 Elsevier B.V. All rights reserved.

The cultural evolution of fertility decline

PubMed Central

Colleran, Heidi

2016-01-01

Cultural evolutionists have long been interested in the problem of why fertility declines as populations develop. By outlining plausible mechanistic links between individual decision-making, information flow in populations and competition between groups, models of cultural evolution offer a novel and powerful approach for integrating multiple levels of explanation of fertility transitions. However, only a modest number of models have been published. Their assumptions often differ from those in other evolutionary approaches to social behaviour, but their empirical predictions are often similar. Here I offer the first overview of cultural evolutionary research on demographic transition, critically compare it with approaches taken by other evolutionary researchers, identify gaps and overlaps, and highlight parallel debates in demography. I suggest that researchers divide their labour between three distinct phases of fertility decline—the origin, spread and maintenance of low fertility—each of which may be driven by different causal processes, at different scales, requiring different theoretical and empirical tools. A comparative, multi-level and mechanistic framework is essential for elucidating both the evolved aspects of our psychology that govern reproductive decision-making, and the social, ecological and cultural contingencies that precipitate and sustain fertility decline. PMID:27022079

From head to tail: new models and approaches in primate functional anatomy and biomechanics.

PubMed

Organ, Jason M; Deleon, Valerie B; Wang, Qian; Smith, Timothy D

2010-04-01

This special issue of The Anatomical Record (AR) is based on interest generated by a symposium at the 2008 annual meeting of the American Association of Anatomists (AAA) at Experimental Biology, entitled "An Evolutionary Perspective on Human Anatomy." The development of this volume in turn provided impetus for a Biological Anthropology Mini-Meeting, organized by members of the AAA for the 2010 Experimental Biology meeting in Anaheim, California. The research presented in these pages reflects the themes of these symposia and provides a snapshot of the current state of primate functional anatomy and biomechanics research. The 17 articles in this special issue utilize new models and/or approaches to study long-standing questions about the evolution of our closest relatives, including soft-tissue dissection and microanatomical techniques, experimental approaches to morphology, kinematic and kinetic biomechanics, high-resolution computed tomography, and Finite Element Analysis (FEA). This volume continues a close historical association between the disciplines of anatomy and biological anthropology: anatomists benefit from an understanding of the evolutionary history of our modern form, and biological anthropologists rely on anatomical principles to make informed evolutionary inferences about our closest relatives. (c) 2010 Wiley-Liss, Inc.

Evolutionary Ensemble for In Silico Prediction of Ames Test Mutagenicity

NASA Astrophysics Data System (ADS)

Chen, Huanhuan; Yao, Xin

Driven by new regulations and animal welfare, the need to develop in silico models has increased recently as alternative approaches to safety assessment of chemicals without animal testing. This paper describes a novel machine learning ensemble approach to building an in silico model for the prediction of the Ames test mutagenicity, one of a battery of the most commonly used experimental in vitro and in vivo genotoxicity tests for safety evaluation of chemicals. Evolutionary random neural ensemble with negative correlation learning (ERNE) [1] was developed based on neural networks and evolutionary algorithms. ERNE combines the method of bootstrap sampling on training data with the method of random subspace feature selection to ensure diversity in creating individuals within an initial ensemble. Furthermore, while evolving individuals within the ensemble, it makes use of the negative correlation learning, enabling individual NNs to be trained as accurate as possible while still manage to maintain them as diverse as possible. Therefore, the resulting individuals in the final ensemble are capable of cooperating collectively to achieve better generalization of prediction. The empirical experiment suggest that ERNE is an effective ensemble approach for predicting the Ames test mutagenicity of chemicals.

Evolutionary Scheduler for the Deep Space Network

NASA Technical Reports Server (NTRS)

Guillaume, Alexandre; Lee, Seungwon; Wang, Yeou-Fang; Zheng, Hua; Chau, Savio; Tung, Yu-Wen; Terrile, Richard J.; Hovden, Robert

2010-01-01

A computer program assists human schedulers in satisfying, to the maximum extent possible, competing demands from multiple spacecraft missions for utilization of the transmitting/receiving Earth stations of NASA s Deep Space Network. The program embodies a concept of optimal scheduling to attain multiple objectives in the presence of multiple constraints.

From experimental systems to evolutionary biology: an impossible journey?

PubMed

Morange, Michel

2013-01-01

The historical approach to the sciences has undergone a sea change during recent decades. Maybe the major contribution of Hans-Jörg Rheinberger to this movement was his demonstration of the importance of experimental systems, and of their transformations, in the development of the sciences. To describe these transformations, Hans-Jörg borrows metaphors from evolutionary biology. I want to argue that evolutionary biologists can find in these recent historical studies plenty of models and concepts to address unresolved issues in their discipline. At a time when transdisciplinarity is highly praised, it is useful to provide a precise description of the obstacles that have so far prevented this exchange.

["Long-branch Attraction" artifact in phylogenetic reconstruction].

PubMed

Li, Yi-Wei; Yu, Li; Zhang, Ya-Ping

2007-06-01

Phylogenetic reconstruction among various organisms not only helps understand their evolutionary history but also reveal several fundamental evolutionary questions. Understanding of the evolutionary relationships among organisms establishes the foundation for the investigations of other biological disciplines. However, almost all the widely used phylogenetic methods have limitations which fail to eliminate systematic errors effectively, preventing the reconstruction of true organismal relationships. "Long-branch Attraction" (LBA) artifact is one of the most disturbing factors in phylogenetic reconstruction. In this review, the conception and analytic method as well as the avoidance strategy of LBA were summarized. In addition, several typical examples were provided. The approach to avoid and resolve LBA artifact has been discussed.

Human compulsivity: A perspective from evolutionary medicine.

PubMed

Stein, Dan J; Hermesh, Haggai; Eilam, David; Segalas, Cosi; Zohar, Joseph; Menchon, Jose; Nesse, Randolph M

2016-05-01

Biological explanations address not only proximal mechanisms (for example, the underlying neurobiology of obsessive-compulsive disorder), but also distal mechanisms (that is, a consideration of how particular neurobiological mechanisms evolved). Evolutionary medicine has emphasized a series of explanations for vulnerability to disease, including constraints, mismatch, and tradeoffs. The current paper will consider compulsive symptoms in obsessive-compulsive and related disorders and behavioral addictions from this evolutionary perspective. It will argue that while obsessive-compulsive disorder (OCD) is typically best conceptualized as a dysfunction, it is theoretically and clinically valuable to understand some symptoms of obsessive-compulsive and related disorders in terms of useful defenses. The symptoms of behavioral addictions can also be conceptualized in evolutionary terms (for example, mismatch), which in turn provides a sound foundation for approaching assessment and intervention. Copyright © 2016. Published by Elsevier B.V.

On Improving Efficiency of Differential Evolution for Aerodynamic Shape Optimization Applications

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.

2004-01-01

Differential Evolution (DE) is a simple and robust evolutionary strategy that has been provEn effective in determining the global optimum for several difficult optimization problems. Although DE offers several advantages over traditional optimization approaches, its use in applications such as aerodynamic shape optimization where the objective function evaluations are computationally expensive is limited by the large number of function evaluations often required. In this paper various approaches for improving the efficiency of DE are reviewed and discussed. Several approaches that have proven effective for other evolutionary algorithms are modified and implemented in a DE-based aerodynamic shape optimization method that uses a Navier-Stokes solver for the objective function evaluations. Parallelization techniques on distributed computers are used to reduce turnaround times. Results are presented for standard test optimization problems and for the inverse design of a turbine airfoil. The efficiency improvements achieved by the different approaches are evaluated and compared.

Knowledge Discovery in Variant Databases Using Inductive Logic Programming

PubMed Central

Nguyen, Hoan; Luu, Tien-Dao; Poch, Olivier; Thompson, Julie D.

2013-01-01

Understanding the effects of genetic variation on the phenotype of an individual is a major goal of biomedical research, especially for the development of diagnostics and effective therapeutic solutions. In this work, we describe the use of a recent knowledge discovery from database (KDD) approach using inductive logic programming (ILP) to automatically extract knowledge about human monogenic diseases. We extracted background knowledge from MSV3d, a database of all human missense variants mapped to 3D protein structure. In this study, we identified 8,117 mutations in 805 proteins with known three-dimensional structures that were known to be involved in human monogenic disease. Our results help to improve our understanding of the relationships between structural, functional or evolutionary features and deleterious mutations. Our inferred rules can also be applied to predict the impact of any single amino acid replacement on the function of a protein. The interpretable rules are available at http://decrypthon.igbmc.fr/kd4v/. PMID:23589683

Knowledge discovery in variant databases using inductive logic programming.

PubMed

Nguyen, Hoan; Luu, Tien-Dao; Poch, Olivier; Thompson, Julie D

2013-01-01

Understanding the effects of genetic variation on the phenotype of an individual is a major goal of biomedical research, especially for the development of diagnostics and effective therapeutic solutions. In this work, we describe the use of a recent knowledge discovery from database (KDD) approach using inductive logic programming (ILP) to automatically extract knowledge about human monogenic diseases. We extracted background knowledge from MSV3d, a database of all human missense variants mapped to 3D protein structure. In this study, we identified 8,117 mutations in 805 proteins with known three-dimensional structures that were known to be involved in human monogenic disease. Our results help to improve our understanding of the relationships between structural, functional or evolutionary features and deleterious mutations. Our inferred rules can also be applied to predict the impact of any single amino acid replacement on the function of a protein. The interpretable rules are available at http://decrypthon.igbmc.fr/kd4v/.

Neural networks with multiple general neuron models: a hybrid computational intelligence approach using Genetic Programming.

PubMed

Barton, Alan J; Valdés, Julio J; Orchard, Robert

2009-01-01

Classical neural networks are composed of neurons whose nature is determined by a certain function (the neuron model), usually pre-specified. In this paper, a type of neural network (NN-GP) is presented in which: (i) each neuron may have its own neuron model in the form of a general function, (ii) any layout (i.e network interconnection) is possible, and (iii) no bias nodes or weights are associated to the connections, neurons or layers. The general functions associated to a neuron are learned by searching a function space. They are not provided a priori, but are rather built as part of an Evolutionary Computation process based on Genetic Programming. The resulting network solutions are evaluated based on a fitness measure, which may, for example, be based on classification or regression errors. Two real-world examples are presented to illustrate the promising behaviour on classification problems via construction of a low-dimensional representation of a high-dimensional parameter space associated to the set of all network solutions.

Evolutionary Connectionism: Algorithmic Principles Underlying the Evolution of Biological Organisation in Evo-Devo, Evo-Eco and Evolutionary Transitions.

PubMed

Watson, Richard A; Mills, Rob; Buckley, C L; Kouvaris, Kostas; Jackson, Adam; Powers, Simon T; Cox, Chris; Tudge, Simon; Davies, Adam; Kounios, Loizos; Power, Daniel

2016-01-01

The mechanisms of variation, selection and inheritance, on which evolution by natural selection depends, are not fixed over evolutionary time. Current evolutionary biology is increasingly focussed on understanding how the evolution of developmental organisations modifies the distribution of phenotypic variation, the evolution of ecological relationships modifies the selective environment, and the evolution of reproductive relationships modifies the heritability of the evolutionary unit. The major transitions in evolution, in particular, involve radical changes in developmental, ecological and reproductive organisations that instantiate variation, selection and inheritance at a higher level of biological organisation. However, current evolutionary theory is poorly equipped to describe how these organisations change over evolutionary time and especially how that results in adaptive complexes at successive scales of organisation (the key problem is that evolution is self-referential, i.e. the products of evolution change the parameters of the evolutionary process). Here we first reinterpret the central open questions in these domains from a perspective that emphasises the common underlying themes. We then synthesise the findings from a developing body of work that is building a new theoretical approach to these questions by converting well-understood theory and results from models of cognitive learning. Specifically, connectionist models of memory and learning demonstrate how simple incremental mechanisms, adjusting the relationships between individually-simple components, can produce organisations that exhibit complex system-level behaviours and improve the adaptive capabilities of the system. We use the term "evolutionary connectionism" to recognise that, by functionally equivalent processes, natural selection acting on the relationships within and between evolutionary entities can result in organisations that produce complex system-level behaviours in evolutionary systems and modify the adaptive capabilities of natural selection over time. We review the evidence supporting the functional equivalences between the domains of learning and of evolution, and discuss the potential for this to resolve conceptual problems in our understanding of the evolution of developmental, ecological and reproductive organisations and, in particular, the major evolutionary transitions.

Influence of different positive emotions on persuasion processing: a functional evolutionary approach.

PubMed

Griskevicius, Vladas; Shiota, Michelle N; Neufeld, Samantha L

2010-04-01

Much research has found that positive affect facilitates increased reliance on heuristics in cognition. However, theories proposing distinct evolutionary fitness-enhancing functions for specific positive emotions also predict important differences among the consequences of different positive emotion states. Two experiments investigated how six positive emotions influenced the processing of persuasive messages. Using different methods to induce emotions and assess processing, we showed that the positive emotions of anticipatory enthusiasm, amusement, and attachment love tended to facilitate greater acceptance of weak persuasive messages (consistent with previous research), whereas the positive emotions of awe and nurturant love reduced persuasion by weak messages. In addition, a series of mediation analyses suggested that the effects distinguishing different positive emotions from a neutral control condition were best accounted for by different mediators rather than by one common mediator. These findings build upon approaches that link affective valence to certain types of processing, documenting emotion-specific effects on cognition that are consistent with functional evolutionary accounts of discrete positive emotions. Copyright 2010 APA, all rights reserved.

Science, precaution, and the politics of technological risk: converging implications in evolutionary and social scientific perspectives.

PubMed

Stirling, Andy

2008-04-01

This paper examines apparent tensions between "science-based," "precautionary," and "participatory" approaches to decision making on risk. Partly by reference to insights currently emerging in evolutionary studies, the present paper looks for ways to reconcile some of the contradictions. First, I argue that technological evolution is a much more plural and open-ended process than is conventionally supposed. Risk politics is thus implicitly as much about social choice of technological pathways as narrow issues of safety. Second, it is shown how conventional "science-based" risk assessment techniques address only limited aspects of incomplete knowledge in complex, dynamic, evolutionary processes. Together, these understandings open the door to more sophisticated, comprehensive, rational, and robust decision-making processes. Despite their own limitations, it is found that precautionary and participatory approaches help to address these needs. A concrete framework is outlined through which the synergies can be more effectively harnessed. By this means, we can hope simultaneously to improve scientific rigor and democratic legitimacy in risk governance.

Phylomemetics—Evolutionary Analysis beyond the Gene

PubMed Central

Howe, Christopher J.; Windram, Heather F.

2011-01-01

Genes are propagated by error-prone copying, and the resulting variation provides the basis for phylogenetic reconstruction of evolutionary relationships. Horizontal gene transfer may be superimposed on a tree-like evolutionary pattern, with some relationships better depicted as networks. The copying of manuscripts by scribes is very similar to the replication of genes, and phylogenetic inference programs can be used directly for reconstructing the copying history of different versions of a manuscript text. Phylogenetic methods have also been used for some time to analyse the evolution of languages and the development of physical cultural artefacts. These studies can help to answer a range of anthropological questions. We propose the adoption of the term “phylomemetics” for phylogenetic analysis of reproducing non-genetic elements. PMID:21655311

On the evolution of specialization with a mechanistic underpinning in structured metapopulations.

PubMed

Nurmi, Tuomas; Parvinen, Kalle

2008-03-01

We analyze the evolution of specialization in resource utilization in a discrete-time metapopulation model using the adaptive dynamics approach. The local dynamics in the metapopulation are based on the Beverton-Holt model with mechanistic underpinnings. The consumer faces a trade-off in the abilities to consume two resources that are spatially heterogeneously distributed to patches that are prone to local catastrophes. We explore the factors favoring the spread of generalist or specialist strategies. Increasing fecundity or decreasing catastrophe probability favors the spread of the generalist strategy and increasing environmental heterogeneity enlarges the parameter domain where the evolutionary branching is possible. When there are no catastrophes, increasing emigration diminishes the parameter domain where the evolutionary branching may occur. Otherwise, the effect of emigration on evolutionary dynamics is non-monotonous: both small and large values of emigration probability favor the spread of the specialist strategies whereas the parameter domain where evolutionary branching may occur is largest when the emigration probability has intermediate values. We compare how different forms of spatial heterogeneity and different models of local growth affect the evolutionary dynamics. We show that even small changes in the resource dynamics may have outstanding evolutionary effects to the consumers.

The evolutionary ecology of molecular replicators

PubMed Central

2016-01-01

By reasonable criteria, life on the Earth consists mainly of molecular replicators. These include viruses, transposons, transpovirons, coviruses and many more, with continuous new discoveries like Sputnik Virophage. Their study is inherently multidisciplinary, spanning microbiology, genetics, immunology and evolutionary theory, and the current view is that taking a unified approach has great power and promise. We support this with a new, unified, model of their evolutionary ecology, using contemporary evolutionary theory coupling the Price equation with game theory, studying the consequences of the molecular replicators' promiscuous use of each others' gene products for their natural history and evolutionary ecology. Even at this simple expository level, we can make a firm prediction of a new class of replicators exploiting viruses such as lentiviruses like SIVs, a family which includes HIV: these have been explicitly stated in the primary literature to be non-existent. Closely connected to this departure is the view that multicellular organism immunology is more about the management of chronic infections rather than the elimination of acute ones and new understandings emerging are changing our view of the kind of theatre we ourselves provide for the evolutionary play of molecular replicators. This study adds molecular replicators to bacteria in the emerging field of sociomicrobiology. PMID:27853598

The Generation of Variation and The Developmental Basis for Evolutionary Novelty

PubMed Central

Hallgrímsson, Benedikt; Jamniczky, Heather A.; Young, Nathan M.; Rolian, Campbell; Schmidt-Ott, Urs; Marcucio, Ralph S.

2013-01-01

Organisms exhibit an incredible diversity of form, a fact that makes the evolution of novelty seemingly self-evident. However, despite the “obvious” case for novelty, defining this concept in evolutionary terms is highly problematic, so much so that some have suggested discarding it altogether. Approaches to this problem tend to take either an adaptation or development-based perspective, but we argue here that an exclusive focus on either of these misses the original intent of the novelty concept and undermines its practical utility. We instead propose that for a feature to be novel it must have evolved both by a transition between adaptive peaks on the fitness landscape and that this transition must have overcome a previous developmental constraint. This definition focuses novelty on the explanation of apparently difficult or low probability evolutionary transitions and highlights how the integration of developmental and functional considerations is necessary to evolutionary explanation. It further reinforces that novelty is a central concern not just of evolutionary developmental biology (i.e., “evo-devo”) but of evolutionary biology more generally. We explore this definition of novelty in light of four examples that range from the obvious to subtle. PMID:22649039

Natural selection. IV. The Price equation.

PubMed

Frank, S A

2012-06-01

The Price equation partitions total evolutionary change into two components. The first component provides an abstract expression of natural selection. The second component subsumes all other evolutionary processes, including changes during transmission. The natural selection component is often used in applications. Those applications attract widespread interest for their simplicity of expression and ease of interpretation. Those same applications attract widespread criticism by dropping the second component of evolutionary change and by leaving unspecified the detailed assumptions needed for a complete study of dynamics. Controversies over approximation and dynamics have nothing to do with the Price equation itself, which is simply a mathematical equivalence relation for total evolutionary change expressed in an alternative form. Disagreements about approach have to do with the tension between the relative valuation of abstract versus concrete analyses. The Price equation's greatest value has been on the abstract side, particularly the invariance relations that illuminate the understanding of natural selection. Those abstract insights lay the foundation for applications in terms of kin selection, information theory interpretations of natural selection and partitions of causes by path analysis. I discuss recent critiques of the Price equation by Nowak and van Veelen. © 2012 The Authors. Journal of Evolutionary Biology © 2012 European Society For Evolutionary Biology.

The evolutionary ecology of molecular replicators.

PubMed

Nee, Sean

2016-08-01

By reasonable criteria, life on the Earth consists mainly of molecular replicators. These include viruses, transposons, transpovirons, coviruses and many more, with continuous new discoveries like Sputnik Virophage. Their study is inherently multidisciplinary, spanning microbiology, genetics, immunology and evolutionary theory, and the current view is that taking a unified approach has great power and promise. We support this with a new, unified, model of their evolutionary ecology, using contemporary evolutionary theory coupling the Price equation with game theory, studying the consequences of the molecular replicators' promiscuous use of each others' gene products for their natural history and evolutionary ecology. Even at this simple expository level, we can make a firm prediction of a new class of replicators exploiting viruses such as lentiviruses like SIVs, a family which includes HIV: these have been explicitly stated in the primary literature to be non-existent. Closely connected to this departure is the view that multicellular organism immunology is more about the management of chronic infections rather than the elimination of acute ones and new understandings emerging are changing our view of the kind of theatre we ourselves provide for the evolutionary play of molecular replicators. This study adds molecular replicators to bacteria in the emerging field of sociomicrobiology.

Evolutionary genetics of maternal effects

PubMed Central

Wolf, Jason B.; Wade, Michael J.

2016-01-01

Maternal genetic effects (MGEs), where genes expressed by mothers affect the phenotype of their offspring, are important sources of phenotypic diversity in a myriad of organisms. We use a single‐locus model to examine how MGEs contribute patterns of heritable and nonheritable variation and influence evolutionary dynamics in randomly mating and inbreeding populations. We elucidate the influence of MGEs by examining the offspring genotype‐phenotype relationship, which determines how MGEs affect evolutionary dynamics in response to selection on offspring phenotypes. This approach reveals important results that are not apparent from classic quantitative genetic treatments of MGEs. We show that additive and dominance MGEs make different contributions to evolutionary dynamics and patterns of variation, which are differentially affected by inbreeding. Dominance MGEs make the offspring genotype‐phenotype relationship frequency dependent, resulting in the appearance of negative frequency‐dependent selection, while additive MGEs contribute a component of parent‐of‐origin dependent variation. Inbreeding amplifies the contribution of MGEs to the additive genetic variance and, therefore enhances their evolutionary response. Considering evolutionary dynamics of allele frequency change on an adaptive landscape, we show that this landscape differs from the mean fitness surface, and therefore, under some condition, fitness peaks can exist but not be “available” to the evolving population. PMID:26969266

Computability, Gödel's incompleteness theorem, and an inherent limit on the predictability of evolution

PubMed Central

Day, Troy

2012-01-01

The process of evolutionary diversification unfolds in a vast genotypic space of potential outcomes. During the past century, there have been remarkable advances in the development of theory for this diversification, and the theory's success rests, in part, on the scope of its applicability. A great deal of this theory focuses on a relatively small subset of the space of potential genotypes, chosen largely based on historical or contemporary patterns, and then predicts the evolutionary dynamics within this pre-defined set. To what extent can such an approach be pushed to a broader perspective that accounts for the potential open-endedness of evolutionary diversification? There have been a number of significant theoretical developments along these lines but the question of how far such theory can be pushed has not been addressed. Here a theorem is proven demonstrating that, because of the digital nature of inheritance, there are inherent limits on the kinds of questions that can be answered using such an approach. In particular, even in extremely simple evolutionary systems, a complete theory accounting for the potential open-endedness of evolution is unattainable unless evolution is progressive. The theorem is closely related to Gödel's incompleteness theorem, and to the halting problem from computability theory. PMID:21849390

An integrative approach to understanding bird origins.

PubMed

Xu, Xing; Zhou, Zhonghe; Dudley, Robert; Mackem, Susan; Chuong, Cheng-Ming; Erickson, Gregory M; Varricchio, David J

2014-12-12

Recent discoveries of spectacular dinosaur fossils overwhelmingly support the hypothesis that birds are descended from maniraptoran theropod dinosaurs, and furthermore, demonstrate that distinctive bird characteristics such as feathers, flight, endothermic physiology, unique strategies for reproduction and growth, and a novel pulmonary system originated among Mesozoic terrestrial dinosaurs. The transition from ground-living to flight-capable theropod dinosaurs now probably represents one of the best-documented major evolutionary transitions in life history. Recent studies in developmental biology and other disciplines provide additional insights into how bird characteristics originated and evolved. The iconic features of extant birds for the most part evolved in a gradual and stepwise fashion throughout archosaur evolution. However, new data also highlight occasional bursts of morphological novelty at certain stages particularly close to the origin of birds and an unavoidable complex, mosaic evolutionary distribution of major bird characteristics on the theropod tree. Research into bird origins provides a premier example of how paleontological and neontological data can interact to reveal the complexity of major innovations, to answer key evolutionary questions, and to lead to new research directions. A better understanding of bird origins requires multifaceted and integrative approaches, yet fossils necessarily provide the final test of any evolutionary model. Copyright © 2014, American Association for the Advancement of Science.

An evolutionary algorithm for large traveling salesman problems.

PubMed

Tsai, Huai-Kuang; Yang, Jinn-Moon; Tsai, Yuan-Fang; Kao, Cheng-Yan

2004-08-01

This work proposes an evolutionary algorithm, called the heterogeneous selection evolutionary algorithm (HeSEA), for solving large traveling salesman problems (TSP). The strengths and limitations of numerous well-known genetic operators are first analyzed, along with local search methods for TSPs from their solution qualities and mechanisms for preserving and adding edges. Based on this analysis, a new approach, HeSEA is proposed which integrates edge assembly crossover (EAX) and Lin-Kernighan (LK) local search, through family competition and heterogeneous pairing selection. This study demonstrates experimentally that EAX and LK can compensate for each other's disadvantages. Family competition and heterogeneous pairing selections are used to maintain the diversity of the population, which is especially useful for evolutionary algorithms in solving large TSPs. The proposed method was evaluated on 16 well-known TSPs in which the numbers of cities range from 318 to 13509. Experimental results indicate that HeSEA performs well and is very competitive with other approaches. The proposed method can determine the optimum path when the number of cities is under 10,000 and the mean solution quality is within 0.0074% above the optimum for each test problem. These findings imply that the proposed method can find tours robustly with a fixed small population and a limited family competition length in reasonable time, when used to solve large TSPs.

Comparative modeling of coevolution in communities of unicellular organisms: adaptability and biodiversity.

PubMed

Lashin, Sergey A; Suslov, Valentin V; Matushkin, Yuri G

2010-06-01

We propose an original program "Evolutionary constructor" that is capable of computationally efficient modeling of both population-genetic and ecological problems, combining these directions in one model of required detail level. We also present results of comparative modeling of stability, adaptability and biodiversity dynamics in populations of unicellular haploid organisms which form symbiotic ecosystems. The advantages and disadvantages of two evolutionary strategies of biota formation--a few generalists' taxa-based biota formation and biodiversity-based biota formation--are discussed.

SUNPLIN: Simulation with Uncertainty for Phylogenetic Investigations

PubMed Central

2013-01-01

Background Phylogenetic comparative analyses usually rely on a single consensus phylogenetic tree in order to study evolutionary processes. However, most phylogenetic trees are incomplete with regard to species sampling, which may critically compromise analyses. Some approaches have been proposed to integrate non-molecular phylogenetic information into incomplete molecular phylogenies. An expanded tree approach consists of adding missing species to random locations within their clade. The information contained in the topology of the resulting expanded trees can be captured by the pairwise phylogenetic distance between species and stored in a matrix for further statistical analysis. Thus, the random expansion and processing of multiple phylogenetic trees can be used to estimate the phylogenetic uncertainty through a simulation procedure. Because of the computational burden required, unless this procedure is efficiently implemented, the analyses are of limited applicability. Results In this paper, we present efficient algorithms and implementations for randomly expanding and processing phylogenetic trees so that simulations involved in comparative phylogenetic analysis with uncertainty can be conducted in a reasonable time. We propose algorithms for both randomly expanding trees and calculating distance matrices. We made available the source code, which was written in the C++ language. The code may be used as a standalone program or as a shared object in the R system. The software can also be used as a web service through the link: http://purl.oclc.org/NET/sunplin/. Conclusion We compare our implementations to similar solutions and show that significant performance gains can be obtained. Our results open up the possibility of accounting for phylogenetic uncertainty in evolutionary and ecological analyses of large datasets. PMID:24229408

SUNPLIN: simulation with uncertainty for phylogenetic investigations.

PubMed

Martins, Wellington S; Carmo, Welton C; Longo, Humberto J; Rosa, Thierson C; Rangel, Thiago F

2013-11-15

Phylogenetic comparative analyses usually rely on a single consensus phylogenetic tree in order to study evolutionary processes. However, most phylogenetic trees are incomplete with regard to species sampling, which may critically compromise analyses. Some approaches have been proposed to integrate non-molecular phylogenetic information into incomplete molecular phylogenies. An expanded tree approach consists of adding missing species to random locations within their clade. The information contained in the topology of the resulting expanded trees can be captured by the pairwise phylogenetic distance between species and stored in a matrix for further statistical analysis. Thus, the random expansion and processing of multiple phylogenetic trees can be used to estimate the phylogenetic uncertainty through a simulation procedure. Because of the computational burden required, unless this procedure is efficiently implemented, the analyses are of limited applicability. In this paper, we present efficient algorithms and implementations for randomly expanding and processing phylogenetic trees so that simulations involved in comparative phylogenetic analysis with uncertainty can be conducted in a reasonable time. We propose algorithms for both randomly expanding trees and calculating distance matrices. We made available the source code, which was written in the C++ language. The code may be used as a standalone program or as a shared object in the R system. The software can also be used as a web service through the link: http://purl.oclc.org/NET/sunplin/. We compare our implementations to similar solutions and show that significant performance gains can be obtained. Our results open up the possibility of accounting for phylogenetic uncertainty in evolutionary and ecological analyses of large datasets.

Ecological speciation in the tropics: insights from comparative genetic studies in Amazonia

PubMed Central

Beheregaray, Luciano B.; Cooke, Georgina M.; Chao, Ning L.; Landguth, Erin L.

2015-01-01

Evolution creates and sustains biodiversity via adaptive changes in ecologically relevant traits. Ecologically mediated selection contributes to genetic divergence both in the presence or absence of geographic isolation between populations, and is considered an important driver of speciation. Indeed, the genetics of ecological speciation is becoming increasingly studied across a variety of taxa and environments. In this paper we review the literature of ecological speciation in the tropics. We report on low research productivity in tropical ecosystems and discuss reasons accounting for the rarity of studies. We argue for research programs that simultaneously address biogeographical and taxonomic questions in the tropics, while effectively assessing relationships between reproductive isolation and ecological divergence. To contribute toward this goal, we propose a new framework for ecological speciation that integrates information from phylogenetics, phylogeography, population genomics, and simulations in evolutionary landscape genetics (ELG). We introduce components of the framework, describe ELG simulations (a largely unexplored approach in ecological speciation), and discuss design and experimental feasibility within the context of tropical research. We then use published genetic datasets from populations of five codistributed Amazonian fish species to assess the performance of the framework in studies of tropical speciation. We suggest that these approaches can assist in distinguishing the relative contribution of natural selection from biogeographic history in the origin of biodiversity, even in complex ecosystems such as Amazonia. We also discuss on how to assess ecological speciation using ELG simulations that include selection. These integrative frameworks have considerable potential to enhance conservation management in biodiversity rich ecosystems and to complement historical biogeographic and evolutionary studies of tropical biotas. PMID:25653668

Simple versus complex models of trait evolution and stasis as a response to environmental change

NASA Astrophysics Data System (ADS)

Hunt, Gene; Hopkins, Melanie J.; Lidgard, Scott

2015-04-01

Previous analyses of evolutionary patterns, or modes, in fossil lineages have focused overwhelmingly on three simple models: stasis, random walks, and directional evolution. Here we use likelihood methods to fit an expanded set of evolutionary models to a large compilation of ancestor-descendant series of populations from the fossil record. In addition to the standard three models, we assess more complex models with punctuations and shifts from one evolutionary mode to another. As in previous studies, we find that stasis is common in the fossil record, as is a strict version of stasis that entails no real evolutionary changes. Incidence of directional evolution is relatively low (13%), but higher than in previous studies because our analytical approach can more sensitively detect noisy trends. Complex evolutionary models are often favored, overwhelmingly so for sequences comprising many samples. This finding is consistent with evolutionary dynamics that are, in reality, more complex than any of the models we consider. Furthermore, the timing of shifts in evolutionary dynamics varies among traits measured from the same series. Finally, we use our empirical collection of evolutionary sequences and a long and highly resolved proxy for global climate to inform simulations in which traits adaptively track temperature changes over time. When realistically calibrated, we find that this simple model can reproduce important aspects of our paleontological results. We conclude that observed paleontological patterns, including the prevalence of stasis, need not be inconsistent with adaptive evolution, even in the face of unstable physical environments.

Inferring the mode of origin of polyploid species from next-generation sequence data.

PubMed

Roux, Camille; Pannell, John R

2015-03-01

Many eukaryote organisms are polyploid. However, despite their importance, evolutionary inference of polyploid origins and modes of inheritance has been limited by a need for analyses of allele segregation at multiple loci using crosses. The increasing availability of sequence data for nonmodel species now allows the application of established approaches for the analysis of genomic data in polyploids. Here, we ask whether approximate Bayesian computation (ABC), applied to realistic traditional and next-generation sequence data, allows correct inference of the evolutionary and demographic history of polyploids. Using simulations, we evaluate the robustness of evolutionary inference by ABC for tetraploid species as a function of the number of individuals and loci sampled, and the presence or absence of an outgroup. We find that ABC adequately retrieves the recent evolutionary history of polyploid species on the basis of both old and new sequencing technologies. The application of ABC to sequence data from diploid and polyploid species of the plant genus Capsella confirms its utility. Our analysis strongly supports an allopolyploid origin of C. bursa-pastoris about 80 000 years ago. This conclusion runs contrary to previous findings based on the same data set but using an alternative approach and is in agreement with recent findings based on whole-genome sequencing. Our results indicate that ABC is a promising and powerful method for revealing the evolution of polyploid species, without the need to attribute alleles to a homeologous chromosome pair. The approach can readily be extended to more complex scenarios involving higher ploidy levels. © 2015 John Wiley & Sons Ltd.

How hardwired is human behavior?

PubMed

Nicholson, N

1998-01-01

Time and time again managers have tried to eliminate hierarchies, politics, and interorganizational rivalry--but to no avail. Why? Evolutionary psychologists would say that they are working against nature--emotional and behavioral "hardwiring" that is the legacy of our Stone Age ancestors. In this evolutionary psychology primer for executives, Nigel Nicholson explores many of the Science's central tenets. Of course, evolutionary psychology is still an emerging discipline, and its strong connection with the theory of natural selection has sparked significant controversy. But, as Nicholson suggests, evolutionary psychology is now well established enough that its insights into human instinct will prove illuminating to anyone seeking to understand why people act the way they do in organizational settings. Take gossip. According to evolutionary psychology, our Stone Age ancestors needed this skill to survive the socially unpredictable conditions of the Savannah Plain. Thus, over time, the propensity to gossip became part of our mental programming. Executives trying to eradicate gossip at work might as well try to change their employees' musical tastes. Better to put one's energy into making sure the "rumor mill" avoids dishonesty or unkindness as much as possible. Evolutionary psychology also explores the dynamics of the human group. Clans on the Savannah Plain, for example, appear to have had no more than 150 members. The message for managers? People will likely be most effective in small organizational units. As every executive knows, it pays to be an insightful student of human nature. Evolutionary psychology adds another important chapter to consider.

Clinical software development for the Web: lessons learned from the BOADICEA project

PubMed Central

2012-01-01

Background In the past 20 years, society has witnessed the following landmark scientific advances: (i) the sequencing of the human genome, (ii) the distribution of software by the open source movement, and (iii) the invention of the World Wide Web. Together, these advances have provided a new impetus for clinical software development: developers now translate the products of human genomic research into clinical software tools; they use open-source programs to build them; and they use the Web to deliver them. Whilst this open-source component-based approach has undoubtedly made clinical software development easier, clinical software projects are still hampered by problems that traditionally accompany the software process. This study describes the development of the BOADICEA Web Application, a computer program used by clinical geneticists to assess risks to patients with a family history of breast and ovarian cancer. The key challenge of the BOADICEA Web Application project was to deliver a program that was safe, secure and easy for healthcare professionals to use. We focus on the software process, problems faced, and lessons learned. Our key objectives are: (i) to highlight key clinical software development issues; (ii) to demonstrate how software engineering tools and techniques can facilitate clinical software development for the benefit of individuals who lack software engineering expertise; and (iii) to provide a clinical software development case report that can be used as a basis for discussion at the start of future projects. Results We developed the BOADICEA Web Application using an evolutionary software process. Our approach to Web implementation was conservative and we used conventional software engineering tools and techniques. The principal software development activities were: requirements, design, implementation, testing, documentation and maintenance. The BOADICEA Web Application has now been widely adopted by clinical geneticists and researchers. BOADICEA Web Application version 1 was released for general use in November 2007. By May 2010, we had > 1200 registered users based in the UK, USA, Canada, South America, Europe, Africa, Middle East, SE Asia, Australia and New Zealand. Conclusions We found that an evolutionary software process was effective when we developed the BOADICEA Web Application. The key clinical software development issues identified during the BOADICEA Web Application project were: software reliability, Web security, clinical data protection and user feedback. PMID:22490389

Clinical software development for the Web: lessons learned from the BOADICEA project.

PubMed

Cunningham, Alex P; Antoniou, Antonis C; Easton, Douglas F

2012-04-10

In the past 20 years, society has witnessed the following landmark scientific advances: (i) the sequencing of the human genome, (ii) the distribution of software by the open source movement, and (iii) the invention of the World Wide Web. Together, these advances have provided a new impetus for clinical software development: developers now translate the products of human genomic research into clinical software tools; they use open-source programs to build them; and they use the Web to deliver them. Whilst this open-source component-based approach has undoubtedly made clinical software development easier, clinical software projects are still hampered by problems that traditionally accompany the software process. This study describes the development of the BOADICEA Web Application, a computer program used by clinical geneticists to assess risks to patients with a family history of breast and ovarian cancer. The key challenge of the BOADICEA Web Application project was to deliver a program that was safe, secure and easy for healthcare professionals to use. We focus on the software process, problems faced, and lessons learned. Our key objectives are: (i) to highlight key clinical software development issues; (ii) to demonstrate how software engineering tools and techniques can facilitate clinical software development for the benefit of individuals who lack software engineering expertise; and (iii) to provide a clinical software development case report that can be used as a basis for discussion at the start of future projects. We developed the BOADICEA Web Application using an evolutionary software process. Our approach to Web implementation was conservative and we used conventional software engineering tools and techniques. The principal software development activities were: requirements, design, implementation, testing, documentation and maintenance. The BOADICEA Web Application has now been widely adopted by clinical geneticists and researchers. BOADICEA Web Application version 1 was released for general use in November 2007. By May 2010, we had > 1200 registered users based in the UK, USA, Canada, South America, Europe, Africa, Middle East, SE Asia, Australia and New Zealand. We found that an evolutionary software process was effective when we developed the BOADICEA Web Application. The key clinical software development issues identified during the BOADICEA Web Application project were: software reliability, Web security, clinical data protection and user feedback.

Combining analysis with optimization at Langley Research Center. An evolutionary process

NASA Technical Reports Server (NTRS)

Rogers, J. L., Jr.

1982-01-01

The evolutionary process of combining analysis and optimization codes was traced with a view toward providing insight into the long term goal of developing the methodology for an integrated, multidisciplinary software system for the concurrent analysis and optimization of aerospace structures. It was traced along the lines of strength sizing, concurrent strength and flutter sizing, and general optimization to define a near-term goal for combining analysis and optimization codes. Development of a modular software system combining general-purpose, state-of-the-art, production-level analysis computer programs for structures, aerodynamics, and aeroelasticity with a state-of-the-art optimization program is required. Incorporation of a modular and flexible structural optimization software system into a state-of-the-art finite element analysis computer program will facilitate this effort. This effort results in the software system used that is controlled with a special-purpose language, communicates with a data management system, and is easily modified for adding new programs and capabilities. A 337 degree-of-freedom finite element model is used in verifying the accuracy of this system.

A program to compute the soft Robinson-Foulds distance between phylogenetic networks.

PubMed

Lu, Bingxin; Zhang, Louxin; Leong, Hon Wai

2017-03-14

Over the past two decades, phylogenetic networks have been studied to model reticulate evolutionary events. The relationships among phylogenetic networks, phylogenetic trees and clusters serve as the basis for reconstruction and comparison of phylogenetic networks. To understand these relationships, two problems are raised: the tree containment problem, which asks whether a phylogenetic tree is displayed in a phylogenetic network, and the cluster containment problem, which asks whether a cluster is represented at a node in a phylogenetic network. Both the problems are NP-complete. A fast exponential-time algorithm for the cluster containment problem on arbitrary networks is developed and implemented in C. The resulting program is further extended into a computer program for fast computation of the Soft Robinson-Foulds distance between phylogenetic networks. Two computer programs are developed for facilitating reconstruction and validation of phylogenetic network models in evolutionary and comparative genomics. Our simulation tests indicated that they are fast enough for use in practice. Additionally, the distribution of the Soft Robinson-Foulds distance between phylogenetic networks is demonstrated to be unlikely normal by our simulation data.

Doves and hawks in economics revisited: An evolutionary quantum game theory based analysis of financial crises

NASA Astrophysics Data System (ADS)

Hanauske, Matthias; Kunz, Jennifer; Bernius, Steffen; König, Wolfgang

2010-11-01

The last financial and economic crisis demonstrated the dysfunctional long-term effects of aggressive behaviour in financial markets. Yet, evolutionary game theory predicts that under the condition of strategic dependence a certain degree of aggressive behaviour remains within a given population of agents. However, as a consequence of the financial crisis, it would be desirable to change the “rules of the game” in a way that prevents the occurrence of any aggressive behaviour and thereby also the danger of market crashes. The paper picks up this aspect. Through the extension of the well-known hawk-dove game by a quantum approach, we can show that dependent on entanglement, evolutionary stable strategies also can emerge, which are not predicted by the classical evolutionary game theory and where the total economic population uses a non-aggressive quantum strategy.

Evolutionary engineering for industrial microbiology.

PubMed

Vanee, Niti; Fisher, Adam B; Fong, Stephen S

2012-01-01

Superficially, evolutionary engineering is a paradoxical field that balances competing interests. In natural settings, evolution iteratively selects and enriches subpopulations that are best adapted to a particular ecological niche using random processes such as genetic mutation. In engineering desired approaches utilize rational prospective design to address targeted problems. When considering details of evolutionary and engineering processes, more commonality can be found. Engineering relies on detailed knowledge of the problem parameters and design properties in order to predict design outcomes that would be an optimized solution. When detailed knowledge of a system is lacking, engineers often employ algorithmic search strategies to identify empirical solutions. Evolution epitomizes this iterative optimization by continuously diversifying design options from a parental design, and then selecting the progeny designs that represent satisfactory solutions. In this chapter, the technique of applying the natural principles of evolution to engineer microbes for industrial applications is discussed to highlight the challenges and principles of evolutionary engineering.

Evolutionary genomics and HIV restriction factors.

PubMed

Pyndiah, Nitisha; Telenti, Amalio; Rausell, Antonio

2015-03-01

To provide updated insights into innate antiviral immunity and highlight prototypical evolutionary features of well characterized HIV restriction factors. Recently, a new HIV restriction factor, Myxovirus resistance 2, has been discovered and the region/residue responsible for its activity identified using an evolutionary approach. Furthermore, IFI16, an innate immunity protein known to sense several viruses, has been shown to contribute to the defense to HIV-1 by causing cell death upon sensing HIV-1 DNA. Restriction factors against HIV show characteristic signatures of positive selection. Different patterns of accelerated sequence evolution can distinguish antiviral strategies--offense or defence--as well as the level of specificity of the antiviral properties. Sequence analysis of primate orthologs of restriction factors serves to localize functional domains and sites responsible for antiviral action. We use recent discoveries to illustrate how evolutionary genomic analyses help identify new antiviral genes and their mechanisms of action.

Under pressure: evolutionary engineering of yeast strains for improved performance in fuels and chemicals production.

PubMed

Mans, Robert; Daran, Jean-Marc G; Pronk, Jack T

2018-04-01

Evolutionary engineering, which uses laboratory evolution to select for industrially relevant traits, is a popular strategy in the development of high-performing yeast strains for industrial production of fuels and chemicals. By integrating whole-genome sequencing, bioinformatics, classical genetics and genome-editing techniques, evolutionary engineering has also become a powerful approach for identification and reverse engineering of molecular mechanisms that underlie industrially relevant traits. New techniques enable acceleration of in vivo mutation rates, both across yeast genomes and at specific loci. Recent studies indicate that phenotypic trade-offs, which are often observed after evolution under constant conditions, can be mitigated by using dynamic cultivation regimes. Advances in research on synthetic regulatory circuits offer exciting possibilities to extend the applicability of evolutionary engineering to products of yeasts whose synthesis requires a net input of cellular energy. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Selection on Network Dynamics Drives Differential Rates of Protein Domain Evolution

PubMed Central

Mannakee, Brian K.; Gutenkunst, Ryan N.

2016-01-01

The long-held principle that functionally important proteins evolve slowly has recently been challenged by studies in mice and yeast showing that the severity of a protein knockout only weakly predicts that protein’s rate of evolution. However, the relevance of these studies to evolutionary changes within proteins is unknown, because amino acid substitutions, unlike knockouts, often only slightly perturb protein activity. To quantify the phenotypic effect of small biochemical perturbations, we developed an approach to use computational systems biology models to measure the influence of individual reaction rate constants on network dynamics. We show that this dynamical influence is predictive of protein domain evolutionary rate within networks in vertebrates and yeast, even after controlling for expression level and breadth, network topology, and knockout effect. Thus, our results not only demonstrate the importance of protein domain function in determining evolutionary rate, but also the power of systems biology modeling to uncover unanticipated evolutionary forces. PMID:27380265

Incorporating evolutionary processes into population viability models.

PubMed

Pierson, Jennifer C; Beissinger, Steven R; Bragg, Jason G; Coates, David J; Oostermeijer, J Gerard B; Sunnucks, Paul; Schumaker, Nathan H; Trotter, Meredith V; Young, Andrew G

2015-06-01

We examined how ecological and evolutionary (eco-evo) processes in population dynamics could be better integrated into population viability analysis (PVA). Complementary advances in computation and population genomics can be combined into an eco-evo PVA to offer powerful new approaches to understand the influence of evolutionary processes on population persistence. We developed the mechanistic basis of an eco-evo PVA using individual-based models with individual-level genotype tracking and dynamic genotype-phenotype mapping to model emergent population-level effects, such as local adaptation and genetic rescue. We then outline how genomics can allow or improve parameter estimation for PVA models by providing genotypic information at large numbers of loci for neutral and functional genome regions. As climate change and other threatening processes increase in rate and scale, eco-evo PVAs will become essential research tools to evaluate the effects of adaptive potential, evolutionary rescue, and locally adapted traits on persistence. © 2014 Society for Conservation Biology.

An Effective Hybrid Evolutionary Algorithm for Solving the Numerical Optimization Problems

NASA Astrophysics Data System (ADS)

Qian, Xiaohong; Wang, Xumei; Su, Yonghong; He, Liu

2018-04-01

There are many different algorithms for solving complex optimization problems. Each algorithm has been applied successfully in solving some optimization problems, but not efficiently in other problems. In this paper the Cauchy mutation and the multi-parent hybrid operator are combined to propose a hybrid evolutionary algorithm based on the communication (Mixed Evolutionary Algorithm based on Communication), hereinafter referred to as CMEA. The basic idea of the CMEA algorithm is that the initial population is divided into two subpopulations. Cauchy mutation operators and multiple paternal crossover operators are used to perform two subpopulations parallelly to evolve recursively until the downtime conditions are met. While subpopulation is reorganized, the individual is exchanged together with information. The algorithm flow is given and the performance of the algorithm is compared using a number of standard test functions. Simulation results have shown that this algorithm converges significantly faster than FEP (Fast Evolutionary Programming) algorithm, has good performance in global convergence and stability and is superior to other compared algorithms.

The Growth of Developmental Thought: Implications for a New Evolutionary Psychology

PubMed Central

Lickliter, Robert

2009-01-01

Evolution has come to be increasingly discussed in terms of changes in developmental processes rather than simply in terms of changes in gene frequencies. This shift is based in large part on the recognition that since all phenotypic traits arise during ontogeny as products of individual development, a primary basis for evolutionary change must be variations in the patterns and processes of development. Further, the products of development are epigenetic, not just genetic, and this is the case even when considering the evolutionary process. These insights have led investigators to reconsider the established notion of genes as the primary cause of development, opening the door to research programs focused on identifying how genetic and non-genetic factors coact to guide and constrain the process of development and its outcomes. I explore this growth of developmental thought and its implications for the achievement of a unified theory of heredity, development, and evolution and consider its implications for the realization of a new, developmentally-based evolutionary psychology. PMID:19956346

Evolutionary Algorithms for Boolean Functions in Diverse Domains of Cryptography.

PubMed

Picek, Stjepan; Carlet, Claude; Guilley, Sylvain; Miller, Julian F; Jakobovic, Domagoj

2016-01-01

The role of Boolean functions is prominent in several areas including cryptography, sequences, and coding theory. Therefore, various methods for the construction of Boolean functions with desired properties are of direct interest. New motivations on the role of Boolean functions in cryptography with attendant new properties have emerged over the years. There are still many combinations of design criteria left unexplored and in this matter evolutionary computation can play a distinct role. This article concentrates on two scenarios for the use of Boolean functions in cryptography. The first uses Boolean functions as the source of the nonlinearity in filter and combiner generators. Although relatively well explored using evolutionary algorithms, it still presents an interesting goal in terms of the practical sizes of Boolean functions. The second scenario appeared rather recently where the objective is to find Boolean functions that have various orders of the correlation immunity and minimal Hamming weight. In both these scenarios we see that evolutionary algorithms are able to find high-quality solutions where genetic programming performs the best.

A new evolutionary system for evolving artificial neural networks.

PubMed

Yao, X; Liu, Y

1997-01-01

This paper presents a new evolutionary system, i.e., EPNet, for evolving artificial neural networks (ANNs). The evolutionary algorithm used in EPNet is based on Fogel's evolutionary programming (EP). Unlike most previous studies on evolving ANN's, this paper puts its emphasis on evolving ANN's behaviors. Five mutation operators proposed in EPNet reflect such an emphasis on evolving behaviors. Close behavioral links between parents and their offspring are maintained by various mutations, such as partial training and node splitting. EPNet evolves ANN's architectures and connection weights (including biases) simultaneously in order to reduce the noise in fitness evaluation. The parsimony of evolved ANN's is encouraged by preferring node/connection deletion to addition. EPNet has been tested on a number of benchmark problems in machine learning and ANNs, such as the parity problem, the medical diagnosis problems, the Australian credit card assessment problem, and the Mackey-Glass time series prediction problem. The experimental results show that EPNet can produce very compact ANNs with good generalization ability in comparison with other algorithms.

Mission building blocks for outer solar system exploration.

NASA Technical Reports Server (NTRS)

Herman, D.; Tarver, P.; Moore, J.

1973-01-01

Description of the technological building blocks required for exploring the outer planets with maximum scientific yields under stringent resource constraints. Two generic spacecraft types are considered: the Mariner and the Pioneer. Following a discussion of the outer planet mission constraints, the evolutionary development of spacecraft, probes, and propulsion building blocks is presented. Then, program genealogies are shown for Pioneer and Mariner missions and advanced propulsion systems to illustrate the soundness of a program based on spacecraft modification rather than on the development of new spacecraft for each mission. It is argued that, for minimum costs, technological advancement should occur in an evolutionary manner from mission to mission. While this strategy is likely to result in compromises on specific missions, the realization of the overall objectives calls for an advance commitment to the entire mission series.

Multidisciplinary Approaches in Evolutionary Linguistics

ERIC Educational Resources Information Center

Gong, Tao; Shuai, Lan; Wu, Yicheng

2013-01-01

Studying language evolution has become resurgent in modern scientific research. In this revival field, approaches from a number of disciplines other than linguistics, including (paleo)anthropology and archaeology, animal behaviors, genetics, neuroscience, computer simulation, and psychological experimentation, have been adopted, and a wide scope…

Genome Alignment Spanning Major Poaceae Lineages Reveals Heterogeneous Evolutionary Rates and Alters Inferred Dates for Key Evolutionary Events.

PubMed

Wang, Xiyin; Wang, Jingpeng; Jin, Dianchuan; Guo, Hui; Lee, Tae-Ho; Liu, Tao; Paterson, Andrew H

2015-06-01

Multiple comparisons among genomes can clarify their evolution, speciation, and functional innovations. To date, the genome sequences of eight grasses representing the most economically important Poaceae (grass) clades have been published, and their genomic-level comparison is an essential foundation for evolutionary, functional, and translational research. Using a formal and conservative approach, we aligned these genomes. Direct comparison of paralogous gene pairs all duplicated simultaneously reveal striking variation in evolutionary rates among whole genomes, with nucleotide substitution slowest in rice and up to 48% faster in other grasses, adding a new dimension to the value of rice as a grass model. We reconstructed ancestral genome contents for major evolutionary nodes, potentially contributing to understanding the divergence and speciation of grasses. Recent fossil evidence suggests revisions of the estimated dates of key evolutionary events, implying that the pan-grass polyploidization occurred ∼96 million years ago and could not be related to the Cretaceous-Tertiary mass extinction as previously inferred. Adjusted dating to reflect both updated fossil evidence and lineage-specific evolutionary rates suggested that maize subgenome divergence and maize-sorghum divergence were virtually simultaneous, a coincidence that would be explained if polyploidization directly contributed to speciation. This work lays a solid foundation for Poaceae translational genomics. Copyright © 2015 The Author. Published by Elsevier Inc. All rights reserved.

Modeling Open Architecture and Evolutionary Acquisition: Implementation Lessons from the ARCI Program for the Rapid Capability Insertion Process

DTIC Science & Technology

2009-04-22

Implementation Issues Another RCIP implementation risk is program management burnout . The ACRI program manager specifically identified the potential...of burnout in his program management team due to the repeated, intense Integration phases. To investigate the possibility and severity of this risk to...the ACRI simulation. This suggests that the burnout risk will be larger for RCIP than it was for ACRI. Successfully implementing a sustainable RCIP

SWPhylo - A Novel Tool for Phylogenomic Inferences by Comparison of Oligonucleotide Patterns and Integration of Genome-Based and Gene-Based Phylogenetic Trees.

PubMed

Yu, Xiaoyu; Reva, Oleg N

2018-01-01

Modern phylogenetic studies may benefit from the analysis of complete genome sequences of various microorganisms. Evolutionary inferences based on genome-scale analysis are believed to be more accurate than the gene-based alternative. However, the computational complexity of current phylogenomic procedures, inappropriateness of standard phylogenetic tools to process genome-wide data, and lack of reliable substitution models which correlates with alignment-free phylogenomic approaches deter microbiologists from using these opportunities. For example, the super-matrix and super-tree approaches of phylogenomics use multiple integrated genomic loci or individual gene-based trees to infer an overall consensus tree. However, these approaches potentially multiply errors of gene annotation and sequence alignment not mentioning the computational complexity and laboriousness of the methods. In this article, we demonstrate that the annotation- and alignment-free comparison of genome-wide tetranucleotide frequencies, termed oligonucleotide usage patterns (OUPs), allowed a fast and reliable inference of phylogenetic trees. These were congruent to the corresponding whole genome super-matrix trees in terms of tree topology when compared with other known approaches including 16S ribosomal RNA and GyrA protein sequence comparison, complete genome-based MAUVE, and CVTree methods. A Web-based program to perform the alignment-free OUP-based phylogenomic inferences was implemented at http://swphylo.bi.up.ac.za/. Applicability of the tool was tested on different taxa from subspecies to intergeneric levels. Distinguishing between closely related taxonomic units may be enforced by providing the program with alignments of marker protein sequences, eg, GyrA.

SWPhylo – A Novel Tool for Phylogenomic Inferences by Comparison of Oligonucleotide Patterns and Integration of Genome-Based and Gene-Based Phylogenetic Trees

PubMed Central

Yu, Xiaoyu; Reva, Oleg N

2018-01-01

Modern phylogenetic studies may benefit from the analysis of complete genome sequences of various microorganisms. Evolutionary inferences based on genome-scale analysis are believed to be more accurate than the gene-based alternative. However, the computational complexity of current phylogenomic procedures, inappropriateness of standard phylogenetic tools to process genome-wide data, and lack of reliable substitution models which correlates with alignment-free phylogenomic approaches deter microbiologists from using these opportunities. For example, the super-matrix and super-tree approaches of phylogenomics use multiple integrated genomic loci or individual gene-based trees to infer an overall consensus tree. However, these approaches potentially multiply errors of gene annotation and sequence alignment not mentioning the computational complexity and laboriousness of the methods. In this article, we demonstrate that the annotation- and alignment-free comparison of genome-wide tetranucleotide frequencies, termed oligonucleotide usage patterns (OUPs), allowed a fast and reliable inference of phylogenetic trees. These were congruent to the corresponding whole genome super-matrix trees in terms of tree topology when compared with other known approaches including 16S ribosomal RNA and GyrA protein sequence comparison, complete genome-based MAUVE, and CVTree methods. A Web-based program to perform the alignment-free OUP-based phylogenomic inferences was implemented at http://swphylo.bi.up.ac.za/. Applicability of the tool was tested on different taxa from subspecies to intergeneric levels. Distinguishing between closely related taxonomic units may be enforced by providing the program with alignments of marker protein sequences, eg, GyrA. PMID:29511354

The Ancient Evolutionary History of Polyomaviruses

PubMed Central

Buck, Christopher B.; Van Doorslaer, Koenraad; Peretti, Alberto; Geoghegan, Eileen M.; Tisza, Michael J.; An, Ping; Katz, Joshua P.; Pipas, James M.; McBride, Alison A.; Camus, Alvin C.; McDermott, Alexa J.; Dill, Jennifer A.; Delwart, Eric; Ng, Terry F. F.; Farkas, Kata; Austin, Charlotte; Kraberger, Simona; Davison, William; Pastrana, Diana V.; Varsani, Arvind

2016-01-01

Polyomaviruses are a family of DNA tumor viruses that are known to infect mammals and birds. To investigate the deeper evolutionary history of the family, we used a combination of viral metagenomics, bioinformatics, and structural modeling approaches to identify and characterize polyomavirus sequences associated with fish and arthropods. Analyses drawing upon the divergent new sequences indicate that polyomaviruses have been gradually co-evolving with their animal hosts for at least half a billion years. Phylogenetic analyses of individual polyomavirus genes suggest that some modern polyomavirus species arose after ancient recombination events involving distantly related polyomavirus lineages. The improved evolutionary model provides a useful platform for developing a more accurate taxonomic classification system for the viral family Polyomaviridae. PMID:27093155

Evolutionary perspectives on stress and affective disorder.

PubMed

Gardner, R

2001-01-01

Three general approaches to evolutionary perspectives in psychiatry include the following domains. (1) information from general medicine and physiology that involves defenses against infectious disease and predators, with obsessive compulsive disorder and posttraumatic stress disorder (PTSD) amongst the psychiatric results of this. (2) Sociophysiology assumes that normal brain functions mediate social interactions, including social rank hierarchy, in-out group formation, and family bonding. At times these function maladroitly resulting in psychiatric symptoms, for example, mania, persecutory delusions, and depression. (3) Evolutionary psychology explains self-sacrificing and generous behavior despite how genes act selfishly in natural selection theory, via the helping of relatives, reciprocal altruism, and manipulation of social contracts. Copyright 2001 by W.B. Saunders Company

Mapping Phylogenetic Trees to Reveal Distinct Patterns of Evolution

PubMed Central

Kendall, Michelle; Colijn, Caroline

2016-01-01

Evolutionary relationships are frequently described by phylogenetic trees, but a central barrier in many fields is the difficulty of interpreting data containing conflicting phylogenetic signals. We present a metric-based method for comparing trees which extracts distinct alternative evolutionary relationships embedded in data. We demonstrate detection and resolution of phylogenetic uncertainty in a recent study of anole lizards, leading to alternate hypotheses about their evolutionary relationships. We use our approach to compare trees derived from different genes of Ebolavirus and find that the VP30 gene has a distinct phylogenetic signature composed of three alternatives that differ in the deep branching structure. Key words: phylogenetics, evolution, tree metrics, genetics, sequencing. PMID:27343287

Structure of a viscoplastic theory

NASA Technical Reports Server (NTRS)

Freed, Alan D.

1988-01-01

The general structure of a viscoplastic theory is developed from physical and thermodynamical considerations. The flow equation is of classical form. The dynamic recovery approach is shown to be superior to the hardening function approach for incorporating nonlinear strain hardening into the material response through the evolutionary equation for back stress. A novel approach for introducing isotropic strain hardening into the theory is presented, which results in a useful simplification. In particular, the limiting stress for the kinematic saturation of state (not the drag stress) is the chosen scalar-valued state variable. The resulting simplification is that there is no coupling between dynamic and thermal recovery terms in each evolutionary equation. The derived theory of viscoplasticity has the structure of a two-surface plasticity theory when the response is plasticlike, and the structure of a Bailey-Orowan creep theory when the response is creeplike.

The kW power module evolution study: Executive summary

NASA Technical Reports Server (NTRS)

1979-01-01

Using the Marshall Space Flight Center 25 kW Power Module (PM) reference design as a point of departure, the study defined evolutionary growth paths to 100 kW and above. A recommended development approach and initial configurations were described. Specific hardware changes from the reference design are recommended for the initial PM configuration to ensure evolutionary growth, improved replicability, and reduced cost. Certain functional changes are also recommended to enhance system capabilities.

Design Mining Interacting Wind Turbines.

PubMed

Preen, Richard J; Bull, Larry

2016-01-01

An initial study has recently been presented of surrogate-assisted evolutionary algorithms used to design vertical-axis wind turbines wherein candidate prototypes are evaluated under fan-generated wind conditions after being physically instantiated by a 3D printer. Unlike other approaches, such as computational fluid dynamics simulations, no mathematical formulations were used and no model assumptions were made. This paper extends that work by exploring alternative surrogate modelling and evolutionary techniques. The accuracy of various modelling algorithms used to estimate the fitness of evaluated individuals from the initial experiments is compared. The effect of temporally windowing surrogate model training samples is explored. A surrogate-assisted approach based on an enhanced local search is introduced; and alternative coevolution collaboration schemes are examined.

Extremely high frequency sensitivity in a 'simple' ear.

PubMed

Moir, Hannah M; Jackson, Joseph C; Windmill, James F C

2013-08-23

An evolutionary war is being played out between the bat, which uses ultrasonic calls to locate insect prey, and the moth, which uses microscale ears to listen for the approaching bat. While the highest known frequency of bat echolocation calls is 212 kHz, the upper limit of moth hearing is considered much lower. Here, we show that the greater wax moth, Galleria mellonella, is capable of hearing ultrasonic frequencies approaching 300 kHz; the highest frequency sensitivity of any animal. With auditory frequency sensitivity that is unprecedented in the animal kingdom, the greater wax moth is ready and armed for any echolocation call adaptations made by the bat in the on-going bat-moth evolutionary war.

THE `IN' AND THE `OUT': An Evolutionary Approach

NASA Astrophysics Data System (ADS)

Medina-Martins, P. R.; Rocha, L.

It is claimed that a great deal of the problems which the mechanist approaches to the emulation/modelling of the human mind are presently facing are due to a host of canons so `readily' accepted and acquainted that some of their underlying processes have not yet been the objective of intensive research. The essay proposes a (possible) solution for some of these problems introducing the tenets of a new paradigm which, based on a reappraisal of the concepts of purposiveness and teleology, lays emphasis on the evolutionary aspects (biological and mental) of alive beings. A complex neuro-fuzzy system which works as the supporting realization of this paradigm is briefly described in the essay.

Constructing phylogenetic trees using interacting pathways.

PubMed

Wan, Peng; Che, Dongsheng

2013-01-01

Phylogenetic trees are used to represent evolutionary relationships among biological species or organisms. The construction of phylogenetic trees is based on the similarities or differences of their physical or genetic features. Traditional approaches of constructing phylogenetic trees mainly focus on physical features. The recent advancement of high-throughput technologies has led to accumulation of huge amounts of biological data, which in turn changed the way of biological studies in various aspects. In this paper, we report our approach of building phylogenetic trees using the information of interacting pathways. We have applied hierarchical clustering on two domains of organisms-eukaryotes and prokaryotes. Our preliminary results have shown the effectiveness of using the interacting pathways in revealing evolutionary relationships.

Genomic clocks and evolutionary timescales

NASA Technical Reports Server (NTRS)

Blair Hedges, S.; Kumar, Sudhir

2003-01-01

For decades, molecular clocks have helped to illuminate the evolutionary timescale of life, but now genomic data pose a challenge for time estimation methods. It is unclear how to integrate data from many genes, each potentially evolving under a different model of substitution and at a different rate. Current methods can be grouped by the way the data are handled (genes considered separately or combined into a 'supergene') and the way gene-specific rate models are applied (global versus local clock). There are advantages and disadvantages to each of these approaches, and the optimal method has not yet emerged. Fortunately, time estimates inferred using many genes or proteins have greater precision and appear to be robust to different approaches.

Sharing programming resources between Bio* projects through remote procedure call and native call stack strategies.

PubMed

Prins, Pjotr; Goto, Naohisa; Yates, Andrew; Gautier, Laurent; Willis, Scooter; Fields, Christopher; Katayama, Toshiaki

2012-01-01

Open-source software (OSS) encourages computer programmers to reuse software components written by others. In evolutionary bioinformatics, OSS comes in a broad range of programming languages, including C/C++, Perl, Python, Ruby, Java, and R. To avoid writing the same functionality multiple times for different languages, it is possible to share components by bridging computer languages and Bio* projects, such as BioPerl, Biopython, BioRuby, BioJava, and R/Bioconductor. In this chapter, we compare the two principal approaches for sharing software between different programming languages: either by remote procedure call (RPC) or by sharing a local call stack. RPC provides a language-independent protocol over a network interface; examples are RSOAP and Rserve. The local call stack provides a between-language mapping not over the network interface, but directly in computer memory; examples are R bindings, RPy, and languages sharing the Java Virtual Machine stack. This functionality provides strategies for sharing of software between Bio* projects, which can be exploited more often. Here, we present cross-language examples for sequence translation, and measure throughput of the different options. We compare calling into R through native R, RSOAP, Rserve, and RPy interfaces, with the performance of native BioPerl, Biopython, BioJava, and BioRuby implementations, and with call stack bindings to BioJava and the European Molecular Biology Open Software Suite. In general, call stack approaches outperform native Bio* implementations and these, in turn, outperform RPC-based approaches. To test and compare strategies, we provide a downloadable BioNode image with all examples, tools, and libraries included. The BioNode image can be run on VirtualBox-supported operating systems, including Windows, OSX, and Linux.

A mathematical programming approach for sequential clustering of dynamic networks

NASA Astrophysics Data System (ADS)

Silva, Jonathan C.; Bennett, Laura; Papageorgiou, Lazaros G.; Tsoka, Sophia

2016-02-01

A common analysis performed on dynamic networks is community structure detection, a challenging problem that aims to track the temporal evolution of network modules. An emerging area in this field is evolutionary clustering, where the community structure of a network snapshot is identified by taking into account both its current state as well as previous time points. Based on this concept, we have developed a mixed integer non-linear programming (MINLP) model, SeqMod, that sequentially clusters each snapshot of a dynamic network. The modularity metric is used to determine the quality of community structure of the current snapshot and the historical cost is accounted for by optimising the number of node pairs co-clustered at the previous time point that remain so in the current snapshot partition. Our method is tested on social networks of interactions among high school students, college students and members of the Brazilian Congress. We show that, for an adequate parameter setting, our algorithm detects the classes that these students belong more accurately than partitioning each time step individually or by partitioning the aggregated snapshots. Our method also detects drastic discontinuities in interaction patterns across network snapshots. Finally, we present comparative results with similar community detection methods for time-dependent networks from the literature. Overall, we illustrate the applicability of mathematical programming as a flexible, adaptable and systematic approach for these community detection problems. Contribution to the Topical Issue "Temporal Network Theory and Applications", edited by Petter Holme.

Threatened species and the potential loss of phylogenetic diversity: conservation scenarios based on estimated extinction probabilities and phylogenetic risk analysis.

PubMed

Faith, Daniel P

2008-12-01

New species conservation strategies, including the EDGE of Existence (EDGE) program, have expanded threatened species assessments by integrating information about species' phylogenetic distinctiveness. Distinctiveness has been measured through simple scores that assign shared credit among species for evolutionary heritage represented by the deeper phylogenetic branches. A species with a high score combined with a high extinction probability receives high priority for conservation efforts. Simple hypothetical scenarios for phylogenetic trees and extinction probabilities demonstrate how such scoring approaches can provide inefficient priorities for conservation. An existing probabilistic framework derived from the phylogenetic diversity measure (PD) properly captures the idea of shared responsibility for the persistence of evolutionary history. It avoids static scores, takes into account the status of close relatives through their extinction probabilities, and allows for the necessary updating of priorities in light of changes in species threat status. A hypothetical phylogenetic tree illustrates how changes in extinction probabilities of one or more species translate into changes in expected PD. The probabilistic PD framework provided a range of strategies that moved beyond expected PD to better consider worst-case PD losses. In another example, risk aversion gave higher priority to a conservation program that provided a smaller, but less risky, gain in expected PD. The EDGE program could continue to promote a list of top species conservation priorities through application of probabilistic PD and simple estimates of current extinction probability. The list might be a dynamic one, with all the priority scores updated as extinction probabilities change. Results of recent studies suggest that estimation of extinction probabilities derived from the red list criteria linked to changes in species range sizes may provide estimated probabilities for many different species. Probabilistic PD provides a framework for single-species assessment that is well-integrated with a broader measurement of impacts on PD owing to climate change and other factors.

Dynamic programming algorithms for biological sequence comparison.

PubMed

Pearson, W R; Miller, W

1992-01-01

Efficient dynamic programming algorithms are available for a broad class of protein and DNA sequence comparison problems. These algorithms require computer time proportional to the product of the lengths of the two sequences being compared [O(N2)] but require memory space proportional only to the sum of these lengths [O(N)]. Although the requirement for O(N2) time limits use of the algorithms to the largest computers when searching protein and DNA sequence databases, many other applications of these algorithms, such as calculation of distances for evolutionary trees and comparison of a new sequence to a library of sequence profiles, are well within the capabilities of desktop computers. In particular, the results of library searches with rapid searching programs, such as FASTA or BLAST, should be confirmed by performing a rigorous optimal alignment. Whereas rapid methods do not overlook significant sequence similarities, FASTA limits the number of gaps that can be inserted into an alignment, so that a rigorous alignment may extend the alignment substantially in some cases. BLAST does not allow gaps in the local regions that it reports; a calculation that allows gaps is very likely to extend the alignment substantially. Although a Monte Carlo evaluation of the statistical significance of a similarity score with a rigorous algorithm is much slower than the heuristic approach used by the RDF2 program, the dynamic programming approach should take less than 1 hr on a 386-based PC or desktop Unix workstation. For descriptive purposes, we have limited our discussion to methods for calculating similarity scores and distances that use gap penalties of the form g = rk. Nevertheless, programs for the more general case (g = q+rk) are readily available. Versions of these programs that run either on Unix workstations, IBM-PC class computers, or the Macintosh can be obtained from either of the authors.

Toward a method for tracking virus evolutionary trajectory applied to the pandemic H1N1 2009 influenza virus.

PubMed

Squires, R Burke; Pickett, Brett E; Das, Sajal; Scheuermann, Richard H

2014-12-01

In 2009 a novel pandemic H1N1 influenza virus (H1N1pdm09) emerged as the first official influenza pandemic of the 21st century. Early genomic sequence analysis pointed to the swine origin of the virus. Here we report a novel computational approach to determine the evolutionary trajectory of viral sequences that uses data-driven estimations of nucleotide substitution rates to track the gradual accumulation of observed sequence alterations over time. Phylogenetic analysis and multiple sequence alignments show that sequences belonging to the resulting evolutionary trajectory of the H1N1pdm09 lineage exhibit a gradual accumulation of sequence variations and tight temporal correlations in the topological structure of the phylogenetic trees. These results suggest that our evolutionary trajectory analysis (ETA) can more effectively pinpoint the evolutionary history of viruses, including the host and geographical location traversed by each segment, when compared against either BLAST or traditional phylogenetic analysis alone. Copyright © 2014 Elsevier B.V. All rights reserved.

Understanding plant reproductive diversity.

PubMed

Barrett, Spencer C H

2010-01-12

Flowering plants display spectacular floral diversity and a bewildering array of reproductive adaptations that promote mating, particularly outbreeding. A striking feature of this diversity is that related species often differ in pollination and mating systems, and intraspecific variation in sexual traits is not unusual, especially among herbaceous plants. This variation provides opportunities for evolutionary biologists to link micro-evolutionary processes to the macro-evolutionary patterns that are evident within lineages. Here, I provide some personal reflections on recent progress in our understanding of the ecology and evolution of plant reproductive diversity. I begin with a brief historical sketch of the major developments in this field and then focus on three of the most significant evolutionary transitions in the reproductive biology of flowering plants: the pathway from outcrossing to predominant self-fertilization, the origin of separate sexes (females and males) from hermaphroditism and the shift from animal pollination to wind pollination. For each evolutionary transition, I consider what we have discovered and some of the problems that still remain unsolved. I conclude by discussing how new approaches might influence future research in plant reproductive biology.

Optimality and stability of symmetric evolutionary games with applications in genetic selection.

PubMed

Huang, Yuanyuan; Hao, Yiping; Wang, Min; Zhou, Wen; Wu, Zhijun

2015-06-01

Symmetric evolutionary games, i.e., evolutionary games with symmetric fitness matrices, have important applications in population genetics, where they can be used to model for example the selection and evolution of the genotypes of a given population. In this paper, we review the theory for obtaining optimal and stable strategies for symmetric evolutionary games, and provide some new proofs and computational methods. In particular, we review the relationship between the symmetric evolutionary game and the generalized knapsack problem, and discuss the first and second order necessary and sufficient conditions that can be derived from this relationship for testing the optimality and stability of the strategies. Some of the conditions are given in different forms from those in previous work and can be verified more efficiently. We also derive more efficient computational methods for the evaluation of the conditions than conventional approaches. We demonstrate how these conditions can be applied to justifying the strategies and their stabilities for a special class of genetic selection games including some in the study of genetic disorders.

A molecular signaling approach to linking intraspecific variation and macro-evolutionary patterns.

PubMed

Swanson, Eli M; Snell-Rood, Emilie C

2014-11-01

Macro-evolutionary comparisons are a valued tool in evolutionary biology. Nevertheless, our understanding of how systems involved in molecular signaling change in concert with phenotypic diversification has lagged. We argue that integrating our understanding of the evolution of molecular signaling systems with phylogenetic comparative methods is an important step toward understanding the processes linking variation among individuals with variation among species. Focusing mostly on the endocrine system, we discuss how the complexity and mechanistic nature of molecular signaling systems may influence the application and interpretation of macro-evolutionary comparisons. We also detail five hypotheses concerning the role that physiological mechanisms can play in shaping macro-evolutionary patterns, and discuss ways in which these hypotheses could influence phenotypic diversification. Finally, we review a series of tools able to analyze the complexity of physiological systems and the way they change in concert with the phenotypes for which they coordinate development. © The Author 2014. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

The locus of sexual selection: moving sexual selection studies into the post-genomics era.

PubMed

Wilkinson, G S; Breden, F; Mank, J E; Ritchie, M G; Higginson, A D; Radwan, J; Jaquiery, J; Salzburger, W; Arriero, E; Barribeau, S M; Phillips, P C; Renn, S C P; Rowe, L

2015-04-01

Sexual selection drives fundamental evolutionary processes such as trait elaboration and speciation. Despite this importance, there are surprisingly few examples of genes unequivocally responsible for variation in sexually selected phenotypes. This lack of information inhibits our ability to predict phenotypic change due to universal behaviours, such as fighting over mates and mate choice. Here, we discuss reasons for this apparent gap and provide recommendations for how it can be overcome by adopting contemporary genomic methods, exploiting underutilized taxa that may be ideal for detecting the effects of sexual selection and adopting appropriate experimental paradigms. Identifying genes that determine variation in sexually selected traits has the potential to improve theoretical models and reveal whether the genetic changes underlying phenotypic novelty utilize common or unique molecular mechanisms. Such a genomic approach to sexual selection will help answer questions in the evolution of sexually selected phenotypes that were first asked by Darwin and can furthermore serve as a model for the application of genomics in all areas of evolutionary biology. © 2015 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2015 European Society For Evolutionary Biology.

Process Engineering with the Evolutionary Spiral Process Model. Version 01.00.06

DTIC Science & Technology

1994-01-01

program . Process Definition and SPC-92041-CMC Provides methods for defining and Modeling Guidebook documenting processes so they can be analyzed, modified...and Program Evaluation and Review Technique (PERT) support the activity of developing a project schedule. A variety of automated tools, such as...keep the organiza- tion from becoming disoriented during the improvement program (Curtis, Kellner, and Over 1992). Analyzing and documenting how

Insights into the evolution of enzyme substrate promiscuity after the discovery of (βα)₈ isomerase evolutionary intermediates from a diverse metagenome.

PubMed

Noda-García, Lianet; Juárez-Vázquez, Ana L; Ávila-Arcos, María C; Verduzco-Castro, Ernesto A; Montero-Morán, Gabriela; Gaytán, Paul; Carrillo-Tripp, Mauricio; Barona-Gómez, Francisco

2015-06-10

Current sequence-based approaches to identify enzyme functional shifts, such as enzyme promiscuity, have proven to be highly dependent on a priori functional knowledge, hampering our ability to reconstruct evolutionary history behind these mechanisms. Hidden Markov Model (HMM) profiles, broadly used to classify enzyme families, can be useful to distinguish between closely related enzyme families with different specificities. The (βα)8-isomerase HisA/PriA enzyme family, involved in L-histidine (HisA, mono-substrate) biosynthesis in most bacteria and plants, but also in L-tryptophan (HisA/TrpF or PriA, dual-substrate) biosynthesis in most Actinobacteria, has been used as model system to explore evolutionary hypotheses and therefore has a considerable amount of evolutionary, functional and structural knowledge available. We searched for functional evolutionary intermediates between the HisA and PriA enzyme families in order to understand the functional divergence between these families. We constructed a HMM profile that correctly classifies sequences of unknown function into the HisA and PriA enzyme sub-families. Using this HMM profile, we mined a large metagenome to identify plausible evolutionary intermediate sequences between HisA and PriA. These sequences were used to perform phylogenetic reconstructions and to identify functionally conserved amino acids. Biochemical characterization of one selected enzyme (CAM1) with a mutation within the functionally essential N-terminus phosphate-binding site, namely, an alanine instead of a glycine in HisA or a serine in PriA, showed that this evolutionary intermediate has dual-substrate specificity. Moreover, site-directed mutagenesis of this alanine residue, either backwards into a glycine or forward into a serine, revealed the robustness of this enzyme. None of these mutations, presumably upon functionally essential amino acids, significantly abolished its enzyme activities. A truncated version of this enzyme (CAM2) predicted to adopt a (βα)6-fold, and thus entirely lacking a C-terminus phosphate-binding site, was identified and shown to have HisA activity. As expected, reconstruction of the evolution of PriA from HisA with HMM profiles suggest that functional shifts involve mutations in evolutionarily intermediate enzymes of otherwise functionally essential residues or motifs. These results are in agreement with a link between promiscuous enzymes and intragenic epistasis. HMM provides a convenient approach for gaining insights into these evolutionary processes.

The extended evolutionary synthesis: its structure, assumptions and predictions

PubMed Central

Laland, Kevin N.; Uller, Tobias; Feldman, Marcus W.; Sterelny, Kim; Müller, Gerd B.; Moczek, Armin; Jablonka, Eva; Odling-Smee, John

2015-01-01

Scientific activities take place within the structured sets of ideas and assumptions that define a field and its practices. The conceptual framework of evolutionary biology emerged with the Modern Synthesis in the early twentieth century and has since expanded into a highly successful research program to explore the processes of diversification and adaptation. Nonetheless, the ability of that framework satisfactorily to accommodate the rapid advances in developmental biology, genomics and ecology has been questioned. We review some of these arguments, focusing on literatures (evo-devo, developmental plasticity, inclusive inheritance and niche construction) whose implications for evolution can be interpreted in two ways—one that preserves the internal structure of contemporary evolutionary theory and one that points towards an alternative conceptual framework. The latter, which we label the ‘extended evolutionary synthesis' (EES), retains the fundaments of evolutionary theory, but differs in its emphasis on the role of constructive processes in development and evolution, and reciprocal portrayals of causation. In the EES, developmental processes, operating through developmental bias, inclusive inheritance and niche construction, share responsibility for the direction and rate of evolution, the origin of character variation and organism–environment complementarity. We spell out the structure, core assumptions and novel predictions of the EES, and show how it can be deployed to stimulate and advance research in those fields that study or use evolutionary biology. PMID:26246559

Marr's levels and the minimalist program.

PubMed

Johnson, Mark

2017-02-01

A simple change to a cognitive system at Marr's computational level may entail complex changes at the other levels of description of the system. The implementational level complexity of a change, rather than its computational level complexity, may be more closely related to the plausibility of a discrete evolutionary event causing that change. Thus the formal complexity of a change at the computational level may not be a good guide to the plausibility of an evolutionary event introducing that change. For example, while the Minimalist Program's Merge is a simple formal operation (Berwick & Chomsky, 2016), the computational mechanisms required to implement the language it generates (e.g., to parse the language) may be considerably more complex. This has implications for the theory of grammar: theories of grammar which involve several kinds of syntactic operations may be no less evolutionarily plausible than a theory of grammar that involves only one. A deeper understanding of human language at the algorithmic and implementational levels could strengthen Minimalist Program's account of the evolution of language.

Empirical verification of evolutionary theories of aging.

PubMed

Kyryakov, Pavlo; Gomez-Perez, Alejandra; Glebov, Anastasia; Asbah, Nimara; Bruno, Luigi; Meunier, Carolynne; Iouk, Tatiana; Titorenko, Vladimir I

2016-10-25

We recently selected 3 long-lived mutant strains of Saccharomyces cerevisiae by a lasting exposure to exogenous lithocholic acid. Each mutant strain can maintain the extended chronological lifespan after numerous passages in medium without lithocholic acid. In this study, we used these long-lived yeast mutants for empirical verification of evolutionary theories of aging. We provide evidence that the dominant polygenic trait extending longevity of each of these mutants 1) does not affect such key features of early-life fitness as the exponential growth rate, efficacy of post-exponential growth and fecundity; and 2) enhances such features of early-life fitness as susceptibility to chronic exogenous stresses, and the resistance to apoptotic and liponecrotic forms of programmed cell death. These findings validate evolutionary theories of programmed aging. We also demonstrate that under laboratory conditions that imitate the process of natural selection within an ecosystem, each of these long-lived mutant strains is forced out of the ecosystem by the parental wild-type strain exhibiting shorter lifespan. We therefore concluded that yeast cells have evolved some mechanisms for limiting their lifespan upon reaching a certain chronological age. These mechanisms drive the evolution of yeast longevity towards maintaining a finite yeast chronological lifespan within ecosystems.

Atmospheric lidar multi-user instrument system definition study

NASA Technical Reports Server (NTRS)

Greco, R. V. (Editor)

1980-01-01

A spaceborne lidar system for atmospheric studies was defined. The primary input was the Science Objectives Experiment Description and Evolutionary Flow Document. The first task of the study was to perform an experiment evolutionary analysis of the SEED. The second task was the system definition effort of the instrument system. The third task was the generation of a program plan for the hardware phase. The fourth task was the supporting studies which included a Shuttle deficiency analysis, a preliminary safety hazard analysis, the identification of long lead items, and development studies required. As a result of the study an evolutionary Lidar Multi-User Instrument System (MUIS) was defined. The MUIS occupies a full Spacelab pallet and has a weight of 1300 kg. The Lidar MUIS laser provides a 2 joule frequency doubled Nd:YAG laser that can also pump a tuneable dye laser wide frequency range and bandwidth. The MUIS includes a 1.25 meter diameter aperture Cassegrain receiver, with a moveable secondary mirror to provide precise alignment with the laser. The receiver can transmit the return signal to three single and multiple photomultiple tube detectors by use of a rotating fold mirror. It is concluded that the Lidar MUIS proceed to program implementation.

Punctuated equilibrium in the large-scale evolution of programming languages†

PubMed Central

Valverde, Sergi; Solé, Ricard V.

2015-01-01

The analogies and differences between biological and cultural evolution have been explored by evolutionary biologists, historians, engineers and linguists alike. Two well-known domains of cultural change are language and technology. Both share some traits relating the evolution of species, but technological change is very difficult to study. A major challenge in our way towards a scientific theory of technological evolution is how to properly define evolutionary trees or clades and how to weight the role played by horizontal transfer of information. Here, we study the large-scale historical development of programming languages, which have deeply marked social and technological advances in the last half century. We analyse their historical connections using network theory and reconstructed phylogenetic networks. Using both data analysis and network modelling, it is shown that their evolution is highly uneven, marked by innovation events where new languages are created out of improved combinations of different structural components belonging to previous languages. These radiation events occur in a bursty pattern and are tied to novel technological and social niches. The method can be extrapolated to other systems and consistently captures the major classes of languages and the widespread horizontal design exchanges, revealing a punctuated evolutionary path. PMID:25994298

Advantages of Task-Specific Multi-Objective Optimisation in Evolutionary Robotics.

PubMed

Trianni, Vito; López-Ibáñez, Manuel

2015-01-01

The application of multi-objective optimisation to evolutionary robotics is receiving increasing attention. A survey of the literature reveals the different possibilities it offers to improve the automatic design of efficient and adaptive robotic systems, and points to the successful demonstrations available for both task-specific and task-agnostic approaches (i.e., with or without reference to the specific design problem to be tackled). However, the advantages of multi-objective approaches over single-objective ones have not been clearly spelled out and experimentally demonstrated. This paper fills this gap for task-specific approaches: starting from well-known results in multi-objective optimisation, we discuss how to tackle commonly recognised problems in evolutionary robotics. In particular, we show that multi-objective optimisation (i) allows evolving a more varied set of behaviours by exploring multiple trade-offs of the objectives to optimise, (ii) supports the evolution of the desired behaviour through the introduction of objectives as proxies, (iii) avoids the premature convergence to local optima possibly introduced by multi-component fitness functions, and (iv) solves the bootstrap problem exploiting ancillary objectives to guide evolution in the early phases. We present an experimental demonstration of these benefits in three different case studies: maze navigation in a single robot domain, flocking in a swarm robotics context, and a strictly collaborative task in collective robotics.

The Schistosoma mansoni phylome: using evolutionary genomics to gain insight into a parasite's biology.

PubMed

Silva, Larissa Lopes; Marcet-Houben, Marina; Nahum, Laila Alves; Zerlotini, Adhemar; Gabaldón, Toni; Oliveira, Guilherme

2012-11-13

Schistosoma mansoni is one of the causative agents of schistosomiasis, a neglected tropical disease that affects about 237 million people worldwide. Despite recent efforts, we still lack a general understanding of the relevant host-parasite interactions, and the possible treatments are limited by the emergence of resistant strains and the absence of a vaccine. The S. mansoni genome was completely sequenced and still under continuous annotation. Nevertheless, more than 45% of the encoded proteins remain without experimental characterization or even functional prediction. To improve our knowledge regarding the biology of this parasite, we conducted a proteome-wide evolutionary analysis to provide a broad view of the S. mansoni's proteome evolution and to improve its functional annotation. Using a phylogenomic approach, we reconstructed the S. mansoni phylome, which comprises the evolutionary histories of all parasite proteins and their homologs across 12 other organisms. The analysis of a total of 7,964 phylogenies allowed a deeper understanding of genomic complexity and evolutionary adaptations to a parasitic lifestyle. In particular, the identification of lineage-specific gene duplications pointed to the diversification of several protein families that are relevant for host-parasite interaction, including proteases, tetraspanins, fucosyltransferases, venom allergen-like proteins, and tegumental-allergen-like proteins. In addition to the evolutionary knowledge, the phylome data enabled us to automatically re-annotate 3,451 proteins through a phylogenetic-based approach rather than solely sequence similarity searches. To allow further exploitation of this valuable data, all information has been made available at PhylomeDB (http://www.phylomedb.org). In this study, we used an evolutionary approach to assess S. mansoni parasite biology, improve genome/proteome functional annotation, and provide insights into host-parasite interactions. Taking advantage of a proteome-wide perspective rather than focusing on individual proteins, we identified that this parasite has experienced specific gene duplication events, particularly affecting genes that are potentially related to the parasitic lifestyle. These innovations may be related to the mechanisms that protect S. mansoni against host immune responses being important adaptations for the parasite survival in a potentially hostile environment. Continuing this work, a comparative analysis involving genomic, transcriptomic, and proteomic data from other helminth parasites, other parasites, and vectors will supply more information regarding parasite's biology as well as host-parasite interactions.

Paleontology at the "high table"? Popularization and disciplinary status in recent paleontology.

PubMed

Sepkoski, David

2014-03-01

This paper examines the way in which paleontologists used "popular books" to call for a broader "expanded synthesis" of evolutionary biology. Beginning in the 1970s, a group of influential paleontologists, including Stephen Jay Gould, Niles Eldredge, David Raup, Steven Stanley, and others, aggressively promoted a new theoretical, evolutionary approach to the fossil record as an important revision of the existing synthetic view of Darwinism. This work had a transformative effect within the discipline of paleontology. However, by the 1980s, paleontologists began making their case to a wider audience, both within evolutionary biology, and to the general public. Many of their books-for example, Eldredge's provocatively-titled Unfinished Synthesis-explicitly argued that the received synthetic view of Darwinian evolution was incomplete, and that paleontological contributions such as punctuated equilibria, the hierarchical model of macroevolution, and the study of mass extinction dynamics offered a substantial corrective to evolutionary theory. This paper argues that books-far from being "mere popularizations" of scientific ideas-played an important role in disciplinary debates surrounding evolutionary theory during the 1980s, and in particular that paleontologists like Gould and Eldredge self-consciously adopted the book format because of the importance of that genre in the history of evolutionary biology. Copyright © 2013 Elsevier Ltd. All rights reserved.

[Evolutionary medicine: the future looking at the past].

PubMed

Carvalho, Serafim; Rosado, Margarida

2008-01-01

Evolutionary medicine is an emergent basic science that offers new and varied perspectives to the comprehension of the human health and disease, considering them as a result of a gap between our modern lives and the environment where human beings evolve. This work's goals are to understand the importance of the evolutionary theories on concepts of health and disease, providing a new insight on medicine investigation. This bibliography review is based on Medline and PsycINFO articles research between 1996 and 2007 about review and experimental studies published in English, using the key words evolutionary and medicine, psychiatry, psychology, behaviour, health, disease, gene. There were selected forty-five articles based on and with special interest on the authors' practice. There were also consulted some allusive books. The present human genome and phenotypes are essentially Palaeolithic ones: they are not adapted to the modern life style, thus favouring the so called diseases of civilization. Fitting evolutionary strategies, apparently protective ones, when excessive, are the core syndromes of many emotional disruptive behaviours and diseases. Having the stone age's genes, we are obliged to live in the space age. With the evolutionary approach, postmodern medicine is detecting better the vulnerabilities, restrictions, biases, adaptations and maladaptations of human body, its actual diseases and its preventions and treatment.

Making evolutionary history count: biodiversity planning for coral reef fishes and the conservation of evolutionary processes

NASA Astrophysics Data System (ADS)

von der Heyden, Sophie

2017-03-01

Anthropogenic activities are having devastating impacts on marine systems with numerous knock-on effects on trophic functioning, species interactions and an accelerated loss of biodiversity. Establishing conservation areas can not only protect biodiversity, but also confer resilience against changes to coral reefs and their inhabitants. Planning for protection and conservation in marine systems is complex, but usually focuses on maintaining levels of biodiversity and protecting special and unique landscape features while avoiding negative impacts to socio-economic benefits. Conversely, the integration of evolutionary processes that have shaped extant species assemblages is rarely taken into account. However, it is as important to protect processes as it is to protect patterns for maintaining the evolutionary trajectories of populations and species. This review focuses on different approaches for integrating genetic analyses, such as phylogenetic diversity, phylogeography and the delineation of management units, temporal and spatial monitoring of genetic diversity and quantification of adaptive variation for protecting evolutionary resilience, into marine spatial planning, specifically for coral reef fishes. Many of these concepts are not yet readily applied to coral reef fish studies, but this synthesis highlights their potential and the importance of including historical processes into systematic biodiversity planning for conserving not only extant, but also future, biodiversity and its evolutionary potential.

Applying Evolutionary Genetics to Developmental Toxicology and Risk Assessment

PubMed Central

Leung, Maxwell C. K.; Procter, Andrew C.; Goldstone, Jared V.; Foox, Jonathan; DeSalle, Robert; Mattingly, Carolyn J.; Siddall, Mark E.; Timme-Laragy, Alicia R.

2018-01-01

Evolutionary thinking continues to challenge our views on health and disease. Yet, there is a communication gap between evolutionary biologists and toxicologists in recognizing the connections among developmental pathways, high-throughput screening, and birth defects in humans. To increase our capability in identifying potential developmental toxicants in humans, we propose to apply evolutionary genetics to improve the experimental design and data interpretation with various in vitro and whole-organism models. We review five molecular systems of stress response and update 18 consensual cell-cell signaling pathways that are the hallmark for early development, organogenesis, and differentiation; and revisit the principles of teratology in light of recent advances in high-throughput screening, big data techniques, and systems toxicology. Multiscale systems modeling plays an integral role in the evolutionary approach to cross-species extrapolation. Phylogenetic analysis and comparative bioinformatics are both valuable tools in identifying and validating the molecular initiating events that account for adverse developmental outcomes in humans. The discordance of susceptibility between test species and humans (ontogeny) reflects their differences in evolutionary history (phylogeny). This synthesis not only can lead to novel applications in developmental toxicity and risk assessment, but also can pave the way for applying an evo-devo perspective to the study of developmental origins of health and disease. PMID:28267574

Evolutionary perspectives on learning: conceptual and methodological issues in the study of adaptive specializations.

PubMed

Krause, Mark A

2015-07-01

Inquiry into evolutionary adaptations has flourished since the modern synthesis of evolutionary biology. Comparative methods, genetic techniques, and various experimental and modeling approaches are used to test adaptive hypotheses. In psychology, the concept of adaptation is broadly applied and is central to comparative psychology and cognition. The concept of an adaptive specialization of learning is a proposed account for exceptions to general learning processes, as seen in studies of Pavlovian conditioning of taste aversions, sexual responses, and fear. The evidence generally consists of selective associations forming between biologically relevant conditioned and unconditioned stimuli, with conditioned responses differing in magnitude, persistence, or other measures relative to non-biologically relevant stimuli. Selective associations for biologically relevant stimuli may suggest adaptive specializations of learning, but do not necessarily confirm adaptive hypotheses as conceived of in evolutionary biology. Exceptions to general learning processes do not necessarily default to an adaptive specialization explanation, even if experimental results "make biological sense". This paper examines the degree to which hypotheses of adaptive specializations of learning in sexual and fear response systems have been tested using methodologies developed in evolutionary biology (e.g., comparative methods, quantitative and molecular genetics, survival experiments). A broader aim is to offer perspectives from evolutionary biology for testing adaptive hypotheses in psychological science.

Integrating Evolutionary and Molecular Genetics of Aging

PubMed Central

Flatt, Thomas; Schmidt, Paul S.

2010-01-01

Aging or senescence is an age-dependent decline in physiological function, demographically manifest as decreased survival and fecundity with increasing age. Since aging is disadvantageous it should not evolve by natural selection. So why do organisms age and die? In the 1940’s and 1950’s evolutionary geneticists resolved this paradox by positing that aging evolves because selection is inefficient at maintaining function late in life. By the 1980’s and 1990’s this evolutionary theory of aging had received firm empirical support, but little was known about the mechanisms of aging. Around the same time biologists began to apply the tools of molecular genetics to aging and successfully identified mutations that affect longevity. Today, the molecular genetics of aging is a burgeoning field, but progress in evolutionary genetics of aging has largely stalled. Here we argue that some of the most exciting and unresolved questions about aging require an integration of molecular and evolutionary approaches. Is aging a universal process? Why do species age at different rates? Are the mechanisms of aging conserved or lineage-specific? Are longevity genes identified in the laboratory under selection in natural populations? What is the genetic basis of plasticity in aging in response to environmental cues and is this plasticity adaptive? What are the mechanisms underlying trade-offs between early fitness traits and life span? To answer these questions evolutionary biologists must adopt the tools of molecular biology, while molecular biologists must put their experiments into an evolutionary framework. The time is ripe for a synthesis of molecular biogerontology and the evolutionary biology of aging. PMID:19619612

Some assembly required: evolutionary and systems perspectives on the mammalian reproductive system.

PubMed

Mordhorst, Bethany R; Wilson, Miranda L; Conant, Gavin C

2016-01-01

In this review, we discuss the way that insights from evolutionary theory and systems biology shed light on form and function in mammalian reproductive systems. In the first part of the review, we contrast the rapid evolution seen in some reproductive genes with the generally conservative nature of development. We discuss directional selection and coevolution as potential drivers of rapid evolution in sperm and egg proteins. Such rapid change is very different from the highly conservative nature of later embryo development. However, it is not unique, as some regions of the sex chromosomes also show elevated rates of evolutionary change. To explain these contradictory trends, we argue that it is not reproductive functions per se that induce rapid evolution. Rather, it is the fact that biotic interactions, such as speciation events and sexual conflict, have no evolutionary endpoint and hence can drive continuous evolutionary changes. Returning to the question of sex chromosome evolution, we discuss the way that recent advances in evolutionary genomics and systems biology and, in particular, the development of a theory of gene balance provide a better understanding of the evolutionary patterns seen on these chromosomes. We end the review with a discussion of a surprising and incompletely understood phenomenon observed in early embryos: namely the Warburg effect, whereby glucose is fermented to lactate and alanine rather than respired to carbon dioxide. We argue that evolutionary insights, from both yeasts and tumor cells, help to explain the Warburg effect, and that new metabolic modeling approaches are useful in assessing the potential sources of the effect.

Integrating evolutionary and molecular genetics of aging.

PubMed

Flatt, Thomas; Schmidt, Paul S

2009-10-01

Aging or senescence is an age-dependent decline in physiological function, demographically manifest as decreased survival and fecundity with increasing age. Since aging is disadvantageous it should not evolve by natural selection. So why do organisms age and die? In the 1940s and 1950s evolutionary geneticists resolved this paradox by positing that aging evolves because selection is inefficient at maintaining function late in life. By the 1980s and 1990s this evolutionary theory of aging had received firm empirical support, but little was known about the mechanisms of aging. Around the same time biologists began to apply the tools of molecular genetics to aging and successfully identified mutations that affect longevity. Today, the molecular genetics of aging is a burgeoning field, but progress in evolutionary genetics of aging has largely stalled. Here we argue that some of the most exciting and unresolved questions about aging require an integration of molecular and evolutionary approaches. Is aging a universal process? Why do species age at different rates? Are the mechanisms of aging conserved or lineage-specific? Are longevity genes identified in the laboratory under selection in natural populations? What is the genetic basis of plasticity in aging in response to environmental cues and is this plasticity adaptive? What are the mechanisms underlying trade-offs between early fitness traits and life span? To answer these questions evolutionary biologists must adopt the tools of molecular biology, while molecular biologists must put their experiments into an evolutionary framework. The time is ripe for a synthesis of molecular biogerontology and the evolutionary biology of aging.

Approaches to Macroevolution: 1. General Concepts and Origin of Variation.

PubMed

Jablonski, David

2017-01-01

Approaches to macroevolution require integration of its two fundamental components, i.e. the origin and the sorting of variation, in a hierarchical framework. Macroevolution occurs in multiple currencies that are only loosely correlated, notably taxonomic diversity, morphological disparity, and functional variety. The origin of variation within this conceptual framework is increasingly understood in developmental terms, with the semi-hierarchical structure of gene regulatory networks (GRNs, used here in a broad sense incorporating not just the genetic circuitry per se but the factors controlling the timing and location of gene expression and repression), the non-linear relation between magnitude of genetic change and the phenotypic results, the evolutionary potential of co-opting existing GRNs, and developmental responsiveness to nongenetic signals (i.e. epigenetics and plasticity), all requiring modification of standard microevolutionary models, and rendering difficult any simple definition of evolutionary novelty. The developmental factors underlying macroevolution create anisotropic probabilities-i.e., an uneven density distribution-of evolutionary change around any given phenotypic starting point, and the potential for coordinated changes among traits that can accommodate change via epigenetic mechanisms. From this standpoint, "punctuated equilibrium" and "phyletic gradualism" simply represent two cells in a matrix of evolutionary models of phenotypic change, and the origin of trends and evolutionary novelty are not simply functions of ecological opportunity. Over long timescales, contingency becomes especially important, and can be viewed in terms of macroevolutionary lags (the temporal separation between the origin of a trait or clade and subsequent diversification); such lags can arise by several mechanisms: as geological or phylogenetic artifacts, or when diversifications require synergistic interactions among traits, or between traits and external events. The temporal and spatial patterns of the origins of evolutionary novelties are a challenge to macroevolutionary theory; individual events can be described retrospectively, but a general model relating development, genetics, and ecology is needed. An accompanying paper (Jablonski in Evol Biol 2017) reviews diversity dynamics and the sorting of variation, with some general conclusions.

Introducing Evolution to Non-Biology Majors via the Fossil Record: A Case Study from the Israeli High School System.

ERIC Educational Resources Information Center

Dodick, Jeff; Orion, Nir

2003-01-01

Discusses challenges faced in the teaching and learning of evolution. Presents a curricular program and a case study on evolutionary biology. Investigates students' conceptual knowledge after exposure to the program "From Dinosaurs to Darwin," which focuses on fossil records as evidence of evolution. (Contains 32 references.) (YDS)

Post-Test Inspection of Nasa's Evolutionary Xenon Thruster Long Duration Test Hardware: Ion Optics

NASA Technical Reports Server (NTRS)

Soulas, George C.; Shastry, Rohit

2016-01-01

A Long Duration Test (LDT) was initiated in June 2005 as a part of NASAs Evolutionary Xenon Thruster (NEXT) service life validation approach. Testing was voluntarily terminated in February 2014, with the thruster accumulating 51,184 hours of operation, processing 918 kg of xenon propellant, and delivering 35.5 MN-s of total impulse. This presentation will present the post-test inspection results to date for the thrusters ion optics.

Predicting patchy particle crystals: variable box shape simulations and evolutionary algorithms.

PubMed

Bianchi, Emanuela; Doppelbauer, Günther; Filion, Laura; Dijkstra, Marjolein; Kahl, Gerhard

2012-06-07

We consider several patchy particle models that have been proposed in literature and we investigate their candidate crystal structures in a systematic way. We compare two different algorithms for predicting crystal structures: (i) an approach based on Monte Carlo simulations in the isobaric-isothermal ensemble and (ii) an optimization technique based on ideas of evolutionary algorithms. We show that the two methods are equally successful and provide consistent results on crystalline phases of patchy particle systems.

When everything is not everywhere but species evolve: an alternative method to model adaptive properties of marine ecosystems

PubMed Central

Sauterey, Boris; Ward, Ben A.; Follows, Michael J.; Bowler, Chris; Claessen, David

2015-01-01

The functional and taxonomic biogeography of marine microbial systems reflects the current state of an evolving system. Current models of marine microbial systems and biogeochemical cycles do not reflect this fundamental organizing principle. Here, we investigate the evolutionary adaptive potential of marine microbial systems under environmental change and introduce explicit Darwinian adaptation into an ocean modelling framework, simulating evolving phytoplankton communities in space and time. To this end, we adopt tools from adaptive dynamics theory, evaluating the fitness of invading mutants over annual timescales, replacing the resident if a fitter mutant arises. Using the evolutionary framework, we examine how community assembly, specifically the emergence of phytoplankton cell size diversity, reflects the combined effects of bottom-up and top-down controls. When compared with a species-selection approach, based on the paradigm that “Everything is everywhere, but the environment selects”, we show that (i) the selected optimal trait values are similar; (ii) the patterns emerging from the adaptive model are more robust, but (iii) the two methods lead to different predictions in terms of emergent diversity. We demonstrate that explicitly evolutionary approaches to modelling marine microbial populations and functionality are feasible and practical in time-varying, space-resolving settings and provide a new tool for exploring evolutionary interactions on a range of timescales in the ocean. PMID:25852217

When everything is not everywhere but species evolve: an alternative method to model adaptive properties of marine ecosystems.

PubMed

Sauterey, Boris; Ward, Ben A; Follows, Michael J; Bowler, Chris; Claessen, David

2015-01-01

The functional and taxonomic biogeography of marine microbial systems reflects the current state of an evolving system. Current models of marine microbial systems and biogeochemical cycles do not reflect this fundamental organizing principle. Here, we investigate the evolutionary adaptive potential of marine microbial systems under environmental change and introduce explicit Darwinian adaptation into an ocean modelling framework, simulating evolving phytoplankton communities in space and time. To this end, we adopt tools from adaptive dynamics theory, evaluating the fitness of invading mutants over annual timescales, replacing the resident if a fitter mutant arises. Using the evolutionary framework, we examine how community assembly, specifically the emergence of phytoplankton cell size diversity, reflects the combined effects of bottom-up and top-down controls. When compared with a species-selection approach, based on the paradigm that "Everything is everywhere, but the environment selects", we show that (i) the selected optimal trait values are similar; (ii) the patterns emerging from the adaptive model are more robust, but (iii) the two methods lead to different predictions in terms of emergent diversity. We demonstrate that explicitly evolutionary approaches to modelling marine microbial populations and functionality are feasible and practical in time-varying, space-resolving settings and provide a new tool for exploring evolutionary interactions on a range of timescales in the ocean.

Helminths and Cancers From the Evolutionary Perspective.

PubMed

Scholte, Larissa L S; Pascoal-Xavier, Marcelo A; Nahum, Laila A

2018-01-01

Helminths include free-living and parasitic Platyhelminthes and Nematoda which infect millions of people worldwide. Some Platyhelminthes species of blood flukes ( Schistosoma haematobium, Schistosoma japonicum , and Schistosoma mansoni ) and liver flukes ( Clonorchis sinensis and Opisthorchis viverrini ) are known to be involved in human cancers. Other helminths are likely to be carcinogenic. Our main goals are to summarize the current knowledge of human cancers caused by Platyhelminthes, point out some helminth and human biomarkers identified so far, and highlight the potential contributions of phylogenetics and molecular evolution to cancer research. Human cancers caused by helminth infection include cholangiocarcinoma, colorectal hepatocellular carcinoma, squamous cell carcinoma, and urinary bladder cancer. Chronic inflammation is proposed as a common pathway for cancer initiation and development. Furthermore, different bacteria present in gastric, colorectal, and urogenital microbiomes might be responsible for enlarging inflammatory and fibrotic responses in cancers. Studies have suggested that different biomarkers are involved in helminth infection and human cancer development; although, the detailed mechanisms remain under debate. Different helminth proteins have been studied by different approaches. However, their evolutionary relationships remain unsolved. Here, we illustrate the strengths of homology identification and function prediction of uncharacterized proteins from genome sequencing projects based on an evolutionary framework. Together, these approaches may help identifying new biomarkers for disease diagnostics and intervention measures. This work has potential applications in the field of phylomedicine (evolutionary medicine) and may contribute to parasite and cancer research.

Genetic Regulatory Networks in Embryogenesis and Evolution

NASA Technical Reports Server (NTRS)

1998-01-01

The article introduces a series of papers that were originally presented at a workshop titled Genetic Regulatory Network in Embryogenesis and Evaluation. Contents include the following: evolution of cleavage programs in relationship to axial specification and body plan evolution, changes in cell lineage specification elucidate evolutionary relations in spiralia, axial patterning in the leech: developmental mechanisms and evolutionary implications, hox genes in arthropod development and evolution, heterochronic genes in development and evolution, a common theme for LIM homeobox gene function across phylogeny, and mechanisms of specification in ascidian embryos.

An evolutionary solution to anesthesia automated record keeping.

PubMed

Bicker, A A; Gage, J S; Poppers, P J

1998-08-01

In the course of five years the development of an automated anesthesia record keeper has evolved through nearly a dozen stages, each marked by new features and sophistication. Commodity PC hardware and software minimized development costs. Object oriented analysis, programming and design supported the process of change. In addition, we developed an evolutionary strategy that optimized motivation, risk management, and maximized return on investment. Besides providing record keeping services, the system supports educational and research activities and through a flexible plotting paradigm, supports each anesthesiologist's focus on physiological data during and after anesthesia.

CDMetaPOP: An individual-based, eco-evolutionary model for spatially explicit simulation of landscape demogenetics

USGS Publications Warehouse

Landguth, Erin L; Bearlin, Andrew; Day, Casey; Dunham, Jason B.

2016-01-01

1. Combining landscape demographic and genetics models offers powerful methods for addressing questions for eco-evolutionary applications.2. Using two illustrative examples, we present Cost–Distance Meta-POPulation, a program to simulate changes in neutral and/or selection-driven genotypes through time as a function of individual-based movement, complex spatial population dynamics, and multiple and changing landscape drivers.3. Cost–Distance Meta-POPulation provides a novel tool for questions in landscape genetics by incorporating population viability analysis, while linking directly to conservation applications.

Developmental biology, the stem cell of biological disciplines.

PubMed

Gilbert, Scott F

2017-12-01

Developmental biology (including embryology) is proposed as "the stem cell of biological disciplines." Genetics, cell biology, oncology, immunology, evolutionary mechanisms, neurobiology, and systems biology each has its ancestry in developmental biology. Moreover, developmental biology continues to roll on, budding off more disciplines, while retaining its own identity. While its descendant disciplines differentiate into sciences with a restricted set of paradigms, examples, and techniques, developmental biology remains vigorous, pluripotent, and relatively undifferentiated. In many disciplines, especially in evolutionary biology and oncology, the developmental perspective is being reasserted as an important research program.

Fixism and conservation science.

PubMed

Robert, Alexandre; Fontaine, Colin; Veron, Simon; Monnet, Anne-Christine; Legrand, Marine; Clavel, Joanne; Chantepie, Stéphane; Couvet, Denis; Ducarme, Frédéric; Fontaine, Benoît; Jiguet, Frédéric; le Viol, Isabelle; Rolland, Jonathan; Sarrazin, François; Teplitsky, Céline; Mouchet, Maud

2017-08-01

The field of biodiversity conservation has recently been criticized as relying on a fixist view of the living world in which existing species constitute at the same time targets of conservation efforts and static states of reference, which is in apparent disagreement with evolutionary dynamics. We reviewed the prominent role of species as conservation units and the common benchmark approach to conservation that aims to use past biodiversity as a reference to conserve current biodiversity. We found that the species approach is justified by the discrepancy between the time scales of macroevolution and human influence and that biodiversity benchmarks are based on reference processes rather than fixed reference states. Overall, we argue that the ethical and theoretical frameworks underlying conservation research are based on macroevolutionary processes, such as extinction dynamics. Current species, phylogenetic, community, and functional conservation approaches constitute short-term responses to short-term human effects on these reference processes, and these approaches are consistent with evolutionary principles. © 2016 Society for Conservation Biology.

On the Evolutionary and Biogeographic History of Saxifraga sect. Trachyphyllum (Gaud.) Koch (Saxifragaceae Juss.)

PubMed Central

DeChaine, Eric G.; Anderson, Stacy A.; McNew, Jennifer M.; Wendling, Barry M.

2013-01-01

Arctic-alpine plants in the genus Saxifraga L. (Saxifragaceae Juss.) provide an excellent system for investigating the process of diversification in northern regions. Yet, sect. Trachyphyllum (Gaud.) Koch, which is comprised of about 8 to 26 species, has still not been explored by molecular systematists even though taxonomists concur that the section needs to be thoroughly re-examined. Our goals were to use chloroplast trnL-F and nuclear ITS DNA sequence data to circumscribe the section phylogenetically, test models of geographically-based population divergence, and assess the utility of morphological characters in estimating evolutionary relationships. To do so, we sequenced both genetic markers for 19 taxa within the section. The phylogenetic inferences of sect. Trachyphyllum using maximum likelihood and Bayesian analyses showed that the section is polyphyletic, with S. aspera L. and S bryoides L. falling outside the main clade. In addition, the analyses supported several taxonomic re-classifications to prior names. We used two approaches to test biogeographic hypotheses: i) a coalescent approach in Mesquite to test the fit of our reconstructed gene trees to geographically-based models of population divergence and ii) a maximum likelihood inference in Lagrange. These tests uncovered strong support for an origin of the clade in the Southern Rocky Mountains of North America followed by dispersal and divergence episodes across refugia. Finally we adopted a stochastic character mapping approach in SIMMAP to investigate the utility of morphological characters in estimating evolutionary relationships among taxa. We found that few morphological characters were phylogenetically informative and many were misleading. Our molecular analyses provide a foundation for the diversity and evolutionary relationships within sect. Trachyphyllum and hypotheses for better understanding the patterns and processes of divergence in this section, other saxifrages, and plants inhabiting the North Pacific Rim. PMID:23922810

Life's attractors : understanding developmental systems through reverse engineering and in silico evolution.

PubMed

Jaeger, Johannes; Crombach, Anton

2012-01-01

We propose an approach to evolutionary systems biology which is based on reverse engineering of gene regulatory networks and in silico evolutionary simulations. We infer regulatory parameters for gene networks by fitting computational models to quantitative expression data. This allows us to characterize the regulatory structure and dynamical repertoire of evolving gene regulatory networks with a reasonable amount of experimental and computational effort. We use the resulting network models to identify those regulatory interactions that are conserved, and those that have diverged between different species. Moreover, we use the models obtained by data fitting as starting points for simulations of evolutionary transitions between species. These simulations enable us to investigate whether such transitions are random, or whether they show stereotypical series of regulatory changes which depend on the structure and dynamical repertoire of an evolving network. Finally, we present a case study-the gap gene network in dipterans (flies, midges, and mosquitoes)-to illustrate the practical application of the proposed methodology, and to highlight the kind of biological insights that can be gained by this approach.

Evolutionary programming-based univector field navigation method for past mobile robots.

PubMed

Kim, Y J; Kim, J H; Kwon, D S

2001-01-01

Most of navigation techniques with obstacle avoidance do not consider the robot orientation at the target position. These techniques deal with the robot position only and are independent of its orientation and velocity. To solve these problems this paper proposes a novel univector field method for fast mobile robot navigation which introduces a normalized two dimensional vector field. The method provides fast moving robots with the desired posture at the target position and obstacle avoidance. To obtain the sub-optimal vector field, a function approximator is used and trained by evolutionary programming. Two kinds of vector fields are trained, one for the final posture acquisition and the other for obstacle avoidance. Computer simulations and real experiments are carried out for a fast moving mobile robot to demonstrate the effectiveness of the proposed scheme.

Affective Neuronal Selection: The Nature of the Primordial Emotion Systems

PubMed Central

Toronchuk, Judith A.; Ellis, George F. R.

2013-01-01

Based on studies in affective neuroscience and evolutionary psychiatry, a tentative new proposal is made here as to the nature and identification of primordial emotional systems. Our model stresses phylogenetic origins of emotional systems, which we believe is necessary for a full understanding of the functions of emotions and additionally suggests that emotional organizing systems play a role in sculpting the brain during ontogeny. Nascent emotional systems thus affect cognitive development. A second proposal concerns two additions to the affective systems identified by Panksepp. We suggest there is substantial evidence for a primary emotional organizing program dealing with power, rank, dominance, and subordination which instantiates competitive and territorial behavior and is an evolutionary contributor to self-esteem in humans. A program underlying disgust reactions which originally functioned in ancient vertebrates to protect against infection and toxins is also suggested. PMID:23316177

Can An Evolutionary Process Create English Text?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bailey, David H.

Critics of the conventional theory of biological evolution have asserted that while natural processes might result in some limited diversity, nothing fundamentally new can arise from 'random' evolution. In response, biologists such as Richard Dawkins have demonstrated that a computer program can generate a specific short phrase via evolution-like iterations starting with random gibberish. While such demonstrations are intriguing, they are flawed in that they have a fixed, pre-specified future target, whereas in real biological evolution there is no fixed future target, but only a complicated 'fitness landscape'. In this study, a significantly more sophisticated evolutionary scheme is employed tomore » produce text segments reminiscent of a Charles Dickens novel. The aggregate size of these segments is larger than the computer program and the input Dickens text, even when comparing compressed data (as a measure of information content).« less

Optimization of Artificial Neural Network using Evolutionary Programming for Prediction of Cascading Collapse Occurrence due to the Hidden Failure Effect

NASA Astrophysics Data System (ADS)

Idris, N. H.; Salim, N. A.; Othman, M. M.; Yasin, Z. M.

2018-03-01

This paper presents the Evolutionary Programming (EP) which proposed to optimize the training parameters for Artificial Neural Network (ANN) in predicting cascading collapse occurrence due to the effect of protection system hidden failure. The data has been collected from the probability of hidden failure model simulation from the historical data. The training parameters of multilayer-feedforward with backpropagation has been optimized with objective function to minimize the Mean Square Error (MSE). The optimal training parameters consists of the momentum rate, learning rate and number of neurons in first hidden layer and second hidden layer is selected in EP-ANN. The IEEE 14 bus system has been tested as a case study to validate the propose technique. The results show the reliable prediction of performance validated through MSE and Correlation Coefficient (R).