Energy and time determine scaling in biological and computer designs.

PubMed

Moses, Melanie; Bezerra, George; Edwards, Benjamin; Brown, James; Forrest, Stephanie

2016-08-19

Metabolic rate in animals and power consumption in computers are analogous quantities that scale similarly with size. We analyse vascular systems of mammals and on-chip networks of microprocessors, where natural selection and human engineering, respectively, have produced systems that minimize both energy dissipation and delivery times. Using a simple network model that simultaneously minimizes energy and time, our analysis explains empirically observed trends in the scaling of metabolic rate in mammals and power consumption and performance in microprocessors across several orders of magnitude in size. Just as the evolutionary transitions from unicellular to multicellular animals in biology are associated with shifts in metabolic scaling, our model suggests that the scaling of power and performance will change as computer designs transition to decentralized multi-core and distributed cyber-physical systems. More generally, a single energy-time minimization principle may govern the design of many complex systems that process energy, materials and information.This article is part of the themed issue 'The major synthetic evolutionary transitions'. © 2016 The Author(s).

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.

Development of X-TOOLSS: Preliminary Design of Space Systems Using Evolutionary Computation

NASA Technical Reports Server (NTRS)

Schnell, Andrew R.; Hull, Patrick V.; Turner, Mike L.; Dozier, Gerry; Alverson, Lauren; Garrett, Aaron; Reneau, Jarred

2008-01-01

Evolutionary computational (EC) techniques such as genetic algorithms (GA) have been identified as promising methods to explore the design space of mechanical and electrical systems at the earliest stages of design. In this paper the authors summarize their research in the use of evolutionary computation to develop preliminary designs for various space systems. An evolutionary computational solver developed over the course of the research, X-TOOLSS (Exploration Toolset for the Optimization of Launch and Space Systems) is discussed. With the success of early, low-fidelity example problems, an outline of work involving more computationally complex models is discussed.

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.

An Orthogonal Evolutionary Algorithm With Learning Automata for Multiobjective Optimization.

PubMed

Dai, Cai; Wang, Yuping; Ye, Miao; Xue, Xingsi; Liu, Hailin

2016-12-01

Research on multiobjective optimization problems becomes one of the hottest topics of intelligent computation. In order to improve the search efficiency of an evolutionary algorithm and maintain the diversity of solutions, in this paper, the learning automata (LA) is first used for quantization orthogonal crossover (QOX), and a new fitness function based on decomposition is proposed to achieve these two purposes. Based on these, an orthogonal evolutionary algorithm with LA for complex multiobjective optimization problems with continuous variables is proposed. The experimental results show that in continuous states, the proposed algorithm is able to achieve accurate Pareto-optimal sets and wide Pareto-optimal fronts efficiently. Moreover, the comparison with the several existing well-known algorithms: nondominated sorting genetic algorithm II, decomposition-based multiobjective evolutionary algorithm, decomposition-based multiobjective evolutionary algorithm with an ensemble of neighborhood sizes, multiobjective optimization by LA, and multiobjective immune algorithm with nondominated neighbor-based selection, on 15 multiobjective benchmark problems, shows that the proposed algorithm is able to find more accurate and evenly distributed Pareto-optimal fronts than the compared ones.

Practical advantages of evolutionary computation

NASA Astrophysics Data System (ADS)

Fogel, David B.

1997-10-01

Evolutionary computation is becoming a common technique for solving difficult, real-world problems in industry, medicine, and defense. This paper reviews some of the practical advantages to using evolutionary algorithms as compared with classic methods of optimization or artificial intelligence. Specific advantages include the flexibility of the procedures, as well as their ability to self-adapt the search for optimum solutions on the fly. As desktop computers increase in speed, the application of evolutionary algorithms will become routine.

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.

Fitness Probability Distribution of Bit-Flip Mutation.

PubMed

Chicano, Francisco; Sutton, Andrew M; Whitley, L Darrell; Alba, Enrique

2015-01-01

Bit-flip mutation is a common mutation operator for evolutionary algorithms applied to optimize functions over binary strings. In this paper, we develop results from the theory of landscapes and Krawtchouk polynomials to exactly compute the probability distribution of fitness values of a binary string undergoing uniform bit-flip mutation. We prove that this probability distribution can be expressed as a polynomial in p, the probability of flipping each bit. We analyze these polynomials and provide closed-form expressions for an easy linear problem (Onemax), and an NP-hard problem, MAX-SAT. We also discuss a connection of the results with runtime analysis.

MultiPhyl: a high-throughput phylogenomics webserver using distributed computing

PubMed Central

Keane, Thomas M.; Naughton, Thomas J.; McInerney, James O.

2007-01-01

With the number of fully sequenced genomes increasing steadily, there is greater interest in performing large-scale phylogenomic analyses from large numbers of individual gene families. Maximum likelihood (ML) has been shown repeatedly to be one of the most accurate methods for phylogenetic construction. Recently, there have been a number of algorithmic improvements in maximum-likelihood-based tree search methods. However, it can still take a long time to analyse the evolutionary history of many gene families using a single computer. Distributed computing refers to a method of combining the computing power of multiple computers in order to perform some larger overall calculation. In this article, we present the first high-throughput implementation of a distributed phylogenetics platform, MultiPhyl, capable of using the idle computational resources of many heterogeneous non-dedicated machines to form a phylogenetics supercomputer. MultiPhyl allows a user to upload hundreds or thousands of amino acid or nucleotide alignments simultaneously and perform computationally intensive tasks such as model selection, tree searching and bootstrapping of each of the alignments using many desktop machines. The program implements a set of 88 amino acid models and 56 nucleotide maximum likelihood models and a variety of statistical methods for choosing between alternative models. A MultiPhyl webserver is available for public use at: http://www.cs.nuim.ie/distributed/multiphyl.php. PMID:17553837

Evolutionary model selection and parameter estimation for protein-protein interaction network based on differential evolution algorithm

PubMed Central

Huang, Lei; Liao, Li; Wu, Cathy H.

2016-01-01

Revealing the underlying evolutionary mechanism plays an important role in understanding protein interaction networks in the cell. While many evolutionary models have been proposed, the problem about applying these models to real network data, especially for differentiating which model can better describe evolutionary process for the observed network urgently remains as a challenge. The traditional way is to use a model with presumed parameters to generate a network, and then evaluate the fitness by summary statistics, which however cannot capture the complete network structures information and estimate parameter distribution. In this work we developed a novel method based on Approximate Bayesian Computation and modified Differential Evolution (ABC-DEP) that is capable of conducting model selection and parameter estimation simultaneously and detecting the underlying evolutionary mechanisms more accurately. We tested our method for its power in differentiating models and estimating parameters on the simulated data and found significant improvement in performance benchmark, as compared with a previous method. We further applied our method to real data of protein interaction networks in human and yeast. Our results show Duplication Attachment model as the predominant evolutionary mechanism for human PPI networks and Scale-Free model as the predominant mechanism for yeast PPI networks. PMID:26357273

Sixty-Five Million Years of Change in Temperature and Topography Explain Evolutionary History in Eastern North American Plethodontid Salamanders.

PubMed

Barnes, Richard; Clark, Adam Thomas

2017-07-01

For many taxa and systems, species richness peaks at midelevations. One potential explanation for this pattern is that large-scale changes in climate and geography have, over evolutionary time, selected for traits that are favored under conditions found in contemporary midelevation regions. To test this hypothesis, we use records of historical temperature and topographic changes over the past 65 Myr to construct a general simulation model of plethodontid salamander evolution in eastern North America. We then explore possible mechanisms constraining species to midelevation bands by using the model to predict plethodontid evolutionary history and contemporary geographic distributions. Our results show that models that incorporate both temperature and topographic changes are better able to predict these patterns, suggesting that both processes may have played an important role in driving plethodontid evolution in the region. Additionally, our model (whose annotated source code is included as a supplement) represents a proof of concept to encourage future work that takes advantage of recent advances in computing power to combine models of ecology, evolution, and earth history to better explain the abundance and distribution of species over time.

Evolutionary Telemetry and Command Processor (TCP) architecture

NASA Technical Reports Server (NTRS)

Schneider, John R.

1992-01-01

A low cost, modular, high performance, and compact Telemetry and Command Processor (TCP) is being built as the foundation of command and data handling subsystems for the next generation of satellites. The TCP product line will support command and telemetry requirements for small to large spacecraft and from low to high rate data transmission. It is compatible with the latest TDRSS, STDN and SGLS transponders and provides CCSDS protocol communications in addition to standard TDM formats. Its high performance computer provides computing resources for hosted flight software. Layered and modular software provides common services using standardized interfaces to applications thereby enhancing software re-use, transportability, and interoperability. The TCP architecture is based on existing standards, distributed networking, distributed and open system computing, and packet technology. The first TCP application is planned for the 94 SDIO SPAS 3 mission. The architecture enhances rapid tailoring of functions thereby reducing costs and schedules developed for individual spacecraft missions.

Multi-heuristic dynamic task allocation using genetic algorithms in a heterogeneous distributed system

PubMed Central

Page, Andrew J.; Keane, Thomas M.; Naughton, Thomas J.

2010-01-01

We present a multi-heuristic evolutionary task allocation algorithm to dynamically map tasks to processors in a heterogeneous distributed system. It utilizes a genetic algorithm, combined with eight common heuristics, in an effort to minimize the total execution time. It operates on batches of unmapped tasks and can preemptively remap tasks to processors. The algorithm has been implemented on a Java distributed system and evaluated with a set of six problems from the areas of bioinformatics, biomedical engineering, computer science and cryptography. Experiments using up to 150 heterogeneous processors show that the algorithm achieves better efficiency than other state-of-the-art heuristic algorithms. PMID:20862190

Computing the origin and evolution of the ribosome from its structure — Uncovering processes of macromolecular accretion benefiting synthetic biology

PubMed Central

Caetano-Anollés, Gustavo; Caetano-Anollés, Derek

2015-01-01

Accretion occurs pervasively in nature at widely different timeframes. The process also manifests in the evolution of macromolecules. Here we review recent computational and structural biology studies of evolutionary accretion that make use of the ideographic (historical, retrodictive) and nomothetic (universal, predictive) scientific frameworks. Computational studies uncover explicit timelines of accretion of structural parts in molecular repertoires and molecules. Phylogenetic trees of protein structural domains and proteomes and their molecular functions were built from a genomic census of millions of encoded proteins and associated terminal Gene Ontology terms. Trees reveal a ‘metabolic-first’ origin of proteins, the late development of translation, and a patchwork distribution of proteins in biological networks mediated by molecular recruitment. Similarly, the natural history of ancient RNA molecules inferred from trees of molecular substructures built from a census of molecular features shows patchwork-like accretion patterns. Ideographic analyses of ribosomal history uncover the early appearance of structures supporting mRNA decoding and tRNA translocation, the coevolution of ribosomal proteins and RNA, and a first evolutionary transition that brings ribosomal subunits together into a processive protein biosynthetic complex. Nomothetic structural biology studies of tertiary interactions and ancient insertions in rRNA complement these findings, once concentric layering assumptions are removed. Patterns of coaxial helical stacking reveal a frustrated dynamics of outward and inward ribosomal growth possibly mediated by structural grafting. The early rise of the ribosomal ‘turnstile’ suggests an evolutionary transition in natural biological computation. Results make explicit the need to understand processes of molecular growth and information transfer of macromolecules. PMID:27096056

Ensemble modeling of stochastic unsteady open-channel flow in terms of its time-space evolutionary probability distribution - Part 2: numerical application

NASA Astrophysics Data System (ADS)

Dib, Alain; Kavvas, M. Levent

2018-03-01

The characteristic form of the Saint-Venant equations is solved in a stochastic setting by using a newly proposed Fokker-Planck Equation (FPE) methodology. This methodology computes the ensemble behavior and variability of the unsteady flow in open channels by directly solving for the flow variables' time-space evolutionary probability distribution. The new methodology is tested on a stochastic unsteady open-channel flow problem, with an uncertainty arising from the channel's roughness coefficient. The computed statistical descriptions of the flow variables are compared to the results obtained through Monte Carlo (MC) simulations in order to evaluate the performance of the FPE methodology. The comparisons show that the proposed methodology can adequately predict the results of the considered stochastic flow problem, including the ensemble averages, variances, and probability density functions in time and space. Unlike the large number of simulations performed by the MC approach, only one simulation is required by the FPE methodology. Moreover, the total computational time of the FPE methodology is smaller than that of the MC approach, which could prove to be a particularly crucial advantage in systems with a large number of uncertain parameters. As such, the results obtained in this study indicate that the proposed FPE methodology is a powerful and time-efficient approach for predicting the ensemble average and variance behavior, in both space and time, for an open-channel flow process under an uncertain roughness coefficient.

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.

A new stellar spectrum interpolation algorithm and its application to Yunnan-III evolutionary population synthesis models

NASA Astrophysics Data System (ADS)

Cheng, Liantao; Zhang, Fenghui; Kang, Xiaoyu; Wang, Lang

2018-05-01

In evolutionary population synthesis (EPS) models, we need to convert stellar evolutionary parameters into spectra via interpolation in a stellar spectral library. For theoretical stellar spectral libraries, the spectrum grid is homogeneous on the effective-temperature and gravity plane for a given metallicity. It is relatively easy to derive stellar spectra. For empirical stellar spectral libraries, stellar parameters are irregularly distributed and the interpolation algorithm is relatively complicated. In those EPS models that use empirical stellar spectral libraries, different algorithms are used and the codes are often not released. Moreover, these algorithms are often complicated. In this work, based on a radial basis function (RBF) network, we present a new spectrum interpolation algorithm and its code. Compared with the other interpolation algorithms that are used in EPS models, it can be easily understood and is highly efficient in terms of computation. The code is written in MATLAB scripts and can be used on any computer system. Using it, we can obtain the interpolated spectra from a library or a combination of libraries. We apply this algorithm to several stellar spectral libraries (such as MILES, ELODIE-3.1 and STELIB-3.2) and give the integrated spectral energy distributions (ISEDs) of stellar populations (with ages from 1 Myr to 14 Gyr) by combining them with Yunnan-III isochrones. Our results show that the differences caused by the adoption of different EPS model components are less than 0.2 dex. All data about the stellar population ISEDs in this work and the RBF spectrum interpolation code can be obtained by request from the first author or downloaded from http://www1.ynao.ac.cn/˜zhangfh.

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

An Artificial Immune System-Inspired Multiobjective Evolutionary Algorithm with Application to the Detection of Distributed Computer Network Intrusions

DTIC Science & Technology

2007-03-01

Intelligence AIS Artificial Immune System ANN Artificial Neural Networks API Application Programming Interface BFS Breadth-First Search BIS Biological...problem domain is too large for only one algorithm’s application . It ranges from network - based sniffer systems, responsible for Enterprise-wide coverage...options to network administrators in choosing detectors to employ in future ID applications . Objectives Our hypothesis validity is based on a set

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.

Structural Analysis Methods for Structural Health Management of Future Aerospace Vehicles

NASA Technical Reports Server (NTRS)

Tessler, Alexander

2007-01-01

Two finite element based computational methods, Smoothing Element Analysis (SEA) and the inverse Finite Element Method (iFEM), are reviewed, and examples of their use for structural health monitoring are discussed. Due to their versatility, robustness, and computational efficiency, the methods are well suited for real-time structural health monitoring of future space vehicles, large space structures, and habitats. The methods may be effectively employed to enable real-time processing of sensing information, specifically for identifying three-dimensional deformed structural shapes as well as the internal loads. In addition, they may be used in conjunction with evolutionary algorithms to design optimally distributed sensors. These computational tools have demonstrated substantial promise for utilization in future Structural Health Management (SHM) systems.

Recombinant transfer in the basic genome of E. coli

DOE PAGES

Dixit, Purushottam; Studier, F. William; Pang, Tin Yau; ...

2015-07-07

An approximation to the ~4-Mbp basic genome shared by 32 strains of E. coli representing six evolutionary groups has been derived and analyzed computationally. A multiple-alignment of the 32 complete genome sequences was filtered to remove mobile elements and identify the most reliable ~90% of the aligned length of each of the resulting 496 basic-genome pairs. Patterns of single bp mutations (SNPs) in aligned pairs distinguish clonally inherited regions from regions where either genome has acquired DNA fragments from diverged genomes by homologous recombination since their last common ancestor. Such recombinant transfer is pervasive across the basic genome, mostly betweenmore » genomes in the same evolutionary group, and generates many unique mosaic patterns. The six least-diverged genome-pairs have one or two recombinant transfers of length ~40–115 kbp (and few if any other transfers), each containing one or more gene clusters known to confer strong selective advantage in some environments. Moderately diverged genome pairs (0.4–1% SNPs) show mosaic patterns of interspersed clonal and recombinant regions of varying lengths throughout the basic genome, whereas more highly diverged pairs within an evolutionary group or pairs between evolutionary groups having >1.3% SNPs have few clonal matches longer than a few kbp. Many recombinant transfers appear to incorporate fragments of the entering DNA produced by restriction systems of the recipient cell. A simple computational model can closely fit the data. As a result, most recombinant transfers seem likely to be due to generalized transduction by co-evolving populations of phages, which could efficiently distribute variability throughout bacterial genomes.« less

Recombinant transfer in the basic genome of E. coli

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

Dixit, Purushottam; Studier, F. William; Pang, Tin Yau

An approximation to the ~4-Mbp basic genome shared by 32 strains of E. coli representing six evolutionary groups has been derived and analyzed computationally. A multiple-alignment of the 32 complete genome sequences was filtered to remove mobile elements and identify the most reliable ~90% of the aligned length of each of the resulting 496 basic-genome pairs. Patterns of single bp mutations (SNPs) in aligned pairs distinguish clonally inherited regions from regions where either genome has acquired DNA fragments from diverged genomes by homologous recombination since their last common ancestor. Such recombinant transfer is pervasive across the basic genome, mostly betweenmore » genomes in the same evolutionary group, and generates many unique mosaic patterns. The six least-diverged genome-pairs have one or two recombinant transfers of length ~40–115 kbp (and few if any other transfers), each containing one or more gene clusters known to confer strong selective advantage in some environments. Moderately diverged genome pairs (0.4–1% SNPs) show mosaic patterns of interspersed clonal and recombinant regions of varying lengths throughout the basic genome, whereas more highly diverged pairs within an evolutionary group or pairs between evolutionary groups having >1.3% SNPs have few clonal matches longer than a few kbp. Many recombinant transfers appear to incorporate fragments of the entering DNA produced by restriction systems of the recipient cell. A simple computational model can closely fit the data. As a result, most recombinant transfers seem likely to be due to generalized transduction by co-evolving populations of phages, which could efficiently distribute variability throughout bacterial genomes.« less

Evolutionary dynamics on graphs: Efficient method for weak selection

NASA Astrophysics Data System (ADS)

Fu, Feng; Wang, Long; Nowak, Martin A.; Hauert, Christoph

2009-04-01

Investigating the evolutionary dynamics of game theoretical interactions in populations where individuals are arranged on a graph can be challenging in terms of computation time. Here, we propose an efficient method to study any type of game on arbitrary graph structures for weak selection. In this limit, evolutionary game dynamics represents a first-order correction to neutral evolution. Spatial correlations can be empirically determined under neutral evolution and provide the basis for formulating the game dynamics as a discrete Markov process by incorporating a detailed description of the microscopic dynamics based on the neutral correlations. This framework is then applied to one of the most intriguing questions in evolutionary biology: the evolution of cooperation. We demonstrate that the degree heterogeneity of a graph impedes cooperation and that the success of tit for tat depends not only on the number of rounds but also on the degree of the graph. Moreover, considering the mutation-selection equilibrium shows that the symmetry of the stationary distribution of states under weak selection is skewed in favor of defectors for larger selection strengths. In particular, degree heterogeneity—a prominent feature of scale-free networks—generally results in a more pronounced increase in the critical benefit-to-cost ratio required for evolution to favor cooperation as compared to regular graphs. This conclusion is corroborated by an analysis of the effects of population structures on the fixation probabilities of strategies in general 2×2 games for different types of graphs. Computer simulations confirm the predictive power of our method and illustrate the improved accuracy as compared to previous studies.

When the mean is not enough: Calculating fixation time distributions in birth-death processes.

PubMed

Ashcroft, Peter; Traulsen, Arne; Galla, Tobias

2015-10-01

Studies of fixation dynamics in Markov processes predominantly focus on the mean time to absorption. This may be inadequate if the distribution is broad and skewed. We compute the distribution of fixation times in one-step birth-death processes with two absorbing states. These are expressed in terms of the spectrum of the process, and we provide different representations as forward-only processes in eigenspace. These allow efficient sampling of fixation time distributions. As an application we study evolutionary game dynamics, where invading mutants can reach fixation or go extinct. We also highlight the median fixation time as a possible analog of mixing times in systems with small mutation rates and no absorbing states, whereas the mean fixation time has no such interpretation.

A Multi Agent System for Flow-Based Intrusion Detection Using Reputation and Evolutionary Computation

DTIC Science & Technology

2011-03-01

the actions of malicious and benign users of the Internet, as well as the engi- neering decisions giving rise to observed network topologies. Say and...with resilience, which is particularly important in the domain of quickly-evolving cyber threats. “Self-organization,” says Meadows, “is basically the...system design paradigm is to leverage the advantages of a distributed approach? What is meant by saying the witness conceptually rates the target

Quantum decision-maker theory and simulation

NASA Astrophysics Data System (ADS)

Zak, Michail; Meyers, Ronald E.; Deacon, Keith S.

2000-07-01

A quantum device simulating the human decision making process is introduced. It consists of quantum recurrent nets generating stochastic processes which represent the motor dynamics, and of classical neural nets describing the evolution of probabilities of these processes which represent the mental dynamics. The autonomy of the decision making process is achieved by a feedback from the mental to motor dynamics which changes the stochastic matrix based upon the probability distribution. This feedback replaces unavailable external information by an internal knowledge- base stored in the mental model in the form of probability distributions. As a result, the coupled motor-mental dynamics is described by a nonlinear version of Markov chains which can decrease entropy without an external source of information. Applications to common sense based decisions as well as to evolutionary games are discussed. An example exhibiting self-organization is computed using quantum computer simulation. Force on force and mutual aircraft engagements using the quantum decision maker dynamics are considered.

Bioinformatics education dissemination with an evolutionary problem solving perspective.

PubMed

Jungck, John R; Donovan, Samuel S; Weisstein, Anton E; Khiripet, Noppadon; Everse, Stephen J

2010-11-01

Bioinformatics is central to biology education in the 21st century. With the generation of terabytes of data per day, the application of computer-based tools to stored and distributed data is fundamentally changing research and its application to problems in medicine, agriculture, conservation and forensics. In light of this 'information revolution,' undergraduate biology curricula must be redesigned to prepare the next generation of informed citizens as well as those who will pursue careers in the life sciences. The BEDROCK initiative (Bioinformatics Education Dissemination: Reaching Out, Connecting and Knitting together) has fostered an international community of bioinformatics educators. The initiative's goals are to: (i) Identify and support faculty who can take leadership roles in bioinformatics education; (ii) Highlight and distribute innovative approaches to incorporating evolutionary bioinformatics data and techniques throughout undergraduate education; (iii) Establish mechanisms for the broad dissemination of bioinformatics resource materials and teaching models; (iv) Emphasize phylogenetic thinking and problem solving; and (v) Develop and publish new software tools to help students develop and test evolutionary hypotheses. Since 2002, BEDROCK has offered more than 50 faculty workshops around the world, published many resources and supported an environment for developing and sharing bioinformatics education approaches. The BEDROCK initiative builds on the established pedagogical philosophy and academic community of the BioQUEST Curriculum Consortium to assemble the diverse intellectual and human resources required to sustain an international reform effort in undergraduate bioinformatics education.

Phylogeography of Arenaria balearica L. (Caryophyllaceae): evolutionary history of a disjunct endemic from the Western Mediterranean continental islands.

PubMed

Bobo-Pinilla, Javier; Barrios de León, Sara B; Seguí Colomar, Jaume; Fenu, Giuseppe; Bacchetta, Gianluigi; Peñas de Giles, Julio; Martínez-Ortega, María Montserrat

2016-01-01

Although it has been traditionally accepted that Arenaria balearica (Caryophyllaceae) could be a relict Tertiary plant species, this has never been experimentally tested. Nor have the palaeohistorical reasons underlying the highly fragmented distribution of the species in the Western Mediterranean region been investigated. We have analysed AFLP data (213) and plastid DNA sequences (226) from a total of 250 plants from 29 populations sampled throughout the entire distribution range of the species in Majorca, Corsica, Sardinia, and the Tuscan Archipelago. The AFLP data analyses indicate very low geographic structure and population differentiation. Based on plastid DNA data, six alternative phylogeographic hypotheses were tested using Approximate Bayesian Computation (ABC). These analyses revealed ancient area fragmentation as the most probable scenario, which is in accordance with the star-like topology of the parsimony network that suggests a pattern of long term survival and subsequent in situ differentiation. Overall low levels of genetic diversity and plastid DNA variation were found, reflecting evolutionary stasis of a species preserved in locally long-term stable habitats.

Alignment-Independent Comparisons of Human Gastrointestinal Tract Microbial Communities in a Multidimensional 16S rRNA Gene Evolutionary Space▿

PubMed Central

Rudi, Knut; Zimonja, Monika; Kvenshagen, Bente; Rugtveit, Jarle; Midtvedt, Tore; Eggesbø, Merete

2007-01-01

We present a novel approach for comparing 16S rRNA gene clone libraries that is independent of both DNA sequence alignment and definition of bacterial phylogroups. These steps are the major bottlenecks in current microbial comparative analyses. We used direct comparisons of taxon density distributions in an absolute evolutionary coordinate space. The coordinate space was generated by using alignment-independent bilinear multivariate modeling. Statistical analyses for clone library comparisons were based on multivariate analysis of variance, partial least-squares regression, and permutations. Clone libraries from both adult and infant gastrointestinal tract microbial communities were used as biological models. We reanalyzed a library consisting of 11,831 clones covering complete colons from three healthy adults in addition to a smaller 390-clone library from infant feces. We show that it is possible to extract detailed information about microbial community structures using our alignment-independent method. Our density distribution analysis is also very efficient with respect to computer operation time, meeting the future requirements of large-scale screenings to understand the diversity and dynamics of microbial communities. PMID:17337554

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

Protein 3D Structure Computed from Evolutionary Sequence Variation

PubMed Central

Sheridan, Robert; Hopf, Thomas A.; Pagnani, Andrea; Zecchina, Riccardo; Sander, Chris

2011-01-01

The evolutionary trajectory of a protein through sequence space is constrained by its function. Collections of sequence homologs record the outcomes of millions of evolutionary experiments in which the protein evolves according to these constraints. Deciphering the evolutionary record held in these sequences and exploiting it for predictive and engineering purposes presents a formidable challenge. The potential benefit of solving this challenge is amplified by the advent of inexpensive high-throughput genomic sequencing. In this paper we ask whether we can infer evolutionary constraints from a set of sequence homologs of a protein. The challenge is to distinguish true co-evolution couplings from the noisy set of observed correlations. We address this challenge using a maximum entropy model of the protein sequence, constrained by the statistics of the multiple sequence alignment, to infer residue pair couplings. Surprisingly, we find that the strength of these inferred couplings is an excellent predictor of residue-residue proximity in folded structures. Indeed, the top-scoring residue couplings are sufficiently accurate and well-distributed to define the 3D protein fold with remarkable accuracy. We quantify this observation by computing, from sequence alone, all-atom 3D structures of fifteen test proteins from different fold classes, ranging in size from 50 to 260 residues., including a G-protein coupled receptor. These blinded inferences are de novo, i.e., they do not use homology modeling or sequence-similar fragments from known structures. The co-evolution signals provide sufficient information to determine accurate 3D protein structure to 2.7–4.8 Å Cα-RMSD error relative to the observed structure, over at least two-thirds of the protein (method called EVfold, details at http://EVfold.org). This discovery provides insight into essential interactions constraining protein evolution and will facilitate a comprehensive survey of the universe of protein structures, new strategies in protein and drug design, and the identification of functional genetic variants in normal and disease genomes. PMID:22163331

New trends in species distribution modelling

USGS Publications Warehouse

Zimmermann, Niklaus E.; Edwards, Thomas C.; Graham, Catherine H.; Pearman, Peter B.; Svenning, Jens-Christian

2010-01-01

Species distribution modelling has its origin in the late 1970s when computing capacity was limited. Early work in the field concentrated mostly on the development of methods to model effectively the shape of a species' response to environmental gradients (Austin 1987, Austin et al. 1990). The methodology and its framework were summarized in reviews 10–15 yr ago (Franklin 1995, Guisan and Zimmermann 2000), and these syntheses are still widely used as reference landmarks in the current distribution modelling literature. However, enormous advancements have occurred over the last decade, with hundreds – if not thousands – of publications on species distribution model (SDM) methodologies and their application to a broad set of conservation, ecological and evolutionary questions. With this special issue, originating from the third of a set of specialized SDM workshops (2008 Riederalp) entitled 'The Utility of Species Distribution Models as Tools for Conservation Ecology', we reflect on current trends and the progress achieved over the last decade.

DeCoSTAR: Reconstructing the Ancestral Organization of Genes or Genomes Using Reconciled Phylogenies

PubMed Central

Anselmetti, Yoann; Patterson, Murray; Ponty, Yann; B�rard, S�verine; Chauve, Cedric; Scornavacca, Celine; Daubin, Vincent; Tannier, Eric

2017-01-01

DeCoSTAR is a software that aims at reconstructing the organization of ancestral genes or genomes in the form of sets of neighborhood relations (adjacencies) between pairs of ancestral genes or gene domains. It can also improve the assembly of fragmented genomes by proposing evolutionary-induced adjacencies between scaffolding fragments. Ancestral genes or domains are deduced from reconciled phylogenetic trees under an evolutionary model that considers gains, losses, speciations, duplications, and transfers as possible events for gene evolution. Reconciliations are either given as input or computed with the ecceTERA package, into which DeCoSTAR is integrated. DeCoSTAR computes adjacency evolutionary scenarios using a scoring scheme based on a weighted sum of adjacency gains and breakages. Solutions, both optimal and near-optimal, are sampled according to the Boltzmann–Gibbs distribution centered around parsimonious solutions, and statistical supports on ancestral and extant adjacencies are provided. DeCoSTAR supports the features of previously contributed tools that reconstruct ancestral adjacencies, namely DeCo, DeCoLT, ART-DeCo, and DeClone. In a few minutes, DeCoSTAR can reconstruct the evolutionary history of domains inside genes, of gene fusion and fission events, or of gene order along chromosomes, for large data sets including dozens of whole genomes from all kingdoms of life. We illustrate the potential of DeCoSTAR with several applications: ancestral reconstruction of gene orders for Anopheles mosquito genomes, multidomain proteins in Drosophila, and gene fusion and fission detection in Actinobacteria. Availability: http://pbil.univ-lyon1.fr/software/DeCoSTAR (Last accessed April 24, 2017). PMID:28402423

More efficient evolutionary strategies for model calibration with watershed model for demonstration

NASA Astrophysics Data System (ADS)

Baggett, J. S.; Skahill, B. E.

2008-12-01

Evolutionary strategies allow automatic calibration of more complex models than traditional gradient based approaches, but they are more computationally intensive. We present several efficiency enhancements for evolution strategies, many of which are not new, but when combined have been shown to dramatically decrease the number of model runs required for calibration of synthetic problems. To reduce the number of expensive model runs we employ a surrogate objective function for an adaptively determined fraction of the population at each generation (Kern et al., 2006). We demonstrate improvements to the adaptive ranking strategy that increase its efficiency while sacrificing little reliability and further reduce the number of model runs required in densely sampled parts of parameter space. Furthermore, we include a gradient individual in each generation that is usually not selected when the search is in a global phase or when the derivatives are poorly approximated, but when selected near a smooth local minimum can dramatically increase convergence speed (Tahk et al., 2007). Finally, the selection of the gradient individual is used to adapt the size of the population near local minima. We show, by incorporating these enhancements into the Covariance Matrix Adaption Evolution Strategy (CMAES; Hansen, 2006), that their synergetic effect is greater than their individual parts. This hybrid evolutionary strategy exploits smooth structure when it is present but degrades to an ordinary evolutionary strategy, at worst, if smoothness is not present. Calibration of 2D-3D synthetic models with the modified CMAES requires approximately 10%-25% of the model runs of ordinary CMAES. Preliminary demonstration of this hybrid strategy will be shown for watershed model calibration problems. Hansen, N. (2006). The CMA Evolution Strategy: A Comparing Review. In J.A. Lozano, P. Larrañga, I. Inza and E. Bengoetxea (Eds.). Towards a new evolutionary computation. Advances in estimation of distribution algorithms. pp. 75-102, Springer Kern, S., N. Hansen and P. Koumoutsakos (2006). Local Meta-Models for Optimization Using Evolution Strategies. In Ninth International Conference on Parallel Problem Solving from Nature PPSN IX, Proceedings, pp.939-948, Berlin: Springer. Tahk, M., Woo, H., and Park. M, (2007). A hybrid optimization of evolutionary and gradient search. Engineering Optimization, (39), 87-104.

Bio-inspired algorithms applied to molecular docking simulations.

PubMed

Heberlé, G; de Azevedo, W F

2011-01-01

Nature as a source of inspiration has been shown to have a great beneficial impact on the development of new computational methodologies. In this scenario, analyses of the interactions between a protein target and a ligand can be simulated by biologically inspired algorithms (BIAs). These algorithms mimic biological systems to create new paradigms for computation, such as neural networks, evolutionary computing, and swarm intelligence. This review provides a description of the main concepts behind BIAs applied to molecular docking simulations. Special attention is devoted to evolutionary algorithms, guided-directed evolutionary algorithms, and Lamarckian genetic algorithms. Recent applications of these methodologies to protein targets identified in the Mycobacterium tuberculosis genome are described.

[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.

Knowledge Guided Evolutionary Algorithms in Financial Investing

ERIC Educational Resources Information Center

Wimmer, Hayden

2013-01-01

A large body of literature exists on evolutionary computing, genetic algorithms, decision trees, codified knowledge, and knowledge management systems; however, the intersection of these computing topics has not been widely researched. Moving through the set of all possible solutions--or traversing the search space--at random exhibits no control…

Automated design of spacecraft systems power subsystems

NASA Technical Reports Server (NTRS)

Terrile, Richard J.; Kordon, Mark; Mandutianu, Dan; Salcedo, Jose; Wood, Eric; Hashemi, Mona

2006-01-01

This paper discusses the application of evolutionary computing to a dynamic space vehicle power subsystem resource and performance simulation in a parallel processing environment. Our objective is to demonstrate the feasibility, application and advantage of using evolutionary computation techniques for the early design search and optimization of space systems.

A rapid application of GA-MODFLOW combined approach to optimization of well placement and operation for drought-ready groundwater reservoir design

NASA Astrophysics Data System (ADS)

Park, C.; Kim, Y.; Jang, H.

2016-12-01

Poor temporal distribution of precipitation increases winter drought risks in mountain valley areas in Korea. Since perennial streams or reservoirs for water use are rare in the areas, groundwater is usually a major water resource. Significant amount of the precipitation contributing groundwater recharge mostly occurs during the summer season. However, a volume of groundwater recharge is limited by rapid runoff because of the topographic characteristics such as steep hill and slope. A groundwater reservoir using artificial recharge method with rain water reuse can be a suitable solution to secure water resource for the mountain valley areas. Successful groundwater reservoir design depends on optimization of well placement and operation. This study introduces a combined approach using GA (Genetic Algorithm) and MODFLOW and its rapid application. The methodology is based on RAD (Rapid Application Development) concept in order to minimize the cost of implementation. DEAP (Distributed Evolutionary Algorithms in Python), a framework for prototyping and testing evolutionary algorithms, is applied for quick code development and CUDA (Compute Unified Device Architecture), a parallel computing platform using GPU (Graphics Processing Unit), is introduced to reduce runtime. The application was successfully applied to Samdeok-ri, Gosung, Korea. The site is located in a mountain valley area and unconfined aquifers are major source of water use. The results of the application produced the best location and optimized operation schedule of wells including pumping and injecting.

Using modified fruit fly optimisation algorithm to perform the function test and case studies

NASA Astrophysics Data System (ADS)

Pan, Wen-Tsao

2013-06-01

Evolutionary computation is a computing mode established by practically simulating natural evolutionary processes based on the concept of Darwinian Theory, and it is a common research method. The main contribution of this paper was to reinforce the function of searching for the optimised solution using the fruit fly optimization algorithm (FOA), in order to avoid the acquisition of local extremum solutions. The evolutionary computation has grown to include the concepts of animal foraging behaviour and group behaviour. This study discussed three common evolutionary computation methods and compared them with the modified fruit fly optimization algorithm (MFOA). It further investigated the ability of the three mathematical functions in computing extreme values, as well as the algorithm execution speed and the forecast ability of the forecasting model built using the optimised general regression neural network (GRNN) parameters. The findings indicated that there was no obvious difference between particle swarm optimization and the MFOA in regards to the ability to compute extreme values; however, they were both better than the artificial fish swarm algorithm and FOA. In addition, the MFOA performed better than the particle swarm optimization in regards to the algorithm execution speed, and the forecast ability of the forecasting model built using the MFOA's GRNN parameters was better than that of the other three forecasting models.

Social Media: Menagerie of Metrics

DTIC Science & Technology

2010-01-27

intelligence, an evolutionary algorithm (EA) is a subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm . An EA...Cloning - 22 Animals were cloned to date; genetic algorithms can help prediction (e.g. “elitism” - attempts to ensure selection by including performers...28, 2010 Evolutionary Algorithm • Evolutionary algorithm From Wikipedia, the free encyclopedia Artificial intelligence portal In artificial

Genealogical Working Distributions for Bayesian Model Testing with Phylogenetic Uncertainty

PubMed Central

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

2016-01-01

Marginal likelihood estimates to compare models using Bayes factors frequently accompany Bayesian phylogenetic inference. Approaches to estimate marginal likelihoods have garnered increased attention over the past decade. In particular, the introduction of path sampling (PS) and stepping-stone sampling (SS) into Bayesian phylogenetics has tremendously improved the accuracy of model selection. These sampling techniques are now used to evaluate complex evolutionary and population genetic models on empirical data sets, but considerable computational demands hamper their widespread adoption. Further, when very diffuse, but proper priors are specified for model parameters, numerical issues complicate the exploration of the priors, a necessary step in marginal likelihood estimation using PS or SS. To avoid such instabilities, generalized SS (GSS) has recently been proposed, introducing the concept of “working distributions” to facilitate—or shorten—the integration process that underlies marginal likelihood estimation. However, the need to fix the tree topology currently limits GSS in a coalescent-based framework. Here, we extend GSS by relaxing the fixed underlying tree topology assumption. To this purpose, we introduce a “working” distribution on the space of genealogies, which enables estimating marginal likelihoods while accommodating phylogenetic uncertainty. We propose two different “working” distributions that help GSS to outperform PS and SS in terms of accuracy when comparing demographic and evolutionary models applied to synthetic data and real-world examples. Further, we show that the use of very diffuse priors can lead to a considerable overestimation in marginal likelihood when using PS and SS, while still retrieving the correct marginal likelihood using both GSS approaches. The methods used in this article are available in BEAST, a powerful user-friendly software package to perform Bayesian evolutionary analyses. PMID:26526428

Aerodynamic Shape Optimization Using Hybridized Differential Evolution

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.

2003-01-01

An aerodynamic shape optimization method that uses an evolutionary algorithm known at Differential Evolution (DE) in conjunction with various hybridization strategies is described. DE is a simple and robust evolutionary strategy that has been proven effective in determining the global optimum for several difficult optimization problems. Various hybridization strategies for DE are explored, including the use of neural networks as well as traditional local search methods. A Navier-Stokes solver is used to evaluate the various intermediate designs and provide inputs to the hybrid DE optimizer. The method is implemented on distributed parallel computers so that new designs can be obtained within reasonable turnaround times. Results are presented for the inverse design of a turbine airfoil from a modern jet engine. (The final paper will include at least one other aerodynamic design application). The capability of the method to search large design spaces and obtain the optimal airfoils in an automatic fashion is demonstrated.

Random Evolutionary Dynamics Driven by Fitness and House-of-Cards Mutations: Sampling Formulae

NASA Astrophysics Data System (ADS)

Huillet, Thierry E.

2017-07-01

We first revisit the multi-allelic mutation-fitness balance problem, especially when mutations obey a house of cards condition, where the discrete-time deterministic evolutionary dynamics of the allelic frequencies derives from a Shahshahani potential. We then consider multi-allelic Wright-Fisher stochastic models whose deviation to neutrality is from the Shahshahani mutation/selection potential. We next focus on the weak selection, weak mutation cases and, making use of a Gamma calculus, we compute the normalizing partition functions of the invariant probability densities appearing in their Wright-Fisher diffusive approximations. Using these results, generalized Ewens sampling formulae (ESF) from the equilibrium distributions are derived. We start treating the ESF in the mixed mutation/selection potential case and then we restrict ourselves to the ESF in the simpler house-of-cards mutations only situation. We also address some issues concerning sampling problems from infinitely-many alleles weak limits.

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.

Using an object-based grid system to evaluate a newly developed EP approach to formulate SVMs as applied to the classification of organophosphate nerve agents

NASA Astrophysics Data System (ADS)

Land, Walker H., Jr.; Lewis, Michael; Sadik, Omowunmi; Wong, Lut; Wanekaya, Adam; Gonzalez, Richard J.; Balan, Arun

2004-04-01

This paper extends the classification approaches described in reference [1] in the following way: (1.) developing and evaluating a new method for evolving organophosphate nerve agent Support Vector Machine (SVM) classifiers using Evolutionary Programming, (2.) conducting research experiments using a larger database of organophosphate nerve agents, and (3.) upgrading the architecture to an object-based grid system for evaluating the classification of EP derived SVMs. Due to the increased threats of chemical and biological weapons of mass destruction (WMD) by international terrorist organizations, a significant effort is underway to develop tools that can be used to detect and effectively combat biochemical warfare. This paper reports the integration of multi-array sensors with Support Vector Machines (SVMs) for the detection of organophosphates nerve agents using a grid computing system called Legion. Grid computing is the use of large collections of heterogeneous, distributed resources (including machines, databases, devices, and users) to support large-scale computations and wide-area data access. Finally, preliminary results using EP derived support vector machines designed to operate on distributed systems have provided accurate classification results. In addition, distributed training time architectures are 50 times faster when compared to standard iterative training time methods.

Packets Distributing Evolutionary Algorithm Based on PSO for Ad Hoc Network

NASA Astrophysics Data System (ADS)

Xu, Xiao-Feng

2018-03-01

Wireless communication network has such features as limited bandwidth, changeful channel and dynamic topology, etc. Ad hoc network has lots of difficulties in accessing control, bandwidth distribution, resource assign and congestion control. Therefore, a wireless packets distributing Evolutionary algorithm based on PSO (DPSO)for Ad Hoc Network is proposed. Firstly, parameters impact on performance of network are analyzed and researched to obtain network performance effective function. Secondly, the improved PSO Evolutionary Algorithm is used to solve the optimization problem from local to global in the process of network packets distributing. The simulation results show that the algorithm can ensure fairness and timeliness of network transmission, as well as improve ad hoc network resource integrated utilization efficiency.

Reconstructing evolutionary trees in parallel for massive sequences.

PubMed

Zou, Quan; Wan, Shixiang; Zeng, Xiangxiang; Ma, Zhanshan Sam

2017-12-14

Building the evolutionary trees for massive unaligned DNA sequences is challenging and crucial. However, reconstructing evolutionary tree for ultra-large sequences is hard. Massive multiple sequence alignment is also challenging and time/space consuming. Hadoop and Spark are developed recently, which bring spring light for the classical computational biology problems. In this paper, we tried to solve the multiple sequence alignment and evolutionary reconstruction in parallel. HPTree, which is developed in this paper, can deal with big DNA sequence files quickly. It works well on the >1GB files, and gets better performance than other evolutionary reconstruction tools. Users could use HPTree for reonstructing evolutioanry trees on the computer clusters or cloud platform (eg. Amazon Cloud). HPTree could help on population evolution research and metagenomics analysis. In this paper, we employ the Hadoop and Spark platform and design an evolutionary tree reconstruction software tool for unaligned massive DNA sequences. Clustering and multiple sequence alignment are done in parallel. Neighbour-joining model was employed for the evolutionary tree building. We opened our software together with source codes via http://lab.malab.cn/soft/HPtree/ .

MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

PubMed

Kumar, Sudhir; Stecher, Glen; Li, Michael; Knyaz, Christina; Tamura, Koichiro

2018-06-01

The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.

Eco-Evo PVAs: Incorporating Eco-Evolutionary Processes into Population Viability Models

EPA Science Inventory

We synthesize how advances in computational methods and population genomics can be combined within an Ecological-Evolutionary (Eco-Evo) PVA model. Eco-Evo PVA models are powerful new tools for understanding the influence of evolutionary processes on plant and animal population pe...

Crowd Computing as a Cooperation Problem: An Evolutionary Approach

NASA Astrophysics Data System (ADS)

Christoforou, Evgenia; Fernández Anta, Antonio; Georgiou, Chryssis; Mosteiro, Miguel A.; Sánchez, Angel

2013-05-01

Cooperation is one of the socio-economic issues that has received more attention from the physics community. The problem has been mostly considered by studying games such as the Prisoner's Dilemma or the Public Goods Game. Here, we take a step forward by studying cooperation in the context of crowd computing. We introduce a model loosely based on Principal-agent theory in which people (workers) contribute to the solution of a distributed problem by computing answers and reporting to the problem proposer (master). To go beyond classical approaches involving the concept of Nash equilibrium, we work on an evolutionary framework in which both the master and the workers update their behavior through reinforcement learning. Using a Markov chain approach, we show theoretically that under certain----not very restrictive—conditions, the master can ensure the reliability of the answer resulting of the process. Then, we study the model by numerical simulations, finding that convergence, meaning that the system reaches a point in which it always produces reliable answers, may in general be much faster than the upper bounds given by the theoretical calculation. We also discuss the effects of the master's level of tolerance to defectors, about which the theory does not provide information. The discussion shows that the system works even with very large tolerances. We conclude with a discussion of our results and possible directions to carry this research further.

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.

Learning Evolution and the Nature of Science Using Evolutionary Computing and Artificial Life

ERIC Educational Resources Information Center

Pennock, Robert T.

2007-01-01

Because evolution in natural systems happens so slowly, it is difficult to design inquiry-based labs where students can experiment and observe evolution in the way they can when studying other phenomena. New research in evolutionary computation and artificial life provides a solution to this problem. This paper describes a new A-Life software…

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.

Using concepts from biology to improve problem-solving methods

NASA Astrophysics Data System (ADS)

Goodman, Erik D.; Rothwell, Edward J.; Averill, Ronald C.

2011-06-01

Observing nature has been a cornerstone of engineering design. Today, engineers look not only at finished products, but imitate the evolutionary process by which highly optimized artifacts have appeared in nature. Evolutionary computation began by capturing only the simplest ideas of evolution, but today, researchers study natural evolution and incorporate an increasing number of concepts in order to evolve solutions to complex engineering problems. At the new BEACON Center for the Study of Evolution in Action, studies in the lab and field and in silico are laying the groundwork for new tools for evolutionary engineering design. This paper, which accompanies a keynote address, describes various steps in development and application of evolutionary computation, particularly as regards sensor design, and sets the stage for future advances.

Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity.

PubMed

Almendro, Vanessa; Cheng, Yu-Kang; Randles, Amanda; Itzkovitz, Shalev; Marusyk, Andriy; Ametller, Elisabet; Gonzalez-Farre, Xavier; Muñoz, Montse; Russnes, Hege G; Helland, Aslaug; Rye, Inga H; Borresen-Dale, Anne-Lise; Maruyama, Reo; van Oudenaarden, Alexander; Dowsett, Mitchell; Jones, Robin L; Reis-Filho, Jorge; Gascon, Pere; Gönen, Mithat; Michor, Franziska; Polyak, Kornelia

2014-02-13

Cancer therapy exerts a strong selection pressure that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here, we report the analysis of cellular heterogeneity for genetic and phenotypic features and their spatial distribution in breast tumors pre- and post-neoadjuvant chemotherapy. We found that intratumor genetic diversity was tumor-subtype specific, and it did not change during treatment in tumors with partial or no response. However, lower pretreatment genetic diversity was significantly associated with pathologic complete response. In contrast, phenotypic diversity was different between pre- and posttreatment samples. We also observed significant changes in the spatial distribution of cells with distinct genetic and phenotypic features. We used these experimental data to develop a stochastic computational model to infer tumor growth patterns and evolutionary dynamics. Our results highlight the importance of integrated analysis of genotypes and phenotypes of single cells in intact tissues to predict tumor evolution. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of cellular diversity for genetic and phenotypic features

PubMed Central

Almendro, Vanessa; Cheng, Yu-Kang; Randles, Amanda; Itzkovitz, Shalev; Marusyk, Andriy; Ametller, Elisabet; Gonzalez-Farre, Xavier; Muñoz, Montse; Russnes, Hege G.; Helland, Åslaug; Rye, Inga H.; Borresen-Dale, Anne-Lise; Maruyama, Reo; van Oudenaarden, Alexander; Dowsett, Mitchell; Jones, Robin L.; Reis-Filho, Jorge; Gascon, Pere; Gönen, Mithat; Michor, Franziska; Polyak, Kornelia

2014-01-01

SUMMARY Cancer therapy exerts a strong selection pressure that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here we report the analysis of cellular heterogeneity for genetic and phenotypic features and their spatial distribution in breast tumors pre- and post-neoadjuvant chemotherapy. We found that intratumor genetic diversity was tumor subtype-specific and it did not change during treatment in tumors with partial or no response. However, lower pre-treatment genetic diversity was significantly associated with complete pathologic response. In contrast, phenotypic diversity was different between pre- and post-treatment samples. We also observed significant changes in the spatial distribution of cells with distinct genetic and phenotypic features. We used these experimental data to develop a stochastic computational model to infer tumor growth patterns and evolutionary dynamics. Our results highlight the importance of integrated analysis of genotypes and phenotypes of single cells in intact tissues to predict tumor evolution. PMID:24462293

Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity

DOE PAGES

Almendro, Vanessa; Cheng, Yu -Kang; Randles, Amanda; ...

2014-02-01

Cancer therapy exerts a strong selection pressure that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here, we report the analysis of cellular heterogeneity for genetic and phenotypic features and their spatial distribution in breast tumors pre- and post-neoadjuvant chemotherapy. We found that intratumor genetic diversity was tumor-subtype specific, and it did not change during treatment in tumors with partial or no response. However, lower pretreatment genetic diversity was significantly associated with pathologic complete response. In contrast, phenotypic diversity was different between pre- and post-treatment samples. We also observed significant changes in the spatialmore » distribution of cells with distinct genetic and phenotypic features. We used these experimental data to develop a stochastic computational model to infer tumor growth patterns and evolutionary dynamics. Our results highlight the importance of integrated analysis of genotypes and phenotypes of single cells in intact tissues to predict tumor evolution.« less

Evolutionary Computation for the Identification of Emergent Behavior in Autonomous Systems

NASA Technical Reports Server (NTRS)

Terrile, Richard J.; Guillaume, Alexandre

2009-01-01

Over the past several years the Center for Evolutionary Computation and Automated Design at the Jet Propulsion Laboratory has developed a technique based on Evolutionary Computational Methods (ECM) that allows for the automated optimization of complex computationally modeled systems. An important application of this technique is for the identification of emergent behaviors in autonomous systems. Mobility platforms such as rovers or airborne vehicles are now being designed with autonomous mission controllers that can find trajectories over a solution space that is larger than can reasonably be tested. It is critical to identify control behaviors that are not predicted and can have surprising results (both good and bad). These emergent behaviors need to be identified, characterized and either incorporated into or isolated from the acceptable range of control characteristics. We use cluster analysis of automatically retrieved solutions to identify isolated populations of solutions with divergent behaviors.

Exploring Evolutionary Patterns in Genetic Sequence: A Computer Exercise

ERIC Educational Resources Information Center

Shumate, Alice M.; Windsor, Aaron J.

2010-01-01

The increase in publications presenting molecular evolutionary analyses and the availability of comparative sequence data through resources such as NCBI's GenBank underscore the necessity of providing undergraduates with hands-on sequence analysis skills in an evolutionary context. This need is particularly acute given that students have been…

Evolutionary conservativeness of electric field in the Cu,Zn superoxide dismutase active site. Evidence for co-ordinated mutation of charged amino acid residues.

PubMed

Desideri, A; Falconi, M; Polticelli, F; Bolognesi, M; Djinovic, K; Rotilio, G

1992-01-05

Equipotential lines were calculated, using the Poisson-Boltzmann equation, for six Cu,Zn superoxide dismutases with different protein electric charge and various degrees of sequence homology, namely those from ox, pig, sheep, yeast, and the isoenzymes A and B from the amphibian Xenopus laevis. The three-dimensional structures of the porcine and ovine superoxide dismutases were obtained by molecular modelling reconstruction using the structure of the highly homologous bovine enzyme as a template. The three-dimensional structure of the evolutionary distant yeast Cu,Zn superoxide dismutase was recently resolved by us, while computer-modelled structures are available for X. laevis isoenzymes. The six proteins display large differences in the net protein charge and distribution of electrically charged surface residues but the trend of the equipotential lines in the proximity of the active sites was found to be constant in all cases. These results are in line with the very similar catlytic rate constants experimentally measured for the corresponding enzyme activities. This analysis shows that electrostatic guidance for the enzyme-substrate interaction in Cu,Zn superoxide dismutases is related to a spatial distribution of charges, arranged so as to maintain, in the area surrounding the active sites, an identical electrostatic potential distribution, which is conserved in the evolution of this protein family.

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.

Target Identification Using Harmonic Wavelet Based ISAR Imaging

NASA Astrophysics Data System (ADS)

Shreyamsha Kumar, B. K.; Prabhakar, B.; Suryanarayana, K.; Thilagavathi, V.; Rajagopal, R.

2006-12-01

A new approach has been proposed to reduce the computations involved in the ISAR imaging, which uses harmonic wavelet-(HW) based time-frequency representation (TFR). Since the HW-based TFR falls into a category of nonparametric time-frequency (T-F) analysis tool, it is computationally efficient compared to parametric T-F analysis tools such as adaptive joint time-frequency transform (AJTFT), adaptive wavelet transform (AWT), and evolutionary AWT (EAWT). Further, the performance of the proposed method of ISAR imaging is compared with the ISAR imaging by other nonparametric T-F analysis tools such as short-time Fourier transform (STFT) and Choi-Williams distribution (CWD). In the ISAR imaging, the use of HW-based TFR provides similar/better results with significant (92%) computational advantage compared to that obtained by CWD. The ISAR images thus obtained are identified using a neural network-based classification scheme with feature set invariant to translation, rotation, and scaling.

Testing for Independence between Evolutionary Processes.

PubMed

Behdenna, Abdelkader; Pothier, Joël; Abby, Sophie S; Lambert, Amaury; Achaz, Guillaume

2016-09-01

Evolutionary events co-occurring along phylogenetic trees usually point to complex adaptive phenomena, sometimes implicating epistasis. While a number of methods have been developed to account for co-occurrence of events on the same internal or external branch of an evolutionary tree, there is a need to account for the larger diversity of possible relative positions of events in a tree. Here we propose a method to quantify to what extent two or more evolutionary events are associated on a phylogenetic tree. The method is applicable to any discrete character, like substitutions within a coding sequence or gains/losses of a biological function. Our method uses a general approach to statistically test for significant associations between events along the tree, which encompasses both events inseparable on the same branch, and events genealogically ordered on different branches. It assumes that the phylogeny and themapping of branches is known without errors. We address this problem from the statistical viewpoint by a linear algebra representation of the localization of the evolutionary events on the tree.We compute the full probability distribution of the number of paired events occurring in the same branch or in different branches of the tree, under a null model of independence where each type of event occurs at a constant rate uniformly inthephylogenetic tree. The strengths andweaknesses of themethodare assessed via simulations;we then apply the method to explore the loss of cell motility in intracellular pathogens. © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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

On the Origin of Protein Superfamilies and Superfolds

NASA Astrophysics Data System (ADS)

Magner, Abram; Szpankowski, Wojciech; Kihara, Daisuke

2015-02-01

Distributions of protein families and folds in genomes are highly skewed, having a small number of prevalent superfamiles/superfolds and a large number of families/folds of a small size. Why are the distributions of protein families and folds skewed? Why are there only a limited number of protein families? Here, we employ an information theoretic approach to investigate the protein sequence-structure relationship that leads to the skewed distributions. We consider that protein sequences and folds constitute an information theoretic channel and computed the most efficient distribution of sequences that code all protein folds. The identified distributions of sequences and folds are found to follow a power law, consistent with those observed for proteins in nature. Importantly, the skewed distributions of sequences and folds are suggested to have different origins: the skewed distribution of sequences is due to evolutionary pressure to achieve efficient coding of necessary folds, whereas that of folds is based on the thermodynamic stability of folds. The current study provides a new information theoretic framework for proteins that could be widely applied for understanding protein sequences, structures, functions, and interactions.

Open Reading Frame Phylogenetic Analysis on the Cloud

PubMed Central

2013-01-01

Phylogenetic analysis has become essential in researching the evolutionary relationships between viruses. These relationships are depicted on phylogenetic trees, in which viruses are grouped based on sequence similarity. Viral evolutionary relationships are identified from open reading frames rather than from complete sequences. Recently, cloud computing has become popular for developing internet-based bioinformatics tools. Biocloud is an efficient, scalable, and robust bioinformatics computing service. In this paper, we propose a cloud-based open reading frame phylogenetic analysis service. The proposed service integrates the Hadoop framework, virtualization technology, and phylogenetic analysis methods to provide a high-availability, large-scale bioservice. In a case study, we analyze the phylogenetic relationships among Norovirus. Evolutionary relationships are elucidated by aligning different open reading frame sequences. The proposed platform correctly identifies the evolutionary relationships between members of Norovirus. PMID:23671843

Evolutionary Technologies: Fundamentals and Applications to Information/Communication Systems and Manufacturing/Logistics Systems

NASA Astrophysics Data System (ADS)

Gen, Mitsuo; Kawakami, Hiroshi; Tsujimura, Yasuhiro; Handa, Hisashi; Lin, Lin; Okamoto, Azuma

As efficient utilization of computational resources is increasing, evolutionary technology based on the Genetic Algorithm (GA), Genetic Programming (GP), Evolution Strategy (ES) and other Evolutionary Computations (ECs) is making rapid progress, and its social recognition and the need as applied technology are increasing. This is explained by the facts that EC offers higher robustness for knowledge information processing systems, intelligent production and logistics systems, most advanced production scheduling and other various real-world problems compared to the approaches based on conventional theories, and EC ensures flexible applicability and usefulness for any unknown system environment even in a case where accurate mathematical modeling fails in the formulation. In this paper, we provide a comprehensive survey of the current state-of-the-art in the fundamentals and applications of evolutionary technologies.

Computationally mapping sequence space to understand evolutionary protein engineering.

PubMed

Armstrong, Kathryn A; Tidor, Bruce

2008-01-01

Evolutionary protein engineering has been dramatically successful, producing a wide variety of new proteins with altered stability, binding affinity, and enzymatic activity. However, the success of such procedures is often unreliable, and the impact of the choice of protein, engineering goal, and evolutionary procedure is not well understood. We have created a framework for understanding aspects of the protein engineering process by computationally mapping regions of feasible sequence space for three small proteins using structure-based design protocols. We then tested the ability of different evolutionary search strategies to explore these sequence spaces. The results point to a non-intuitive relationship between the error-prone PCR mutation rate and the number of rounds of replication. The evolutionary relationships among feasible sequences reveal hub-like sequences that serve as particularly fruitful starting sequences for evolutionary search. Moreover, genetic recombination procedures were examined, and tradeoffs relating sequence diversity and search efficiency were identified. This framework allows us to consider the impact of protein structure on the allowed sequence space and therefore on the challenges that each protein presents to error-prone PCR and genetic recombination procedures.

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.

GALAXY: A new hybrid MOEA for the optimal design of Water Distribution Systems

NASA Astrophysics Data System (ADS)

Wang, Q.; Savić, D. A.; Kapelan, Z.

2017-03-01

A new hybrid optimizer, called genetically adaptive leaping algorithm for approximation and diversity (GALAXY), is proposed for dealing with the discrete, combinatorial, multiobjective design of Water Distribution Systems (WDSs), which is NP-hard and computationally intensive. The merit of GALAXY is its ability to alleviate to a great extent the parameterization issue and the high computational overhead. It follows the generational framework of Multiobjective Evolutionary Algorithms (MOEAs) and includes six search operators and several important strategies. These operators are selected based on their leaping ability in the objective space from the global and local search perspectives. These strategies steer the optimization and balance the exploration and exploitation aspects simultaneously. A highlighted feature of GALAXY lies in the fact that it eliminates majority of parameters, thus being robust and easy-to-use. The comparative studies between GALAXY and three representative MOEAs on five benchmark WDS design problems confirm its competitiveness. GALAXY can identify better converged and distributed boundary solutions efficiently and consistently, indicating a much more balanced capability between the global and local search. Moreover, its advantages over other MOEAs become more substantial as the complexity of the design problem increases.

Statistical Analysis of Hurst Exponents of Essential/Nonessential Genes in 33 Bacterial Genomes

PubMed Central

Liu, Xiao; Wang, Baojin; Xu, Luo

2015-01-01

Methods for identifying essential genes currently depend predominantly on biochemical experiments. However, there is demand for improved computational methods for determining gene essentiality. In this study, we used the Hurst exponent, a characteristic parameter to describe long-range correlation in DNA, and analyzed its distribution in 33 bacterial genomes. In most genomes (31 out of 33) the significance levels of the Hurst exponents of the essential genes were significantly higher than for the corresponding full-gene-set, whereas the significance levels of the Hurst exponents of the nonessential genes remained unchanged or increased only slightly. All of the Hurst exponents of essential genes followed a normal distribution, with one exception. We therefore propose that the distribution feature of Hurst exponents of essential genes can be used as a classification index for essential gene prediction in bacteria. For computer-aided design in the field of synthetic biology, this feature can build a restraint for pre- or post-design checking of bacterial essential genes. Moreover, considering the relationship between gene essentiality and evolution, the Hurst exponents could be used as a descriptive parameter related to evolutionary level, or be added to the annotation of each gene. PMID:26067107

Characterising RNA secondary structure space using information entropy

PubMed Central

2013-01-01

Comparative methods for RNA secondary structure prediction use evolutionary information from RNA alignments to increase prediction accuracy. The model is often described in terms of stochastic context-free grammars (SCFGs), which generate a probability distribution over secondary structures. It is, however, unclear how this probability distribution changes as a function of the input alignment. As prediction programs typically only return a single secondary structure, better characterisation of the underlying probability space of RNA secondary structures is of great interest. In this work, we show how to efficiently compute the information entropy of the probability distribution over RNA secondary structures produced for RNA alignments by a phylo-SCFG, and implement it for the PPfold model. We also discuss interpretations and applications of this quantity, including how it can clarify reasons for low prediction reliability scores. PPfold and its source code are available from http://birc.au.dk/software/ppfold/. PMID:23368905

The Collaborative Seismic Earth Model: Generation 1

NASA Astrophysics Data System (ADS)

Fichtner, Andreas; van Herwaarden, Dirk-Philip; Afanasiev, Michael; SimutÄ--, SaulÄ--; Krischer, Lion; ćubuk-Sabuncu, Yeşim; Taymaz, Tuncay; Colli, Lorenzo; Saygin, Erdinc; Villaseñor, Antonio; Trampert, Jeannot; Cupillard, Paul; Bunge, Hans-Peter; Igel, Heiner

2018-05-01

We present a general concept for evolutionary, collaborative, multiscale inversion of geophysical data, specifically applied to the construction of a first-generation Collaborative Seismic Earth Model. This is intended to address the limited resources of individual researchers and the often limited use of previously accumulated knowledge. Model evolution rests on a Bayesian updating scheme, simplified into a deterministic method that honors today's computational restrictions. The scheme is able to harness distributed human and computing power. It furthermore handles conflicting updates, as well as variable parameterizations of different model refinements or different inversion techniques. The first-generation Collaborative Seismic Earth Model comprises 12 refinements from full seismic waveform inversion, ranging from regional crustal- to continental-scale models. A global full-waveform inversion ensures that regional refinements translate into whole-Earth structure.

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.

Optimal time points sampling in pathway modelling.

PubMed

Hu, Shiyan

2004-01-01

Modelling cellular dynamics based on experimental data is at the heart of system biology. Considerable progress has been made to dynamic pathway modelling as well as the related parameter estimation. However, few of them gives consideration for the issue of optimal sampling time selection for parameter estimation. Time course experiments in molecular biology rarely produce large and accurate data sets and the experiments involved are usually time consuming and expensive. Therefore, to approximate parameters for models with only few available sampling data is of significant practical value. For signal transduction, the sampling intervals are usually not evenly distributed and are based on heuristics. In the paper, we investigate an approach to guide the process of selecting time points in an optimal way to minimize the variance of parameter estimates. In the method, we first formulate the problem to a nonlinear constrained optimization problem by maximum likelihood estimation. We then modify and apply a quantum-inspired evolutionary algorithm, which combines the advantages of both quantum computing and evolutionary computing, to solve the optimization problem. The new algorithm does not suffer from the morass of selecting good initial values and being stuck into local optimum as usually accompanied with the conventional numerical optimization techniques. The simulation results indicate the soundness of the new method.

Efficient Evaluation Functions for Multi-Rover Systems

NASA Technical Reports Server (NTRS)

Agogino, Adrian; Tumer, Kagan

2004-01-01

Evolutionary computation can be a powerful tool in cresting a control policy for a single agent receiving local continuous input. This paper extends single-agent evolutionary computation to multi-agent systems, where a collection of agents strives to maximize a global fitness evaluation function that rates the performance of the entire system. This problem is solved in a distributed manner, where each agent evolves its own population of neural networks that are used as the control policies for the agent. Each agent evolves its population using its own agent-specific fitness evaluation function. We propose to create these agent-specific evaluation functions using the theory of collectives to avoid the coordination problem where each agent evolves a population that maximizes its own fitness function, yet the system has a whole achieves low values of the global fitness function. Instead we will ensure that each fitness evaluation function is both "aligned" with the global evaluation function and is "learnable," i.e., the agents can readily see how their behavior affects their evaluation function. We then show how these agent-specific evaluation functions outperform global evaluation methods by up to 600% in a domain where a set of rovers attempt to maximize the amount of information observed while navigating through a simulated environment.

Stochastic Evolutionary Algorithms for Planning Robot Paths

NASA Technical Reports Server (NTRS)

Fink, Wolfgang; Aghazarian, Hrand; Huntsberger, Terrance; Terrile, Richard

2006-01-01

A computer program implements stochastic evolutionary algorithms for planning and optimizing collision-free paths for robots and their jointed limbs. Stochastic evolutionary algorithms can be made to produce acceptably close approximations to exact, optimal solutions for path-planning problems while often demanding much less computation than do exhaustive-search and deterministic inverse-kinematics algorithms that have been used previously for this purpose. Hence, the present software is better suited for application aboard robots having limited computing capabilities (see figure). The stochastic aspect lies in the use of simulated annealing to (1) prevent trapping of an optimization algorithm in local minima of an energy-like error measure by which the fitness of a trial solution is evaluated while (2) ensuring that the entire multidimensional configuration and parameter space of the path-planning problem is sampled efficiently with respect to both robot joint angles and computation time. Simulated annealing is an established technique for avoiding local minima in multidimensional optimization problems, but has not, until now, been applied to planning collision-free robot paths by use of low-power computers.

Biomimetic design processes in architecture: morphogenetic and evolutionary computational design.

PubMed

Menges, Achim

2012-03-01

Design computation has profound impact on architectural design methods. This paper explains how computational design enables the development of biomimetic design processes specific to architecture, and how they need to be significantly different from established biomimetic processes in engineering disciplines. The paper first explains the fundamental difference between computer-aided and computational design in architecture, as the understanding of this distinction is of critical importance for the research presented. Thereafter, the conceptual relation and possible transfer of principles from natural morphogenesis to design computation are introduced and the related developments of generative, feature-based, constraint-based, process-based and feedback-based computational design methods are presented. This morphogenetic design research is then related to exploratory evolutionary computation, followed by the presentation of two case studies focusing on the exemplary development of spatial envelope morphologies and urban block morphologies.

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.

Big cat phylogenies, consensus trees, and computational thinking.

PubMed

Sul, Seung-Jin; Williams, Tiffani L

2011-07-01

Phylogenetics seeks to deduce the pattern of relatedness between organisms by using a phylogeny or evolutionary tree. For a given set of organisms or taxa, there may be many evolutionary trees depicting how these organisms evolved from a common ancestor. As a result, consensus trees are a popular approach for summarizing the shared evolutionary relationships in a group of trees. We examine these consensus techniques by studying how the pantherine lineage of cats (clouded leopard, jaguar, leopard, lion, snow leopard, and tiger) evolved, which is hotly debated. While there are many phylogenetic resources that describe consensus trees, there is very little information, written for biologists, regarding the underlying computational techniques for building them. The pantherine cats provide us with a small, relevant example to explore the computational techniques (such as sorting numbers, hashing functions, and traversing trees) for constructing consensus trees. Our hope is that life scientists enjoy peeking under the computational hood of consensus tree construction and share their positive experiences with others in their community.

MEGA5: Molecular Evolutionary Genetics Analysis Using Maximum Likelihood, Evolutionary Distance, and Maximum Parsimony Methods

PubMed Central

Tamura, Koichiro; Peterson, Daniel; Peterson, Nicholas; Stecher, Glen; Nei, Masatoshi; Kumar, Sudhir

2011-01-01

Comparative analysis of molecular sequence data is essential for reconstructing the evolutionary histories of species and inferring the nature and extent of selective forces shaping the evolution of genes and species. Here, we announce the release of Molecular Evolutionary Genetics Analysis version 5 (MEGA5), which is a user-friendly software for mining online databases, building sequence alignments and phylogenetic trees, and using methods of evolutionary bioinformatics in basic biology, biomedicine, and evolution. The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models (nucleotide or amino acid), inferring ancestral states and sequences (along with probabilities), and estimating evolutionary rates site-by-site. In computer simulation analyses, ML tree inference algorithms in MEGA5 compared favorably with other software packages in terms of computational efficiency and the accuracy of the estimates of phylogenetic trees, substitution parameters, and rate variation among sites. The MEGA user interface has now been enhanced to be activity driven to make it easier for the use of both beginners and experienced scientists. This version of MEGA is intended for the Windows platform, and it has been configured for effective use on Mac OS X and Linux desktops. It is available free of charge from http://www.megasoftware.net. PMID:21546353

The evolution of distributed sensing and collective computation in animal populations

PubMed Central

Hein, Andrew M; Rosenthal, Sara Brin; Hagstrom, George I; Berdahl, Andrew; Torney, Colin J; Couzin, Iain D

2015-01-01

Many animal groups exhibit rapid, coordinated collective motion. Yet, the evolutionary forces that cause such collective responses to evolve are poorly understood. Here, we develop analytical methods and evolutionary simulations based on experimental data from schooling fish. We use these methods to investigate how populations evolve within unpredictable, time-varying resource environments. We show that populations evolve toward a distinctive regime in behavioral phenotype space, where small responses of individuals to local environmental cues cause spontaneous changes in the collective state of groups. These changes resemble phase transitions in physical systems. Through these transitions, individuals evolve the emergent capacity to sense and respond to resource gradients (i.e. individuals perceive gradients via social interactions, rather than sensing gradients directly), and to allocate themselves among distinct, distant resource patches. Our results yield new insight into how natural selection, acting on selfish individuals, results in the highly effective collective responses evident in nature. DOI: http://dx.doi.org/10.7554/eLife.10955.001 PMID:26652003

Evolutionary and Functional Relationships in the Truncated Hemoglobin Family.

PubMed

Bustamante, Juan P; Radusky, Leandro; Boechi, Leonardo; Estrin, Darío A; Ten Have, Arjen; Martí, Marcelo A

2016-01-01

Predicting function from sequence is an important goal in current biological research, and although, broad functional assignment is possible when a protein is assigned to a family, predicting functional specificity with accuracy is not straightforward. If function is provided by key structural properties and the relevant properties can be computed using the sequence as the starting point, it should in principle be possible to predict function in detail. The truncated hemoglobin family presents an interesting benchmark study due to their ubiquity, sequence diversity in the context of a conserved fold and the number of characterized members. Their functions are tightly related to O2 affinity and reactivity, as determined by the association and dissociation rate constants, both of which can be predicted and analyzed using in-silico based tools. In the present work we have applied a strategy, which combines homology modeling with molecular based energy calculations, to predict and analyze function of all known truncated hemoglobins in an evolutionary context. Our results show that truncated hemoglobins present conserved family features, but that its structure is flexible enough to allow the switch from high to low affinity in a few evolutionary steps. Most proteins display moderate to high oxygen affinities and multiple ligand migration paths, which, besides some minor trends, show heterogeneous distributions throughout the phylogenetic tree, again suggesting fast functional adaptation. Our data not only deepens our comprehension of the structural basis governing ligand affinity, but they also highlight some interesting functional evolutionary trends.

Evolutionary and Functional Relationships in the Truncated Hemoglobin Family

PubMed Central

Bustamante, Juan P.; Radusky, Leandro; Boechi, Leonardo; Estrin, Darío A.; ten Have, Arjen; Martí, Marcelo A.

2016-01-01

Predicting function from sequence is an important goal in current biological research, and although, broad functional assignment is possible when a protein is assigned to a family, predicting functional specificity with accuracy is not straightforward. If function is provided by key structural properties and the relevant properties can be computed using the sequence as the starting point, it should in principle be possible to predict function in detail. The truncated hemoglobin family presents an interesting benchmark study due to their ubiquity, sequence diversity in the context of a conserved fold and the number of characterized members. Their functions are tightly related to O2 affinity and reactivity, as determined by the association and dissociation rate constants, both of which can be predicted and analyzed using in-silico based tools. In the present work we have applied a strategy, which combines homology modeling with molecular based energy calculations, to predict and analyze function of all known truncated hemoglobins in an evolutionary context. Our results show that truncated hemoglobins present conserved family features, but that its structure is flexible enough to allow the switch from high to low affinity in a few evolutionary steps. Most proteins display moderate to high oxygen affinities and multiple ligand migration paths, which, besides some minor trends, show heterogeneous distributions throughout the phylogenetic tree, again suggesting fast functional adaptation. Our data not only deepens our comprehension of the structural basis governing ligand affinity, but they also highlight some interesting functional evolutionary trends. PMID:26788940

Insights into the origin and distribution of biodiversity in the Brazilian Atlantic forest hot spot: a statistical phylogeographic study using a low-dispersal organism.

PubMed

Álvarez-Presas, M; Sánchez-Gracia, A; Carbayo, F; Rozas, J; Riutort, M

2014-06-01

The relative importance of the processes that generate and maintain biodiversity is a major and controversial topic in evolutionary biology with large implications for conservation management. The Atlantic Forest of Brazil, one of the world's richest biodiversity hot spots, is severely damaged by human activities. To formulate an efficient conservation policy, a good understanding of spatial and temporal biodiversity patterns and their underlying evolutionary mechanisms is required. With this aim, we performed a comprehensive phylogeographic study using a low-dispersal organism, the land planarian species Cephaloflexa bergi (Platyhelminthes, Tricladida). Analysing multi-locus DNA sequence variation under the Approximate Bayesian Computation framework, we evaluated two scenarios proposed to explain the diversity of Southern Atlantic Forest (SAF) region. We found that most sampled localities harbour high levels of genetic diversity, with lineages sharing common ancestors that predate the Pleistocene. Remarkably, we detected the molecular hallmark of the isolation-by-distance effect and little evidence of a recent colonization of SAF localities; nevertheless, some populations might result from very recent secondary contacts. We conclude that extant SAF biodiversity originated and has been shaped by complex interactions between ancient geological events and more recent evolutionary processes, whereas Pleistocene climate changes had a minor influence in generating present-day diversity. We also demonstrate that land planarians are an advantageous biological model for making phylogeographic and, particularly, fine-scale evolutionary inferences, and propose appropriate conservation policies.

Multiobjective evolutionary optimization of water distribution systems: Exploiting diversity with infeasible solutions.

PubMed

Tanyimboh, Tiku T; Seyoum, Alemtsehay G

2016-12-01

This article investigates the computational efficiency of constraint handling in multi-objective evolutionary optimization algorithms for water distribution systems. The methodology investigated here encourages the co-existence and simultaneous development including crossbreeding of subpopulations of cost-effective feasible and infeasible solutions based on Pareto dominance. This yields a boundary search approach that also promotes diversity in the gene pool throughout the progress of the optimization by exploiting the full spectrum of non-dominated infeasible solutions. The relative effectiveness of small and moderate population sizes with respect to the number of decision variables is investigated also. The results reveal the optimization algorithm to be efficient, stable and robust. It found optimal and near-optimal solutions reliably and efficiently. The real-world system based optimization problem involved multiple variable head supply nodes, 29 fire-fighting flows, extended period simulation and multiple demand categories including water loss. The least cost solutions found satisfied the flow and pressure requirements consistently. The best solutions achieved indicative savings of 48.1% and 48.2% based on the cost of the pipes in the existing network, for populations of 200 and 1000, respectively. The population of 1000 achieved slightly better results overall. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

The role of internal duplication in the evolution of multi-domain proteins.

PubMed

Nacher, J C; Hayashida, M; Akutsu, T

2010-08-01

Many proteins consist of several structural domains. These multi-domain proteins have likely been generated by selective genome growth dynamics during evolution to perform new functions as well as to create structures that fold on a biologically feasible time scale. Domain units frequently evolved through a variety of genetic shuffling mechanisms. Here we examine the protein domain statistics of more than 1000 organisms including eukaryotic, archaeal and bacterial species. The analysis extends earlier findings on asymmetric statistical laws for proteome to a wider variety of species. While proteins are composed of a wide range of domains, displaying a power-law decay, the computation of domain families for each protein reveals an exponential distribution, characterizing a protein universe composed of a thin number of unique families. Structural studies in proteomics have shown that domain repeats, or internal duplicated domains, represent a small but significant fraction of genome. In spite of its importance, this observation has been largely overlooked until recently. We model the evolutionary dynamics of proteome and demonstrate that these distinct distributions are in fact rooted in an internal duplication mechanism. This process generates the contemporary protein structural domain universe, determines its reduced thickness, and tames its growth. These findings have important implications, ranging from protein interaction network modeling to evolutionary studies based on fundamental mechanisms governing genome expansion.

Stationary stability for evolutionary dynamics in finite populations

DOE PAGES

Harper, Marc; Fryer, Dashiell

2016-08-25

Here, we demonstrate a vast expansion of the theory of evolutionary stability to finite populations with mutation, connecting the theory of the stationary distribution of the Moran process with the Lyapunov theory of evolutionary stability. We define the notion of stationary stability for the Moran process with mutation and generalizations, as well as a generalized notion of evolutionary stability that includes mutation called an incentive stable state (ISS) candidate. For sufficiently large populations, extrema of the stationary distribution are ISS candidates and we give a family of Lyapunov quantities that are locally minimized at the stationary extrema and at ISSmore » candidates. In various examples, including for the Moran andWright–Fisher processes, we show that the local maxima of the stationary distribution capture the traditionally-defined evolutionarily stable states. The classical stability theory of the replicator dynamic is recovered in the large population limit. Finally we include descriptions of possible extensions to populations of variable size and populations evolving on graphs.« less

Bell-Curve Based Evolutionary Optimization Algorithm

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, J.; Laba, K.; Kincaid, R.

1998-01-01

The paper presents an optimization algorithm that falls in the category of genetic, or evolutionary algorithms. While the bit exchange is the basis of most of the Genetic Algorithms (GA) in research and applications in America, some alternatives, also in the category of evolutionary algorithms, but use a direct, geometrical approach have gained popularity in Europe and Asia. The Bell-Curve Based Evolutionary Algorithm (BCB) is in this alternative category and is distinguished by the use of a combination of n-dimensional geometry and the normal distribution, the bell-curve, in the generation of the offspring. The tool for creating a child is a geometrical construct comprising a line connecting two parents and a weighted point on that line. The point that defines the child deviates from the weighted point in two directions: parallel and orthogonal to the connecting line, the deviation in each direction obeying a probabilistic distribution. Tests showed satisfactory performance of BCB. The principal advantage of BCB is its controllability via the normal distribution parameters and the geometrical construct variables.

Evolutionary Strategies for Protein Folding

NASA Astrophysics Data System (ADS)

Murthy Gopal, Srinivasa; Wenzel, Wolfgang

2006-03-01

The free energy approach for predicting the protein tertiary structure describes the native state of a protein as the global minimum of an appropriate free-energy forcefield. The low-energy region of the free-energy landscape of a protein is extremely rugged. Efficient optimization methods must therefore speed up the search for the global optimum by avoiding high energy transition states, adapt large scale moves or accept unphysical intermediates. Here we investigate an evolutionary strategies(ES) for optimizing a protein conformation in our all-atom free-energy force field([1],[2]). A set of random conformations is evolved using an ES to get a diverse population containing low energy structure. The ES is shown to balance energy improvement and yet maintain diversity in structures. The ES is implemented as a master-client model for distributed computing. Starting from random structures and by using this optimization technique, we were able to fold a 20 amino-acid helical protein and 16 amino-acid beta hairpin[3]. We compare ES to basin hopping method. [1]T. Herges and W. Wenzel,Biophys.J. 87,3100(2004) [2] A. Verma and W. Wenzel Stabilization and folding of beta-sheet and alpha-helical proteins in an all-atom free energy model(submitted)(2005) [3] S. M. Gopal and W. Wenzel Evolutionary Strategies for Protein Folding (in preparation)

BAYESIAN PROTEIN STRUCTURE ALIGNMENT.

PubMed

Rodriguez, Abel; Schmidler, Scott C

The analysis of the three-dimensional structure of proteins is an important topic in molecular biochemistry. Structure plays a critical role in defining the function of proteins and is more strongly conserved than amino acid sequence over evolutionary timescales. A key challenge is the identification and evaluation of structural similarity between proteins; such analysis can aid in understanding the role of newly discovered proteins and help elucidate evolutionary relationships between organisms. Computational biologists have developed many clever algorithmic techniques for comparing protein structures, however, all are based on heuristic optimization criteria, making statistical interpretation somewhat difficult. Here we present a fully probabilistic framework for pairwise structural alignment of proteins. Our approach has several advantages, including the ability to capture alignment uncertainty and to estimate key "gap" parameters which critically affect the quality of the alignment. We show that several existing alignment methods arise as maximum a posteriori estimates under specific choices of prior distributions and error models. Our probabilistic framework is also easily extended to incorporate additional information, which we demonstrate by including primary sequence information to generate simultaneous sequence-structure alignments that can resolve ambiguities obtained using structure alone. This combined model also provides a natural approach for the difficult task of estimating evolutionary distance based on structural alignments. The model is illustrated by comparison with well-established methods on several challenging protein alignment examples.

Interplay between cooperation-enhancing mechanisms in evolutionary games with tag-mediated interactions

NASA Astrophysics Data System (ADS)

Hadzibeganovic, Tarik; Stauffer, Dietrich; Han, Xiao-Pu

2018-04-01

Cooperation is fundamental for the long-term survival of biological, social, and technological networks. Previously, mechanisms for the enhancement of cooperation, such as network reciprocity, have largely been studied in isolation and with often inconclusive findings. Here, we present an evolutionary, multiagent-based, and spatially explicit computer model to specifically address the interactive interplay between such mechanisms. We systematically investigate the effects of phenotypic diversity, network structure, and rewards on cooperative behavior emerging in a population of reproducing artificial decision makers playing tag-mediated evolutionary games. Cooperative interactions are rewarded such that both the benefits of recipients and costs of donators are affected by the reward size. The reward size is determined by the number of cooperative acts occurring within a given reward time frame. Our computational experiments reveal that small reward frames promote unconditional cooperation in populations with both low and high diversity, whereas large reward frames lead to cycles of conditional and unconditional strategies at high but not at low diversity. Moreover, an interaction between rewards and spatial structure shows that relative to small reward frames, there is a strong difference between the frequency of conditional cooperators populating rewired versus non-rewired networks when the reward frame is large. Notably, in a less diverse population, the total number of defections is comparable across different network topologies, whereas in more diverse environments defections become more frequent in a regularly structured than in a rewired, small-world network of contacts. Acknowledging the importance of such interaction effects in social dilemmas will have inevitable consequences for the future design of cooperation-enhancing protocols in large-scale, distributed, and decentralized systems such as peer-to-peer networks.

From cacti to carnivores: Improved phylotranscriptomic sampling and hierarchical homology inference provide further insight into the evolution of Caryophyllales.

PubMed

Walker, Joseph F; Yang, Ya; Feng, Tao; Timoneda, Alfonso; Mikenas, Jessica; Hutchison, Vera; Edwards, Caroline; Wang, Ning; Ahluwalia, Sonia; Olivieri, Julia; Walker-Hale, Nathanael; Majure, Lucas C; Puente, Raúl; Kadereit, Gudrun; Lauterbach, Maximilian; Eggli, Urs; Flores-Olvera, Hilda; Ochoterena, Helga; Brockington, Samuel F; Moore, Michael J; Smith, Stephen A

2018-03-01

The Caryophyllales contain ~12,500 species and are known for their cosmopolitan distribution, convergence of trait evolution, and extreme adaptations. Some relationships within the Caryophyllales, like those of many large plant clades, remain unclear, and phylogenetic studies often recover alternative hypotheses. We explore the utility of broad and dense transcriptome sampling across the order for resolving evolutionary relationships in Caryophyllales. We generated 84 transcriptomes and combined these with 224 publicly available transcriptomes to perform a phylogenomic analysis of Caryophyllales. To overcome the computational challenge of ortholog detection in such a large data set, we developed an approach for clustering gene families that allowed us to analyze >300 transcriptomes and genomes. We then inferred the species relationships using multiple methods and performed gene-tree conflict analyses. Our phylogenetic analyses resolved many clades with strong support, but also showed significant gene-tree discordance. This discordance is not only a common feature of phylogenomic studies, but also represents an opportunity to understand processes that have structured phylogenies. We also found taxon sampling influences species-tree inference, highlighting the importance of more focused studies with additional taxon sampling. Transcriptomes are useful both for species-tree inference and for uncovering evolutionary complexity within lineages. Through analyses of gene-tree conflict and multiple methods of species-tree inference, we demonstrate that phylogenomic data can provide unparalleled insight into the evolutionary history of Caryophyllales. We also discuss a method for overcoming computational challenges associated with homolog clustering in large data sets. © 2018 The Authors. American Journal of Botany is published by Wiley Periodicals, Inc. on behalf of the Botanical Society of America.

Regulatory RNA design through evolutionary computation and strand displacement.

PubMed

Rostain, William; Landrain, Thomas E; Rodrigo, Guillermo; Jaramillo, Alfonso

2015-01-01

The discovery and study of a vast number of regulatory RNAs in all kingdoms of life over the past decades has allowed the design of new synthetic RNAs that can regulate gene expression in vivo. Riboregulators, in particular, have been used to activate or repress gene expression. However, to accelerate and scale up the design process, synthetic biologists require computer-assisted design tools, without which riboregulator engineering will remain a case-by-case design process requiring expert attention. Recently, the design of RNA circuits by evolutionary computation and adapting strand displacement techniques from nanotechnology has proven to be suited to the automated generation of DNA sequences implementing regulatory RNA systems in bacteria. Herein, we present our method to carry out such evolutionary design and how to use it to create various types of riboregulators, allowing the systematic de novo design of genetic control systems in synthetic biology.

Genomicus 2018: karyotype evolutionary trees and on-the-fly synteny computing

PubMed Central

Nguyen, Nga Thi Thuy; Vincens, Pierre

2018-01-01

Abstract Since 2010, the Genomicus web server is available online at http://genomicus.biologie.ens.fr/genomicus. This graphical browser provides access to comparative genomic analyses in four different phyla (Vertebrate, Plants, Fungi, and non vertebrate Metazoans). Users can analyse genomic information from extant species, as well as ancestral gene content and gene order for vertebrates and flowering plants, in an integrated evolutionary context. New analyses and visualization tools have recently been implemented in Genomicus Vertebrate. Karyotype structures from several genomes can now be compared along an evolutionary pathway (Multi-KaryotypeView), and synteny blocks can be computed and visualized between any two genomes (PhylDiagView). PMID:29087490

Star formation history: Modeling of visual binaries

NASA Astrophysics Data System (ADS)

Gebrehiwot, Y. M.; Tessema, S. B.; Malkov, O. Yu.; Kovaleva, D. A.; Sytov, A. Yu.; Tutukov, A. V.

2018-05-01

Most stars form in binary or multiple systems. Their evolution is defined by masses of components, orbital separation and eccentricity. In order to understand star formation and evolutionary processes, it is vital to find distributions of physical parameters of binaries. We have carried out Monte Carlo simulations in which we simulate different pairing scenarios: random pairing, primary-constrained pairing, split-core pairing, and total and primary pairing in order to get distributions of binaries over physical parameters at birth. Next, for comparison with observations, we account for stellar evolution and selection effects. Brightness, radius, temperature, and other parameters of components are assigned or calculated according to approximate relations for stars in different evolutionary stages (main-sequence stars, red giants, white dwarfs, relativistic objects). Evolutionary stage is defined as a function of system age and component masses. We compare our results with the observed IMF, binarity rate, and binary mass-ratio distributions for field visual binaries to find initial distributions and pairing scenarios that produce observed distributions.

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. These approaches are 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 the inverse design of a turbine airfoil. The efficiency improvements achieved by the different approaches are evaluated and compared.

A Hybrid Soft-computing Method for Image Analysis of Digital Plantar Scanners.

PubMed

Razjouyan, Javad; Khayat, Omid; Siahi, Mehdi; Mansouri, Ali Alizadeh

2013-01-01

Digital foot scanners have been developed in recent years to yield anthropometrists digital image of insole with pressure distribution and anthropometric information. In this paper, a hybrid algorithm containing gray level spatial correlation (GLSC) histogram and Shanbag entropy is presented for analysis of scanned foot images. An evolutionary algorithm is also employed to find the optimum parameters of GLSC and transform function of the membership values. Resulting binary images as the thresholded images are undergone anthropometric measurements taking in to account the scale factor of pixel size to metric scale. The proposed method is finally applied to plantar images obtained through scanning feet of randomly selected subjects by a foot scanner system as our experimental setup described in the paper. Running computation time and the effects of GLSC parameters are investigated in the simulation results.

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...

In search of a general theory of species' range evolution.

PubMed

Connallon, Tim; Sgrò, Carla M

2018-06-13

Despite the pervasiveness of the world's biodiversity, no single species has a truly global distribution. In fact, most species have very restricted distributions. What limits species from expanding beyond their current geographic ranges? This has been classically treated by ecologists as an ecological problem and by evolutionary biologist as an evolutionary problem. Such a dichotomy is false-the problem of species' ranges sits firmly within the realm of evolutionary ecology. In support of this view, Polechová presents new theory that explains species' range limits with reference to two key factors central to both ecological and evolutionary theory-migration and population size. This new model sets the scene for empirical tests of range limit theory and builds the case for assisted gene flow as a key management tool for threatened species.

Avoiding Local Optima with Interactive Evolutionary Robotics

DTIC Science & Technology

2012-07-09

the top of a flight of stairs selects for climbing ; suspending the robot and the target object above the ground and creating rungs between the two will...REPORT Avoiding Local Optimawith Interactive Evolutionary Robotics 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: The main bottleneck in evolutionary... robotics has traditionally been the time required to evolve robot controllers. However with the continued acceleration in computational resources, the

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.

Evolutionary inference via the Poisson Indel Process.

PubMed

Bouchard-Côté, Alexandre; Jordan, Michael I

2013-01-22

We address the problem of the joint statistical inference of phylogenetic trees and multiple sequence alignments from unaligned molecular sequences. This problem is generally formulated in terms of string-valued evolutionary processes along the branches of a phylogenetic tree. The classic evolutionary process, the TKF91 model [Thorne JL, Kishino H, Felsenstein J (1991) J Mol Evol 33(2):114-124] is a continuous-time Markov chain model composed of insertion, deletion, and substitution events. Unfortunately, this model gives rise to an intractable computational problem: The computation of the marginal likelihood under the TKF91 model is exponential in the number of taxa. In this work, we present a stochastic process, the Poisson Indel Process (PIP), in which the complexity of this computation is reduced to linear. The Poisson Indel Process is closely related to the TKF91 model, differing only in its treatment of insertions, but it has a global characterization as a Poisson process on the phylogeny. Standard results for Poisson processes allow key computations to be decoupled, which yields the favorable computational profile of inference under the PIP model. We present illustrative experiments in which Bayesian inference under the PIP model is compared with separate inference of phylogenies and alignments.

Evolutionary inference via the Poisson Indel Process

PubMed Central

Bouchard-Côté, Alexandre; Jordan, Michael I.

2013-01-01

We address the problem of the joint statistical inference of phylogenetic trees and multiple sequence alignments from unaligned molecular sequences. This problem is generally formulated in terms of string-valued evolutionary processes along the branches of a phylogenetic tree. The classic evolutionary process, the TKF91 model [Thorne JL, Kishino H, Felsenstein J (1991) J Mol Evol 33(2):114–124] is a continuous-time Markov chain model composed of insertion, deletion, and substitution events. Unfortunately, this model gives rise to an intractable computational problem: The computation of the marginal likelihood under the TKF91 model is exponential in the number of taxa. In this work, we present a stochastic process, the Poisson Indel Process (PIP), in which the complexity of this computation is reduced to linear. The Poisson Indel Process is closely related to the TKF91 model, differing only in its treatment of insertions, but it has a global characterization as a Poisson process on the phylogeny. Standard results for Poisson processes allow key computations to be decoupled, which yields the favorable computational profile of inference under the PIP model. We present illustrative experiments in which Bayesian inference under the PIP model is compared with separate inference of phylogenies and alignments. PMID:23275296

Is specialization an evolutionary dead end? Testing for differences in speciation, extinction and trait transition rates across diverse phylogenies of specialists and generalists.

PubMed

Day, E H; Hua, X; Bromham, L

2016-06-01

Specialization has often been claimed to be an evolutionary dead end, with specialist lineages having a reduced capacity to persist or diversify. In a phylogenetic comparative framework, an evolutionary dead end may be detectable from the phylogenetic distribution of specialists, if specialists rarely give rise to large, diverse clades. Previous phylogenetic studies of the influence of specialization on macroevolutionary processes have demonstrated a range of patterns, including examples where specialists have both higher and lower diversification rates than generalists, as well as examples where the rates of evolutionary transitions from generalists to specialists are higher, lower or equal to transitions from specialists to generalists. Here, we wish to ask whether these varied answers are due to the differences in macroevolutionary processes in different clades, or partly due to differences in methodology. We analysed ten phylogenies containing multiple independent origins of specialization and quantified the phylogenetic distribution of specialists by applying a common set of metrics to all datasets. We compared the tip branch lengths of specialists to generalists, the size of specialist clades arising from each evolutionary origin of a specialized trait and whether specialists tend to be clustered or scattered on phylogenies. For each of these measures, we compared the observed values to expectations under null models of trait evolution and expected outcomes under alternative macroevolutionary scenarios. We found that specialization is sometimes an evolutionary dead end: in two of the ten case studies (pollinator-specific plants and host-specific flies), specialization is associated with a reduced rate of diversification or trait persistence. However, in the majority of studies, we could not distinguish the observed phylogenetic distribution of specialists from null models in which specialization has no effect on diversification or trait persistence. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

VizieR Online Data Catalog: Comparison of evolutionary tracks (Martins+, 2013)

NASA Astrophysics Data System (ADS)

Martins, F.; Palacios, A.

2013-11-01

Tables of evolutionary models for massive stars. The files m*_stol.dat correspond to models computed with the code STAREVOL. The files m*_mesa.dat correspond to models computed with the code MESA. For each code, models with initial masses equal to 7, 9, 15, 20, 25, 40 and 60M⊙ are provided. No rotation is included. The overshooting parameter f is equal to 0.01. The metallicity is solar. (14 data files).

NexGen PVAs: Incorporating Eco-Evolutionary Processes into Population Viability Models

EPA Science Inventory

We examine how the integration of evolutionary and ecological processes in population dynamics – an emerging framework in ecology – could be incorporated into population viability analysis (PVA). Driven by parallel, complementary advances in population genomics and computational ...

Evolutionary trends in directional hearing

PubMed Central

Carr, Catherine E.; Christensen-Dalsgaard, Jakob

2016-01-01

Tympanic hearing is a true evolutionary novelty that arose in parallel within early tetrapods. We propose that in these tetrapods, selection for sound localization in air acted upon pre-existing directionally sensitive brainstem circuits, similar to those in fishes. Auditory circuits in birds and lizards resemble this ancestral, directionally sensitive framework. Despite this anatomically similarity, coding of sound source location differs between birds and lizards. In birds, brainstem circuits compute sound location from interaural cues. Lizards, however, have coupled ears, and do not need to compute source location in the brain. Thus their neural processing of sound direction differs, although all show mechanisms for enhancing sound source directionality. Comparisons with mammals reveal similarly complex interactions between coding strategies and evolutionary history. PMID:27448850

Genomicus 2018: karyotype evolutionary trees and on-the-fly synteny computing.

PubMed

Nguyen, Nga Thi Thuy; Vincens, Pierre; Roest Crollius, Hugues; Louis, Alexandra

2018-01-04

Since 2010, the Genomicus web server is available online at http://genomicus.biologie.ens.fr/genomicus. This graphical browser provides access to comparative genomic analyses in four different phyla (Vertebrate, Plants, Fungi, and non vertebrate Metazoans). Users can analyse genomic information from extant species, as well as ancestral gene content and gene order for vertebrates and flowering plants, in an integrated evolutionary context. New analyses and visualization tools have recently been implemented in Genomicus Vertebrate. Karyotype structures from several genomes can now be compared along an evolutionary pathway (Multi-KaryotypeView), and synteny blocks can be computed and visualized between any two genomes (PhylDiagView). © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Phylogenetic tree and community structure from a Tangled Nature model.

PubMed

Canko, Osman; Taşkın, Ferhat; Argın, Kamil

2015-10-07

In evolutionary biology, the taxonomy and origination of species are widely studied subjects. An estimation of the evolutionary tree can be done via available DNA sequence data. The calculation of the tree is made by well-known and frequently used methods such as maximum likelihood and neighbor-joining. In order to examine the results of these methods, an evolutionary tree is pursued computationally by a mathematical model, called Tangled Nature. A relatively small genome space is investigated due to computational burden and it is found that the actual and predicted trees are in reasonably good agreement in terms of shape. Moreover, the speciation and the resulting community structure of the food-web are investigated by modularity. Copyright © 2015 Elsevier Ltd. All rights reserved.

Extensively Parameterized Mutation-Selection Models Reliably Capture Site-Specific Selective Constraint.

PubMed

Spielman, Stephanie J; Wilke, Claus O

2016-11-01

The mutation-selection model of coding sequence evolution has received renewed attention for its use in estimating site-specific amino acid propensities and selection coefficient distributions. Two computationally tractable mutation-selection inference frameworks have been introduced: One framework employs a fixed-effects, highly parameterized maximum likelihood approach, whereas the other employs a random-effects Bayesian Dirichlet Process approach. While both implementations follow the same model, they appear to make distinct predictions about the distribution of selection coefficients. The fixed-effects framework estimates a large proportion of highly deleterious substitutions, whereas the random-effects framework estimates that all substitutions are either nearly neutral or weakly deleterious. It remains unknown, however, how accurately each method infers evolutionary constraints at individual sites. Indeed, selection coefficient distributions pool all site-specific inferences, thereby obscuring a precise assessment of site-specific estimates. Therefore, in this study, we use a simulation-based strategy to determine how accurately each approach recapitulates the selective constraint at individual sites. We find that the fixed-effects approach, despite its extensive parameterization, consistently and accurately estimates site-specific evolutionary constraint. By contrast, the random-effects Bayesian approach systematically underestimates the strength of natural selection, particularly for slowly evolving sites. We also find that, despite the strong differences between their inferred selection coefficient distributions, the fixed- and random-effects approaches yield surprisingly similar inferences of site-specific selective constraint. We conclude that the fixed-effects mutation-selection framework provides the more reliable software platform for model application and future development. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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

Scalable computing for evolutionary genomics.

PubMed

Prins, Pjotr; Belhachemi, Dominique; Möller, Steffen; Smant, Geert

2012-01-01

Genomic data analysis in evolutionary biology is becoming so computationally intensive that analysis of multiple hypotheses and scenarios takes too long on a single desktop computer. In this chapter, we discuss techniques for scaling computations through parallelization of calculations, after giving a quick overview of advanced programming techniques. Unfortunately, parallel programming is difficult and requires special software design. The alternative, especially attractive for legacy software, is to introduce poor man's parallelization by running whole programs in parallel as separate processes, using job schedulers. Such pipelines are often deployed on bioinformatics computer clusters. Recent advances in PC virtualization have made it possible to run a full computer operating system, with all of its installed software, on top of another operating system, inside a "box," or virtual machine (VM). Such a VM can flexibly be deployed on multiple computers, in a local network, e.g., on existing desktop PCs, and even in the Cloud, to create a "virtual" computer cluster. Many bioinformatics applications in evolutionary biology can be run in parallel, running processes in one or more VMs. Here, we show how a ready-made bioinformatics VM image, named BioNode, effectively creates a computing cluster, and pipeline, in a few steps. This allows researchers to scale-up computations from their desktop, using available hardware, anytime it is required. BioNode is based on Debian Linux and can run on networked PCs and in the Cloud. Over 200 bioinformatics and statistical software packages, of interest to evolutionary biology, are included, such as PAML, Muscle, MAFFT, MrBayes, and BLAST. Most of these software packages are maintained through the Debian Med project. In addition, BioNode contains convenient configuration scripts for parallelizing bioinformatics software. Where Debian Med encourages packaging free and open source bioinformatics software through one central project, BioNode encourages creating free and open source VM images, for multiple targets, through one central project. BioNode can be deployed on Windows, OSX, Linux, and in the Cloud. Next to the downloadable BioNode images, we provide tutorials online, which empower bioinformaticians to install and run BioNode in different environments, as well as information for future initiatives, on creating and building such images.

Evolutionary model of stock markets

NASA Astrophysics Data System (ADS)

Kaldasch, Joachim

2014-12-01

The paper presents an evolutionary economic model for the price evolution of stocks. Treating a stock market as a self-organized system governed by a fast purchase process and slow variations of demand and supply the model suggests that the short term price distribution has the form a logistic (Laplace) distribution. The long term return can be described by Laplace-Gaussian mixture distributions. The long term mean price evolution is governed by a Walrus equation, which can be transformed into a replicator equation. This allows quantifying the evolutionary price competition between stocks. The theory suggests that stock prices scaled by the price over all stocks can be used to investigate long-term trends in a Fisher-Pry plot. The price competition that follows from the model is illustrated by examining the empirical long-term price trends of two stocks.

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.

MEGA-CC: computing core of molecular evolutionary genetics analysis program for automated and iterative data analysis.

PubMed

Kumar, Sudhir; Stecher, Glen; Peterson, Daniel; Tamura, Koichiro

2012-10-15

There is a growing need in the research community to apply the molecular evolutionary genetics analysis (MEGA) software tool for batch processing a large number of datasets and to integrate it into analysis workflows. Therefore, we now make available the computing core of the MEGA software as a stand-alone executable (MEGA-CC), along with an analysis prototyper (MEGA-Proto). MEGA-CC provides users with access to all the computational analyses available through MEGA's graphical user interface version. This includes methods for multiple sequence alignment, substitution model selection, evolutionary distance estimation, phylogeny inference, substitution rate and pattern estimation, tests of natural selection and ancestral sequence inference. Additionally, we have upgraded the source code for phylogenetic analysis using the maximum likelihood methods for parallel execution on multiple processors and cores. Here, we describe MEGA-CC and outline the steps for using MEGA-CC in tandem with MEGA-Proto for iterative and automated data analysis. http://www.megasoftware.net/.

Computational Substrates of Social Norm Enforcement by Unaffected Third Parties

PubMed Central

Zhong, Songfa; Chark, Robin; Hsu, Ming; Chew, Soo Hong

2016-01-01

Enforcement of social norms by impartial bystanders in the human species reveals a possibly unique capacity to sense and to enforce norms from a third party perspective. Such behavior, however, cannot be accounted by current computational models based on an egocentric notion of norms. Here, using a combination of model-based fMRI and third party punishment games, we show that brain regions previously implicated in egocentric norm enforcement critically extend to the important case of norm enforcement by unaffected third parties. Specifically, we found that responses in the ACC and insula cortex were positively associated with detection of distributional inequity, while those in the anterior DLPFC were associated with assessment of intentionality to the violator. Moreover, during sanction decisions, the subjective value of sanctions modulated activity in both vmPFC and rTPJ. These results shed light on the neurocomputational underpinnings of third party punishment and evolutionary origin of human norm enforcement. PMID:26825438

Confessions of a robot lobotomist

NASA Technical Reports Server (NTRS)

Gottshall, R. Marc

1994-01-01

Since its inception, numerically controlled (NC) machining methods have been used throughout the aerospace industry to mill, drill, and turn complex shapes by sequentially stepping through motion programs. However, the recent demand for more precision, faster feeds, exotic sensors, and branching execution have existing computer numerical control (CNC) and distributed numerical control (DNC) systems running at maximum controller capacity. Typical disadvantages of current CNC's include fixed memory capacities, limited communication ports, and the use of multiple control languages. The need to tailor CNC's to meet specific applications, whether it be expanded memory, additional communications, or integrated vision, often requires replacing the original controller supplied with the commercial machine tool with a more powerful and capable system. This paper briefly describes the process and equipment requirements for new controllers and their evolutionary implementation in an aerospace environment. The process of controller retrofit with currently available machines is examined, along with several case studies and their computational and architectural implications.

The markup is the model: reasoning about systems biology models in the Semantic Web era.

PubMed

Kell, Douglas B; Mendes, Pedro

2008-06-07

Metabolic control analysis, co-invented by Reinhart Heinrich, is a formalism for the analysis of biochemical networks, and is a highly important intellectual forerunner of modern systems biology. Exchanging ideas and exchanging models are part of the international activities of science and scientists, and the Systems Biology Markup Language (SBML) allows one to perform the latter with great facility. Encoding such models in SBML allows their distributed analysis using loosely coupled workflows, and with the advent of the Internet the various software modules that one might use to analyze biochemical models can reside on entirely different computers and even on different continents. Optimization is at the core of many scientific and biotechnological activities, and Reinhart made many major contributions in this area, stimulating our own activities in the use of the methods of evolutionary computing for optimization.

Metabolic analysis of adaptive evolution for in silico-designed lactate-producing strains.

PubMed

Hua, Qiang; Joyce, Andrew R; Fong, Stephen S; Palsson, Bernhard Ø

2006-12-05

Experimental evolution is now frequently applied to many biological systems to achieve desired objectives. To obtain optimized performance for metabolite production, a successful strategy has been recently developed that couples metabolic engineering techniques with laboratory evolution of microorganisms. Previously, we reported the growth characteristics of three lactate-producing, adaptively evolved Escherichia coli mutant strains designed by the OptKnock computational algorithm. Here, we describe the use of (13)C-labeled experiments and mass distribution measurements to study the evolutionary effects on the fluxome of these differently designed strains. Metabolic flux ratios and intracellular flux distributions as well as physiological data were used to elucidate metabolic responses over the course of adaptive evolution and metabolic differences among strains. The study of 3 unevolved and 12 evolved engineered strains as well as a wild-type strain suggests that evolution resulted in remarkable improvements in both substrate utilization rate and the proportion of glycolytic flux to total glucose utilization flux. Among three strain designs, the most significant increases in the fraction of glucose catabolized through glycolysis (>50%) and the glycolytic fluxes (>twofold) were observed in phosphotransacetylase and phosphofructokinase 1 (PFK1) double deletion (pta- pfkA) strains, which were likely attributed to the dramatic evolutionary increase in gene expression and catalytic activity of the minor PFK encoded by pfkB. These fluxomic studies also revealed the important role of acetate synthetic pathway in anaerobic lactate production. Moreover, flux analysis suggested that independent of genetic background, optimal relative flux distributions in cells could be achieved faster than physiological parameters such as nutrient utilization rate. (c) 2006 Wiley Periodicals, Inc.

Evolutionary Computing Methods for Spectral Retrieval

NASA Technical Reports Server (NTRS)

Terrile, Richard; Fink, Wolfgang; Huntsberger, Terrance; Lee, Seugwon; Tisdale, Edwin; VonAllmen, Paul; Tinetti, Geivanna

2009-01-01

A methodology for processing spectral images to retrieve information on underlying physical, chemical, and/or biological phenomena is based on evolutionary and related computational methods implemented in software. In a typical case, the solution (the information that one seeks to retrieve) consists of parameters of a mathematical model that represents one or more of the phenomena of interest. The methodology was developed for the initial purpose of retrieving the desired information from spectral image data acquired by remote-sensing instruments aimed at planets (including the Earth). Examples of information desired in such applications include trace gas concentrations, temperature profiles, surface types, day/night fractions, cloud/aerosol fractions, seasons, and viewing angles. The methodology is also potentially useful for retrieving information on chemical and/or biological hazards in terrestrial settings. In this methodology, one utilizes an iterative process that minimizes a fitness function indicative of the degree of dissimilarity between observed and synthetic spectral and angular data. The evolutionary computing methods that lie at the heart of this process yield a population of solutions (sets of the desired parameters) within an accuracy represented by a fitness-function value specified by the user. The evolutionary computing methods (ECM) used in this methodology are Genetic Algorithms and Simulated Annealing, both of which are well-established optimization techniques and have also been described in previous NASA Tech Briefs articles. These are embedded in a conceptual framework, represented in the architecture of the implementing software, that enables automatic retrieval of spectral and angular data and analysis of the retrieved solutions for uniqueness.

PhyloDet: a scalable visualization tool for mapping multiple traits to large evolutionary trees

PubMed Central

Lee, Bongshin; Nachmanson, Lev; Robertson, George; Carlson, Jonathan M.; Heckerman, David

2009-01-01

Summary: Evolutionary biologists are often interested in finding correlations among biological traits across a number of species, as such correlations may lead to testable hypotheses about the underlying function. Because some species are more closely related than others, computing and visualizing these correlations must be done in the context of the evolutionary tree that relates species. In this note, we introduce PhyloDet (short for PhyloDetective), an evolutionary tree visualization tool that enables biologists to visualize multiple traits mapped to the tree. Availability: http://research.microsoft.com/cue/phylodet/ Contact: bongshin@microsoft.com. PMID:19633096

A mistletoe tale: postglacial invasion of Psittacanthus schiedeanus (Loranthaceae) to Mesoamerican cloud forests revealed by molecular data and species distribution modeling.

PubMed

Ornelas, Juan Francisco; Gándara, Etelvina; Vásquez-Aguilar, Antonio Acini; Ramírez-Barahona, Santiago; Ortiz-Rodriguez, Andrés Ernesto; González, Clementina; Mejía Saules, María Teresa; Ruiz-Sanchez, Eduardo

2016-04-12

Ecological adaptation to host taxa is thought to result in mistletoe speciation via race formation. However, historical and ecological factors could also contribute to explain genetic structuring particularly when mistletoe host races are distributed allopatrically. Using sequence data from nuclear (ITS) and chloroplast (trnL-F) DNA, we investigate the genetic differentiation of 31 Psittacanthus schiedeanus (Loranthaceae) populations across the Mesoamerican species range. We conducted phylogenetic, population and spatial genetic analyses on 274 individuals of P. schiedeanus to gain insight of the evolutionary history of these populations. Species distribution modeling, isolation with migration and Bayesian inference methods were used to infer the evolutionary transition of mistletoe invasion, in which evolutionary scenarios were compared through posterior probabilities. Our analyses revealed shallow levels of population structure with three genetic groups present across the sample area. Nine haplotypes were identified after sequencing the trnL-F intergenic spacer. These haplotypes showed phylogeographic structure, with three groups with restricted gene flow corresponding to the distribution of individuals/populations separated by habitat (cloud forest localities from San Luis Potosí to northwestern Oaxaca and Chiapas, localities with xeric vegetation in central Oaxaca, and localities with tropical deciduous forests in Chiapas), with post-glacial population expansions and potentially corresponding to post-glacial invasion types. Similarly, 44 ITS ribotypes suggest phylogeographic structure, despite the fact that most frequent ribotypes are widespread indicating effective nuclear gene flow via pollen. Gene flow estimates, a significant genetic signal of demographic expansion, and range shifts under past climatic conditions predicted by species distribution modeling suggest post-glacial invasion of P. schiedeanus mistletoes to cloud forests. However, Approximate Bayesian Computation (ABC) analyses strongly supported a scenario of simultaneous divergence among the three groups isolated recently. Our results provide support for the predominant role of isolation and environmental factors in driving genetic differentiation of Mesoamerican parrot-flower mistletoes. The ABC results are consistent with a scenario of post-glacial mistletoe invasion, independent of host identity, and that habitat types recently isolated P. schiedeanus populations, accumulating slight phenotypic differences among genetic groups due to recent migration across habitats. Under this scenario, climatic fluctuations throughout the Pleistocene would have altered the distribution of suitable habitat for mistletoes throughout Mesoamerica leading to variation in population continuity and isolation. Our findings add to an understanding of the role of recent isolation and colonization in shaping cloud forest communities in the region.

Network-level architecture and the evolutionary potential of underground metabolism.

PubMed

Notebaart, Richard A; Szappanos, Balázs; Kintses, Bálint; Pál, Ferenc; Györkei, Ádám; Bogos, Balázs; Lázár, Viktória; Spohn, Réka; Csörgő, Bálint; Wagner, Allon; Ruppin, Eytan; Pál, Csaba; Papp, Balázs

2014-08-12

A central unresolved issue in evolutionary biology is how metabolic innovations emerge. Low-level enzymatic side activities are frequent and can potentially be recruited for new biochemical functions. However, the role of such underground reactions in adaptation toward novel environments has remained largely unknown and out of reach of computational predictions, not least because these issues demand analyses at the level of the entire metabolic network. Here, we provide a comprehensive computational model of the underground metabolism in Escherichia coli. Most underground reactions are not isolated and 45% of them can be fully wired into the existing network and form novel pathways that produce key precursors for cell growth. This observation allowed us to conduct an integrated genome-wide in silico and experimental survey to characterize the evolutionary potential of E. coli to adapt to hundreds of nutrient conditions. We revealed that underground reactions allow growth in new environments when their activity is increased. We estimate that at least ∼20% of the underground reactions that can be connected to the existing network confer a fitness advantage under specific environments. Moreover, our results demonstrate that the genetic basis of evolutionary adaptations via underground metabolism is computationally predictable. The approach used here has potential for various application areas from bioengineering to medical genetics.

Engaging Undergraduate Math Majors in Geoscience Research using Interactive Simulations and Computer Art

NASA Astrophysics Data System (ADS)

Matott, L. S.; Hymiak, B.; Reslink, C. F.; Baxter, C.; Aziz, S.

2012-12-01

As part of the NSF-sponsored 'URGE (Undergraduate Research Group Experiences) to Compute' program, Dr. Matott has been collaborating with talented Math majors to explore the design of cost-effective systems to safeguard groundwater supplies from contaminated sites. Such activity is aided by a combination of groundwater modeling, simulation-based optimization, and high-performance computing - disciplines largely unfamiliar to the students at the outset of the program. To help train and engage the students, a number of interactive and graphical software packages were utilized. Examples include: (1) a tutorial for exploring the behavior of evolutionary algorithms and other heuristic optimizers commonly used in simulation-based optimization; (2) an interactive groundwater modeling package for exploring alternative pump-and-treat containment scenarios at a contaminated site in Billings, Montana; (3) the R software package for visualizing various concepts related to subsurface hydrology; and (4) a job visualization tool for exploring the behavior of numerical experiments run on a large distributed computing cluster. Further engagement and excitement in the program was fostered by entering (and winning) a computer art competition run by the Coalition for Academic Scientific Computation (CASC). The winning submission visualizes an exhaustively mapped optimization cost surface and dramatically illustrates the phenomena of artificial minima - valley locations that correspond to designs whose costs are only partially optimal.

Adaptive landscape and functional diversity of Neotropical cichlids: implications for the ecology and evolution of Cichlinae (Cichlidae; Cichliformes).

PubMed

Arbour, J H; López-Fernández, H

2014-11-01

Morphological, lineage and ecological diversity can vary substantially even among closely related lineages. Factors that influence morphological diversification, especially in functionally relevant traits, can help to explain the modern distribution of disparity across phylogenies and communities. Multivariate axes of feeding functional morphology from 75 species of Neotropical cichlid and a stepwise-AIC algorithm were used to estimate the adaptive landscape of functional morphospace in Cichlinae. Adaptive landscape complexity and convergence, as well as the functional diversity of Cichlinae, were compared with expectations under null evolutionary models. Neotropical cichlid feeding function varied primarily between traits associated with ram feeding vs. suction feeding/biting and secondarily with oral jaw muscle size and pharyngeal crushing capacity. The number of changes in selective regimes and the amount of convergence between lineages was higher than expected under a null model of evolution, but convergence was not higher than expected under a similarly complex adaptive landscape. Functional disparity was compatible with an adaptive landscape model, whereas the distribution of evolutionary change through morphospace corresponded with a process of evolution towards a single adaptive peak. The continentally distributed Neotropical cichlids have evolved relatively rapidly towards a number of adaptive peaks in functional trait space. Selection in Cichlinae functional morphospace is more complex than expected under null evolutionary models. The complexity of selective constraints in feeding morphology has likely been a significant contributor to the diversity of feeding ecology in this clade. © 2014 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

CRITTERS! A Realistic Simulation for Teaching Evolutionary Biology

ERIC Educational Resources Information Center

Latham, Luke G., II; Scully, Erik P.

2008-01-01

Evolutionary processes can be studied in nature and in the laboratory, but time and financial constraints result in few opportunities for undergraduate and high school students to explore the agents of genetic change in populations. One alternative to time consuming and expensive teaching laboratories is the use of computer simulations. We…

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.

Speeding Up Ecological and Evolutionary Computations in R; Essentials of High Performance Computing for Biologists

PubMed Central

Visser, Marco D.; McMahon, Sean M.; Merow, Cory; Dixon, Philip M.; Record, Sydne; Jongejans, Eelke

2015-01-01

Computation has become a critical component of research in biology. A risk has emerged that computational and programming challenges may limit research scope, depth, and quality. We review various solutions to common computational efficiency problems in ecological and evolutionary research. Our review pulls together material that is currently scattered across many sources and emphasizes those techniques that are especially effective for typical ecological and environmental problems. We demonstrate how straightforward it can be to write efficient code and implement techniques such as profiling or parallel computing. We supply a newly developed R package (aprof) that helps to identify computational bottlenecks in R code and determine whether optimization can be effective. Our review is complemented by a practical set of examples and detailed Supporting Information material (S1–S3 Texts) that demonstrate large improvements in computational speed (ranging from 10.5 times to 14,000 times faster). By improving computational efficiency, biologists can feasibly solve more complex tasks, ask more ambitious questions, and include more sophisticated analyses in their research. PMID:25811842

An Adaptive Evolutionary Algorithm for Traveling Salesman Problem with Precedence Constraints

PubMed Central

Sung, Jinmo; Jeong, Bongju

2014-01-01

Traveling sales man problem with precedence constraints is one of the most notorious problems in terms of the efficiency of its solution approach, even though it has very wide range of industrial applications. We propose a new evolutionary algorithm to efficiently obtain good solutions by improving the search process. Our genetic operators guarantee the feasibility of solutions over the generations of population, which significantly improves the computational efficiency even when it is combined with our flexible adaptive searching strategy. The efficiency of the algorithm is investigated by computational experiments. PMID:24701158

An adaptive evolutionary algorithm for traveling salesman problem with precedence constraints.

PubMed

Sung, Jinmo; Jeong, Bongju

2014-01-01

Traveling sales man problem with precedence constraints is one of the most notorious problems in terms of the efficiency of its solution approach, even though it has very wide range of industrial applications. We propose a new evolutionary algorithm to efficiently obtain good solutions by improving the search process. Our genetic operators guarantee the feasibility of solutions over the generations of population, which significantly improves the computational efficiency even when it is combined with our flexible adaptive searching strategy. The efficiency of the algorithm is investigated by computational experiments.

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

Mean-Potential Law in Evolutionary Games

NASA Astrophysics Data System (ADS)

Nałecz-Jawecki, Paweł; Miekisz, Jacek

2018-01-01

The Letter presents a novel way to connect random walks, stochastic differential equations, and evolutionary game theory. We introduce a new concept of a potential function for discrete-space stochastic systems. It is based on a correspondence between one-dimensional stochastic differential equations and random walks, which may be exact not only in the continuous limit but also in finite-state spaces. Our method is useful for computation of fixation probabilities in discrete stochastic dynamical systems with two absorbing states. We apply it to evolutionary games, formulating two simple and intuitive criteria for evolutionary stability of pure Nash equilibria in finite populations. In particular, we show that the 1 /3 law of evolutionary games, introduced by Nowak et al. [Nature, 2004], follows from a more general mean-potential law.

Simple sequence repeats in Escherichia coli: abundance, distribution, composition, and polymorphism.

PubMed

Gur-Arie, R; Cohen, C J; Eitan, Y; Shelef, L; Hallerman, E M; Kashi, Y

2000-01-01

Computer-based genome-wide screening of the DNA sequence of Escherichia coli strain K12 revealed tens of thousands of tandem simple sequence repeat (SSR) tracts, with motifs ranging from 1 to 6 nucleotides. SSRs were well distributed throughout the genome. Mononucleotide SSRs were over-represented in noncoding regions and under-represented in open reading frames (ORFs). Nucleotide composition of mono- and dinucleotide SSRs, both in ORFs and in noncoding regions, differed from that of the genomic region in which they occurred, with 93% of all mononucleotide SSRs proving to be of A or T. Computer-based analysis of the fine position of every SSR locus in the noncoding portion of the genome relative to downstream ORFs showed SSRs located in areas that could affect gene regulation. DNA sequences at 14 arbitrarily chosen SSR tracts were compared among E. coli strains. Polymorphisms of SSR copy number were observed at four of seven mononucleotide SSR tracts screened, with all polymorphisms occurring in noncoding regions. SSR polymorphism could prove important as a genome-wide source of variation, both for practical applications (including rapid detection, strain identification, and detection of loci affecting key phenotypes) and for evolutionary adaptation of microbes.

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.

Toward a unifying framework for evolutionary processes.

PubMed

Paixão, Tiago; Badkobeh, Golnaz; Barton, Nick; Çörüş, Doğan; Dang, Duc-Cuong; Friedrich, Tobias; Lehre, Per Kristian; Sudholt, Dirk; Sutton, Andrew M; Trubenová, Barbora

2015-10-21

The theory of population genetics and evolutionary computation have been evolving separately for nearly 30 years. Many results have been independently obtained in both fields and many others are unique to its respective field. We aim to bridge this gap by developing a unifying framework for evolutionary processes that allows both evolutionary algorithms and population genetics models to be cast in the same formal framework. The framework we present here decomposes the evolutionary process into its several components in order to facilitate the identification of similarities between different models. In particular, we propose a classification of evolutionary operators based on the defining properties of the different components. We cast several commonly used operators from both fields into this common framework. Using this, we map different evolutionary and genetic algorithms to different evolutionary regimes and identify candidates with the most potential for the translation of results between the fields. This provides a unified description of evolutionary processes and represents a stepping stone towards new tools and results to both fields. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks

NASA Technical Reports Server (NTRS)

Rai, Man Mohan

2006-01-01

Genetic and evolutionary algorithms have been applied to solve numerous problems in engineering design where they have been used primarily as optimization procedures. These methods have an advantage over conventional gradient-based search procedures became they are capable of finding global optima of multi-modal functions and searching design spaces with disjoint feasible regions. They are also robust in the presence of noisy data. Another desirable feature of these methods is that they can efficiently use distributed and parallel computing resources since multiple function evaluations (flow simulations in aerodynamics design) can be performed simultaneously and independently on ultiple processors. For these reasons genetic and evolutionary algorithms are being used more frequently in design optimization. Examples include airfoil and wing design and compressor and turbine airfoil design. They are also finding increasing use in multiple-objective and multidisciplinary optimization. This lecture will focus on an evolutionary method that is a relatively new member to the general class of evolutionary methods called differential evolution (DE). This method is easy to use and program and it requires relatively few user-specified constants. These constants are easily determined for a wide class of problems. Fine-tuning the constants will off course yield the solution to the optimization problem at hand more rapidly. DE can be efficiently implemented on parallel computers and can be used for continuous, discrete and mixed discrete/continuous optimization problems. It does not require the objective function to be continuous and is noise tolerant. DE and applications to single and multiple-objective optimization will be included in the presentation and lecture notes. A method for aerodynamic design optimization that is based on neural networks will also be included as a part of this lecture. The method offers advantages over traditional optimization methods. It is more flexible than other methods in dealing with design in the context of both steady and unsteady flows, partial and complete data sets, combined experimental and numerical data, inclusion of various constraints and rules of thumb, and other issues that characterize the aerodynamic design process. Neural networks provide a natural framework within which a succession of numerical solutions of increasing fidelity, incorporating more realistic flow physics, can be represented and utilized for optimization. Neural networks also offer an excellent framework for multiple-objective and multi-disciplinary design optimization. Simulation tools from various disciplines can be integrated within this framework and rapid trade-off studies involving one or many disciplines can be performed. The prospect of combining neural network based optimization methods and evolutionary algorithms to obtain a hybrid method with the best properties of both methods will be included in this presentation. Achieving solution diversity and accurate convergence to the exact Pareto front in multiple objective optimization usually requires a significant computational effort with evolutionary algorithms. In this lecture we will also explore the possibility of using neural networks to obtain estimates of the Pareto optimal front using non-dominated solutions generated by DE as training data. Neural network estimators have the potential advantage of reducing the number of function evaluations required to obtain solution accuracy and diversity, thus reducing cost to design.

The importance of offshore origination revealed through ophiuroid phylogenomics.

PubMed

Bribiesca-Contreras, Guadalupe; Verbruggen, Heroen; Hugall, Andrew F; O'Hara, Timothy D

2017-07-12

Our knowledge of macro-evolutionary processes in the deep sea is poor, leading to much speculation about whether the deep sea is a source or sink of evolutionary adaptation. Here, we use a phylogenetic approach, on large molecular (688 species, 275 kbp) and distributional datasets (104 513 records) across an entire class of marine invertebrates (Ophiuroidea), to infer rates of bathymetric range shift over time between shallow and deep water biomes. Biome conservation is evident through the phylogeny, with the majority of species in most clades distributed within the same bathome. Despite this, bathymetric shifts have occurred. We inferred from ancestral reconstructions that eurybathic or intermediate distributions across both biomes were a transitional state and direct changes between shallow and deep sea did not occur. The macro-evolutionary pattern of bathome shift appeared to reflect micro-evolutionary processes of bathymetric speciation. Results suggest that most of the oldest clades have a deep-sea origin, but multiple colonization events indicate that the evolution of this group conforms neither to a simple onshore-offshore hypothesis, nor the opposite pattern. Both shallow and deep bathomes have played an important role in generating the current diversity of this major benthic class. © 2017 The Author(s).

How does cognition evolve? Phylogenetic comparative psychology

PubMed Central

Matthews, Luke J.; Hare, Brian A.; Nunn, Charles L.; Anderson, Rindy C.; Aureli, Filippo; Brannon, Elizabeth M.; Call, Josep; Drea, Christine M.; Emery, Nathan J.; Haun, Daniel B. M.; Herrmann, Esther; Jacobs, Lucia F.; Platt, Michael L.; Rosati, Alexandra G.; Sandel, Aaron A.; Schroepfer, Kara K.; Seed, Amanda M.; Tan, Jingzhi; van Schaik, Carel P.; Wobber, Victoria

2014-01-01

Now more than ever animal studies have the potential to test hypotheses regarding how cognition evolves. Comparative psychologists have developed new techniques to probe the cognitive mechanisms underlying animal behavior, and they have become increasingly skillful at adapting methodologies to test multiple species. Meanwhile, evolutionary biologists have generated quantitative approaches to investigate the phylogenetic distribution and function of phenotypic traits, including cognition. In particular, phylogenetic methods can quantitatively (1) test whether specific cognitive abilities are correlated with life history (e.g., lifespan), morphology (e.g., brain size), or socio-ecological variables (e.g., social system), (2) measure how strongly phylogenetic relatedness predicts the distribution of cognitive skills across species, and (3) estimate the ancestral state of a given cognitive trait using measures of cognitive performance from extant species. Phylogenetic methods can also be used to guide the selection of species comparisons that offer the strongest tests of a priori predictions of cognitive evolutionary hypotheses (i.e., phylogenetic targeting). Here, we explain how an integration of comparative psychology and evolutionary biology will answer a host of questions regarding the phylogenetic distribution and history of cognitive traits, as well as the evolutionary processes that drove their evolution. PMID:21927850

Evolutionary model of the growth and size of firms

NASA Astrophysics Data System (ADS)

Kaldasch, Joachim

2012-07-01

The key idea of this model is that firms are the result of an evolutionary process. Based on demand and supply considerations the evolutionary model presented here derives explicitly Gibrat's law of proportionate effects as the result of the competition between products. Applying a preferential attachment mechanism for firms, the theory allows to establish the size distribution of products and firms. Also established are the growth rate and price distribution of consumer goods. Taking into account the characteristic property of human activities to occur in bursts, the model allows also an explanation of the size-variance relationship of the growth rate distribution of products and firms. Further the product life cycle, the learning (experience) curve and the market size in terms of the mean number of firms that can survive in a market are derived. The model also suggests the existence of an invariant of a market as the ratio of total profit to total revenue. The relationship between a neo-classic and an evolutionary view of a market is discussed. The comparison with empirical investigations suggests that the theory is able to describe the main stylized facts concerning the size and growth of firms.

How does cognition evolve? Phylogenetic comparative psychology.

PubMed

MacLean, Evan L; Matthews, Luke J; Hare, Brian A; Nunn, Charles L; Anderson, Rindy C; Aureli, Filippo; Brannon, Elizabeth M; Call, Josep; Drea, Christine M; Emery, Nathan J; Haun, Daniel B M; Herrmann, Esther; Jacobs, Lucia F; Platt, Michael L; Rosati, Alexandra G; Sandel, Aaron A; Schroepfer, Kara K; Seed, Amanda M; Tan, Jingzhi; van Schaik, Carel P; Wobber, Victoria

2012-03-01

Now more than ever animal studies have the potential to test hypotheses regarding how cognition evolves. Comparative psychologists have developed new techniques to probe the cognitive mechanisms underlying animal behavior, and they have become increasingly skillful at adapting methodologies to test multiple species. Meanwhile, evolutionary biologists have generated quantitative approaches to investigate the phylogenetic distribution and function of phenotypic traits, including cognition. In particular, phylogenetic methods can quantitatively (1) test whether specific cognitive abilities are correlated with life history (e.g., lifespan), morphology (e.g., brain size), or socio-ecological variables (e.g., social system), (2) measure how strongly phylogenetic relatedness predicts the distribution of cognitive skills across species, and (3) estimate the ancestral state of a given cognitive trait using measures of cognitive performance from extant species. Phylogenetic methods can also be used to guide the selection of species comparisons that offer the strongest tests of a priori predictions of cognitive evolutionary hypotheses (i.e., phylogenetic targeting). Here, we explain how an integration of comparative psychology and evolutionary biology will answer a host of questions regarding the phylogenetic distribution and history of cognitive traits, as well as the evolutionary processes that drove their evolution.

Computation of direct and inverse mutations with the SEGM web server (Stochastic Evolution of Genetic Motifs): an application to splice sites of human genome introns.

PubMed

Benard, Emmanuel; Michel, Christian J

2009-08-01

We present here the SEGM web server (Stochastic Evolution of Genetic Motifs) in order to study the evolution of genetic motifs both in the direct evolutionary sense (past-present) and in the inverse evolutionary sense (present-past). The genetic motifs studied can be nucleotides, dinucleotides and trinucleotides. As an example of an application of SEGM and to understand its functionalities, we give an analysis of inverse mutations of splice sites of human genome introns. SEGM is freely accessible at http://lsiit-bioinfo.u-strasbg.fr:8080/webMathematica/SEGM/SEGM.html directly or by the web site http://dpt-info.u-strasbg.fr/~michel/. To our knowledge, this SEGM web server is to date the only computational biology software in this evolutionary approach.

Biology Needs Evolutionary Software Tools: Let’s Build Them Right

PubMed Central

Team, Galaxy; Goecks, Jeremy; Taylor, James

2018-01-01

Abstract Research in population genetics and evolutionary biology has always provided a computational backbone for life sciences as a whole. Today evolutionary and population biology reasoning are essential for interpretation of large complex datasets that are characteristic of all domains of today’s life sciences ranging from cancer biology to microbial ecology. This situation makes algorithms and software tools developed by our community more important than ever before. This means that we, developers of software tool for molecular evolutionary analyses, now have a shared responsibility to make these tools accessible using modern technological developments as well as provide adequate documentation and training. PMID:29688462

Why is the correlation between gene importance and gene evolutionary rate so weak?

PubMed

Wang, Zhi; Zhang, Jianzhi

2009-01-01

One of the few commonly believed principles of molecular evolution is that functionally more important genes (or DNA sequences) evolve more slowly than less important ones. This principle is widely used by molecular biologists in daily practice. However, recent genomic analysis of a diverse array of organisms found only weak, negative correlations between the evolutionary rate of a gene and its functional importance, typically measured under a single benign lab condition. A frequently suggested cause of the above finding is that gene importance determined in the lab differs from that in an organism's natural environment. Here, we test this hypothesis in yeast using gene importance values experimentally determined in 418 lab conditions or computationally predicted for 10,000 nutritional conditions. In no single condition or combination of conditions did we find a much stronger negative correlation, which is explainable by our subsequent finding that always-essential (enzyme) genes do not evolve significantly more slowly than sometimes-essential or always-nonessential ones. Furthermore, we verified that functional density, approximated by the fraction of amino acid sites within protein domains, is uncorrelated with gene importance. Thus, neither the lab-nature mismatch nor a potentially biased among-gene distribution of functional density explains the observed weakness of the correlation between gene importance and evolutionary rate. We conclude that the weakness is factual, rather than artifactual. In addition to being weakened by population genetic reasons, the correlation is likely to have been further weakened by the presence of multiple nontrivial rate determinants that are independent from gene importance. These findings notwithstanding, we show that the principle of slower evolution of more important genes does have some predictive power when genes with vastly different evolutionary rates are compared, explaining why the principle can be practically useful despite the weakness of the correlation.

Evolutionary profiles derived from the QR factorization of multiple structural alignments gives an economy of information.

PubMed

O'Donoghue, Patrick; Luthey-Schulten, Zaida

2005-02-25

We present a new algorithm, based on the multidimensional QR factorization, to remove redundancy from a multiple structural alignment by choosing representative protein structures that best preserve the phylogenetic tree topology of the homologous group. The classical QR factorization with pivoting, developed as a fast numerical solution to eigenvalue and linear least-squares problems of the form Ax=b, was designed to re-order the columns of A by increasing linear dependence. Removing the most linear dependent columns from A leads to the formation of a minimal basis set which well spans the phase space of the problem at hand. By recasting the problem of redundancy in multiple structural alignments into this framework, in which the matrix A now describes the multiple alignment, we adapted the QR factorization to produce a minimal basis set of protein structures which best spans the evolutionary (phase) space. The non-redundant and representative profiles obtained from this procedure, termed evolutionary profiles, are shown in initial results to outperform well-tested profiles in homology detection searches over a large sequence database. A measure of structural similarity between homologous proteins, Q(H), is presented. By properly accounting for the effect and presence of gaps, a phylogenetic tree computed using this metric is shown to be congruent with the maximum-likelihood sequence-based phylogeny. The results indicate that evolutionary information is indeed recoverable from the comparative analysis of protein structure alone. Applications of the QR ordering and this structural similarity metric to analyze the evolution of structure among key, universally distributed proteins involved in translation, and to the selection of representatives from an ensemble of NMR structures are also discussed.

Simulation of the evolution of root water foraging strategies in dry and shallow soils.

PubMed

Renton, Michael; Poot, Pieter

2014-09-01

The dynamic structural development of plants can be seen as a strategy for exploiting the limited resources available within their environment, and we would expect that evolution would lead to efficient strategies that reduce costs while maximizing resource acquisition. In particular, perennial species endemic to habitats with shallow soils in seasonally dry environments have been shown to have a specialized root system morphology that may enhance access to water resources in the underlying rock. This study aimed to explore these hypotheses by applying evolutionary algorithms to a functional-structural root growth model. A simulation model of a plant's root system was developed, which represents the dynamics of water uptake and structural growth. The model is simple enough for evolutionary optimization to be computationally feasible, yet flexible enough to allow a range of structural development strategies to be explored. The model was combined with an evolutionary algorithm in order to investigate a case study habitat with a highly heterogeneous distribution of resources, both spatially and temporally--the situation of perennial plants occurring on shallow soils in seasonally dry environments. Evolution was simulated under two contrasting fitness criteria: (1) the ability to find wet cracks in underlying rock, and (2) maximizing above-ground biomass. The novel approach successfully resulted in the evolution of more efficient structural development strategies for both fitness criteria. Different rooting strategies evolved when different criteria were applied, and each evolved strategy made ecological sense in terms of the corresponding fitness criterion. Evolution selected for root system morphologies which matched those of real species from corresponding habitats. Specialized root morphology with deeper rather than shallower lateral branching enhances access to water resources in underlying rock. More generally, the approach provides insights into both evolutionary processes and ecological costs and benefits of different plant growth strategies.

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.

General Methods for Evolutionary Quantitative Genetic Inference from Generalized Mixed Models.

PubMed

de Villemereuil, Pierre; Schielzeth, Holger; Nakagawa, Shinichi; Morrissey, Michael

2016-11-01

Methods for inference and interpretation of evolutionary quantitative genetic parameters, and for prediction of the response to selection, are best developed for traits with normal distributions. Many traits of evolutionary interest, including many life history and behavioral traits, have inherently nonnormal distributions. The generalized linear mixed model (GLMM) framework has become a widely used tool for estimating quantitative genetic parameters for nonnormal traits. However, whereas GLMMs provide inference on a statistically convenient latent scale, it is often desirable to express quantitative genetic parameters on the scale upon which traits are measured. The parameters of fitted GLMMs, despite being on a latent scale, fully determine all quantities of potential interest on the scale on which traits are expressed. We provide expressions for deriving each of such quantities, including population means, phenotypic (co)variances, variance components including additive genetic (co)variances, and parameters such as heritability. We demonstrate that fixed effects have a strong impact on those parameters and show how to deal with this by averaging or integrating over fixed effects. The expressions require integration of quantities determined by the link function, over distributions of latent values. In general cases, the required integrals must be solved numerically, but efficient methods are available and we provide an implementation in an R package, QGglmm. We show that known formulas for quantities such as heritability of traits with binomial and Poisson distributions are special cases of our expressions. Additionally, we show how fitted GLMM can be incorporated into existing methods for predicting evolutionary trajectories. We demonstrate the accuracy of the resulting method for evolutionary prediction by simulation and apply our approach to data from a wild pedigreed vertebrate population. Copyright © 2016 de Villemereuil et al.

Evolution of a genetic polymorphism with climate change in a Mediterranean landscape

PubMed Central

Thompson, John; Charpentier, Anne; Bouguet, Guillaume; Charmasson, Faustine; Roset, Stephanie; Buatois, Bruno; Vernet, Philippe; Gouyon, Pierre-Henri

2013-01-01

Many species show changes in distribution and phenotypic trait variation in response to climatic warming. Evidence of genetically based trait responses to climate change is, however, less common. Here, we detected evolutionary variation in the landscape-scale distribution of a genetically based chemical polymorphism in Mediterranean wild thyme (Thymus vulgaris) in association with modified extreme winter freezing events. By comparing current data on morph distribution with that observed in the early 1970s, we detected a significant increase in the proportion of morphs that are sensitive to winter freezing. This increase in frequency was observed in 17 of the 24 populations in which, since the 1970s, annual extreme winter freezing temperatures have risen above the thresholds that cause mortality of freezing-sensitive morphs. Our results provide an original example of rapid ongoing evolutionary change associated with relaxed selection (less extreme freezing events) on a local landscape scale. In species whose distribution and genetic variability are shaped by strong selection gradients, there may be little time lag associated with their ecological and evolutionary response to long-term environmental change. PMID:23382198

Evolving Better Cars: Teaching Evolution by Natural Selection with a Digital Inquiry Activity

ERIC Educational Resources Information Center

Royer, Anne M.; Schultheis, Elizabeth H.

2014-01-01

Evolutionary experiments are usually difficult to perform in the classroom because of the large sizes and long timescales of experiments testing evolutionary hypotheses. Computer applications give students a window to observe evolution in action, allowing them to gain comfort with the process of natural selection and facilitating inquiry…

Memetic Algorithms, Domain Knowledge, and Financial Investing

ERIC Educational Resources Information Center

Du, Jie

2012-01-01

While the question of how to use human knowledge to guide evolutionary search is long-recognized, much remains to be done to answer this question adequately. This dissertation aims to further answer this question by exploring the role of domain knowledge in evolutionary computation as applied to real-world, complex problems, such as financial…

Resistance and relatedness on an evolutionary graph

PubMed Central

Maciejewski, Wes

2012-01-01

When investigating evolution in structured populations, it is often convenient to consider the population as an evolutionary graph—individuals as nodes, and whom they may act with as edges. There has, in recent years, been a surge of interest in evolutionary graphs, especially in the study of the evolution of social behaviours. An inclusive fitness framework is best suited for this type of study. A central requirement for an inclusive fitness analysis is an expression for the genetic similarity between individuals residing on the graph. This has been a major hindrance for work in this area as highly technical mathematics are often required. Here, I derive a result that links genetic relatedness between haploid individuals on an evolutionary graph to the resistance between vertices on a corresponding electrical network. An example that demonstrates the potential computational advantage of this result over contemporary approaches is provided. This result offers more, however, to the study of population genetics than strictly computationally efficient methods. By establishing a link between gene transfer and electric circuit theory, conceptualizations of the latter can enhance understanding of the former. PMID:21849384

An Evolutionary Algorithm for Fast Intensity Based Image Matching Between Optical and SAR Satellite Imagery

NASA Astrophysics Data System (ADS)

Fischer, Peter; Schuegraf, Philipp; Merkle, Nina; Storch, Tobias

2018-04-01

This paper presents a hybrid evolutionary algorithm for fast intensity based matching between satellite imagery from SAR and very high-resolution (VHR) optical sensor systems. The precise and accurate co-registration of image time series and images of different sensors is a key task in multi-sensor image processing scenarios. The necessary preprocessing step of image matching and tie-point detection is divided into a search problem and a similarity measurement. Within this paper we evaluate the use of an evolutionary search strategy for establishing the spatial correspondence between satellite imagery of optical and radar sensors. The aim of the proposed algorithm is to decrease the computational costs during the search process by formulating the search as an optimization problem. Based upon the canonical evolutionary algorithm, the proposed algorithm is adapted for SAR/optical imagery intensity based matching. Extensions are drawn using techniques like hybridization (e.g. local search) and others to lower the number of objective function calls and refine the result. The algorithm significantely decreases the computational costs whilst finding the optimal solution in a reliable way.

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)

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.

Reuse, Recycle, Reweigh: Combating Influenza through Efficient Sequential Bayesian Computation for Massive Data.

PubMed

Tom, Jennifer A; Sinsheimer, Janet S; Suchard, Marc A

Massive datasets in the gigabyte and terabyte range combined with the availability of increasingly sophisticated statistical tools yield analyses at the boundary of what is computationally feasible. Compromising in the face of this computational burden by partitioning the dataset into more tractable sizes results in stratified analyses, removed from the context that justified the initial data collection. In a Bayesian framework, these stratified analyses generate intermediate realizations, often compared using point estimates that fail to account for the variability within and correlation between the distributions these realizations approximate. However, although the initial concession to stratify generally precludes the more sensible analysis using a single joint hierarchical model, we can circumvent this outcome and capitalize on the intermediate realizations by extending the dynamic iterative reweighting MCMC algorithm. In doing so, we reuse the available realizations by reweighting them with importance weights, recycling them into a now tractable joint hierarchical model. We apply this technique to intermediate realizations generated from stratified analyses of 687 influenza A genomes spanning 13 years allowing us to revisit hypotheses regarding the evolutionary history of influenza within a hierarchical statistical framework.

Reuse, Recycle, Reweigh: Combating Influenza through Efficient Sequential Bayesian Computation for Massive Data

PubMed Central

Tom, Jennifer A.; Sinsheimer, Janet S.; Suchard, Marc A.

2015-01-01

Massive datasets in the gigabyte and terabyte range combined with the availability of increasingly sophisticated statistical tools yield analyses at the boundary of what is computationally feasible. Compromising in the face of this computational burden by partitioning the dataset into more tractable sizes results in stratified analyses, removed from the context that justified the initial data collection. In a Bayesian framework, these stratified analyses generate intermediate realizations, often compared using point estimates that fail to account for the variability within and correlation between the distributions these realizations approximate. However, although the initial concession to stratify generally precludes the more sensible analysis using a single joint hierarchical model, we can circumvent this outcome and capitalize on the intermediate realizations by extending the dynamic iterative reweighting MCMC algorithm. In doing so, we reuse the available realizations by reweighting them with importance weights, recycling them into a now tractable joint hierarchical model. We apply this technique to intermediate realizations generated from stratified analyses of 687 influenza A genomes spanning 13 years allowing us to revisit hypotheses regarding the evolutionary history of influenza within a hierarchical statistical framework. PMID:26681992

An evolutionary firefly algorithm for the estimation of nonlinear biological model parameters.

PubMed

Abdullah, Afnizanfaizal; Deris, Safaai; Anwar, Sohail; Arjunan, Satya N V

2013-01-01

The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test.

An Evolutionary Firefly Algorithm for the Estimation of Nonlinear Biological Model Parameters

PubMed Central

Abdullah, Afnizanfaizal; Deris, Safaai; Anwar, Sohail; Arjunan, Satya N. V.

2013-01-01

The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test. PMID:23469172

Evolutionary Dynamics of Microsatellite Distribution in Plants: Insight from the Comparison of Sequenced Brassica, Arabidopsis and Other Angiosperm Species

PubMed Central

Shi, Jiaqin; Huang, Shunmou; Fu, Donghui; Yu, Jinyin; Wang, Xinfa; Hua, Wei; Liu, Shengyi; Liu, Guihua; Wang, Hanzhong

2013-01-01

Despite their ubiquity and functional importance, microsatellites have been largely ignored in comparative genomics, mostly due to the lack of genomic information. In the current study, microsatellite distribution was characterized and compared in the whole genomes and both the coding and non-coding DNA sequences of the sequenced Brassica, Arabidopsis and other angiosperm species to investigate their evolutionary dynamics in plants. The variation in the microsatellite frequencies of these angiosperm species was much smaller than those for their microsatellite numbers and genome sizes, suggesting that microsatellite frequency may be relatively stable in plants. The microsatellite frequencies of these angiosperm species were significantly negatively correlated with both their genome sizes and transposable elements contents. The pattern of microsatellite distribution may differ according to the different genomic regions (such as coding and non-coding sequences). The observed differences in many important microsatellite characteristics (especially the distribution with respect to motif length, type and repeat number) of these angiosperm species were generally accordant with their phylogenetic distance, which suggested that the evolutionary dynamics of microsatellite distribution may be generally consistent with plant divergence/evolution. Importantly, by comparing these microsatellite characteristics (especially the distribution with respect to motif type) the angiosperm species (aside from a few species) all clustered into two obviously different groups that were largely represented by monocots and dicots, suggesting a complex and generally dichotomous evolutionary pattern of microsatellite distribution in angiosperms. Polyploidy may lead to a slight increase in microsatellite frequency in the coding sequences and a significant decrease in microsatellite frequency in the whole genome/non-coding sequences, but have little effect on the microsatellite distribution with respect to motif length, type and repeat number. Interestingly, several microsatellite characteristics seemed to be constant in plant evolution, which can be well explained by the general biological rules. PMID:23555856

Towards a Population Dynamics Theory for Evolutionary Computing: Learning from Biological Population Dynamics in Nature

NASA Astrophysics Data System (ADS)

Ma, Zhanshan (Sam)

In evolutionary computing (EC), population size is one of the critical parameters that a researcher has to deal with. Hence, it was no surprise that the pioneers of EC, such as De Jong (1975) and Holland (1975), had already studied the population sizing from the very beginning of EC. What is perhaps surprising is that more than three decades later, we still largely depend on the experience or ad-hoc trial-and-error approach to set the population size. For example, in a recent monograph, Eiben and Smith (2003) indicated: "In almost all EC applications, the population size is constant and does not change during the evolutionary search." Despite enormous research on this issue in recent years, we still lack a well accepted theory for population sizing. In this paper, I propose to develop a population dynamics theory forEC with the inspiration from the population dynamics theory of biological populations in nature. Essentially, the EC population is considered as a dynamic system over time (generations) and space (search space or fitness landscape), similar to the spatial and temporal dynamics of biological populations in nature. With this conceptual mapping, I propose to 'transplant' the biological population dynamics theory to EC via three steps: (i) experimentally test the feasibility—whether or not emulating natural population dynamics improves the EC performance; (ii) comparatively study the underlying mechanisms—why there are improvements, primarily via statistical modeling analysis; (iii) conduct theoretical analysis with theoretical models such as percolation theory and extended evolutionary game theory that are generally applicable to both EC and natural populations. This article is a summary of a series of studies we have performed to achieve the general goal [27][30]-[32]. In the following, I start with an extremely brief introduction on the theory and models of natural population dynamics (Sections 1 & 2). In Sections 4 to 6, I briefly discuss three categories of population dynamics models: deterministic modeling with Logistic chaos map as an example, stochastic modeling with spatial distribution patterns as an example, as well as survival analysis and extended evolutionary game theory (EEGT) modeling. Sample experiment results with Genetic algorithms (GA) are presented to demonstrate the applications of these models. The proposed EC population dynamics approach also makes survival selection largely unnecessary or much simplified since the individuals are naturally selected (controlled) by the mathematical models for EC population dynamics.

EvolQG - An R package for evolutionary quantitative genetics

PubMed Central

Melo, Diogo; Garcia, Guilherme; Hubbe, Alex; Assis, Ana Paula; Marroig, Gabriel

2016-01-01

We present an open source package for performing evolutionary quantitative genetics analyses in the R environment for statistical computing. Evolutionary theory shows that evolution depends critically on the available variation in a given population. When dealing with many quantitative traits this variation is expressed in the form of a covariance matrix, particularly the additive genetic covariance matrix or sometimes the phenotypic matrix, when the genetic matrix is unavailable and there is evidence the phenotypic matrix is sufficiently similar to the genetic matrix. Given this mathematical representation of available variation, the \\textbf{EvolQG} package provides functions for calculation of relevant evolutionary statistics; estimation of sampling error; corrections for this error; matrix comparison via correlations, distances and matrix decomposition; analysis of modularity patterns; and functions for testing evolutionary hypotheses on taxa diversification. PMID:27785352

Mean-Potential Law in Evolutionary Games.

PubMed

Nałęcz-Jawecki, Paweł; Miękisz, Jacek

2018-01-12

The Letter presents a novel way to connect random walks, stochastic differential equations, and evolutionary game theory. We introduce a new concept of a potential function for discrete-space stochastic systems. It is based on a correspondence between one-dimensional stochastic differential equations and random walks, which may be exact not only in the continuous limit but also in finite-state spaces. Our method is useful for computation of fixation probabilities in discrete stochastic dynamical systems with two absorbing states. We apply it to evolutionary games, formulating two simple and intuitive criteria for evolutionary stability of pure Nash equilibria in finite populations. In particular, we show that the 1/3 law of evolutionary games, introduced by Nowak et al. [Nature, 2004], follows from a more general mean-potential law.

Vertebral Pneumaticity in the Ornithomimosaur Archaeornithomimus (Dinosauria: Theropoda) Revealed by Computed Tomography Imaging and Reappraisal of Axial Pneumaticity in Ornithomimosauria

PubMed Central

Watanabe, Akinobu; Eugenia Leone Gold, Maria; Brusatte, Stephen L.; Benson, Roger B. J.; Choiniere, Jonah; Davidson, Amy; Norell, Mark A.

2015-01-01

Among extant vertebrates, pneumatization of postcranial bones is unique to birds, with few known exceptions in other groups. Through reduction in bone mass, this feature is thought to benefit flight capacity in modern birds, but its prevalence in non-avian dinosaurs of variable sizes has generated competing hypotheses on the initial adaptive significance of postcranial pneumaticity. To better understand the evolutionary history of postcranial pneumaticity, studies have surveyed its distribution among non-avian dinosaurs. Nevertheless, the degree of pneumaticity in the basal coelurosaurian group Ornithomimosauria remains poorly known, despite their potential to greatly enhance our understanding of the early evolution of pneumatic bones along the lineage leading to birds. Historically, the identification of postcranial pneumaticity in non-avian dinosaurs has been based on examination of external morphology, and few studies thus far have focused on the internal architecture of pneumatic structures inside the bones. Here, we describe the vertebral pneumaticity of the ornithomimosaur Archaeornithomimus with the aid of X-ray computed tomography (CT) imaging. Complementary examination of external and internal osteology reveals (1) highly pneumatized cervical vertebrae with an elaborate configuration of interconnected chambers within the neural arch and the centrum; (2) anterior dorsal vertebrae with pneumatic chambers inside the neural arch; (3) apneumatic sacral vertebrae; and (4) a subset of proximal caudal vertebrae with limited pneumatic invasion into the neural arch. Comparisons with other theropod dinosaurs suggest that ornithomimosaurs primitively exhibited a plesiomorphic theropod condition for axial pneumaticity that was extended among later taxa, such as Archaeornithomimus and large bodied Deinocheirus. This finding corroborates the notion that evolutionary increases in vertebral pneumaticity occurred in parallel among independent lineages of bird-line archosaurs. Beyond providing a comprehensive view of vertebral pneumaticity in a non-avian coelurosaur, this study demonstrates the utility and need of CT imaging for further clarifying the early evolutionary history of postcranial pneumaticity. PMID:26682888

The 'Biologically-Inspired Computing' Column

NASA Technical Reports Server (NTRS)

Hinchey, Mike

2006-01-01

The field of Biology changed dramatically in 1953, with the determination by Francis Crick and James Dewey Watson of the double helix structure of DNA. This discovery changed Biology for ever, allowing the sequencing of the human genome, and the emergence of a "new Biology" focused on DNA, genes, proteins, data, and search. Computational Biology and Bioinformatics heavily rely on computing to facilitate research into life and development. Simultaneously, an understanding of the biology of living organisms indicates a parallel with computing systems: molecules in living cells interact, grow, and transform according to the "program" dictated by DNA. Moreover, paradigms of Computing are emerging based on modelling and developing computer-based systems exploiting ideas that are observed in nature. This includes building into computer systems self-management and self-governance mechanisms that are inspired by the human body's autonomic nervous system, modelling evolutionary systems analogous to colonies of ants or other insects, and developing highly-efficient and highly-complex distributed systems from large numbers of (often quite simple) largely homogeneous components to reflect the behaviour of flocks of birds, swarms of bees, herds of animals, or schools of fish. This new field of "Biologically-Inspired Computing", often known in other incarnations by other names, such as: Autonomic Computing, Pervasive Computing, Organic Computing, Biomimetics, and Artificial Life, amongst others, is poised at the intersection of Computer Science, Engineering, Mathematics, and the Life Sciences. Successes have been reported in the fields of drug discovery, data communications, computer animation, control and command, exploration systems for space, undersea, and harsh environments, to name but a few, and augur much promise for future progress.

The evolution of cooperation on geographical networks

NASA Astrophysics Data System (ADS)

Li, Yixiao; Wang, Yi; Sheng, Jichuan

2017-11-01

We study evolutionary public goods game on geographical networks, i.e., complex networks which are located on a geographical plane. The geographical feature effects in two ways: In one way, the geographically-induced network structure influences the overall evolutionary dynamics, and, in the other way, the geographical length of an edge influences the cost when the two players at the two ends interact. For the latter effect, we design a new cost function of cooperators, which simply assumes that the longer the distance between two players, the higher cost the cooperator(s) of them have to pay. In this study, network substrates are generated by a previous spatial network model with a cost-benefit parameter controlling the network topology. Our simulations show that the greatest promotion of cooperation is achieved in the intermediate regime of the parameter, in which empirical estimates of various railway networks fall. Further, we investigate how the distribution of edges' geographical costs influences the evolutionary dynamics and consider three patterns of the distribution: an approximately-equal distribution, a diverse distribution, and a polarized distribution. For normal geographical networks which are generated using intermediate values of the cost-benefit parameter, a diverse distribution hinders the evolution of cooperation, whereas a polarized distribution lowers the threshold value of the amplification factor for cooperation in public goods game. These results are helpful for understanding the evolution of cooperation on real-world geographical networks.

Evolutionary versatility of eukaryotic protein domains revealed by their bigram networks

PubMed Central

2011-01-01

Background Protein domains are globular structures of independently folded polypeptides that exert catalytic or binding activities. Their sequences are recognized as evolutionary units that, through genome recombination, constitute protein repertoires of linkage patterns. Via mutations, domains acquire modified functions that contribute to the fitness of cells and organisms. Recent studies have addressed the evolutionary selection that may have shaped the functions of individual domains and the emergence of particular domain combinations, which led to new cellular functions in multi-cellular animals. This study focuses on modeling domain linkage globally and investigates evolutionary implications that may be revealed by novel computational analysis. Results A survey of 77 completely sequenced eukaryotic genomes implies a potential hierarchical and modular organization of biological functions in most living organisms. Domains in a genome or multiple genomes are modeled as a network of hetero-duplex covalent linkages, termed bigrams. A novel computational technique is introduced to decompose such networks, whereby the notion of domain "networking versatility" is derived and measured. The most and least "versatile" domains (termed "core domains" and "peripheral domains" respectively) are examined both computationally via sequence conservation measures and experimentally using selected domains. Our study suggests that such a versatility measure extracted from the bigram networks correlates with the adaptivity of domains during evolution, where the network core domains are highly adaptive, significantly contrasting the network peripheral domains. Conclusions Domain recombination has played a major part in the evolution of eukaryotes attributing to genome complexity. From a system point of view, as the results of selection and constant refinement, networks of domain linkage are structured in a hierarchical modular fashion. Domains with high degree of networking versatility appear to be evolutionary adaptive, potentially through functional innovations. Domain bigram networks are informative as a model of biological functions. The networking versatility indices extracted from such networks for individual domains reflect the strength of evolutionary selection that the domains have experienced. PMID:21849086

Evolutionary versatility of eukaryotic protein domains revealed by their bigram networks.

PubMed

Xie, Xueying; Jin, Jing; Mao, Yongyi

2011-08-18

Protein domains are globular structures of independently folded polypeptides that exert catalytic or binding activities. Their sequences are recognized as evolutionary units that, through genome recombination, constitute protein repertoires of linkage patterns. Via mutations, domains acquire modified functions that contribute to the fitness of cells and organisms. Recent studies have addressed the evolutionary selection that may have shaped the functions of individual domains and the emergence of particular domain combinations, which led to new cellular functions in multi-cellular animals. This study focuses on modeling domain linkage globally and investigates evolutionary implications that may be revealed by novel computational analysis. A survey of 77 completely sequenced eukaryotic genomes implies a potential hierarchical and modular organization of biological functions in most living organisms. Domains in a genome or multiple genomes are modeled as a network of hetero-duplex covalent linkages, termed bigrams. A novel computational technique is introduced to decompose such networks, whereby the notion of domain "networking versatility" is derived and measured. The most and least "versatile" domains (termed "core domains" and "peripheral domains" respectively) are examined both computationally via sequence conservation measures and experimentally using selected domains. Our study suggests that such a versatility measure extracted from the bigram networks correlates with the adaptivity of domains during evolution, where the network core domains are highly adaptive, significantly contrasting the network peripheral domains. Domain recombination has played a major part in the evolution of eukaryotes attributing to genome complexity. From a system point of view, as the results of selection and constant refinement, networks of domain linkage are structured in a hierarchical modular fashion. Domains with high degree of networking versatility appear to be evolutionary adaptive, potentially through functional innovations. Domain bigram networks are informative as a model of biological functions. The networking versatility indices extracted from such networks for individual domains reflect the strength of evolutionary selection that the domains have experienced.

Euryhalinity in an evolutionary context

USGS Publications Warehouse

Schultz, Eric T.; McCormick, Stephen D.; McCormick, Stephen D.; Farrell, Anthony Peter; Brauner, Colin J.

2013-01-01

This chapter focuses on the evolutionary importance and taxonomic distribution of euryhalinity. Euryhalinity refers to broad halotolerance and broad halohabitat distribution. Salinity exposure experiments have demonstrated that species vary tenfold in their range of tolerable salinity levels, primarily because of differences in upper limits. Halotolerance breadth varies with the species’ evolutionary history, as represented by its ordinal classification, and with the species’ halohabitat. Freshwater and seawater species tolerate brackish water; their empirically-determined fundamental haloniche is broader than their realized haloniche, as revealed by the halohabitats they occupy. With respect to halohabitat distribution, a minority of species (<10%) are euryhaline. Habitat-euryhalinity is prevalent among basal actinopterygian fishes, is largely absent from orders arising from intermediate nodes, and reappears in the most derived taxa. There is pronounced family-level variability in the tendency to be halohabitat-euryhaline, which may have arisen during a burst of diversification following the Cretaceous-Palaeogene extinction. Low prevalence notwithstanding, euryhaline species are potent sources of evolutionary diversity. Euryhalinity is regarded as a key innovation trait whose evolution enables exploitation of new adaptive zone, triggering cladogenesis. We review phylogenetically-informed studies that demonstrate freshwater species diversifying from euryhaline ancestors through processes such as landlocking. These studies indicate that some euryhaline taxa are particularly susceptible to changes in halohabitat and subsequent diversification, and some geographic regions have been hotspots for transitions to freshwater. Comparative studies on mechanisms among multiple taxa and at multiple levels of biological integration are needed to clarify evolutionary pathways to, and from, euryhalinity.

Are there laws of genome evolution?

PubMed

Koonin, Eugene V

2011-08-01

Research in quantitative evolutionary genomics and systems biology led to the discovery of several universal regularities connecting genomic and molecular phenomic variables. These universals include the log-normal distribution of the evolutionary rates of orthologous genes; the power law-like distributions of paralogous family size and node degree in various biological networks; the negative correlation between a gene's sequence evolution rate and expression level; and differential scaling of functional classes of genes with genome size. The universals of genome evolution can be accounted for by simple mathematical models similar to those used in statistical physics, such as the birth-death-innovation model. These models do not explicitly incorporate selection; therefore, the observed universal regularities do not appear to be shaped by selection but rather are emergent properties of gene ensembles. Although a complete physical theory of evolutionary biology is inconceivable, the universals of genome evolution might qualify as "laws of evolutionary genomics" in the same sense "law" is understood in modern physics.

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.

Computational Identification Raises a Riddle for Distribution of Putative NACHT NTPases in the Genome of Early Green Plants.

PubMed

Arya, Preeti; Acharya, Vishal

2016-01-01

NACHT NTPases and AP-ATPases belongs to STAND (signal transduction ATPases with numerous domain) P-loop NTPase class, which are known to be involved in defense signaling pathways and apoptosis regulation. The AP-ATPases (also known as NB-ARC) and NACHT NTPases are widely spread throughout all kingdoms of life except in plants, where only AP-ATPases have been extensively studied in the scenario of plant defense response against pathogen invasion and in hypersensitive response (HR). In the present study, we have employed a genome-wide survey (using stringent computational analysis) of 67 diverse organisms viz., archaebacteria, cyanobacteria, fungi, animalia and plantae to revisit the evolutionary history of these two STAND P-loop NTPases. This analysis divulged the presence of NACHT NTPases in the early green plants (green algae and the lycophyte) which had not been previously reported. These NACHT NTPases were known to be involved in diverse functional activities such as transcription regulation in addition to the defense signaling cascades depending on the domain association. In Chalmydomonas reinhardtii, a green algae, WD40 repeats found to be at the carboxyl-terminus of NACHT NTPases suggest probable role in apoptosis regulation. Moreover, the genome of Selaginella moellendorffii, an extant lycophyte, intriguingly shows the considerable number of both AP-ATPases and NACHT NTPases in contrast to a large repertoire of AP-ATPases in plants and emerge as an important node in the evolutionary tree of life. The large complement of AP-ATPases overtakes the function of NACHT NTPases and plausible reason behind the absence of the later in the plant lineages. The presence of NACHT NTPases in the early green plants and phyletic patterns results from this study raises a quandary for the distribution of this STAND P-loop NTPase with the apparent horizontal gene transfer from cyanobacteria.

Is mammalian chromosomal evolution driven by regions of genome fragility?

PubMed Central

Ruiz-Herrera, Aurora; Castresana, Jose; Robinson, Terence J

2006-01-01

Background A fundamental question in comparative genomics concerns the identification of mechanisms that underpin chromosomal change. In an attempt to shed light on the dynamics of mammalian genome evolution, we analyzed the distribution of syntenic blocks, evolutionary breakpoint regions, and evolutionary breakpoints taken from public databases available for seven eutherian species (mouse, rat, cattle, dog, pig, cat, and horse) and the chicken, and examined these for correspondence with human fragile sites and tandem repeats. Results Our results confirm previous investigations that showed the presence of chromosomal regions in the human genome that have been repeatedly used as illustrated by a high breakpoint accumulation in certain chromosomes and chromosomal bands. We show, however, that there is a striking correspondence between fragile site location, the positions of evolutionary breakpoints, and the distribution of tandem repeats throughout the human genome, which similarly reflect a non-uniform pattern of occurrence. Conclusion These observations provide further evidence that certain chromosomal regions in the human genome have been repeatedly used in the evolutionary process. As a consequence, the genome is a composite of fragile regions prone to reorganization that have been conserved in different lineages, and genomic tracts that do not exhibit the same levels of evolutionary plasticity. PMID:17156441

Delay-time distribution of core-collapse supernovae with late events resulting from binary interaction

NASA Astrophysics Data System (ADS)

Zapartas, E.; de Mink, S. E.; Izzard, R. G.; Yoon, S.-C.; Badenes, C.; Götberg, Y.; de Koter, A.; Neijssel, C. J.; Renzo, M.; Schootemeijer, A.; Shrotriya, T. S.

2017-05-01

Most massive stars, the progenitors of core-collapse supernovae, are in close binary systems and may interact with their companion through mass transfer or merging. We undertake a population synthesis study to compute the delay-time distribution of core-collapse supernovae, that is, the supernova rate versus time following a starburst, taking into account binary interactions. We test the systematic robustness of our results by running various simulations to account for the uncertainties in our standard assumptions. We find that a significant fraction, %, of core-collapse supernovae are "late", that is, they occur 50-200 Myr after birth, when all massive single stars have already exploded. These late events originate predominantly from binary systems with at least one, or, in most cases, with both stars initially being of intermediate mass (4-8 M⊙). The main evolutionary channels that contribute often involve either the merging of the initially more massive primary star with its companion or the engulfment of the remaining core of the primary by the expanding secondary that has accreted mass at an earlier evolutionary stage. Also, the total number of core-collapse supernovae increases by % because of binarity for the same initial stellar mass. The high rate implies that we should have already observed such late core-collapse supernovae, but have not recognized them as such. We argue that φ Persei is a likely progenitor and that eccentric neutron star - white dwarf systems are likely descendants. Late events can help explain the discrepancy in the delay-time distributions derived from supernova remnants in the Magellanic Clouds and extragalactic type Ia events, lowering the contribution of prompt Ia events. We discuss ways to test these predictions and speculate on the implications for supernova feedback in simulations of galaxy evolution.

Genetic structure and hierarchical population divergence history of Acer mono var. mono in South and Northeast China.

PubMed

Liu, Chunping; Tsuda, Yoshiaki; Shen, Hailong; Hu, Lijiang; Saito, Yoko; Ide, Yuji

2014-01-01

Knowledge of the genetic structure and evolutionary history of tree species across their ranges is essential for the development of effective conservation and forest management strategies. Acer mono var. mono, an economically and ecologically important maple species, is extensively distributed in Northeast China (NE), whereas it has a scattered and patchy distribution in South China (SC). In this study, the genetic structure and demographic history of 56 natural populations of A. mono var. mono were evaluated using seven nuclear microsatellite markers. Neighbor-joining tree and STRUCTURE analysis clearly separated populations into NE and SC groups with two admixed-like populations. Allelic richness significantly decreased with increasing latitude within the NE group while both allelic richness and expected heterozygosity showed significant positive correlation with latitude within the SC group. Especially in the NE region, previous studies in Quercus mongolica and Fraxinus mandshurica have also detected reductions in genetic diversity with increases in latitude, suggesting this pattern may be common for tree species in this region, probably due to expansion from single refugium following the last glacial maximum (LGM). Approximate Bayesian Computation-based analysis revealed two major features of hierarchical population divergence in the species' evolutionary history. Recent divergence between the NE group and the admixed-like group corresponded to the LGM period and ancient divergence of SC groups took place during mid-late Pleistocene period. The level of genetic differentiation was moderate (FST  = 0.073; G'ST  = 0.278) among all populations, but significantly higher in the SC group than the NE group, mirroring the species' more scattered distribution in SC. Conservation measures for this species are proposed, taking into account the genetic structure and past demographic history identified in this study.

Genetic Structure and Hierarchical Population Divergence History of Acer mono var. mono in South and Northeast China

PubMed Central

Shen, Hailong; Hu, Lijiang; Saito, Yoko; Ide, Yuji

2014-01-01

Knowledge of the genetic structure and evolutionary history of tree species across their ranges is essential for the development of effective conservation and forest management strategies. Acer mono var. mono, an economically and ecologically important maple species, is extensively distributed in Northeast China (NE), whereas it has a scattered and patchy distribution in South China (SC). In this study, the genetic structure and demographic history of 56 natural populations of A. mono var. mono were evaluated using seven nuclear microsatellite markers. Neighbor-joining tree and STRUCTURE analysis clearly separated populations into NE and SC groups with two admixed-like populations. Allelic richness significantly decreased with increasing latitude within the NE group while both allelic richness and expected heterozygosity showed significant positive correlation with latitude within the SC group. Especially in the NE region, previous studies in Quercus mongolica and Fraxinus mandshurica have also detected reductions in genetic diversity with increases in latitude, suggesting this pattern may be common for tree species in this region, probably due to expansion from single refugium following the last glacial maximum (LGM). Approximate Bayesian Computation-based analysis revealed two major features of hierarchical population divergence in the species’ evolutionary history. Recent divergence between the NE group and the admixed-like group corresponded to the LGM period and ancient divergence of SC groups took place during mid-late Pleistocene period. The level of genetic differentiation was moderate (FST = 0.073; G′ST = 0.278) among all populations, but significantly higher in the SC group than the NE group, mirroring the species’ more scattered distribution in SC. Conservation measures for this species are proposed, taking into account the genetic structure and past demographic history identified in this study. PMID:24498039

The Evolution of Biological Complexity in Digital Organisms

NASA Astrophysics Data System (ADS)

Ofria, Charles

2013-03-01

When Darwin first proposed his theory of evolution by natural selection, he realized that it had a problem explaining the origins of traits of ``extreme perfection and complication'' such as the vertebrate eye. Critics of Darwin's theory have latched onto this perceived flaw as a proof that Darwinian evolution is impossible. In anticipation of this issue, Darwin described the perfect data needed to understand this process, but lamented that such data are ``scarcely ever possible'' to obtain. In this talk, I will discuss research where we use populations of digital organisms (self-replicating and evolving computer programs) to elucidate the genetic and evolutionary processes by which new, highly-complex traits arise, drawing inspiration directly from Darwin's wistful thinking and hypotheses. During the process of evolution in these fully-transparent computational environments we can measure the incorporation of new information into the genome, a process akin to a natural Maxwell's Demon, and identify the original source of any such information. We show that, as Darwin predicted, much of the information used to encode a complex trait was already in the genome as part of simpler evolved traits, and that many routes must be possible for a new complex trait to have a high probability of successfully evolving. In even more extreme examples of the evolution of complexity, we are now using these same principles to examine the evolutionary dynamics the drive major transitions in evolution; that is transitions to higher-levels of organization, which are some of the most complex evolutionary events to occur in nature. Finally, I will explore some of the implications of this research to other aspects of evolutionary biology and as well as ways that these evolutionary principles can be applied toward solving computational and engineering problems.

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

PubMed

Mrowinski, Maciej J; 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.

Evolutionary fuzzy modeling human diagnostic decisions.

PubMed

Peña-Reyes, Carlos Andrés

2004-05-01

Fuzzy CoCo is a methodology, combining fuzzy logic and evolutionary computation, for constructing systems able to accurately predict the outcome of a human decision-making process, while providing an understandable explanation of the underlying reasoning. Fuzzy logic provides a formal framework for constructing systems exhibiting both good numeric performance (accuracy) and linguistic representation (interpretability). However, fuzzy modeling--meaning the construction of fuzzy systems--is an arduous task, demanding the identification of many parameters. To solve it, we use evolutionary computation techniques (specifically cooperative coevolution), which are widely used to search for adequate solutions in complex spaces. We have successfully applied the algorithm to model the decision processes involved in two breast cancer diagnostic problems, the WBCD problem and the Catalonia mammography interpretation problem, obtaining systems both of high performance and high interpretability. For the Catalonia problem, an evolved system was embedded within a Web-based tool-called COBRA-for aiding radiologists in mammography interpretation.

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

Geologic map of the Agnesi quadrangle (V-45), Venus

USGS Publications Warehouse

Hansen, Vicki L.; Tharalson, Erik R.

2014-01-01

Two general classes of hypotheses have emerged to address the near random spatial distribution of ~970 apparently pristine impact craters across the surface of Venus: (1) catastrophic/episodic resurfacing and (2) equilibrium/evolutionary resurfacing. Catastrophic/episodic hypotheses propose that a global-scale, temporally punctuated event or events dominated Venus’ evolution and that the generally uniform impact crater distribution (Schaber and others, 1992; Phillips and others, 1992; Herrick and others, 1997) reflects craters that accumulated during relative global quiescence since that event (for example, Strom and others, 1994; Herrick, 1994; Turcotte and others, 1999). Equilibrium/evolutionary hypotheses suggest instead that the near random crater distribution results from relatively continuous, but spatially localized, resurfacing in which volcanic and (or) tectonic processes occur across the planet through time, although the style of operative processes may have varied temporally and spatially (for example, Phillips and others, 1992; Guest and Stofan, 1999; Hansen and Young, 2007). Geologic relations within the map area allow us to test the catastrophic/episodic versus equilibrium/evolutionary resurfacing hypotheses.

Analysis of the expected density of internal equilibria in random evolutionary multi-player multi-strategy games.

PubMed

Duong, Manh Hong; Han, The Anh

2016-12-01

In this paper, we study the distribution and behaviour of internal equilibria in a d-player n-strategy random evolutionary game where the game payoff matrix is generated from normal distributions. The study of this paper reveals and exploits interesting connections between evolutionary game theory and random polynomial theory. The main contributions of the paper are some qualitative and quantitative results on the expected density, [Formula: see text], and the expected number, E(n, d), of (stable) internal equilibria. Firstly, we show that in multi-player two-strategy games, they behave asymptotically as [Formula: see text] as d is sufficiently large. Secondly, we prove that they are monotone functions of d. We also make a conjecture for games with more than two strategies. Thirdly, we provide numerical simulations for our analytical results and to support the conjecture. As consequences of our analysis, some qualitative and quantitative results on the distribution of zeros of a random Bernstein polynomial are also obtained.

INTEGRATING PARASITES AND PATHOGENS INTO THE STUDY OF GEOGRAPHIC RANGE LIMITS.

PubMed

Bozick, Brooke A; Real, Leslie A

2015-12-01

The geographic distributions of all species are limited, and the determining factors that set these limits are of fundamental importance to the fields of ecology and evolutionary biology. Plant and animal ranges have been of primary concern, while those of parasites, which represent much of the Earth's biodiversity, have been neglected. Here, we review the determinants of the geographic ranges of parasites and pathogens, and explore how parasites provide novel systems with which to investigate the ecological and evolutionary processes governing host/parasite spatial distributions. Although there is significant overlap in the causative factors that determine range borders of parasites and free-living species, parasite distributions are additionally constrained by the geographic range and ecology of the host species' population, as well as by evolutionary factors that promote host-parasite coevolution. Recently, parasites have been used to infer population demographic and ecological information about their host organisms and we conclude that this strategy can be further exploited to understand geographic range limitations of both host and parasite populations.

A Bright Future for Evolutionary Methods in Drug Design.

PubMed

Le, Tu C; Winkler, David A

2015-08-01

Most medicinal chemists understand that chemical space is extremely large, essentially infinite. Although high-throughput experimental methods allow exploration of drug-like space more rapidly, they are still insufficient to fully exploit the opportunities that such large chemical space offers. Evolutionary methods can synergistically blend automated synthesis and characterization methods with computational design to identify promising regions of chemical space more efficiently. We describe how evolutionary methods are implemented, and provide examples of published drug development research in which these methods have generated molecules with increased efficacy. We anticipate that evolutionary methods will play an important role in future drug discovery. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

EvoluZion: A Computer Simulator for Teaching Genetic and Evolutionary Concepts

ERIC Educational Resources Information Center

Zurita, Adolfo R.

2017-01-01

EvoluZion is a forward-in-time genetic simulator developed in Java and designed to perform real time simulations on the evolutionary history of virtual organisms. These model organisms harbour a set of 13 genes that codify an equal number of phenotypic features. These genes change randomly during replication, and mutant genes can have null,…

3D Computational Mechanics Elucidate the Evolutionary Implications of Orbit Position and Size Diversity of Early Amphibians

PubMed Central

Marcé-Nogué, Jordi; Fortuny, Josep; De Esteban-Trivigno, Soledad; Sánchez, Montserrat; Gil, Lluís; Galobart, Àngel

2015-01-01

For the first time in vertebrate palaeontology, the potential of joining Finite Element Analysis (FEA) and Parametrical Analysis (PA) is used to shed new light on two different cranial parameters from the orbits to evaluate their biomechanical role and evolutionary patterns. The early tetrapod group of Stereospondyls, one of the largest groups of Temnospondyls is used as a case study because its orbits position and size vary hugely within the members of this group. An adult skull of Edingerella madagascariensis was analysed using two different cases of boundary and loading conditions in order to quantify stress and deformation response under a bilateral bite and during skull raising. Firstly, the variation of the original geometry of its orbits was introduced in the models producing new FEA results, allowing the exploration of the ecomorphology, feeding strategy and evolutionary patterns of these top predators. Secondly, the quantitative results were analysed in order to check if the orbit size and position were correlated with different stress patterns. These results revealed that in most of the cases the stress distribution is not affected by changes in the size and position of the orbit. This finding supports the high mechanical plasticity of this group during the Triassic period. The absence of mechanical constraints regarding the orbit probably promoted the ecomorphological diversity acknowledged for this group, as well as its ecological niche differentiation in the terrestrial Triassic ecosystems in clades as lydekkerinids, trematosaurs, capitosaurs or metoposaurs. PMID:26107295

Generative Representations for Computer-Automated Evolutionary Design

NASA Technical Reports Server (NTRS)

Hornby, Gregory S.

2006-01-01

With the increasing computational power of computers, software design systems are progressing from being tools for architects and designers to express their ideas to tools capable of creating designs under human guidance. One of the main limitations for these computer-automated design systems is the representation with which they encode designs. If the representation cannot encode a certain design, then the design system cannot produce it. To be able to produce new types of designs, and not just optimize pre-defined parameterizations, evolutionary design systems must use generative representations. Generative representations are assembly procedures, or algorithms, for constructing a design thereby allowing for truly novel design solutions to be encoded. In addition, by enabling modularity, regularity and hierarchy, the level of sophistication that can be evolved is increased. We demonstrate the advantages of generative representations on two different design domains: the evolution of spacecraft antennas and the evolution of 3D objects.

An improved approximate-Bayesian model-choice method for estimating shared evolutionary history

PubMed Central

2014-01-01

Background To understand biological diversification, it is important to account for large-scale processes that affect the evolutionary history of groups of co-distributed populations of organisms. Such events predict temporally clustered divergences times, a pattern that can be estimated using genetic data from co-distributed species. I introduce a new approximate-Bayesian method for comparative phylogeographical model-choice that estimates the temporal distribution of divergences across taxa from multi-locus DNA sequence data. The model is an extension of that implemented in msBayes. Results By reparameterizing the model, introducing more flexible priors on demographic and divergence-time parameters, and implementing a non-parametric Dirichlet-process prior over divergence models, I improved the robustness, accuracy, and power of the method for estimating shared evolutionary history across taxa. Conclusions The results demonstrate the improved performance of the new method is due to (1) more appropriate priors on divergence-time and demographic parameters that avoid prohibitively small marginal likelihoods for models with more divergence events, and (2) the Dirichlet-process providing a flexible prior on divergence histories that does not strongly disfavor models with intermediate numbers of divergence events. The new method yields more robust estimates of posterior uncertainty, and thus greatly reduces the tendency to incorrectly estimate models of shared evolutionary history with strong support. PMID:24992937

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.

Computational evolution: taking liberties.

PubMed

Correia, Luís

2010-09-01

Evolution has, for a long time, inspired computer scientists to produce computer models mimicking its behavior. Evolutionary algorithm (EA) is one of the areas where this approach has flourished. EAs have been used to model and study evolution, but they have been especially developed for their aptitude as optimization tools for engineering. Developed models are quite simple in comparison with their natural sources of inspiration. However, since EAs run on computers, we have the freedom, especially in optimization models, to test approaches both realistic and outright speculative, from the biological point of view. In this article, we discuss different common evolutionary algorithm models, and then present some alternatives of interest. These include biologically inspired models, such as co-evolution and, in particular, symbiogenetics and outright artificial operators and representations. In each case, the advantages of the modifications to the standard model are identified. The other area of computational evolution, which has allowed us to study basic principles of evolution and ecology dynamics, is the development of artificial life platforms for open-ended evolution of artificial organisms. With these platforms, biologists can test theories by directly manipulating individuals and operators, observing the resulting effects in a realistic way. An overview of the most prominent of such environments is also presented. If instead of artificial platforms we use the real world for evolving artificial life, then we are dealing with evolutionary robotics (ERs). A brief description of this area is presented, analyzing its relations to biology. Finally, we present the conclusions and identify future research avenues in the frontier of computation and biology. Hopefully, this will help to draw the attention of more biologists and computer scientists to the benefits of such interdisciplinary research.

Understanding sequence similarity and framework analysis between centromere proteins using computational biology.

PubMed

Doss, C George Priya; Chakrabarty, Chiranjib; Debajyoti, C; Debottam, S

2014-11-01

Certain mysteries pointing toward their recruitment pathways, cell cycle regulation mechanisms, spindle checkpoint assembly, and chromosome segregation process are considered the centre of attraction in cancer research. In modern times, with the established databases, ranges of computational platforms have provided a platform to examine almost all the physiological and biochemical evidences in disease-associated phenotypes. Using existing computational methods, we have utilized the amino acid residues to understand the similarity within the evolutionary variance of different associated centromere proteins. This study related to sequence similarity, protein-protein networking, co-expression analysis, and evolutionary trajectory of centromere proteins will speed up the understanding about centromere biology and will create a road map for upcoming researchers who are initiating their work of clinical sequencing using centromere proteins.

ON THE EVOLUTIONARY AND PULSATION MASS OF CLASSICAL CEPHEIDS. III. THE CASE OF THE ECLIPSING BINARY CEPHEID CEP0227 IN THE LARGE MAGELLANIC CLOUD

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

Prada Moroni, P. G.; Gennaro, M.; Bono, G.

2012-04-20

We present a new Bayesian approach to constrain the intrinsic parameters (stellar mass and age) of the eclipsing binary system-CEP0227-in the Large Magellanic Cloud (LMC). We computed several sets of evolutionary models covering a broad range in chemical compositions and in stellar mass. Independent sets of models were also constructed either by neglecting or by including a moderate convective core overshooting ({beta}{sub ov} = 0.2) during central hydrogen-burning phases. Sets of models were also constructed either by neglecting or by assuming a canonical ({eta} = 0.4, 0.8) or an enhanced ({eta} = 4) mass-loss rate. The most probable solutions weremore » computed in three different planes: luminosity-temperature, mass-radius, and gravity-temperature. By using the Bayes factor, we found that the most probable solutions were obtained in the gravity-temperature plane with a Gaussian mass prior distribution. The evolutionary models constructed by assuming a moderate convective core overshooting ({beta}{sub ov} = 0.2) and a canonical mass-loss rate ({eta} = 0.4) give stellar masses for the primary (Cepheid)-M = 4.14{sup +0.04}{sub -0.05} M{sub Sun }-and for the secondary-M = 4.15{sup +0.04}{sub -0.05} M{sub Sun }-that agree at the 1% level with dynamical measurements. Moreover, we found ages for the two components and for the combined system-t = 151{sup +4}{sub -3} Myr-that agree at the 5% level. The solutions based on evolutionary models that neglect the mass loss attain similar parameters, while those ones based on models that either account for an enhanced mass loss or neglect convective core overshooting have lower Bayes factors and larger confidence intervals. The dependence on the mass-loss rate might be the consequence of the crude approximation we use to mimic this phenomenon. By using the isochrone of the most probable solution and a Gaussian prior on the LMC distance, we found a true distance modulus-18.53{sup +0.02}{sub -0.02} mag-and a reddening value-E(B - V) = 0.142{sup +0.005}{sub -0.010} mag-that agree quite well with similar estimates in the literature.« less

Binary black hole mergers within the LIGO horizon: statistical properties and prospects for detecting electromagnetic counterparts

NASA Astrophysics Data System (ADS)

Perna, Rosalba; Chruslinska, Martyna; Corsi, Alessandra; Belczynski, Krzysztof

2018-07-01

Binary black holes (BBHs) are one of the endpoints of isolated binary evolution, and their mergers a leading channel for gravitational wave events. Here, using the evolutionary code STARTRACK, we study the statistical properties of the BBH population from isolated binary evolution for a range of progenitor star metallicities and BH natal kicks. We compute the mass function and the distribution of the primary BH spin a as a result of mass accretion during the binary evolution, and find that this is not an efficient process to spin-up BHs, producing an increase by at most a ˜ 0.2-0.3 for very low natal BH spins. We further compute the distribution of merger sites within the host galaxy, after tracking the motion of the binaries in the potentials of a massive spiral, a massive elliptical, and a dwarf galaxy. We find that a fraction of 70-90 per cent of mergers in massive galaxies and of 40-60 per cent in dwarfs (range mostly sensitive to the natal kicks) are expected to occur inside of their hosts. The number density distribution at the merger sites further allows us to estimate the broad-band luminosity distribution that BBH mergers would produce, if associated with a kinetic energy release in an outflow, which, as a reference, we assume at the level inferred for the Fermi GBM counterpart to GW150914, with the understanding that current limits from the O1 and O2 runs would require such emission to be produced within a jet of angular size within ≲50°.

Binary Black Hole Mergers within the LIGO Horizon: Statistical Properties and prospects for detecting Electromagnetic Counterparts

NASA Astrophysics Data System (ADS)

Perna, Rosalba; Chruslinska, Martyna; Corsi, Alessandra; Belczynski, Krzysztof

2018-03-01

Binary black holes (BBHs) are one of the endpoints of isolated binary evolution, and their mergers a leading channel for gravitational wave events. Here, using the evolutionary code STARTRACK, we study the statistical properties of the BBH population from isolated binary evolution for a range of progenitor star metallicities and BH natal kicks. We compute the mass function and the distribution of the primary BH spin a as a result of mass accretion during the binary evolution, and find that this is not an efficient process to spin up BHs, producing an increase by at most a ˜ 0.2-0.3 for very low natal BH spins. We further compute the distribution of merger sites within the host galaxy, after tracking the motion of the binaries in the potentials of a massive spiral, a massive elliptical, and a dwarf galaxy. We find that a fraction of 70-90% of mergers in massive galaxies and of 40-60% in dwarfs (range mostly sensitive to the natal kicks) is expected to occur inside of their hosts. The number density distribution at the merger sites further allows us to estimate the broadband luminosity distribution that BBH mergers would produce, if associated with a kinetic energy release in an outflow, which, as a reference, we assume at the level inferred for the Fermi GBM counterpart to GW150914, with the understanding that current limits from the O1 and O2 runs would require such emission to be produced within a jet of angular size within ≲ 50°.

The Handicap Principle for Trust in Computer Security, the Semantic Web and Social Networking

NASA Astrophysics Data System (ADS)

Ma, Zhanshan (Sam); Krings, Axel W.; Hung, Chih-Cheng

Communication is a fundamental function of life, and it exists in almost all living things: from single-cell bacteria to human beings. Communication, together with competition and cooperation,arethree fundamental processes in nature. Computer scientists are familiar with the study of competition or 'struggle for life' through Darwin's evolutionary theory, or even evolutionary computing. They may be equally familiar with the study of cooperation or altruism through the Prisoner's Dilemma (PD) game. However, they are likely to be less familiar with the theory of animal communication. The objective of this article is three-fold: (i) To suggest that the study of animal communication, especially the honesty (reliability) of animal communication, in which some significant advances in behavioral biology have been achieved in the last three decades, should be on the verge to spawn important cross-disciplinary research similar to that generated by the study of cooperation with the PD game. One of the far-reaching advances in the field is marked by the publication of "The Handicap Principle: a Missing Piece of Darwin's Puzzle" by Zahavi (1997). The 'Handicap' principle [34][35], which states that communication signals must be costly in some proper way to be reliable (honest), is best elucidated with evolutionary games, e.g., Sir Philip Sidney (SPS) game [23]. Accordingly, we suggest that the Handicap principle may serve as a fundamental paradigm for trust research in computer science. (ii) To suggest to computer scientists that their expertise in modeling computer networks may help behavioral biologists in their study of the reliability of animal communication networks. This is largely due to the historical reason that, until the last decade, animal communication was studied with the dyadic paradigm (sender-receiver) rather than with the network paradigm. (iii) To pose several open questions, the answers to which may bear some refreshing insights to trust research in computer science, especially secure and resilient computing, the semantic web, and social networking. One important thread unifying the three aspects is the evolutionary game theory modeling or its extensions with survival analysis and agreement algorithms [19][20], which offer powerful game models for describing time-, space-, and covariate-dependent frailty (uncertainty and vulnerability) and deception (honesty).

Multi Agent Systems with Symbiotic Learning and Evolution using GNP

NASA Astrophysics Data System (ADS)

Eguchi, Toru; Hirasawa, Kotaro; Hu, Jinglu; Murata, Junichi

Recently, various attempts relevant to Multi Agent Systems (MAS) which is one of the most promising systems based on Distributed Artificial Intelligence have been studied to control large and complicated systems efficiently. In these trends of MAS, Multi Agent Systems with Symbiotic Learning and Evolution named Masbiole has been proposed. In Masbiole, symbiotic phenomena among creatures are considered in the process of learning and evolution of MAS. So we can expect more flexible and sophisticated solutions than conventional MAS. In this paper, we apply Masbiole to Iterative Prisoner’s Dilemma Games (IPD Games) using Genetic Network Programming (GNP) which is a newly developed evolutionary computation method for constituting agents. Some characteristics of Masbiole using GNP in IPD Games are clarified.

Molecular clock on a neutral network.

PubMed

Raval, Alpan

2007-09-28

The number of fixed mutations accumulated in an evolving population often displays a variance that is significantly larger than the mean (the overdispersed molecular clock). By examining a generic evolutionary process on a neutral network of high-fitness genotypes, we establish a formalism for computing all cumulants of the full probability distribution of accumulated mutations in terms of graph properties of the neutral network, and use the formalism to prove overdispersion of the molecular clock. We further show that significant overdispersion arises naturally in evolution when the neutral network is highly sparse, exhibits large global fluctuations in neutrality, and small local fluctuations in neutrality. The results are also relevant for elucidating aspects of neutral network topology from empirical measurements of the substitution process.

Molecular Clock on a Neutral Network

NASA Astrophysics Data System (ADS)

Raval, Alpan

2007-09-01

The number of fixed mutations accumulated in an evolving population often displays a variance that is significantly larger than the mean (the overdispersed molecular clock). By examining a generic evolutionary process on a neutral network of high-fitness genotypes, we establish a formalism for computing all cumulants of the full probability distribution of accumulated mutations in terms of graph properties of the neutral network, and use the formalism to prove overdispersion of the molecular clock. We further show that significant overdispersion arises naturally in evolution when the neutral network is highly sparse, exhibits large global fluctuations in neutrality, and small local fluctuations in neutrality. The results are also relevant for elucidating aspects of neutral network topology from empirical measurements of the substitution process.

ARES I Aerodynamic Testing at the NASA Langley Unitary Plan Wind Tunnel

NASA Technical Reports Server (NTRS)

Erickson, Gary E.; Wilcox, Floyd J.

2011-01-01

Small-scale force and moment and pressure models based on the outer mold lines of the Ares I design analysis cycle crew launch vehicle were tested in the NASA Langley Research Center Unitary Plan Wind Tunnel from May 2006 to September 2009. The test objectives were to establish supersonic ascent aerodynamic databases and to obtain force and moment, surface pressure, and longitudinal line-load distributions for comparison to computational predictions. Test data were obtained at low through high supersonic Mach numbers for ranges of the Reynolds number, angle of attack, and roll angle. This paper focuses on (1) the sensitivity of the supersonic aerodynamic characteristics to selected protuberances, outer mold line changes, and wind tunnel boundary layer transition techniques, (2) comparisons of experimental data to computational predictions, and (3) data reproducibility. The experimental data obtained in the Unitary Plan Wind Tunnel captured the effects of evolutionary changes to the Ares I crew launch vehicle, exhibited good agreement with predictions, and displayed satisfactory within-test and tunnel-to-tunnel data reproducibility.

Computational substrates of social norm enforcement by unaffected third parties.

PubMed

Zhong, Songfa; Chark, Robin; Hsu, Ming; Chew, Soo Hong

2016-04-01

Enforcement of social norms by impartial bystanders in the human species reveals a possibly unique capacity to sense and to enforce norms from a third party perspective. Such behavior, however, cannot be accounted by current computational models based on an egocentric notion of norms. Here, using a combination of model-based fMRI and third party punishment games, we show that brain regions previously implicated in egocentric norm enforcement critically extend to the important case of norm enforcement by unaffected third parties. Specifically, we found that responses in the ACC and insula cortex were positively associated with detection of distributional inequity, while those in the anterior DLPFC were associated with assessment of intentionality to the violator. Moreover, during sanction decisions, the subjective value of sanctions modulated activity in both vmPFC and rTPJ. These results shed light on the neurocomputational underpinnings of third party punishment and evolutionary origin of human norm enforcement. Copyright © 2016 Elsevier Inc. All rights reserved.

Energetics and solvation structure of a dihalogen dopant (I2) in (4)He clusters.

PubMed

Pérez de Tudela, Ricardo; Barragán, Patricia; Valdés, Álvaro; Prosmiti, Rita

2014-08-21

The energetics and structure of small HeNI2 clusters are analyzed as the size of the system changes, with N up to 38. The full interaction between the I2 molecule and the He atoms is based on analytical ab initio He-I2 potentials plus the He-He interaction, obtained from first-principle calculations. The most stable structures, as a function of the number of solvent He atoms, are obtained by employing an evolutionary algorithm and compared with CCSD(T) and MP2 ab initio computations. Further, the classical description is completed by explicitly including thermal corrections and quantum features, such as zero-point-energy values and spatial delocalization. From quantum PIMC calculations, the binding energies and radial/angular probability density distributions of the thermal equilibrium state for selected-size clusters are computed at a low temperature. The sequential formation of regular shell structures is analyzed and discussed for both classical and quantum treatments.

Two new species of Ateuchus with remarks on ecology, distributions, and evolutionary relationships (Coleoptera, Scarabaeidae, Scarabaeinae).

PubMed

Moctezuma, Victor; Sánchez-Huerta, José Luis; Halffter, Gonzalo

2018-01-01

Two new species of the genus Ateuchus Weber are described from the region of Los Chimalapas, Oaxaca, Mexico: A. benitojuarezi sp. n. and A. colossus sp. n. A diagnosis for distinguishing these new species from the other species of this genus in North America is included. This paper is illustrated with pictures of the dorsal habitus and the male genitalia of the new species. The evolutionary relationships of the species are discussed, as well as their distribution and ecology. It is considered that the species of the genus Ateuchus present in North and Central America correspond to the Typical Neotropical and Mountain Mesoamerican distribution patterns.

Two new species of Ateuchus with remarks on ecology, distributions, and evolutionary relationships (Coleoptera, Scarabaeidae, Scarabaeinae)

PubMed Central

Moctezuma, Victor; Sánchez-Huerta, José Luis; Halffter, Gonzalo

2018-01-01

Abstract Two new species of the genus Ateuchus Weber are described from the region of Los Chimalapas, Oaxaca, Mexico: A. benitojuarezi sp. n. and A. colossus sp. n. A diagnosis for distinguishing these new species from the other species of this genus in North America is included. This paper is illustrated with pictures of the dorsal habitus and the male genitalia of the new species. The evolutionary relationships of the species are discussed, as well as their distribution and ecology. It is considered that the species of the genus Ateuchus present in North and Central America correspond to the Typical Neotropical and Mountain Mesoamerican distribution patterns. PMID:29674904

Computer-Automated Evolution of Spacecraft X-Band Antennas

NASA Technical Reports Server (NTRS)

Lohn, Jason D.; Homby, Gregory S.; Linden, Derek S.

2010-01-01

A document discusses the use of computer- aided evolution in arriving at a design for X-band communication antennas for NASA s three Space Technology 5 (ST5) satellites, which were launched on March 22, 2006. Two evolutionary algorithms, incorporating different representations of the antenna design and different fitness functions, were used to automatically design and optimize an X-band antenna design. A set of antenna designs satisfying initial ST5 mission requirements was evolved by use these algorithms. The two best antennas - one from each evolutionary algorithm - were built. During flight-qualification testing of these antennas, the mission requirements were changed. After minimal changes in the evolutionary algorithms - mostly in the fitness functions - new antenna designs satisfying the changed mission requirements were evolved and within one month of this change, two new antennas were designed and prototypes of the antennas were built and tested. One of these newly evolved antennas was approved for deployment on the ST5 mission, and flight-qualified versions of this design were built and installed on the spacecraft. At the time of writing the document, these antennas were the first computer-evolved hardware in outer space.

Optimizing a reconfigurable material via evolutionary computation

NASA Astrophysics Data System (ADS)

Wilken, Sam; Miskin, Marc Z.; Jaeger, Heinrich M.

2015-08-01

Rapid prototyping by combining evolutionary computation with simulations is becoming a powerful tool for solving complex design problems in materials science. This method of optimization operates in a virtual design space that simulates potential material behaviors and after completion needs to be validated by experiment. However, in principle an evolutionary optimizer can also operate on an actual physical structure or laboratory experiment directly, provided the relevant material parameters can be accessed by the optimizer and information about the material's performance can be updated by direct measurements. Here we provide a proof of concept of such direct, physical optimization by showing how a reconfigurable, highly nonlinear material can be tuned to respond to impact. We report on an entirely computer controlled laboratory experiment in which a 6 ×6 grid of electromagnets creates a magnetic field pattern that tunes the local rigidity of a concentrated suspension of ferrofluid and iron filings. A genetic algorithm is implemented and tasked to find field patterns that minimize the force transmitted through the suspension. Searching within a space of roughly 1010 possible configurations, after testing only 1500 independent trials the algorithm identifies an optimized configuration of layered rigid and compliant regions.

Spiking Neural Network With Distributed Plasticity Reproduces Cerebellar Learning in Eye Blink Conditioning Paradigms.

PubMed

Antonietti, Alberto; Casellato, Claudia; Garrido, Jesús A; Luque, Niceto R; Naveros, Francisco; Ros, Eduardo; D' Angelo, Egidio; Pedrocchi, Alessandra

2016-01-01

In this study, we defined a realistic cerebellar model through the use of artificial spiking neural networks, testing it in computational simulations that reproduce associative motor tasks in multiple sessions of acquisition and extinction. By evolutionary algorithms, we tuned the cerebellar microcircuit to find out the near-optimal plasticity mechanism parameters that better reproduced human-like behavior in eye blink classical conditioning, one of the most extensively studied paradigms related to the cerebellum. We used two models: one with only the cortical plasticity and another including two additional plasticity sites at nuclear level. First, both spiking cerebellar models were able to well reproduce the real human behaviors, in terms of both "timing" and "amplitude", expressing rapid acquisition, stable late acquisition, rapid extinction, and faster reacquisition of an associative motor task. Even though the model with only the cortical plasticity site showed good learning capabilities, the model with distributed plasticity produced faster and more stable acquisition of conditioned responses in the reacquisition phase. This behavior is explained by the effect of the nuclear plasticities, which have slow dynamics and can express memory consolidation and saving. We showed how the spiking dynamics of multiple interactive neural mechanisms implicitly drive multiple essential components of complex learning processes.  This study presents a very advanced computational model, developed together by biomedical engineers, computer scientists, and neuroscientists. Since its realistic features, the proposed model can provide confirmations and suggestions about neurophysiological and pathological hypotheses and can be used in challenging clinical applications.

Evaluation of Generation Alternation Models in Evolutionary Robotics

NASA Astrophysics Data System (ADS)

Oiso, Masashi; Matsumura, Yoshiyuki; Yasuda, Toshiyuki; Ohkura, Kazuhiro

For efficient implementation of Evolutionary Algorithms (EA) to a desktop grid computing environment, we propose a new generation alternation model called Grid-Oriented-Deletion (GOD) based on comparison with the conventional techniques. In previous research, generation alternation models are generally evaluated by using test functions. However, their exploration performance on the real problems such as Evolutionary Robotics (ER) has not been made very clear yet. Therefore we investigate the relationship between the exploration performance of EA on an ER problem and its generation alternation model. We applied four generation alternation models to the Evolutionary Multi-Robotics (EMR), which is the package-pushing problem to investigate their exploration performance. The results show that GOD is more effective than the other conventional models.

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.

Nanotube Heterojunctions and Endo-Fullerenes for Nanoelectronics

NASA Technical Reports Server (NTRS)

Srivastava, Deepak; Menon, M.; Andriotis, Antonis; Cho, K.; Park, Jun; Biegel, Bryan A. (Technical Monitor)

2002-01-01

Topics discussed include: (1) Light-Weight Multi-Functional Materials: Nanomechanics; Nanotubes and Composites; Thermal/Chemical/Electrical Characterization; (2) Biomimetic/Revolutionary Concepts: Evolutionary Computing and Sensing; Self-Heating Materials; (3) Central Computing System: Molecular Electronics; Materials for Quantum Bits; and (4) Molecular Machines.

A review of estimation of distribution algorithms in bioinformatics

PubMed Central

Armañanzas, Rubén; Inza, Iñaki; Santana, Roberto; Saeys, Yvan; Flores, Jose Luis; Lozano, Jose Antonio; Peer, Yves Van de; Blanco, Rosa; Robles, Víctor; Bielza, Concha; Larrañaga, Pedro

2008-01-01

Evolutionary search algorithms have become an essential asset in the algorithmic toolbox for solving high-dimensional optimization problems in across a broad range of bioinformatics problems. Genetic algorithms, the most well-known and representative evolutionary search technique, have been the subject of the major part of such applications. Estimation of distribution algorithms (EDAs) offer a novel evolutionary paradigm that constitutes a natural and attractive alternative to genetic algorithms. They make use of a probabilistic model, learnt from the promising solutions, to guide the search process. In this paper, we set out a basic taxonomy of EDA techniques, underlining the nature and complexity of the probabilistic model of each EDA variant. We review a set of innovative works that make use of EDA techniques to solve challenging bioinformatics problems, emphasizing the EDA paradigm's potential for further research in this domain. PMID:18822112

Evolutionary prisoner's dilemma on Newman-Watts social networks with an asymmetric payoff distribution mechanism

NASA Astrophysics Data System (ADS)

Du, Wen-Bo; Cao, Xian-Bin; Yang, Han-Xin; Hu, Mao-Bin

2010-01-01

In this paper, we introduce an asymmetric payoff distribution mechanism into the evolutionary prisoner's dilemma game (PDG) on Newman-Watts social networks, and study its effects on the evolution of cooperation. The asymmetric payoff distribution mechanism can be adjusted by the parameter α: if α > 0, the rich will exploit the poor to get richer; if α < 0, the rich are forced to offer part of their income to the poor. Numerical results show that the cooperator frequency monotonously increases with α and is remarkably promoted when α > 0. The effects of updating order and self-interaction are also investigated. The co-action of random updating and self-interaction can induce the highest cooperation level. Moreover, we employ the Gini coefficient to investigate the effect of asymmetric payoff distribution on the the system's wealth distribution. This work may be helpful for understanding cooperative behaviour and wealth inequality in society.

Future distribution of tundra refugia in northern Alaska

USGS Publications Warehouse

Hope, Andrew G.; Waltari, Eric; Payer, David C.; Cook, Joseph A.; Talbot, Sandra L.

2013-01-01

Climate change in the Arctic is a growing concern for natural resource conservation and management as a result of accelerated warming and associated shifts in the distribution and abundance of northern species. We introduce a predictive framework for assessing the future extent of Arctic tundra and boreal biomes in northern Alaska. We use geo-referenced museum specimens to predict the velocity of distributional change into the next century and compare predicted tundra refugial areas with current land-use. The reliability of predicted distributions, including differences between fundamental and realized niches, for two groups of species is strengthened by fossils and genetic signatures of demographic shifts. Evolutionary responses to environmental change through the late Quaternary are generally consistent with past distribution models. Predicted future refugia overlap managed areas and indicate potential hotspots for tundra diversity. To effectively assess future refugia, variable responses among closely related species to climate change warrants careful consideration of both evolutionary and ecological histories.

Mistaking geography for biology: inferring processes from species distributions.

PubMed

Warren, Dan L; Cardillo, Marcel; Rosauer, Dan F; Bolnick, Daniel I

2014-10-01

Over the past few decades, there has been a rapid proliferation of statistical methods that infer evolutionary and ecological processes from data on species distributions. These methods have led to considerable new insights, but they often fail to account for the effects of historical biogeography on present-day species distributions. Because the geography of speciation can lead to patterns of spatial and temporal autocorrelation in the distributions of species within a clade, this can result in misleading inferences about the importance of deterministic processes in generating spatial patterns of biodiversity. In this opinion article, we discuss ways in which patterns of species distributions driven by historical biogeography are often interpreted as evidence of particular evolutionary or ecological processes. We focus on three areas that are especially prone to such misinterpretations: community phylogenetics, environmental niche modelling, and analyses of beta diversity (compositional turnover of biodiversity). Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Mitochondrial DNA haplotype distribution patterns in Pinus ponderosa (pinaceae): range-wide evolutionary history and implications for conservation

Treesearch

Kevin M. Potter; Valerie D. Hipkins; Mary F. Mahalovich; Robert E. Means

2013-01-01

Premise of the study: Ponderosa pine ( Pinus ponderosa Douglas ex P. Lawson & C. Lawson) exhibits complicated patterns of morphological and genetic variation across its range in western North America. This study aims to clarify P. ponderosa evolutionary history and phylogeography using a highly polymorphic...

Statistical distribution of amino acid sequences: a proof of Darwinian evolution.

PubMed

Eitner, Krystian; Koch, Uwe; Gaweda, Tomasz; Marciniak, Jedrzej

2010-12-01

The article presents results of the listing of the quantity of amino acids, dipeptides and tripeptides for all proteins available in the UNIPROT-TREMBL database and the listing for selected species and enzymes. UNIPROT-TREMBL contains protein sequences associated with computationally generated annotations and large-scale functional characterization. Due to the distinct metabolic pathways of amino acid syntheses and their physicochemical properties, the quantities of subpeptides in proteins vary. We have proved that the distribution of amino acids, dipeptides and tripeptides is statistical which confirms that the evolutionary biodiversity development model is subject to the theory of independent events. It seems interesting that certain short peptide combinations occur relatively rarely or even not at all. First, it confirms the Darwinian theory of evolution and second, it opens up opportunities for designing pharmaceuticals among rarely represented short peptide combinations. Furthermore, an innovative approach to the mass analysis of bioinformatic data is presented. eitner@amu.edu.pl Supplementary data are available at Bioinformatics online.

The black tide model of QSOs

NASA Technical Reports Server (NTRS)

Young, P. J.; Shields, G. A.; Wheeler, J. C.

1977-01-01

The paper develops certain aspects of a model wherein a QSO is a massive black hole located in a dense galactic nucleus, with its growth and luminosity fueled by tidal disruption of passing stars. Cross sections for tidal disruptions are calculated, taking into account the thermal energy of stars, relativistic effects, and partial disruption removing only the outer layers of a star. Accretion rates are computed for a realistic distribution of stellar masses and evolutionary phases, the effect of the black hole on the cluster distribution is examined, and the red-giant disruption rate is evaluated for hole mass of at least 300 million solar masses, the cutoff of disruption of main-sequence stars. The results show that this black-tide model can explain QSO luminosities of at least 1 trillion suns if the black hole remains almost maximally Kerr as it grows above 100 million solar masses and if 'loss-cone' depletion of the number of stars in disruptive orbits is unimportant.

Mutation-selection balance in mixed mating populations.

PubMed

Kelly, John K

2007-05-21

An approximation to the average number of deleterious mutations per gamete, Q, is derived from a model allowing selection on both zygotes and male gametes. Progeny are produced by either outcrossing or self-fertilization with fixed probabilities. The genetic model is a standard in evolutionary biology: mutations occur at unlinked loci, have equivalent effects, and combine multiplicatively to determine fitness. The approximation developed here treats individual mutation counts with a generalized Poisson model conditioned on the distribution of selfing histories in the population. The approximation is accurate across the range of parameter sets considered and provides both analytical insights and greatly increased computational speed. Model predictions are discussed in relation to several outstanding problems, including the estimation of the genomic deleterious mutation rates (U), the generality of "selective interference" among loci, and the consequences of gametic selection for the joint distribution of inbreeding depression and mating system across species. Finally, conflicting results from previous analytical treatments of mutation-selection balance are resolved to assumptions about the life-cycle and the initial fate of mutations.

Vision 2010: The Future of Higher Education Business and Learning Applications

ERIC Educational Resources Information Center

Carey, Patrick; Gleason, Bernard

2006-01-01

The global software industry is in the midst of a major evolutionary shift--one based on open computing--and this trend, like many transformative trends in technology, is being led by the IT staffs and academic computing faculty of the higher education industry. The elements of this open computing approach are open source, open standards, open…

Multi-Objective UAV Mission Planning Using Evolutionary Computation

DTIC Science & Technology

2008-03-01

on a Solution Space. . . . . . . . . . . . . . . . . . . . 41 4.3. Crowding distance calculation. Dark points are non-dominated solutions. [14...SPEA2 was devel- oped by Zitzler [64] as an improvement to the original SPEA algorithm [65]. SPEA2 Figure 4.3: Crowding distance calculation. Dark ...thesis, Los Angeles, CA, USA, 2003. Adviser-Maja J. Mataric . 114 21. Homberger, Joerg and Hermann Gehring. “Two Evolutionary Metaheuristics for the

Evolutionary Models for Simple Biosystems

NASA Astrophysics Data System (ADS)

Bagnoli, Franco

The concept of evolutionary development of structures constituted a real revolution in biology: it was possible to understand how the very complex structures of life can arise in an out-of-equilibrium system. The investigation of such systems has shown that indeed, systems under a flux of energy or matter can self-organize into complex patterns, think for instance to Rayleigh-Bernard convection, Liesegang rings, patterns formed by granular systems under shear. Following this line, one could characterize life as a state of matter, characterized by the slow, continuous process that we call evolution. In this paper we try to identify the organizational level of life, that spans several orders of magnitude from the elementary constituents to whole ecosystems. Although similar structures can be found in other contexts like ideas (memes) in neural systems and self-replicating elements (computer viruses, worms, etc.) in computer systems, we shall concentrate on biological evolutionary structure, and try to put into evidence the role and the emergence of network structure in such systems.

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

Artificial Exo-Society Modeling: a New Tool for SETI Research

NASA Astrophysics Data System (ADS)

Gardner, James N.

2002-01-01

One of the newest fields of complexity research is artificial society modeling. Methodologically related to artificial life research, artificial society modeling utilizes agent-based computer simulation tools like SWARM and SUGARSCAPE developed by the Santa Fe Institute, Los Alamos National Laboratory and the Bookings Institution in an effort to introduce an unprecedented degree of rigor and quantitative sophistication into social science research. The broad aim of artificial society modeling is to begin the development of a more unified social science that embeds cultural evolutionary processes in a computational environment that simulates demographics, the transmission of culture, conflict, economics, disease, the emergence of groups and coadaptation with an environment in a bottom-up fashion. When an artificial society computer model is run, artificial societal patterns emerge from the interaction of autonomous software agents (the "inhabitants" of the artificial society). Artificial society modeling invites the interpretation of society as a distributed computational system and the interpretation of social dynamics as a specialized category of computation. Artificial society modeling techniques offer the potential of computational simulation of hypothetical alien societies in much the same way that artificial life modeling techniques offer the potential to model hypothetical exobiological phenomena. NASA recently announced its intention to begin exploring the possibility of including artificial life research within the broad portfolio of scientific fields comprised by the interdisciplinary astrobiology research endeavor. It may be appropriate for SETI researchers to likewise commence an exploration of the possible inclusion of artificial exo-society modeling within the SETI research endeavor. Artificial exo-society modeling might be particularly useful in a post-detection environment by (1) coherently organizing the set of data points derived from a detected ETI signal, (2) mapping trends in the data points over time (assuming receipt of an extended ETI signal), and (3) projecting such trends forward to derive alternative cultural evolutionary scenarios for the exo-society under analysis. The latter exercise might be particularly useful to compensate for the inevitable time lag between generation of an ETI signal and receipt of an ETI signal on Earth. For this reason, such an exercise might be a helpful adjunct to the decisional process contemplated by Paragraph 9 of the Declaration of Principles Concerning Activities Following the Detection of Extraterrestrial Intelligence.

Beyond topology: coevolution of structure and flux in metabolic networks.

PubMed

Morrison, E S; Badyaev, A V

2017-10-01

Interactions between the structure of a metabolic network and its functional properties underlie its evolutionary diversification, but the mechanism by which such interactions arise remains elusive. Particularly unclear is whether metabolic fluxes that determine the concentrations of compounds produced by a metabolic network, are causally linked to a network's structure or emerge independently of it. A direct empirical study of populations where both structural and functional properties vary among individuals' metabolic networks is required to establish whether changes in structure affect the distribution of metabolic flux. In a population of house finches (Haemorhous mexicanus), we reconstructed full carotenoid metabolic networks for 442 individuals and uncovered 11 structural variants of this network with different compounds and reactions. We examined the consequences of this structural diversity for the concentrations of plumage-bound carotenoids produced by flux in these networks. We found that concentrations of metabolically derived, but not dietary carotenoids, depended on network structure. Flux was partitioned similarly among compounds in individuals of the same network structure: within each network, compound concentrations were closely correlated. The highest among-individual variation in flux occurred in networks with the strongest among-compound correlations, suggesting that changes in the magnitude, but not the distribution of flux, underlie individual differences in compound concentrations on a static network structure. These findings indicate that the distribution of flux in carotenoid metabolism closely follows network structure. Thus, evolutionary diversification and local adaptations in carotenoid metabolism may depend more on the gain or loss of enzymatic reactions than on changes in flux within a network structure. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

Hotspots and the conservation of evolutionary history

PubMed Central

Sechrest, Wes; Brooks, Thomas M.; da Fonseca, Gustavo A. B.; Konstant, William R.; Mittermeier, Russell A.; Purvis, Andy; Rylands, Anthony B.; Gittleman, John L.

2002-01-01

Species diversity is unevenly distributed across the globe, with terrestrial diversity concentrated in a few restricted biodiversity hotspots. These areas are associated with high losses of primary vegetation and increased human population density, resulting in growing numbers of threatened species. We show that conservation of these hotspots is critical because they harbor even greater amounts of evolutionary history than expected by species numbers alone. We used supertrees for carnivores and primates to estimate that nearly 70% of the total amount of evolutionary history represented in these groups is found in 25 biodiversity hotspots. PMID:11854502

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.

Leveraging ecological theory to guide natural product discovery.

PubMed

Smanski, Michael J; Schlatter, Daniel C; Kinkel, Linda L

2016-03-01

Technological improvements have accelerated natural product (NP) discovery and engineering to the point that systematic genome mining for new molecules is on the horizon. NP biosynthetic potential is not equally distributed across organisms, environments, or microbial life histories, but instead is enriched in a number of prolific clades. Also, NPs are not equally abundant in nature; some are quite common and others markedly rare. Armed with this knowledge, random 'fishing expeditions' for new NPs are increasingly harder to justify. Understanding the ecological and evolutionary pressures that drive the non-uniform distribution of NP biosynthesis provides a rational framework for the targeted isolation of strains enriched in new NP potential. Additionally, ecological theory leads to testable hypotheses regarding the roles of NPs in shaping ecosystems. Here we review several recent strain prioritization practices and discuss the ecological and evolutionary underpinnings for each. Finally, we offer perspectives on leveraging microbial ecology and evolutionary biology for future NP discovery.

Communications and Tracking Distributed Systems Evolution Study

NASA Technical Reports Server (NTRS)

Culpepper, William

1990-01-01

The Communications and Tracking (C & T) techniques and equipment to support evolutionary space station concepts are being analyzed. Evolutionary space station configurations and operational concepts are used to derive the results to date. A description of the C & T system based on future capability needs is presented. Included are the hooks and scars currently identified to support future growth.

Soft computing approach to 3D lung nodule segmentation in CT.

PubMed

Badura, P; Pietka, E

2014-10-01

This paper presents a novel, multilevel approach to the segmentation of various types of pulmonary nodules in computed tomography studies. It is based on two branches of computational intelligence: the fuzzy connectedness (FC) and the evolutionary computation. First, the image and auxiliary data are prepared for the 3D FC analysis during the first stage of an algorithm - the masks generation. Its main goal is to process some specific types of nodules connected to the pleura or vessels. It consists of some basic image processing operations as well as dedicated routines for the specific cases of nodules. The evolutionary computation is performed on the image and seed points in order to shorten the FC analysis and improve its accuracy. After the FC application, the remaining vessels are removed during the postprocessing stage. The method has been validated using the first dataset of studies acquired and described by the Lung Image Database Consortium (LIDC) and by its latest release - the LIDC-IDRI (Image Database Resource Initiative) database. Copyright © 2014 Elsevier Ltd. All rights reserved.

Past climate change drives current genetic structure of an endangered freshwater mussel species.

PubMed

Inoue, Kentaro; Lang, Brian K; Berg, David J

2015-04-01

Historical-to-recent climate change and anthropogenic disturbance affect species distributions and genetic structure. The Rio Grande watershed of the United States and Mexico encompasses ecosystems that are intensively exploited, resulting in substantial degradation of aquatic habitats. While significant anthropogenic disturbances in the Rio Grande are recent, inhospitable conditions for freshwater organisms likely existed prior to such disturbances. A combination of anthropogenic and past climate factors may contribute to current distributions of aquatic fauna in the Rio Grande basin. We used mitochondrial DNA and 18 microsatellite loci to infer evolutionary history and genetic structure of an endangered freshwater mussel, Popenaias popeii, throughout the Rio Grande drainage. We estimated spatial connectivity and gene flow across extant populations of P. popeii and used ecological niche models (ENMs) and approximate Bayesian computation (ABC) to infer its evolutionary history during the Pleistocene. structure results recovered regional and local population clusters in the Rio Grande. ENMs predicted drastic reductions in suitable habitat during the last glacial maximum. ABC analyses suggested that regional population structure likely arose in this species during the mid-to-late Pleistocene and was followed by a late Pleistocene population bottleneck in New Mexico populations. The local population structure arose relatively recently, perhaps due to anthropogenic factors. Popenaias popeii, one of the few freshwater mussel species native to the Rio Grande basin, is a case study for understanding how both geological and anthropogenic factors shape current population genetic structure. Conservation strategies for this species should account for the fragmented nature of contemporary populations. © 2015 John Wiley & Sons Ltd.

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.

Nasal airflow simulations suggest convergent adaptation in Neanderthals and modern humans.

PubMed

de Azevedo, S; González, M F; Cintas, C; Ramallo, V; Quinto-Sánchez, M; Márquez, F; Hünemeier, T; Paschetta, C; Ruderman, A; Navarro, P; Pazos, B A; Silva de Cerqueira, C C; Velan, O; Ramírez-Rozzi, F; Calvo, N; Castro, H G; Paz, R R; González-José, R

2017-11-21

Both modern humans (MHs) and Neanderthals successfully settled across western Eurasian cold-climate landscapes. Among the many adaptations considered as essential to survival in such landscapes, changes in the nasal morphology and/or function aimed to humidify and warm the air before it reaches the lungs are of key importance. Unfortunately, the lack of soft-tissue evidence in the fossil record turns difficult any comparative study of respiratory performance. Here, we reconstruct the internal nasal cavity of a Neanderthal plus two representatives of climatically divergent MH populations (southwestern Europeans and northeastern Asians). The reconstruction includes mucosa distribution enabling a realistic simulation of the breathing cycle in different climatic conditions via computational fluid dynamics. Striking across-specimens differences in fluid residence times affecting humidification and warming performance at the anterior tract were found under cold/dry climate simulations. Specifically, the Asian model achieves a rapid air conditioning, followed by the Neanderthals, whereas the European model attains a proper conditioning only around the medium-posterior tract. In addition, quantitative-genetic evolutionary analyses of nasal morphology provided signals of stabilizing selection for MH populations, with the removal of Arctic populations turning covariation patterns compatible with evolution by genetic drift. Both results indicate that, departing from important craniofacial differences existing among Neanderthals and MHs, an advantageous species-specific respiratory performance in cold climates may have occurred in both species. Fluid dynamics and evolutionary biology independently provided evidence of nasal evolution, suggesting that adaptive explanations regarding complex functional phenotypes require interdisciplinary approaches aimed to quantify both performance and evolutionary signals on covariation patterns.

Evidence for past and present hybridization in three Antarctic icefish species provides new perspectives on an evolutionary radiation.

PubMed

Marino, I A M; Benazzo, A; Agostini, C; Mezzavilla, M; Hoban, S M; Patarnello, T; Zane, L; Bertorelle, G

2013-10-01

Determining the timing, extent and underlying causes of interspecific gene exchange during or following speciation is central to understanding species' evolution. Antarctic notothenioid fish, thanks to the acquisition of antifreeze glycoproteins during Oligocene transition to polar conditions, experienced a spectacular radiation to >100 species during Late Miocene cooling events. The impact of recent glacial cycles on this group is poorly known, but alternating warming and cooling periods may have affected species' distributions, promoted ecological divergence into recurrently opening niches and/or possibly brought allopatric species into contact. Using microsatellite markers and statistical methods including Approximate Bayesian Computation, we investigated genetic differentiation, hybridization and the possible influence of the last glaciation/deglaciation events in three icefish species of the genus Chionodraco. Our results provide strong evidence of contemporary and past introgression by showing that: (i) a substantial fraction of contemporary individuals in each species has mixed ancestry, (ii) evolutionary scenarios excluding hybridization or including it only in ancient times have small or zero posterior probabilities, (iii) the data support a scenario of interspecific gene flow associated with the two most recent interglacial periods. Glacial cycles might therefore have had a profound impact on the genetic composition of Antarctic fauna, as newly available shelf areas during the warmer intervals might have favoured secondary contacts and hybridization between diversified groups. If our findings are confirmed in other notothenioids, they offer new perspectives for understanding evolutionary dynamics of Antarctic fish and suggest a need for new predictions on the effects of global warming in this group. © 2013 John Wiley & Sons Ltd.

Evolutionary Developmental Biology (Evo-Devo) Research in Latin America.

PubMed

Marcellini, Sylvain; González, Favio; Sarrazin, Andres F; Pabón-Mora, Natalia; Benítez, Mariana; Piñeyro-Nelson, Alma; Rezende, Gustavo L; Maldonado, Ernesto; Schneider, Patricia Neiva; Grizante, Mariana B; Da Fonseca, Rodrigo Nunes; Vergara-Silva, Francisco; Suaza-Gaviria, Vanessa; Zumajo-Cardona, Cecilia; Zattara, Eduardo E; Casasa, Sofia; Suárez-Baron, Harold; Brown, Federico D

2017-01-01

Famous for its blind cavefish and Darwin's finches, Latin America is home to some of the richest biodiversity hotspots of our planet. The Latin American fauna and flora inspired and captivated naturalists from the nineteenth and twentieth centuries, including such notable pioneers such as Fritz Müller, Florentino Ameghino, and Léon Croizat who made a significant contribution to the study of embryology and evolutionary thinking. But, what are the historical and present contributions of the Latin American scientific community to Evo-Devo? Here, we provide the first comprehensive overview of the Evo-Devo laboratories based in Latin America and describe current lines of research based on endemic species, focusing on body plans and patterning, systematics, physiology, computational modeling approaches, ecology, and domestication. Literature searches reveal that Evo-Devo in Latin America is still in its early days; while showing encouraging indicators of productivity, it has not stabilized yet, because it relies on few and sparsely distributed laboratories. Coping with the rapid changes in national scientific policies and contributing to solve social and health issues specific to each region are among the main challenges faced by Latin American researchers. The 2015 inaugural meeting of the Pan-American Society for Evolutionary Developmental Biology played a pivotal role in bringing together Latin American researchers eager to initiate and consolidate regional and worldwide collaborative networks. Such networks will undoubtedly advance research on the extremely high genetic and phenotypic biodiversity of Latin America, bound to be an almost infinite source of amazement and fascinating findings for the Evo-Devo community. © 2016 Wiley Periodicals, Inc.

Robust electromagnetically guided endoscopic procedure using enhanced particle swarm optimization for multimodal information fusion.

PubMed

Luo, Xiongbiao; Wan, Ying; He, Xiangjian

2015-04-01

Electromagnetically guided endoscopic procedure, which aims at accurately and robustly localizing the endoscope, involves multimodal sensory information during interventions. However, it still remains challenging in how to integrate these information for precise and stable endoscopic guidance. To tackle such a challenge, this paper proposes a new framework on the basis of an enhanced particle swarm optimization method to effectively fuse these information for accurate and continuous endoscope localization. The authors use the particle swarm optimization method, which is one of stochastic evolutionary computation algorithms, to effectively fuse the multimodal information including preoperative information (i.e., computed tomography images) as a frame of reference, endoscopic camera videos, and positional sensor measurements (i.e., electromagnetic sensor outputs). Since the evolutionary computation method usually limits its possible premature convergence and evolutionary factors, the authors introduce the current (endoscopic camera and electromagnetic sensor's) observation to boost the particle swarm optimization and also adaptively update evolutionary parameters in accordance with spatial constraints and the current observation, resulting in advantageous performance in the enhanced algorithm. The experimental results demonstrate that the authors' proposed method provides a more accurate and robust endoscopic guidance framework than state-of-the-art methods. The average guidance accuracy of the authors' framework was about 3.0 mm and 5.6° while the previous methods show at least 3.9 mm and 7.0°. The average position and orientation smoothness of their method was 1.0 mm and 1.6°, which is significantly better than the other methods at least with (2.0 mm and 2.6°). Additionally, the average visual quality of the endoscopic guidance was improved to 0.29. A robust electromagnetically guided endoscopy framework was proposed on the basis of an enhanced particle swarm optimization method with using the current observation information and adaptive evolutionary factors. The authors proposed framework greatly reduced the guidance errors from (4.3, 7.8) to (3.0 mm, 5.6°), compared to state-of-the-art methods.

A road map for integrating eco-evolutionary processes into biodiversity models.

PubMed

Thuiller, Wilfried; Münkemüller, Tamara; Lavergne, Sébastien; Mouillot, David; Mouquet, Nicolas; Schiffers, Katja; Gravel, Dominique

2013-05-01

The demand for projections of the future distribution of biodiversity has triggered an upsurge in modelling at the crossroads between ecology and evolution. Despite the enthusiasm around these so-called biodiversity models, most approaches are still criticised for not integrating key processes known to shape species ranges and community structure. Developing an integrative modelling framework for biodiversity distribution promises to improve the reliability of predictions and to give a better understanding of the eco-evolutionary dynamics of species and communities under changing environments. In this article, we briefly review some eco-evolutionary processes and interplays among them, which are essential to provide reliable projections of species distributions and community structure. We identify gaps in theory, quantitative knowledge and data availability hampering the development of an integrated modelling framework. We argue that model development relying on a strong theoretical foundation is essential to inspire new models, manage complexity and maintain tractability. We support our argument with an example of a novel integrated model for species distribution modelling, derived from metapopulation theory, which accounts for abiotic constraints, dispersal, biotic interactions and evolution under changing environmental conditions. We hope such a perspective will motivate exciting and novel research, and challenge others to improve on our proposed approach. © 2013 John Wiley & Sons Ltd/CNRS.

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

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.

Sign changes as a universal concept in first-passage-time calculations

NASA Astrophysics Data System (ADS)

Braun, Wilhelm; Thul, Rüdiger

2017-01-01

First-passage-time problems are ubiquitous across many fields of study, including transport processes in semiconductors and biological synapses, evolutionary game theory and percolation. Despite their prominence, first-passage-time calculations have proven to be particularly challenging. Analytical results to date have often been obtained under strong conditions, leaving most of the exploration of first-passage-time problems to direct numerical computations. Here we present an analytical approach that allows the derivation of first-passage-time distributions for the wide class of nondifferentiable Gaussian processes. We demonstrate that the concept of sign changes naturally generalizes the common practice of counting crossings to determine first-passage events. Our method works across a wide range of time-dependent boundaries and noise strengths, thus alleviating common hurdles in first-passage-time calculations.

The Affective Core of Emotion: Linking Pleasure, Subjective Well-Being, and Optimal Metastability in the Brain

PubMed Central

Kringelbach, Morten L.; Berridge, Kent C.

2017-01-01

Arguably, emotion is always valenced—either pleasant or unpleasant—and dependent on the pleasure system. This system serves adaptive evolutionary functions; relying on separable wanting, liking, and learning neural mechanisms mediated by mesocorticolimbic networks driving pleasure cycles with appetitive, consummatory, and satiation phases. Liking is generated in a small set of discrete hedonic hotspots and coldspots, while wanting is linked to dopamine and to larger distributed brain networks. Breakdown of the pleasure system can lead to anhedonia and other features of affective disorders. Eudaimonia and well-being are difficult to study empirically, yet whole-brain computational models could offer novel insights (e.g., routes to eudaimonia such as caregiving of infants or music) potentially linking eudaimonia to optimal metastability in the pleasure system. PMID:28943891

Framework for computationally efficient optimal irrigation scheduling using ant colony optimization

USDA-ARS?s Scientific Manuscript database

A general optimization framework is introduced with the overall goal of reducing search space size and increasing the computational efficiency of evolutionary algorithm application for optimal irrigation scheduling. The framework achieves this goal by representing the problem in the form of a decisi...

Pervasive Computing and Communication Technologies for U-Learning

ERIC Educational Resources Information Center

Park, Young C.

2014-01-01

The development of digital information transfer, storage and communication methods influences a significant effect on education. The assimilation of pervasive computing and communication technologies marks another great step forward, with Ubiquitous Learning (U-learning) emerging for next generation learners. In the evolutionary view the 5G (or…

Why Is the Correlation between Gene Importance and Gene Evolutionary Rate So Weak?

PubMed Central

Wang, Zhi; Zhang, Jianzhi

2009-01-01

One of the few commonly believed principles of molecular evolution is that functionally more important genes (or DNA sequences) evolve more slowly than less important ones. This principle is widely used by molecular biologists in daily practice. However, recent genomic analysis of a diverse array of organisms found only weak, negative correlations between the evolutionary rate of a gene and its functional importance, typically measured under a single benign lab condition. A frequently suggested cause of the above finding is that gene importance determined in the lab differs from that in an organism's natural environment. Here, we test this hypothesis in yeast using gene importance values experimentally determined in 418 lab conditions or computationally predicted for 10,000 nutritional conditions. In no single condition or combination of conditions did we find a much stronger negative correlation, which is explainable by our subsequent finding that always-essential (enzyme) genes do not evolve significantly more slowly than sometimes-essential or always-nonessential ones. Furthermore, we verified that functional density, approximated by the fraction of amino acid sites within protein domains, is uncorrelated with gene importance. Thus, neither the lab-nature mismatch nor a potentially biased among-gene distribution of functional density explains the observed weakness of the correlation between gene importance and evolutionary rate. We conclude that the weakness is factual, rather than artifactual. In addition to being weakened by population genetic reasons, the correlation is likely to have been further weakened by the presence of multiple nontrivial rate determinants that are independent from gene importance. These findings notwithstanding, we show that the principle of slower evolution of more important genes does have some predictive power when genes with vastly different evolutionary rates are compared, explaining why the principle can be practically useful despite the weakness of the correlation. PMID:19132081

Simulation of the evolution of root water foraging strategies in dry and shallow soils

PubMed Central

Renton, Michael; Poot, Pieter

2014-01-01

Background and Aims The dynamic structural development of plants can be seen as a strategy for exploiting the limited resources available within their environment, and we would expect that evolution would lead to efficient strategies that reduce costs while maximizing resource acquisition. In particular, perennial species endemic to habitats with shallow soils in seasonally dry environments have been shown to have a specialized root system morphology that may enhance access to water resources in the underlying rock. This study aimed to explore these hypotheses by applying evolutionary algorithms to a functional–structural root growth model. Methods A simulation model of a plant's root system was developed, which represents the dynamics of water uptake and structural growth. The model is simple enough for evolutionary optimization to be computationally feasible, yet flexible enough to allow a range of structural development strategies to be explored. The model was combined with an evolutionary algorithm in order to investigate a case study habitat with a highly heterogeneous distribution of resources, both spatially and temporally – the situation of perennial plants occurring on shallow soils in seasonally dry environments. Evolution was simulated under two contrasting fitness criteria: (1) the ability to find wet cracks in underlying rock, and (2) maximizing above-ground biomass. Key Results The novel approach successfully resulted in the evolution of more efficient structural development strategies for both fitness criteria. Different rooting strategies evolved when different criteria were applied, and each evolved strategy made ecological sense in terms of the corresponding fitness criterion. Evolution selected for root system morphologies which matched those of real species from corresponding habitats. Conclusions Specialized root morphology with deeper rather than shallower lateral branching enhances access to water resources in underlying rock. More generally, the approach provides insights into both evolutionary processes and ecological costs and benefits of different plant growth strategies. PMID:24651371

Toll-like receptor variation in the bottlenecked population of the Seychelles warbler: computer simulations see the 'ghost of selection past' and quantify the 'drift debt'.

PubMed

Gilroy, D L; Phillips, K P; Richardson, D S; van Oosterhout, C

2017-07-01

Balancing selection can maintain immunogenetic variation within host populations, but detecting its signal in a postbottlenecked population is challenging due to the potentially overriding effects of drift. Toll-like receptor genes (TLRs) play a fundamental role in vertebrate immune defence and are predicted to be under balancing selection. We previously characterized variation at TLR loci in the Seychelles warbler (Acrocephalus sechellensis), an endemic passerine that has undergone a historical bottleneck. Five of seven TLR loci were polymorphic, which is in sharp contrast to the low genomewide variation observed. However, standard population genetic statistical methods failed to detect a contemporary signature of selection at any TLR locus. We examined whether the observed TLR polymorphism could be explained by neutral evolution, simulating the population's demography in the software DIYABC. This showed that the posterior distributions of mutation rates had to be unrealistically high to explain the observed genetic variation. We then conducted simulations with an agent-based model using typical values for the mutation rate, which indicated that weak balancing selection has acted on the three TLR genes. The model was able to detect evidence of past selection elevating TLR polymorphism in the prebottleneck populations, but was unable to discern any effects of balancing selection in the contemporary population. Our results show drift is the overriding evolutionary force that has shaped TLR variation in the contemporary Seychelles warbler population, and the observed TLR polymorphisms might be merely the 'ghost of selection past'. Forecast models predict immunogenetic variation in this species will continue to be eroded in the absence of contemporary balancing selection. Such 'drift debt' occurs when a gene pool has not yet reached its new equilibrium level of polymorphism, and this loss could be an important threat to many recently bottlenecked populations. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

Evolutionary model of an anonymous consumer durable market

NASA Astrophysics Data System (ADS)

Kaldasch, Joachim

2011-07-01

An analytic model is presented that considers the evolution of a market of durable goods. The model suggests that after introduction goods spread always according to a Bass diffusion. However, this phase will be followed by a diffusion process for durable consumer goods governed by a variation-selection-reproduction mechanism and the growth dynamics can be described by a replicator equation. The theory suggests that products play the role of species in biological evolutionary models. It implies that the evolution of man-made products can be arranged into an evolutionary tree. The model suggests that each product can be characterized by its product fitness. The fitness space contains elements of both sites of the market, supply and demand. The unit sales of products with a higher product fitness compared to the mean fitness increase. Durables with a constant fitness advantage replace other goods according to a logistic law. The model predicts in particular that the mean price exhibits an exponential decrease over a long time period for durable goods. The evolutionary diffusion process is directly related to this price decline and is governed by Gompertz equation. Therefore it is denoted as Gompertz diffusion. Describing the aggregate sales as the sum of first, multiple and replacement purchase the product life cycle can be derived. Replacement purchase causes periodic variations of the sales determined by the finite lifetime of the good (Juglar cycles). The model suggests that both, Bass- and Gompertz diffusion may contribute to the product life cycle of a consumer durable. The theory contains the standard equilibrium view of a market as a special case. It depends on the time scale, whether an equilibrium or evolutionary description is more appropriate. The evolutionary framework is used to derive also the size, growth rate and price distribution of manufacturing business units. It predicts that the size distribution of the business units (products) is lognormal, while the growth rates exhibit a Laplace distribution. Large price deviations from the mean price are also governed by a Laplace distribution (fat tails). These results are in agreement with empirical findings. The explicit comparison of the time evolution of consumer durables with empirical investigations confirms the close relationship between price decline and Gompertz diffusion, while the product life cycle can be described qualitatively for a long time period.

Relationship between the column density distribution and evolutionary class of molecular clouds as viewed by ATLASGAL

NASA Astrophysics Data System (ADS)

Abreu-Vicente, J.; Kainulainen, J.; Stutz, A.; Henning, Th.; Beuther, H.

2015-09-01

We present the first study of the relationship between the column density distribution of molecular clouds within nearby Galactic spiral arms and their evolutionary status as measured from their stellar content. We analyze a sample of 195 molecular clouds located at distances below 5.5 kpc, identified from the ATLASGAL 870 μm data. We define three evolutionary classes within this sample: starless clumps, star-forming clouds with associated young stellar objects, and clouds associated with H ii regions. We find that the N(H2) probability density functions (N-PDFs) of these three classes of objects are clearly different: the N-PDFs of starless clumps are narrowest and close to log-normal in shape, while star-forming clouds and H ii regions exhibit a power-law shape over a wide range of column densities and log-normal-like components only at low column densities. We use the N-PDFs to estimate the evolutionary time-scales of the three classes of objects based on a simple analytic model from literature. Finally, we show that the integral of the N-PDFs, the dense gas mass fraction, depends on the total mass of the regions as measured by ATLASGAL: more massive clouds contain greater relative amounts of dense gas across all evolutionary classes. Appendices are available in electronic form at http://www.aanda.org

Evidence for Different Disk Mass Distributions between Early- and Late-type Be Stars in the BeSOS Survey

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

Arcos, C.; Kanaan, S.; Curé, M.

The circumstellar disk density distributions for a sample of 63 Be southern stars from the BeSOS survey were found by modeling their H α emission line profiles. These disk densities were used to compute disk masses and disk angular momenta for the sample. Average values for the disk mass are 3.4 × 10{sup −9} and 9.5 × 10{sup −10} M {sub ⋆} for early (B0–B3) and late (B4–B9) spectral types, respectively. We also find that the range of disk angular momentum relative to the star is (150–200) J {sub ⋆}/ M {sub ⋆} and (100–150) J {sub ⋆}/ M {submore » ⋆}, again for early- and late-type Be stars, respectively. The distributions of the disk mass and disk angular momentum are different between early- and late-type Be stars at a 1% level of significance. Finally, we construct the disk mass distribution for the BeSOS sample as a function of spectral type and compare it to the predictions of stellar evolutionary models with rapid rotation. The observed disk masses are typically larger than the theoretical predictions, although the observed spread in disk masses is typically large.« less

Langley's CSI evolutionary model: Phase O

NASA Technical Reports Server (NTRS)

Belvin, W. Keith; Elliott, Kenny B.; Horta, Lucas G.; Bailey, Jim P.; Bruner, Anne M.; Sulla, Jeffrey L.; Won, John; Ugoletti, Roberto M.

1991-01-01

A testbed for the development of Controls Structures Interaction (CSI) technology to improve space science platform pointing is described. The evolutionary nature of the testbed will permit the study of global line-of-sight pointing in phases 0 and 1, whereas, multipayload pointing systems will be studied beginning with phase 2. The design, capabilities, and typical dynamic behavior of the phase 0 version of the CSI evolutionary model (CEM) is documented for investigator both internal and external to NASA. The model description includes line-of-sight pointing measurement, testbed structure, actuators, sensors, and real time computers, as well as finite element and state space models of major components.

Efficiency of the neighbor-joining method in reconstructing deep and shallow evolutionary relationships in large phylogenies.

PubMed

Kumar, S; Gadagkar, S R

2000-12-01

The neighbor-joining (NJ) method is widely used in reconstructing large phylogenies because of its computational speed and the high accuracy in phylogenetic inference as revealed in computer simulation studies. However, most computer simulation studies have quantified the overall performance of the NJ method in terms of the percentage of branches inferred correctly or the percentage of replications in which the correct tree is recovered. We have examined other aspects of its performance, such as the relative efficiency in correctly reconstructing shallow (close to the external branches of the tree) and deep branches in large phylogenies; the contribution of zero-length branches to topological errors in the inferred trees; and the influence of increasing the tree size (number of sequences), evolutionary rate, and sequence length on the efficiency of the NJ method. Results show that the correct reconstruction of deep branches is no more difficult than that of shallower branches. The presence of zero-length branches in realized trees contributes significantly to the overall error observed in the NJ tree, especially in large phylogenies or slowly evolving genes. Furthermore, the tree size does not influence the efficiency of NJ in reconstructing shallow and deep branches in our simulation study, in which the evolutionary process is assumed to be homogeneous in all lineages.

Spore: Spawning Evolutionary Misconceptions?

NASA Astrophysics Data System (ADS)

Bean, Thomas E.; Sinatra, Gale M.; Schrader, P. G.

2010-10-01

The use of computer simulations as educational tools may afford the means to develop understanding of evolution as a natural, emergent, and decentralized process. However, special consideration of developmental constraints on learning may be necessary when using these technologies. Specifically, the essentialist (biological forms possess an immutable essence), teleological (assignment of purpose to living things and/or parts of living things that may not be purposeful), and intentionality (assumption that events are caused by an intelligent agent) biases may be reinforced through the use of computer simulations, rather than addressed with instruction. We examine the video game Spore for its depiction of evolutionary content and its potential to reinforce these cognitive biases. In particular, we discuss three pedagogical strategies to mitigate weaknesses of Spore and other computer simulations: directly targeting misconceptions through refutational approaches, targeting specific principles of scientific inquiry, and directly addressing issues related to models as cognitive tools.

Parallel Evolutionary Optimization for Neuromorphic Network Training

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

Schuman, Catherine D; Disney, Adam; Singh, Susheela

One of the key impediments to the success of current neuromorphic computing architectures is the issue of how best to program them. Evolutionary optimization (EO) is one promising programming technique; in particular, its wide applicability makes it especially attractive for neuromorphic architectures, which can have many different characteristics. In this paper, we explore different facets of EO on a spiking neuromorphic computing model called DANNA. We focus on the performance of EO in the design of our DANNA simulator, and on how to structure EO on both multicore and massively parallel computing systems. We evaluate how our parallel methods impactmore » the performance of EO on Titan, the U.S.'s largest open science supercomputer, and BOB, a Beowulf-style cluster of Raspberry Pi's. We also focus on how to improve the EO by evaluating commonality in higher performing neural networks, and present the result of a study that evaluates the EO performed by Titan.« less

A computer lab exploring evolutionary aspects of chromatin structure and dynamics for an undergraduate chromatin course*.

PubMed

Eirín-López, José M

2013-01-01

The study of chromatin constitutes one of the most active research fields in life sciences, being subject to constant revisions that continuously redefine the state of the art in its knowledge. As every other rapidly changing field, chromatin biology requires clear and straightforward educational strategies able to efficiently translate such a vast body of knowledge to the classroom. With this aim, the present work describes a multidisciplinary computer lab designed to introduce undergraduate students to the dynamic nature of chromatin, within the context of the one semester course "Chromatin: Structure, Function and Evolution." This exercise is organized in three parts including (a) molecular evolutionary biology of histone families (using the H1 family as example), (b) histone structure and variation across different animal groups, and (c) effect of histone diversity on nucleosome structure and chromatin dynamics. By using freely available bioinformatic tools that can be run on common computers, the concept of chromatin dynamics is interactively illustrated from a comparative/evolutionary perspective. At the end of this computer lab, students are able to translate the bioinformatic information into a biochemical context in which the relevance of histone primary structure on chromatin dynamics is exposed. During the last 8 years this exercise has proven to be a powerful approach for teaching chromatin structure and dynamics, allowing students a higher degree of independence during the processes of learning and self-assessment. Copyright © 2013 International Union of Biochemistry and Molecular Biology, Inc.

On the distribution of interspecies correlation for Markov models of character evolution on Yule trees.

PubMed

Mulder, Willem H; Crawford, Forrest W

2015-01-07

Efforts to reconstruct phylogenetic trees and understand evolutionary processes depend fundamentally on stochastic models of speciation and mutation. The simplest continuous-time model for speciation in phylogenetic trees is the Yule process, in which new species are "born" from existing lineages at a constant rate. Recent work has illuminated some of the structural properties of Yule trees, but it remains mostly unknown how these properties affect sequence and trait patterns observed at the tips of the phylogenetic tree. Understanding the interplay between speciation and mutation under simple models of evolution is essential for deriving valid phylogenetic inference methods and gives insight into the optimal design of phylogenetic studies. In this work, we derive the probability distribution of interspecies covariance under Brownian motion and Ornstein-Uhlenbeck models of phenotypic change on a Yule tree. We compute the probability distribution of the number of mutations shared between two randomly chosen taxa in a Yule tree under discrete Markov mutation models. Our results suggest summary measures of phylogenetic information content, illuminate the correlation between site patterns in sequences or traits of related organisms, and provide heuristics for experimental design and reconstruction of phylogenetic trees. Copyright © 2014 Elsevier Ltd. All rights reserved.

Is the political animal politically ignorant? Applying evolutionary psychology to the study of political attitudes.

PubMed

Petersen, Michael Bang; Aarøe, Lene

2012-12-20

As evidenced by research in evolutionary psychology, humans have evolved sophisticated psychological mechanisms tailored to solve enduring adaptive problems of social life. Many of these social problems are political in nature and relate to the distribution of costs and benefits within and between groups. In that sense, evolutionary psychology suggests that humans are, by nature, political animals. By implication, a straightforward application of evolutionary psychology to the study of public opinion seems to entail that modern individuals find politics intrinsically interesting. Yet, as documented by more than fifty years of research in political science, people lack knowledge of basic features of the political process and the ability to form consistent political attitudes. By reviewing and integrating research in evolutionary psychology and public opinion, we describe (1) why modern mass politics often fail to activate evolved mechanisms and (2) the conditions in which these mechanisms are in fact triggered.

Are lowland rainforests really evolutionary museums? Phylogeography of the green hylia (Hylia prasina) in the Afrotropics.

PubMed

Marks, Ben D

2010-04-01

A recent trend in the literature highlights the special role that tropical montane regions and habitat transitions peripheral to large blocks of lowland rainforest play in the diversification process. The emerging view is one of lowland rainforests as evolutionary 'museums'; where biotic diversity is maintained over evolutionary time, and additional diversity is accrued from peripheral areas, but where there has been little recent diversification. This leads to the prediction of genetic diversity without geographic structure in widespread taxa. Here, I assess the notion of the lowland rainforest 'museum' with a phylogeographic study of the green hylia (Aves: Sylviidae: Hylia prasina) using 1132 bp of mtDNA sequence data. The distribution of genetic diversity within the mainland subspecies of Hylia reveals five highly divergent haplotype groups distributed in accordance with broad-scale areas of endemism in the Afrotropics. This pattern of genetic diversity within a currently described subspecies refutes the characterization of lowland forests as evolutionary museums. If the pattern of geographic variation in Hylia occurs broadly in widespread rainforest species, conservation policy makers may need to rethink their priorities for conservation in the Afrotropics. (c) 2009 Elsevier Inc. All rights reserved.

Iteration expansion and regional evolution: phylogeography of Dendrobium officinale and four related taxa in southern China

PubMed Central

Hou, Beiwei; Luo, Jing; Zhang, Yusi; Niu, Zhitao; Xue, Qingyun; Ding, Xiaoyu

2017-01-01

The genus Dendrobium was used as a case study to elucidate the evolutionary history of Orchidaceae in the Sino-Japanese Floristic Region (SJFR) and Southeast Asia region. These evolutionary histories remain largely unknown, including the temporal and spatial distribution of the evolutionary events. The present study used nuclear and plastid DNA to determine the phylogeography of Dendrobium officinale and four closely related taxa. Plastid DNA haplotype and nuclear data were shown to be discordant, suggesting reticulate evolution drove the species’ diversification. Rapid radiation and genetic drift appeared to drive the evolution of D. tosaense and D. flexicaule, whereas introgression or hybridization might have been involved in the evolution of D. scoriarum and D. shixingense. The phylogeographical structure of D. officinale revealed that core natural distribution regions might have served as its glacial refuges. In recent years, human disturbances caused its artificial migration and population extinction. The five taxa may have originated from the Nanling Mountains and the Yungui Plateau and then migrated northward or eastward. After the initial iteration expansion, D. officinale populations appeared to experience the regional evolutionary patterns in different regions and follow the sequential or rapid decline in gene exchange. PMID:28262789

Inquiry-Based Learning of Molecular Phylogenetics

ERIC Educational Resources Information Center

Campo, Daniel; Garcia-Vazquez, Eva

2008-01-01

Reconstructing phylogenies from nucleotide sequences is a challenge for students because it strongly depends on evolutionary models and computer tools that are frequently updated. We present here an inquiry-based course aimed at learning how to trace a phylogeny based on sequences existing in public databases. Computer tools are freely available…

Network analysis of the COSMOS galaxy field

NASA Astrophysics Data System (ADS)

de Regt, R.; Apunevych, S.; von Ferber, C.; Holovatch, Yu; Novosyadlyj, B.

2018-07-01

The galaxy data provided by COSMOS survey for 1°×1° field of sky are analysed by methods of complex networks. Three galaxy samples (slices) with redshifts ranging within intervals 0.88÷0.91, 0.91÷0.94, and 0.94÷0.97 are studied as two-dimensional projections for the spatial distributions of galaxies. We construct networks and calculate network measures for each sample, in order to analyse the network similarity of different samples, distinguish various topological environments, and find associations between galaxy properties (colour index and stellar mass) and their topological environments. Results indicate a high level of similarity between geometry and topology for different galaxy samples and no clear evidence of evolutionary trends in network measures. The distribution of local clustering coefficient C manifests three modes which allow for discrimination between stand-alone singlets and dumbbells (0 ≤ C ≤ 0.1), intermediately packed (0.1 < C < 0.9) and clique (0.9 ≤ C ≤ 1) like galaxies. Analysing astrophysical properties of galaxies (colour index and stellar masses), we show that distributions are similar in all slices, however weak evolutionary trends can also be seen across redshift slices. To specify different topological environments, we have extracted selections of galaxies from each sample according to different modes of C distribution. We have found statistically significant associations between evolutionary parameters of galaxies and selections of C: the distribution of stellar mass for galaxies with interim C differs from the corresponding distributions for stand-alone and clique galaxies, and this difference holds for all redshift slices. The colour index realizes somewhat different behaviour.

Network analysis of the COSMOS galaxy field

NASA Astrophysics Data System (ADS)

de Regt, R.; Apunevych, S.; Ferber, C. von; Holovatch, Yu; Novosyadlyj, B.

2018-03-01

The galaxy data provided by COSMOS survey for 1° × 1° field of sky are analysed by methods of complex networks. Three galaxy samples (slices) with redshifts ranging within intervals 0.88÷0.91, 0.91÷0.94 and 0.94÷0.97 are studied as two-dimensional projections for the spatial distributions of galaxies. We construct networks and calculate network measures for each sample, in order to analyse the network similarity of different samples, distinguish various topological environments, and find associations between galaxy properties (colour index and stellar mass) and their topological environments. Results indicate a high level of similarity between geometry and topology for different galaxy samples and no clear evidence of evolutionary trends in network measures. The distribution of local clustering coefficient C manifests three modes which allow for discrimination between stand-alone singlets and dumbbells (0 ≤ C ≤ 0.1), intermediately packed (0.1 < C < 0.9) and clique (0.9 ≤ C ≤ 1) like galaxies. Analysing astrophysical properties of galaxies (colour index and stellar masses), we show that distributions are similar in all slices, however weak evolutionary trends can also be seen across redshift slices. To specify different topological environments we have extracted selections of galaxies from each sample according to different modes of C distribution. We have found statistically significant associations between evolutionary parameters of galaxies and selections of C: the distribution of stellar mass for galaxies with interim C differ from the corresponding distributions for stand-alone and clique galaxies, and this difference holds for all redshift slices. The colour index realises somewhat different behaviour.

International Conference on Artificial Immune Systems (1st) ICARIS 2002, held on 9, 10, and 11 September 2002

DTIC Science & Technology

2002-03-07

Michalewicz, Eds., Evolutionary Computation 1: Basic Algorithms and Operators, Institute of Physics, Bristol (UK), 2000. [3] David A. Van Veldhuizen ...2000. [4] Carlos A. Coello Coello, David A. Van Veldhuizen , and Gary B. Lamont, Evolutionary Algorithms for Solving Multi-Objective Problems, Kluwer...Academic Publishers, 233 Spring St., New York, NY 10013, 2002. [5] David A. Van Veldhuizen , Multiobjective Evolution- ary Algorithms: Classifications

Using parallel evolutionary development for a biologically-inspired computer vision system for mobile robots.

PubMed

Wright, Cameron H G; Barrett, Steven F; Pack, Daniel J

2005-01-01

We describe a new approach to attacking the problem of robust computer vision for mobile robots. The overall strategy is to mimic the biological evolution of animal vision systems. Our basic imaging sensor is based upon the eye of the common house fly, Musca domestica. The computational algorithms are a mix of traditional image processing, subspace techniques, and multilayer neural networks.

Landscape patterns in rainforest phylogenetic signal: isolated islands of refugia or structured continental distributions?

PubMed

Kooyman, Robert M; Rossetto, Maurizio; Sauquet, Hervé; Laffan, Shawn W

2013-01-01

Identify patterns of change in species distributions, diversity, concentrations of evolutionary history, and assembly of Australian rainforests. We used the distribution records of all known rainforest woody species in Australia across their full continental extent. These were analysed using measures of species richness, phylogenetic diversity (PD), phylogenetic endemism (PE) and phylogenetic structure (net relatedness index; NRI). Phylogenetic structure was assessed using both continental and regional species pools. To test the influence of growth-form, freestanding and climbing plants were analysed independently, and in combination. Species richness decreased along two generally orthogonal continental axes, corresponding with wet to seasonally dry and tropical to temperate habitats. The PE analyses identified four main areas of substantially restricted phylogenetic diversity, including parts of Cape York, Wet Tropics, Border Ranges, and Tasmania. The continental pool NRI results showed evenness (species less related than expected by chance) in groups of grid cells in coastally aligned areas of species rich tropical and sub-tropical rainforest, and in low diversity moist forest areas in the south-east of the Great Dividing Range and in Tasmania. Monsoon and drier vine forests, and moist forests inland from upland refugia showed phylogenetic clustering, reflecting lower diversity and more relatedness. Signals for evenness in Tasmania and clustering in northern monsoon forests weakened in analyses using regional species pools. For climbing plants, values for NRI by grid cell showed strong spatial structuring, with high diversity and PE concentrated in moist tropical and subtropical regions. Concentrations of rainforest evolutionary history (phylo-diversity) were patchily distributed within a continuum of species distributions. Contrasting with previous concepts of rainforest community distribution, our findings of continuous distributions and continental connectivity have significant implications for interpreting rainforest evolutionary history and current day ecological processes, and for managing rainforest diversity in changing circumstances.

Global distribution and evolvement of urbanization and PM2.5 (1998-2015)

NASA Astrophysics Data System (ADS)

Yang, Dongyang; Ye, Chao; Wang, Xiaomin; Lu, Debin; Xu, Jianhua; Yang, Haiqing

2018-06-01

PM2.5 concentrations increased and have been one of the major social issues along with rapid urbanization in many regions of the world in recent decades. The development of urbanization differed among regions, PM2.5 pollution also presented discrepant distribution across the world. Thus, this paper aimed to grasp the profile of global distribution of urbanization and PM2.5 and their evolutionary relationships. Based on global data for the proportion of the urban population and PM2.5 concentrations in 1998-2015, this paper investigated the spatial distribution, temporal variation, and evolutionary relationships of global urbanization and PM2.5. The results showed PM2.5 presented an increasing trend along with urbanization during the study period, but there was a variety of evolutionary relationships in different countries and regions. Most countries in East Asia, Southeast Asia, South Asia, and some African countries developed with the rapid increase in both urbanization and PM2.5. Under the impact of other socioeconomic factors, such as industry and economic growth, the development of urbanization increased PM2.5 concentrations in most Asian countries and some African countries, but decreased PM2.5 concentrations in most European and American countries. The findings of this study revealed the spatial distributions of global urbanization and PM2.5 pollution and provided an interpretation on the evolution of urbanization-PM2.5 relationships, which can contribute to urbanization policies making aimed at successful PM2.5 pollution control and abatement.

Ecotypic differentiation under farmers' selection: Molecular insights into the domestication of Pachyrhizus Rich. ex DC. (Fabaceae) in the Peruvian Andes.

PubMed

Delêtre, Marc; Soengas, Beatriz; Vidaurre, Prem Jai; Meneses, Rosa Isela; Delgado Vásquez, Octavio; Oré Balbín, Isabel; Santayana, Monica; Heider, Bettina; Sørensen, Marten

2017-06-01

Understanding the distribution of crop genetic diversity in relation to environmental factors can give insights into the eco-evolutionary processes involved in plant domestication. Yam beans ( Pachyrhizus Rich. ex DC.) are leguminous crops native to South and Central America that are grown for their tuberous roots but are seed-propagated. Using a landscape genetic approach, we examined correlations between environmental factors and phylogeographic patterns of genetic diversity in Pachyrhizus landrace populations. Molecular analyses based on chloroplast DNA sequencing and a new set of nuclear microsatellite markers revealed two distinct lineages, with strong genetic differentiation between Andean landraces (lineage A) and Amazonian landraces (lineage B). The comparison of different evolutionary scenarios for the diversification history of yam beans in the Andes using approximate Bayesian computation suggests that Pachyrhizus ahipa and Pachyrhizus tuberosus share a progenitor-derivative relationship, with environmental factors playing an important role in driving selection for divergent ecotypes. The new molecular data call for a revision of the taxonomy of Pachyrhizus but are congruent with paleoclimatic and archeological evidence, and suggest that selection for determinate growth was part of ecophysiological adaptations associated with the diversification of the P. tuberosus - P. ahipa complex during the Mid-Holocene.

Free Energy Landscape - Settlements of Key Residues.

NASA Astrophysics Data System (ADS)

Aroutiounian, Svetlana

2007-03-01

FEL perspective in studies of protein folding transitions reflects notion that since there are ˜10^N conformations to scan in search of lowest free energy state, random search is beyond biological timescale. Protein folding must follow certain fel pathways and folding kinetics of evolutionary selected proteins dominates kinetic traps. Good model for functional robustness of natural proteins - coarse-grained model protein is not very accurate but affords bringing simulations closer to biological realm; Go-like potential secures the fel funnel shape; biochemical contacts signify the funnel bottleneck. Boltzmann-weighted ensemble of protein conformations and histogram method are used to obtain from MC sampling of protein conformational space the approximate probability distribution. The fel is F(rmsd) = -1/βLn[Hist(rmsd)], β=kBT and rmsd is root-mean-square-deviation from native conformation. The sperm whale myoglobin has rich dynamic behavior, is small and large - on computational scale, has a symmetry in architecture and unusual sextet of residue pairs. Main idea: there is a mathematical relation between protein fel and a key residues set providing stability to folding transition. Is the set evolutionary conserved also for functional reasons? Hypothesis: primary sequence determines the key residues positions conserved as stabilizers and the fel is the battlefield for the folding stability. Preliminary results: primary sequence - not the architecture, is the rule settler, indeed.

Evolutionary vaccination dynamics with internal support mechanisms

NASA Astrophysics Data System (ADS)

Tang, Guo-Mei; Cai, Chao-Ran; Wu, Zhi-Xi

2017-05-01

This paper reports internal support mechanisms (i.e., without external intervention) to enhance the vaccine coverage in the evolutionary vaccination dynamics. We present two internal support mechanisms, one is global support mechanism in which each individual pays a support cost to build up a public fund and then the public fund is divided by all vaccinated individuals, while another is local support mechanism in which each individual pays a support cost and then this support cost will be divided by its immediate vaccinated neighbors. By means of extensive computer simulations, we show that, in the same strength of support cost, the heterogeneous (local) support mechanism can encourage more people to take vaccination than the homogeneous (global) support mechanism. And then, we study the most general case that includes supporters and troublemakers together, where supporters (troublemakers) mean that the individuals join (do not join) the internal support mechanism, in the population. We surprisingly find that, in scale-free networks, the voluntary vaccination dynamics with the local support mechanism will not degrade into the original voluntary vaccination dynamics, and the vaccination level can still be effectively improved. In view of most social networks are of scale-free degree distribution, we study further in empirical networks and find that the vaccination level can still be improved in the absence of external intervention.

Automated Antenna Design with Evolutionary Algorithms

NASA Technical Reports Server (NTRS)

Hornby, Gregory S.; Globus, Al; Linden, Derek S.; Lohn, Jason D.

2006-01-01

Current methods of designing and optimizing antennas by hand are time and labor intensive, and limit complexity. Evolutionary design techniques can overcome these limitations by searching the design space and automatically finding effective solutions. In recent years, evolutionary algorithms have shown great promise in finding practical solutions in large, poorly understood design spaces. In particular, spacecraft antenna design has proven tractable to evolutionary design techniques. Researchers have been investigating evolutionary antenna design and optimization since the early 1990s, and the field has grown in recent years as computer speed has increased and electromagnetic simulators have improved. Two requirements-compliant antennas, one for ST5 and another for TDRS-C, have been automatically designed by evolutionary algorithms. The ST5 antenna is slated to fly this year, and a TDRS-C phased array element has been fabricated and tested. Such automated evolutionary design is enabled by medium-to-high quality simulators and fast modern computers to evaluate computer-generated designs. Evolutionary algorithms automate cut-and-try engineering, substituting automated search though millions of potential designs for intelligent search by engineers through a much smaller number of designs. For evolutionary design, the engineer chooses the evolutionary technique, parameters and the basic form of the antenna, e.g., single wire for ST5 and crossed-element Yagi for TDRS-C. Evolutionary algorithms then search for optimal configurations in the space defined by the engineer. NASA's Space Technology 5 (ST5) mission will launch three small spacecraft to test innovative concepts and technologies. Advanced evolutionary algorithms were used to automatically design antennas for ST5. The combination of wide beamwidth for a circularly-polarized wave and wide impedance bandwidth made for a challenging antenna design problem. From past experience in designing wire antennas, we chose to constrain the evolutionary design to a monopole wire antenna. The results of the runs produced requirements-compliant antennas that were subsequently fabricated and tested. The evolved antenna has a number of advantages with regard to power consumption, fabrication time and complexity, and performance. Lower power requirements result from achieving high gain across a wider range of elevation angles, thus allowing a broader range of angles over which maximum data throughput can be achieved. Since the evolved antenna does not require a phasing circuit, less design and fabrication work is required. In terms of overall work, the evolved antenna required approximately three person-months to design and fabricate whereas the conventional antenna required about five. Furthermore, when the mission was modified and new orbital parameters selected, a redesign of the antenna to new requirements was required. The evolutionary system was rapidly modified and a new antenna evolved in a few weeks. The evolved antenna was shown to be compliant to the ST5 mission requirements. It has an unusual organic looking structure, one that expert antenna designers would not likely produce. This antenna has been tested, baselined and is scheduled to fly this year. In addition to the ST5 antenna, our laboratory has evolved an S-band phased array antenna element design that meets the requirements for NASA's TDRS-C communications satellite scheduled for launch early next decade. A combination of fairly broad bandwidth, high efficiency and circular polarization at high gain made for another challenging design problem. We chose to constrain the evolutionary design to a crossed-element Yagi antenna. The specification called for two types of elements, one for receive only and one for transmit/receive. We were able to evolve a single element design that meets both specifications thereby simplifying the antenna and reducing testing and integration costs. The highest performance antenna found using a getic algorithm and stochastic hill-climbing has been fabricated and tested. Laboratory results correspond well with simulation. Aerospace component design is an expensive and important step in space development. Evolutionary design can make a significant contribution wherever sufficiently fast, accurate and capable software simulators are available. We have demonstrated successful real-world design in the spacecraft antenna domain; and there is good reason to believe that these results could be replicated in other design spaces.

Neutral Evolution of Duplicated DNA: An Evolutionary Stick-Breaking Process Causes Scale-Invariant Behavior

NASA Astrophysics Data System (ADS)

Massip, Florian; Arndt, Peter F.

2013-04-01

Recently, an enrichment of identical matching sequences has been found in many eukaryotic genomes. Their length distribution exhibits a power law tail raising the question of what evolutionary mechanism or functional constraints would be able to shape this distribution. Here we introduce a simple and evolutionarily neutral model, which involves only point mutations and segmental duplications, and produces the same statistical features as observed for genomic data. Further, we extend a mathematical model for random stick breaking to analytically show that the exponent of the power law tail is -3 and universal as it does not depend on the microscopic details of the model.

Tempo and mode of climatic niche evolution in Primates.

PubMed

Duran, Andressa; Pie, Marcio R

2015-09-01

Climatic niches have increasingly become a nexus in our understanding of a variety of ecological and evolutionary phenomena, from species distributions to latitudinal diversity gradients. Despite the increasing availability of comprehensive datasets on species ranges, phylogenetic histories, and georeferenced environmental conditions, studies on the evolution of climate niches have only begun to understand how niches evolve over evolutionary timescales. Here, using primates as a model system, we integrate recently developed phylogenetic comparative methods, species distribution patterns, and climatic data to explore primate climatic niche evolution, both among clades and over time. In general, we found that simple, constant-rate models provide a poor representation of how climatic niches evolve. For instance, there have been shifts in the rate of climatic niche evolution in several independent clades, particularly in response to the increasingly cooler climates of the past 10 My. Interestingly, rate accelerations greatly outnumbered rate decelerations. These results highlight the importance of considering more realistic evolutionary models that allow for the detection of heterogeneity in the tempo and mode of climatic niche evolution, as well as to infer possible constraining factors for species distributions in geographical space. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

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.

Hardware platforms for MEMS gyroscope tuning based on evolutionary computation using open-loop and closed -loop frequency response

NASA Technical Reports Server (NTRS)

Keymeulen, Didier; Ferguson, Michael I.; Fink, Wolfgang; Oks, Boris; Peay, Chris; Terrile, Richard; Cheng, Yen; Kim, Dennis; MacDonald, Eric; Foor, David

2005-01-01

We propose a tuning method for MEMS gyroscopes based on evolutionary computation to efficiently increase the sensitivity of MEMS gyroscopes through tuning. The tuning method was tested for the second generation JPL/Boeing Post-resonator MEMS gyroscope using the measurement of the frequency response of the MEMS device in open-loop operation. We also report on the development of a hardware platform for integrated tuning and closed loop operation of MEMS gyroscopes. The control of this device is implemented through a digital design on a Field Programmable Gate Array (FPGA). The hardware platform easily transitions to an embedded solution that allows for the miniaturization of the system to a single chip.

Simple Sequence Repeats in Escherichia coli: Abundance, Distribution, Composition, and Polymorphism

PubMed Central

Gur-Arie, Riva; Cohen, Cyril J.; Eitan, Yuval; Shelef, Leora; Hallerman, Eric M.; Kashi, Yechezkel

2000-01-01

Computer-based genome-wide screening of the DNA sequence of Escherichia coli strain K12 revealed tens of thousands of tandem simple sequence repeat (SSR) tracts, with motifs ranging from 1 to 6 nucleotides. SSRs were well distributed throughout the genome. Mononucleotide SSRs were over-represented in noncoding regions and under-represented in open reading frames (ORFs). Nucleotide composition of mono- and dinucleotide SSRs, both in ORFs and in noncoding regions, differed from that of the genomic region in which they occurred, with 93% of all mononucleotide SSRs proving to be of A or T. Computer-based analysis of the fine position of every SSR locus in the noncoding portion of the genome relative to downstream ORFs showed SSRs located in areas that could affect gene regulation. DNA sequences at 14 arbitrarily chosen SSR tracts were compared among E. coli strains. Polymorphisms of SSR copy number were observed at four of seven mononucleotide SSR tracts screened, with all polymorphisms occurring in noncoding regions. SSR polymorphism could prove important as a genome-wide source of variation, both for practical applications (including rapid detection, strain identification, and detection of loci affecting key phenotypes) and for evolutionary adaptation of microbes.[The sequence data described in this paper have been submitted to the GenBank data library under accession numbers AF209020–209030 and AF209508–209518.] PMID:10645951

Global distribution of NA1 genotype of respiratory syncytial virus and its evolutionary dynamics assessed from the past 11 years.

PubMed

Haider, Md Shakir Hussain; Deeba, Farah; Khan, Wajihul Hasan; Naqvi, Irshad H; Ali, Sher; Ahmed, Anwar; Broor, Shobha; Alsenaidy, Hytham A; Alsenaidy, Abdulrahman M; Dohare, Ravins; Parveen, Shama

2018-06-01

Respiratory syncytial virus (RSV) is a potent pathogen having global distribution. The main purpose of this study was to gain an insight into distribution pattern of the NA1 genotype of group A RSV across the globe together with its evolutionary dynamics. We focused on the second hypervariable region of the G protein gene and used the same for Phylogenetic, Bayesian and Network analyses. Eighteen percent of the samples collected from 500 symptomatic pediatric patients with acute respiratory tract infection (ARI) were found to be positive for RSV during 2011-15 from New Delhi, India. Of these, group B RSV was predominant and clustered into two different genotypes (BA and SAB4). Similarly, group A viruses clustered into two genotypes (NA1 and ON1). The data set from the group A viruses included 543 sequences from 23 different countries including 67 strains from India. The local evolutionary dynamics suggested consistent virus population of NA1 genotype in India during 2009 to 2014. The molecular clock analysis suggested that most recent common ancestor of group A and NA1 genotype have emerged in during the years 1953 and 2000, respectively. The global evolutionary rates of group A viruses and NA1 genotype were estimated to be 3.49 × 10 -3 (95% HPD, 2.90-4.17 × 10 -3 ) and 3.56 × 10 -3 (95% HPD, 2.91 × 10 -3 -4.18 × 10 -3 ) substitution/site/year, respectively. Analysis of the NA1 genotype of group A RSV reported during 11 years i.e. from 2004 to 2014 showed its dominance in 21 different countries across the globe reflecting its evolutionary dynamics. The Network analysis showed highly intricate but an inconsistent pattern of haplotypes of NA1 genotype circulating in the world. Present study seems to be first comprehensive attempt on global distribution and evolution of NA1 genotype augmenting the optimism towards the vaccine development. Copyright © 2018 Elsevier B.V. All rights reserved.

Decimetre Waves and Cerebellar Cortex Key Element - Purkinje Cells

NASA Astrophysics Data System (ADS)

Maharramov, Akif A.

2007-04-01

Acute experiments have been carried out on both decerebrated and anaesthetized adult cats exposed to Decimetre Range Microwaves (DRM) (λ=65 cm, duration of exposition -10 min., at least) by the help of a 2 cm radius contact applicator located on the temple part of the head with cerebellum in the centre of projection of irradiation conducted from portable physiotherapeutic apparatus ``Romashka''. Extracelullar registration of Purkinje Cells (PC) impulse activities have been led by glass microelectrodes. Statistical and computational analyses of PC activities have been realized by the help of histograms - the characteristic distribution of the number of interimpulse intervals (II) between electrical discharges of a neuron on the II durations, drawn up by the help of a computer. The results obtained revealed the reaction of PC to DRM as a succession of starting to react of PC electrophysiological parameters, beginning from decreasing of known ``Inhibitory Pause'' duration, and further, at first, ``Simple Spikes'' then ``Complex Spikes'' frequencies' increase, and furthermore, durations' increase in ``Big Interimpulse Intervals'', parameter, introduced for the first time by us, in this way, showing the ``evolutionary'' nature of Electromagnetic Fields and Living object interactions.

Evolution of Collective Behaviour in an Artificial World Using Linguistic Fuzzy Rule-Based Systems

PubMed Central

Lebar Bajec, Iztok

2017-01-01

Collective behaviour is a fascinating and easily observable phenomenon, attractive to a wide range of researchers. In biology, computational models have been extensively used to investigate various properties of collective behaviour, such as: transfer of information across the group, benefits of grouping (defence against predation, foraging), group decision-making process, and group behaviour types. The question ‘why,’ however remains largely unanswered. Here the interest goes into which pressures led to the evolution of such behaviour, and evolutionary computational models have already been used to test various biological hypotheses. Most of these models use genetic algorithms to tune the parameters of previously presented non-evolutionary models, but very few attempt to evolve collective behaviour from scratch. Of these last, the successful attempts display clumping or swarming behaviour. Empirical evidence suggests that in fish schools there exist three classes of behaviour; swarming, milling and polarized. In this paper we present a novel, artificial life-like evolutionary model, where individual agents are governed by linguistic fuzzy rule-based systems, which is capable of evolving all three classes of behaviour. PMID:28045964

An improved shuffled frog leaping algorithm based evolutionary framework for currency exchange rate prediction

NASA Astrophysics Data System (ADS)

Dash, Rajashree

2017-11-01

Forecasting purchasing power of one currency with respect to another currency is always an interesting topic in the field of financial time series prediction. Despite the existence of several traditional and computational models for currency exchange rate forecasting, there is always a need for developing simpler and more efficient model, which will produce better prediction capability. In this paper, an evolutionary framework is proposed by using an improved shuffled frog leaping (ISFL) algorithm with a computationally efficient functional link artificial neural network (CEFLANN) for prediction of currency exchange rate. The model is validated by observing the monthly prediction measures obtained for three currency exchange data sets such as USD/CAD, USD/CHF, and USD/JPY accumulated within same period of time. The model performance is also compared with two other evolutionary learning techniques such as Shuffled frog leaping algorithm and Particle Swarm optimization algorithm. Practical analysis of results suggest that, the proposed model developed using the ISFL algorithm with CEFLANN network is a promising predictor model for currency exchange rate prediction compared to other models included in the study.

Evolution of Collective Behaviour in an Artificial World Using Linguistic Fuzzy Rule-Based Systems.

PubMed

Demšar, Jure; Lebar Bajec, Iztok

2017-01-01

Collective behaviour is a fascinating and easily observable phenomenon, attractive to a wide range of researchers. In biology, computational models have been extensively used to investigate various properties of collective behaviour, such as: transfer of information across the group, benefits of grouping (defence against predation, foraging), group decision-making process, and group behaviour types. The question 'why,' however remains largely unanswered. Here the interest goes into which pressures led to the evolution of such behaviour, and evolutionary computational models have already been used to test various biological hypotheses. Most of these models use genetic algorithms to tune the parameters of previously presented non-evolutionary models, but very few attempt to evolve collective behaviour from scratch. Of these last, the successful attempts display clumping or swarming behaviour. Empirical evidence suggests that in fish schools there exist three classes of behaviour; swarming, milling and polarized. In this paper we present a novel, artificial life-like evolutionary model, where individual agents are governed by linguistic fuzzy rule-based systems, which is capable of evolving all three classes of behaviour.

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.

An Improved Co-evolutionary Particle Swarm Optimization for Wireless Sensor Networks with Dynamic Deployment

PubMed Central

Wang, Xue; Wang, Sheng; Ma, Jun-Jie

2007-01-01

The effectiveness of wireless sensor networks (WSNs) depends on the coverage and target detection probability provided by dynamic deployment, which is usually supported by the virtual force (VF) algorithm. However, in the VF algorithm, the virtual force exerted by stationary sensor nodes will hinder the movement of mobile sensor nodes. Particle swarm optimization (PSO) is introduced as another dynamic deployment algorithm, but in this case the computation time required is the big bottleneck. This paper proposes a dynamic deployment algorithm which is named “virtual force directed co-evolutionary particle swarm optimization” (VFCPSO), since this algorithm combines the co-evolutionary particle swarm optimization (CPSO) with the VF algorithm, whereby the CPSO uses multiple swarms to optimize different components of the solution vectors for dynamic deployment cooperatively and the velocity of each particle is updated according to not only the historical local and global optimal solutions, but also the virtual forces of sensor nodes. Simulation results demonstrate that the proposed VFCPSO is competent for dynamic deployment in WSNs and has better performance with respect to computation time and effectiveness than the VF, PSO and VFPSO algorithms.

The tangled bank of amino acids

PubMed Central

Pollock, David D.

2016-01-01

Abstract The use of amino acid substitution matrices to model protein evolution has yielded important insights into both the evolutionary process and the properties of specific protein families. In order to make these models tractable, standard substitution matrices represent the average results of the evolutionary process rather than the underlying molecular biophysics and population genetics, treating proteins as a set of independently evolving sites rather than as an integrated biomolecular entity. With advances in computing and the increasing availability of sequence data, we now have an opportunity to move beyond current substitution matrices to more interpretable mechanistic models with greater fidelity to the evolutionary process of mutation and selection and the holistic nature of the selective constraints. As part of this endeavour, we consider how epistatic interactions induce spatial and temporal rate heterogeneity, and demonstrate how these generally ignored factors can reconcile standard substitution rate matrices and the underlying biology, allowing us to better understand the meaning of these substitution rates. Using computational simulations of protein evolution, we can demonstrate the importance of both spatial and temporal heterogeneity in modelling protein evolution. PMID:27028523

Evolutionary Optimization of a Geometrically Refined Truss

NASA Technical Reports Server (NTRS)

Hull, P. V.; Tinker, M. L.; Dozier, G. V.

2007-01-01

Structural optimization is a field of research that has experienced noteworthy growth for many years. Researchers in this area have developed optimization tools to successfully design and model structures, typically minimizing mass while maintaining certain deflection and stress constraints. Numerous optimization studies have been performed to minimize mass, deflection, and stress on a benchmark cantilever truss problem. Predominantly traditional optimization theory is applied to this problem. The cross-sectional area of each member is optimized to minimize the aforementioned objectives. This Technical Publication (TP) presents a structural optimization technique that has been previously applied to compliant mechanism design. This technique demonstrates a method that combines topology optimization, geometric refinement, finite element analysis, and two forms of evolutionary computation: genetic algorithms and differential evolution to successfully optimize a benchmark structural optimization problem. A nontraditional solution to the benchmark problem is presented in this TP, specifically a geometrically refined topological solution. The design process begins with an alternate control mesh formulation, multilevel geometric smoothing operation, and an elastostatic structural analysis. The design process is wrapped in an evolutionary computing optimization toolset.

A Large Stellar Evolution Database for Population Synthesis Studies. I. Scaled Solar Models and Isochrones

NASA Astrophysics Data System (ADS)

Pietrinferni, Adriano; Cassisi, Santi; Salaris, Maurizio; Castelli, Fiorella

2004-09-01

We present a large and updated stellar evolution database for low-, intermediate-, and high-mass stars in a wide metallicity range, suitable for studying Galactic and extragalactic simple and composite stellar populations using population synthesis techniques. The stellar mass range is between ~0.5 and 10 Msolar with a fine mass spacing. The metallicity [Fe/H] comprises 10 values ranging from -2.27 to 0.40, with a scaled solar metal distribution. The initial He mass fraction ranges from Y=0.245, for the more metal-poor composition, up to 0.303 for the more metal-rich one, with ΔY/ΔZ~1.4. For each adopted chemical composition, the evolutionary models have been computed without (canonical models) and with overshooting from the Schwarzschild boundary of the convective cores during the central H-burning phase. Semiconvection is included in the treatment of core convection during the He-burning phase. The whole set of evolutionary models can be used to compute isochrones in a wide age range, from ~30 Myr to ~15 Gyr. Both evolutionary models and isochrones are available in several observational planes, employing an updated set of bolometric corrections and color-Teff relations computed for this project. The number of points along the models and the resulting isochrones is selected in such a way that interpolation for intermediate metallicities not contained in the grid is straightforward; a simple quadratic interpolation produces results of sufficient accuracy for population synthesis applications.We compare our isochrones with results from a series of widely used stellar evolution databases and perform some empirical tests for the reliability of our models. Since this work is devoted to scaled solar chemical compositions, we focus our attention on the Galactic disk stellar populations, employing multicolor photometry of unevolved field main-sequence stars with precise Hipparcos parallaxes, well-studied open clusters, and one eclipsing binary system with precise measurements of masses, radii, and [Fe/H] of both components. We find that the predicted metallicity dependence of the location of the lower, unevolved main sequence in the color magnitude diagram (CMD) appears in satisfactory agreement with empirical data. When comparing our models with CMDs of selected, well-studied, open clusters, once again we were able to properly match the whole observed evolutionary sequences by assuming cluster distance and reddening estimates in satisfactory agreement with empirical evaluations of these quantities. In general, models including overshooting during the H-burning phase provide a better match to the observations, at least for ages below ~4 Gyr. At [Fe/H] around solar and higher ages (i.e., smaller convective cores) before the onset of radiative cores, the selected efficiency of core overshooting may be too high in our model, as well as in various other models in the literature. Since we also provide canonical models, the reader is strongly encouraged to always compare the results from both sets in this critical age range.

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 numerical treatment of selected oscillatory evolutionary problems

NASA Astrophysics Data System (ADS)

Cardone, Angelamaria; Conte, Dajana; D'Ambrosio, Raffaele; Paternoster, Beatrice

2017-07-01

We focus on evolutionary problems whose qualitative behaviour is known a-priori and exploited in order to provide efficient and accurate numerical schemes. For classical numerical methods, depending on constant coefficients, the required computational effort could be quite heavy, due to the necessary employ of very small stepsizes needed to accurately reproduce the qualitative behaviour of the solution. In these situations, it may be convenient to use special purpose formulae, i.e. non-polynomially fitted formulae on basis functions adapted to the problem (see [16, 17] and references therein). We show examples of special purpose strategies to solve two families of evolutionary problems exhibiting periodic solutions, i.e. partial differential equations and Volterra integral equations.

Human evolutionary genomics: ethical and interpretive issues.

PubMed

Vitti, Joseph J; Cho, Mildred K; Tishkoff, Sarah A; Sabeti, Pardis C

2012-03-01

Genome-wide computational studies can now identify targets of natural selection. The unique information about humans these studies reveal, and the media attention they attract, indicate the need for caution and precision in communicating results. This need is exacerbated by ways in which evolutionary and genetic considerations have been misapplied to support discriminatory policies, by persistent misconceptions of these fields and by the social sensitivity surrounding discussions of racial ancestry. We discuss the foundations, accomplishments and future directions of human evolutionary genomics, attending to ways in which the interpretation of good science can go awry, and offer suggestions for researchers to prevent misapplication of their work. Copyright © 2011 Elsevier Ltd. All rights reserved.

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.

Regulatory and evolutionary signatures of sex-biased genes on both the X chromosome and the autosomes.

PubMed

Shen, Jiangshan J; Wang, Ting-You; Yang, Wanling

2017-11-02

Sex is an important but understudied factor in the genetics of human diseases. Analyses using a combination of gene expression data, ENCODE data, and evolutionary data of sex-biased gene expression in human tissues can give insight into the regulatory and evolutionary forces acting on sex-biased genes. In this study, we analyzed the differentially expressed genes between males and females. On the X chromosome, we used a novel method and investigated the status of genes that escape X-chromosome inactivation (escape genes), taking into account the clonality of lymphoblastoid cell lines (LCLs). To investigate the regulation of sex-biased differentially expressed genes (sDEG), we conducted pathway and transcription factor enrichment analyses on the sDEGs, as well as analyses on the genomic distribution of sDEGs. Evolutionary analyses were also conducted on both sDEGs and escape genes. Genome-wide, we characterized differential gene expression between sexes in 462 RNA-seq samples and identified 587 sex-biased genes, or 3.2% of the genes surveyed. On the X chromosome, sDEGs were distributed in evolutionary strata in a similar pattern as escape genes. We found a trend of negative correlation between the gene expression breadth and nonsynonymous over synonymous mutation (dN/dS) ratios, showing a possible pleiotropic constraint on evolution of genes. Genome-wide, nine transcription factors were found enriched in binding to the regions surrounding the transcription start sites of female-biased genes. Many pathways and protein domains were enriched in sex-biased genes, some of which hint at sex-biased physiological processes. These findings lend insight into the regulatory and evolutionary forces shaping sex-biased gene expression and their involvement in the physiological and pathological processes in human health and diseases.

Evolving Non-Dominated Parameter Sets for Computational Models from Multiple Experiments

NASA Astrophysics Data System (ADS)

Lane, Peter C. R.; Gobet, Fernand

2013-03-01

Creating robust, reproducible and optimal computational models is a key challenge for theorists in many sciences. Psychology and cognitive science face particular challenges as large amounts of data are collected and many models are not amenable to analytical techniques for calculating parameter sets. Particular problems are to locate the full range of acceptable model parameters for a given dataset, and to confirm the consistency of model parameters across different datasets. Resolving these problems will provide a better understanding of the behaviour of computational models, and so support the development of general and robust models. In this article, we address these problems using evolutionary algorithms to develop parameters for computational models against multiple sets of experimental data; in particular, we propose the `speciated non-dominated sorting genetic algorithm' for evolving models in several theories. We discuss the problem of developing a model of categorisation using twenty-nine sets of data and models drawn from four different theories. We find that the evolutionary algorithms generate high quality models, adapted to provide a good fit to all available data.

Multiobjective Multifactorial Optimization in Evolutionary Multitasking.

PubMed

Gupta, Abhishek; Ong, Yew-Soon; Feng, Liang; Tan, Kay Chen

2016-05-03

In recent decades, the field of multiobjective optimization has attracted considerable interest among evolutionary computation researchers. One of the main features that makes evolutionary methods particularly appealing for multiobjective problems is the implicit parallelism offered by a population, which enables simultaneous convergence toward the entire Pareto front. While a plethora of related algorithms have been proposed till date, a common attribute among them is that they focus on efficiently solving only a single optimization problem at a time. Despite the known power of implicit parallelism, seldom has an attempt been made to multitask, i.e., to solve multiple optimization problems simultaneously. It is contended that the notion of evolutionary multitasking leads to the possibility of automated transfer of information across different optimization exercises that may share underlying similarities, thereby facilitating improved convergence characteristics. In particular, the potential for automated transfer is deemed invaluable from the standpoint of engineering design exercises where manual knowledge adaptation and reuse are routine. Accordingly, in this paper, we present a realization of the evolutionary multitasking paradigm within the domain of multiobjective optimization. The efficacy of the associated evolutionary algorithm is demonstrated on some benchmark test functions as well as on a real-world manufacturing process design problem from the composites industry.

The evolution of body size in extant groups of North American freshwater fishes: speciation, size distributions, and Cope's rule.

PubMed

Knouft, Jason H; Page, Lawrence M

2003-03-01

Change in body size within an evolutionary lineage over time has been under investigation since the synthesis of Cope's rule, which suggested that there is a tendency for mammals to evolve larger body size. Data from the fossil record have subsequently been examined for several other taxonomic groups to determine whether they also displayed an evolutionary increase in body size. However, we are not aware of any species-level study that has investigated the evolution of body size within an extant continental group. Data acquired from the fossil record and data derived from the evolutionary relationships of extant species are not similar, with each set exhibiting both strengths and weaknesses related to inferring evolutionary patterns. Consequently, expectation that general trends exhibited in the fossil record will correspond to patterns in extant groups is not necessarily warranted. Using phylogenetic relationships of extant species, we show that five of nine families of North American freshwater fishes exhibit an evolutionary trend of decreasing body size. These trends result from the basal position of large species and the more derived position of small species within families. Such trends may be caused by the invasion of small streams and subsequent isolation and speciation. This pattern, potentially influenced by size-biased dispersal rates and the high percentage of small streams in North America, suggests a scenario that could result in the generation of the size-frequency distribution of North American freshwater fishes.

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

Replaying evolutionary transitions from the dental fossil record

PubMed Central

Harjunmaa, Enni; Seidel, Kerstin; Häkkinen, Teemu; Renvoisé, Elodie; Corfe, Ian J.; Kallonen, Aki; Zhang, Zhao-Qun; Evans, Alistair R.; Mikkola, Marja L.; Salazar-Ciudad, Isaac; Klein, Ophir D.; Jernvall, Jukka

2014-01-01

The evolutionary relationships of extinct species are ascertained primarily through the analysis of morphological characters. Character inter-dependencies can have a substantial effect on evolutionary interpretations, but the developmental underpinnings of character inter-dependence remain obscure because experiments frequently do not provide detailed resolution of morphological characters. Here we show experimentally and computationally how gradual modification of development differentially affects characters in the mouse dentition. We found that intermediate phenotypes could be produced by gradually adding ectodysplasin A (EDA) protein in culture to tooth explants carrying a null mutation in the tooth-patterning gene Eda. By identifying development-based character interdependencies, we show how to predict morphological patterns of teeth among mammalian species. Finally, in vivo inhibition of sonic hedgehog signalling in Eda null teeth enabled us to reproduce characters deep in the rodent ancestry. Taken together, evolutionarily informative transitions can be experimentally reproduced, thereby providing development-based expectations for character state transitions used in evolutionary studies. PMID:25079326

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.

Historical Contingency in Controlled Evolution

NASA Astrophysics Data System (ADS)

Schuster, Peter

2014-12-01

A basic question in evolution is dealing with the nature of an evolutionary memory. At thermodynamic equilibrium, at stable stationary states or other stable attractors the memory on the path leading to the long-time solution is erased, at least in part. Similar arguments hold for unique optima. Optimality in biology is discussed on the basis of microbial metabolism. Biology, on the other hand, is characterized by historical contingency, which has recently become accessible to experimental test in bacterial populations evolving under controlled conditions. Computer simulations give additional insight into the nature of the evolutionary memory, which is ultimately caused by the enormous space of possibilities that is so large that it escapes all attempts of visualization. In essence, this contribution is dealing with two questions of current evolutionary theory: (i) Are organisms operating at optimal performance? and (ii) How is the evolutionary memory built up in populations?

Human vs. Computer Diagnosis of Students' Natural Selection Knowledge: Testing the Efficacy of Text Analytic Software

NASA Astrophysics Data System (ADS)

Nehm, Ross H.; Haertig, Hendrik

2012-02-01

Our study examines the efficacy of Computer Assisted Scoring (CAS) of open-response text relative to expert human scoring within the complex domain of evolutionary biology. Specifically, we explored whether CAS can diagnose the explanatory elements (or Key Concepts) that comprise undergraduate students' explanatory models of natural selection with equal fidelity as expert human scorers in a sample of >1,000 essays. We used SPSS Text Analysis 3.0 to perform our CAS and measure Kappa values (inter-rater reliability) of KC detection (i.e., computer-human rating correspondence). Our first analysis indicated that the text analysis functions (or extraction rules) developed and deployed in SPSSTA to extract individual Key Concepts (KCs) from three different items differing in several surface features (e.g., taxon, trait, type of evolutionary change) produced "substantial" (Kappa 0.61-0.80) or "almost perfect" (0.81-1.00) agreement. The second analysis explored the measurement of human-computer correspondence for KC diversity (the number of different accurate knowledge elements) in the combined sample of all 827 essays. Here we found outstanding correspondence; extraction rules generated using one prompt type are broadly applicable to other evolutionary scenarios (e.g., bacterial resistance, cheetah running speed, etc.). This result is encouraging, as it suggests that the development of new item sets may not necessitate the development of new text analysis rules. Overall, our findings suggest that CAS tools such as SPSS Text Analysis may compensate for some of the intrinsic limitations of currently used multiple-choice Concept Inventories designed to measure student knowledge of natural selection.

Functional phylogenomics analysis of bacteria and archaea using consistent genome annotation with UniFam

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

Chai, Juanjuan; Kora, Guruprasad; Ahn, Tae-Hyuk

2014-10-09

To supply some background, phylogenetic studies have provided detailed knowledge on the evolutionary mechanisms of genes and species in Bacteria and Archaea. However, the evolution of cellular functions, represented by metabolic pathways and biological processes, has not been systematically characterized. Many clades in the prokaryotic tree of life have now been covered by sequenced genomes in GenBank. This enables a large-scale functional phylogenomics study of many computationally inferred cellular functions across all sequenced prokaryotes. Our results show a total of 14,727 GenBank prokaryotic genomes were re-annotated using a new protein family database, UniFam, to obtain consistent functional annotations for accuratemore » comparison. The functional profile of a genome was represented by the biological process Gene Ontology (GO) terms in its annotation. The GO term enrichment analysis differentiated the functional profiles between selected archaeal taxa. 706 prokaryotic metabolic pathways were inferred from these genomes using Pathway Tools and MetaCyc. The consistency between the distribution of metabolic pathways in the genomes and the phylogenetic tree of the genomes was measured using parsimony scores and retention indices. The ancestral functional profiles at the internal nodes of the phylogenetic tree were reconstructed to track the gains and losses of metabolic pathways in evolutionary history. In conclusion, our functional phylogenomics analysis shows divergent functional profiles of taxa and clades. Such function-phylogeny correlation stems from a set of clade-specific cellular functions with low parsimony scores. On the other hand, many cellular functions are sparsely dispersed across many clades with high parsimony scores. These different types of cellular functions have distinct evolutionary patterns reconstructed from the prokaryotic tree.« less

Thermodynamical interpretation of an adaptive walk on a Mt. Fuji-type fitness landscape: Einstein relation-like formula holds in a stochastic evolution.

PubMed

Aita, Takuyo; Husimi, Yuzuru

2003-11-21

We have theoretically studied the statistical properties of adaptive walks (or hill-climbing) on a Mt. Fuji-type fitness landscape in the multi-dimensional sequence space through mathematical analysis and computer simulation. The adaptive walk is characterized by the "mutation distance" d as the step-width of the walker and the "population size" N as the number of randomly generated d-fold point mutants to be screened. In addition to the fitness W, we introduced the following quantities analogous to thermodynamical concepts: "free fitness" G(W) is identical with W+T x S(W), where T is the "evolutionary temperature" T infinity square root of d/lnN and S(W) is the entropy as a function of W, and the "evolutionary force" X is identical with d(G(W)/T)/dW, that is caused by the mutation and selection pressure. It is known that a single adaptive walker rapidly climbs on the fitness landscape up to the stationary state where a "mutation-selection-random drift balance" is kept. In our interpretation, the walker tends to the maximal free fitness state, driven by the evolutionary force X. Our major findings are as follows: First, near the stationary point W*, the "climbing rate" J as the expected fitness change per generation is described by J approximately L x X with L approximately V/2, where V is the variance of fitness distribution on a local landscape. This simple relationship is analogous to the well-known Einstein relation in Brownian motion. Second, the "biological information gain" (DeltaG/T) through adaptive walk can be described by combining the Shannon's information gain (DeltaS) and the "fitness information gain" (DeltaW/T).

Computer-automated evolution of an X-band antenna for NASA's Space Technology 5 mission.

PubMed

Hornby, Gregory S; Lohn, Jason D; Linden, Derek S

2011-01-01

Whereas the current practice of designing antennas by hand is severely limited because it is both time and labor intensive and requires a significant amount of domain knowledge, evolutionary algorithms can be used to search the design space and automatically find novel antenna designs that are more effective than would otherwise be developed. Here we present our work in using evolutionary algorithms to automatically design an X-band antenna for NASA's Space Technology 5 (ST5) spacecraft. Two evolutionary algorithms were used: the first uses a vector of real-valued parameters and the second uses a tree-structured generative representation for constructing the antenna. The highest-performance antennas from both algorithms were fabricated and tested and both outperformed a hand-designed antenna produced by the antenna contractor for the mission. Subsequent changes to the spacecraft orbit resulted in a change in requirements for the spacecraft antenna. By adjusting our fitness function we were able to rapidly evolve a new set of antennas for this mission in less than a month. One of these new antenna designs was built, tested, and approved for deployment on the three ST5 spacecraft, which were successfully launched into space on March 22, 2006. This evolved antenna design is the first computer-evolved antenna to be deployed for any application and is the first computer-evolved hardware in space.

Criticality in finite dynamical networks

NASA Astrophysics Data System (ADS)

Rohlf, Thimo; Gulbahce, Natali; Teuscher, Christof

2007-03-01

It has been shown analytically and experimentally that both random boolean and random threshold networks show a transition from ordered to chaotic dynamics at a critical average connectivity Kc in the thermodynamical limit [1]. By looking at the statistical distributions of damage spreading (damage sizes), we go beyond this extensively studied mean-field approximation. We study the scaling properties of damage size distributions as a function of system size N and initial perturbation size d(t=0). We present numerical evidence that another characteristic point, Kd exists for finite system sizes, where the expectation value of damage spreading in the network is independent of the system size N. Further, the probability to obtain critical networks is investigated for a given system size and average connectivity k. Our results suggest that, for finite size dynamical networks, phase space structure is very complex and may not exhibit a sharp order-disorder transition. Finally, we discuss the implications of our findings for evolutionary processes and learning applied to networks which solve specific computational tasks. [1] Derrida, B. and Pomeau, Y. (1986), Europhys. Lett., 1, 45-49

Statistical Physics of Population Genetics in the Low Population Size Limit

NASA Astrophysics Data System (ADS)

Atwal, Gurinder

The understanding of evolutionary processes lends itself naturally to theory and computation, and the entire field of population genetics has benefited greatly from the influx of methods from applied mathematics for decades. However, in spite of all this effort, there are a number of key dynamical models of evolution that have resisted analytical treatment. In addition, modern DNA sequencing technologies have magnified the amount of genetic data available, revealing an excess of rare genetic variants in human genomes, challenging the predictions of conventional theory. Here I will show that methods from statistical physics can be used to model the distribution of genetic variants, incorporating selection and spatial degrees of freedom. In particular, a functional path-integral formulation of the Wright-Fisher process maps exactly to the dynamics of a particle in an effective potential, beyond the mean field approximation. In the small population size limit, the dynamics are dominated by instanton-like solutions which determine the probability of fixation in short timescales. These results are directly relevant for understanding the unusual genetic variant distribution at moving frontiers of populations.

Improving Search Properties in Genetic Programming

NASA Technical Reports Server (NTRS)

Janikow, Cezary Z.; DeWeese, Scott

1997-01-01

With the advancing computer processing capabilities, practical computer applications are mostly limited by the amount of human programming required to accomplish a specific task. This necessary human participation creates many problems, such as dramatically increased cost. To alleviate the problem, computers must become more autonomous. In other words, computers must be capable to program/reprogram themselves to adapt to changing environments/tasks/demands/domains. Evolutionary computation offers potential means, but it must be advanced beyond its current practical limitations. Evolutionary algorithms model nature. They maintain a population of structures representing potential solutions to the problem at hand. These structures undergo a simulated evolution by means of mutation, crossover, and a Darwinian selective pressure. Genetic programming (GP) is the most promising example of an evolutionary algorithm. In GP, the structures that evolve are trees, which is a dramatic departure from previously used representations such as strings in genetic algorithms. The space of potential trees is defined by means of their elements: functions, which label internal nodes, and terminals, which label leaves. By attaching semantic interpretation to those elements, trees can be interpreted as computer programs (given an interpreter), evolved architectures, etc. JSC has begun exploring GP as a potential tool for its long-term project on evolving dextrous robotic capabilities. Last year we identified representation redundancies as the primary source of inefficiency in GP. Subsequently, we proposed a method to use problem constraints to reduce those redundancies, effectively reducing GP complexity. This method was implemented afterwards at the University of Missouri. This summer, we have evaluated the payoff from using problem constraints to reduce search complexity on two classes of problems: learning boolean functions and solving the forward kinematics problem. We have also developed and implemented methods to use additional problem heuristics to fine-tune the searchable space, and to use typing information to further reduce the search space. Additional improvements have been proposed, but they are yet to be explored and implemented.

Elements of decisional dynamics: An agent-based approach applied to artificial financial market

NASA Astrophysics Data System (ADS)

Lucas, Iris; Cotsaftis, Michel; Bertelle, Cyrille

2018-02-01

This paper introduces an original mathematical description for describing agents' decision-making process in the case of problems affected by both individual and collective behaviors in systems characterized by nonlinear, path dependent, and self-organizing interactions. An application to artificial financial markets is proposed by designing a multi-agent system based on the proposed formalization. In this application, agents' decision-making process is based on fuzzy logic rules and the price dynamics is purely deterministic according to the basic matching rules of a central order book. Finally, while putting most parameters under evolutionary control, the computational agent-based system is able to replicate several stylized facts of financial time series (distributions of stock returns showing a heavy tail with positive excess kurtosis, absence of autocorrelations in stock returns, and volatility clustering phenomenon).

Elements of decisional dynamics: An agent-based approach applied to artificial financial market.

PubMed

Lucas, Iris; Cotsaftis, Michel; Bertelle, Cyrille

2018-02-01

This paper introduces an original mathematical description for describing agents' decision-making process in the case of problems affected by both individual and collective behaviors in systems characterized by nonlinear, path dependent, and self-organizing interactions. An application to artificial financial markets is proposed by designing a multi-agent system based on the proposed formalization. In this application, agents' decision-making process is based on fuzzy logic rules and the price dynamics is purely deterministic according to the basic matching rules of a central order book. Finally, while putting most parameters under evolutionary control, the computational agent-based system is able to replicate several stylized facts of financial time series (distributions of stock returns showing a heavy tail with positive excess kurtosis, absence of autocorrelations in stock returns, and volatility clustering phenomenon).

Evolutionary squeaky wheel optimization: a new framework for analysis.

PubMed

Li, Jingpeng; Parkes, Andrew J; Burke, Edmund K

2011-01-01

Squeaky wheel optimization (SWO) is a relatively new metaheuristic that has been shown to be effective for many real-world problems. At each iteration SWO does a complete construction of a solution starting from the empty assignment. Although the construction uses information from previous iterations, the complete rebuilding does mean that SWO is generally effective at diversification but can suffer from a relatively weak intensification. Evolutionary SWO (ESWO) is a recent extension to SWO that is designed to improve the intensification by keeping the good components of solutions and only using SWO to reconstruct other poorer components of the solution. In such algorithms a standard challenge is to understand how the various parameters affect the search process. In order to support the future study of such issues, we propose a formal framework for the analysis of ESWO. The framework is based on Markov chains, and the main novelty arises because ESWO moves through the space of partial assignments. This makes it significantly different from the analyses used in local search (such as simulated annealing) which only move through complete assignments. Generally, the exact details of ESWO will depend on various heuristics; so we focus our approach on a case of ESWO that we call ESWO-II and that has probabilistic as opposed to heuristic selection and construction operators. For ESWO-II, we study a simple problem instance and explicitly compute the stationary distribution probability over the states of the search space. We find interesting properties of the distribution. In particular, we find that the probabilities of states generally, but not always, increase with their fitness. This nonmonotonocity is quite different from the monotonicity expected in algorithms such as simulated annealing.

Properties of Starless Clumps through Protoclusters from the Bolocam Galactic Plane Survey

NASA Astrophysics Data System (ADS)

Svoboda, Brian E.; Shirley, Yancy

2014-07-01

High mass stars play a key role in the physical and chemical evolution of the interstellar medium, yet the evolution of physical properties for high-mass star-forming regions remains unclear. We sort a sample of ~4668 molecular cloud clumps from the Bolocam Galactic Plane Survey (BGPS) into different evolutionary stages by combining the BGPS 1.1 mm continuum and observational diagnostics of star-formation activity from a variety of Galactic plane surveys: 70 um compact sources, mid-IR color-selected YSOs, H2O and CH3OH masers, EGOs, and UCHII regions. We apply Monte Carlo techniques to distance probability distribution functions (DPDFs) in order to marginalize over the kinematic distance ambiguity and calculate distributions for derived quantities of clumps in different evolutionary stages. We also present a combined NH3 and H2O maser catalog for ~1590 clumps from the literature and our own GBT 100m observations. We identify a sub-sample of 440 dense clumps with no star-formation indicators, representing the largest and most robust sample of pre-protocluster candidates from a blind survey to date. Distributions of I(HCO+), I(N2H+), dv(HCO+), dv(N2H+), mass surface density, and kinetic temperature show strong progressions when separated by evolutionary stage. No progressions are found in size or dust mass; however, weak progressions are observed in area > 2 pc^2 and dust mass > 3 10^3 Msun. An observed breakdown occurs in the size-linewidth relationship and we find no improvement when sampling by evolutionary stage.

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.

Evolutionary transitions in symbioses: dramatic reductions in bathymetric and geographic ranges of Zoanthidea coincide with loss of symbioses with invertebrates.

PubMed

Swain, Timothy D

2010-06-01

Two fundamental symbiosis-based trophic types are recognized among Zoanthidea (Cnidaria, Anthozoa): fixed carbon is either obtained directly from zooxanthellae photosymbionts or from environmental sources through feeding with the assistance of host-invertebrate behaviour and structure. Each trophic type is characteristic of the suborders of Zoanthidea and is associated with substantial distributional asymmetries: suborder Macrocnemina are symbionts of invertebrates and have global geographic and bathymetric distributions and suborder Brachycnemina are hosts of endosymbiotic zooxanthellae and are restricted to tropical photic zones. While exposure to solar radiation could explain the bathymetric asymmetry it does not explain the geographic asymmetry, nor is it clear why evolutionary transitions to the zooxanthellae-free state have apparently occurred within Macrocnemina but not within Brachycnemina. To better understand the transitions between symbiosis-based trophic types of Zoanthidea, a concatenated data set of nuclear and mitochondrial nucleotide sequences were used to test hypotheses of monophyly for groups defined by morphology and symbiosis, and to reconstruct the evolutionary transitions of morphological and symbiotic characters. The results indicate that the morphological characters that define Macrocnemina are plesiomorphic and the characters that define its subordinate taxa are homoplasious. Symbioses with invertebrates have ancient and recent transitions with a general pattern of stability in host associations through evolutionary time. The reduction in distribution of Zoanthidea is independent of the evolution of zooxanthellae symbiosis and consistent with hypotheses of the benefits of invertebrate symbioses, indicating that the ability to persist in most habitats may have been lost with the termination of symbioses with invertebrates.

Genes mirror geography in Daphnia magna.

PubMed

Fields, Peter D; Reisser, Céline; Dukić, Marinela; Haag, Christoph R; Ebert, Dieter

2015-09-01

Identifying the presence and magnitude of population genetic structure remains a major consideration in evolutionary biology as doing so allows one to understand the demographic history of a species as well as make predictions of how the evolutionary process will proceed. Next-generation sequencing methods allow us to reconsider previous ideas and conclusions concerning the distribution of genetic variation, and what this distribution implies about a given species evolutionary history. A previous phylogeographic study of the crustacean Daphnia magna suggested that, despite strong genetic differentiation among populations at a local scale, the species shows only moderate genetic structure across its European range, with a spatially patchy occurrence of individual lineages. We apply RAD sequencing to a sample of D. magna collected across a wide swath of the species' Eurasian range and analyse the data using principle component analysis (PCA) of genetic variation and Procrustes analytical approaches, to quantify spatial genetic structure. We find remarkable consistency between the first two PCA axes and the geographic coordinates of individual sampling points, suggesting that, on a continent-wide scale, genetic differentiation is driven to a large extent by geographic distance. The observed pattern is consistent with unimpeded (i.e. no barriers, landscape or otherwise) migration at large spatial scales, despite the fragmented and patchy nature of favourable habitats at local scales. With high-resolution genetic data similar patterns may be uncovered for other species with wide geographic distributions, allowing an increased understanding of how genetic drift and selection have shaped their evolutionary history. © 2015 John Wiley & Sons Ltd.

Life on the rocks: Multilocus phylogeography of rock hyrax (Procavia capensis) from southern Africa.

PubMed

Maswanganye, K Amanda; Cunningham, Michael J; Bennett, Nigel C; Chimimba, Christian T; Bloomer, Paulette

2017-09-01

Understanding the role of geography and climatic cycles in determining patterns of biodiversity is important in comparative and evolutionary biology and conservation. We studied the phylogeographic pattern and historical demography of a rock-dwelling small mammal species from southern Africa, the rock hyrax Procavia capensis capensis. Using a multilocus coalescent approach, we assessed the influence of strong habitat dependence and fluctuating regional climates on genetic diversity. We sequenced a mitochondrial gene (cytochrome b) and two nuclear introns (AP5, PRKC1) supplemented with microsatellite genotyping, in order to assess evolutionary processes over multiple temporal scales. In addition, distribution modelling was used to investigate the current and predicted distribution of the species under different climatic scenarios. Collectively, the data reveal a complex history of isolation followed by secondary contact shaping the current intraspecific diversity. The cyt b sequences confirmed the presence of two previously proposed geographically and genetically distinct lineages distributed across the southern African Great Escarpment and north-western mountain ranges. Molecular dating suggests Miocene divergence of the lineages, yet there are no discernible extrinsic barriers to gene flow. The nuclear markers reveal incomplete lineage sorting or ongoing mixing of the two lineages. Although the microsatellite data lend some support to the presence of two subpopulations, there is weak structuring within and between lineages. These data indicate the presence of gene flow from the northern into the southern parts of the southern African sub-region likely following the secondary contact. The distribution modelling predictably reveal the species' preference for rocky areas, with stable refugia through time in the northern mountain ranges, the Great Escarpment, as well as restricted areas of the Northern Cape Province and the Cape Fold Mountains of South Africa. Different microclimatic variables appear to determine the distributional range of the species. Despite strong habitat preference, the micro-habitat offered by rocky crevices and unique life history traits likely promoted the adaptability of P. capensis, resulting in the widespread distribution and persistence of the species over a long evolutionary period. Spatio-temporal comparison of the evolutionary histories of other co-distributed species across the rocky landscapes of southern Africa will improve our understanding of the regional patterns of biodiversity and local endemism. Copyright © 2017 Elsevier Inc. All rights reserved.

Trends in the sand: Directional evolution in the shell shape of recessing scallops (Bivalvia: Pectinidae).

PubMed

Sherratt, Emma; Alejandrino, Alvin; Kraemer, Andrew C; Serb, Jeanne M; Adams, Dean C

2016-09-01

Directional evolution is one of the most compelling evolutionary patterns observed in macroevolution. Yet, despite its importance, detecting such trends in multivariate data remains a challenge. In this study, we evaluate multivariate evolution of shell shape in 93 bivalved scallop species, combining geometric morphometrics and phylogenetic comparative methods. Phylomorphospace visualization described the history of morphological diversification in the group; revealing that taxa with a recessing life habit were the most distinctive in shell shape, and appeared to display a directional trend. To evaluate this hypothesis empirically, we extended existing methods by characterizing the mean directional evolution in phylomorphospace for recessing scallops. We then compared this pattern to what was expected under several alternative evolutionary scenarios using phylogenetic simulations. The observed pattern did not fall within the distribution obtained under multivariate Brownian motion, enabling us to reject this evolutionary scenario. By contrast, the observed pattern was more similar to, and fell within, the distribution obtained from simulations using Brownian motion combined with a directional trend. Thus, the observed data are consistent with a pattern of directional evolution for this lineage of recessing scallops. We discuss this putative directional evolutionary trend in terms of its potential adaptive role in exploiting novel habitats. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Joint scaling laws in functional and evolutionary categories in prokaryotic genomes

PubMed Central

Grilli, J.; Bassetti, B.; Maslov, S.; Cosentino Lagomarsino, M.

2012-01-01

We propose and study a class-expansion/innovation/loss model of genome evolution taking into account biological roles of genes and their constituent domains. In our model, numbers of genes in different functional categories are coupled to each other. For example, an increase in the number of metabolic enzymes in a genome is usually accompanied by addition of new transcription factors regulating these enzymes. Such coupling can be thought of as a proportional ‘recipe’ for genome composition of the type ‘a spoonful of sugar for each egg yolk’. The model jointly reproduces two known empirical laws: the distribution of family sizes and the non-linear scaling of the number of genes in certain functional categories (e.g. transcription factors) with genome size. In addition, it allows us to derive a novel relation between the exponents characterizing these two scaling laws, establishing a direct quantitative connection between evolutionary and functional categories. It predicts that functional categories that grow faster-than-linearly with genome size to be characterized by flatter-than-average family size distributions. This relation is confirmed by our bioinformatics analysis of prokaryotic genomes. This proves that the joint quantitative trends of functional and evolutionary classes can be understood in terms of evolutionary growth with proportional recipes. PMID:21937509

Robust electromagnetically guided endoscopic procedure using enhanced particle swarm optimization for multimodal information fusion

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

Luo, Xiongbiao, E-mail: xluo@robarts.ca, E-mail: Ying.Wan@student.uts.edu.au; Wan, Ying, E-mail: xluo@robarts.ca, E-mail: Ying.Wan@student.uts.edu.au; He, Xiangjian

Purpose: Electromagnetically guided endoscopic procedure, which aims at accurately and robustly localizing the endoscope, involves multimodal sensory information during interventions. However, it still remains challenging in how to integrate these information for precise and stable endoscopic guidance. To tackle such a challenge, this paper proposes a new framework on the basis of an enhanced particle swarm optimization method to effectively fuse these information for accurate and continuous endoscope localization. Methods: The authors use the particle swarm optimization method, which is one of stochastic evolutionary computation algorithms, to effectively fuse the multimodal information including preoperative information (i.e., computed tomography images) asmore » a frame of reference, endoscopic camera videos, and positional sensor measurements (i.e., electromagnetic sensor outputs). Since the evolutionary computation method usually limits its possible premature convergence and evolutionary factors, the authors introduce the current (endoscopic camera and electromagnetic sensor’s) observation to boost the particle swarm optimization and also adaptively update evolutionary parameters in accordance with spatial constraints and the current observation, resulting in advantageous performance in the enhanced algorithm. Results: The experimental results demonstrate that the authors’ proposed method provides a more accurate and robust endoscopic guidance framework than state-of-the-art methods. The average guidance accuracy of the authors’ framework was about 3.0 mm and 5.6° while the previous methods show at least 3.9 mm and 7.0°. The average position and orientation smoothness of their method was 1.0 mm and 1.6°, which is significantly better than the other methods at least with (2.0 mm and 2.6°). Additionally, the average visual quality of the endoscopic guidance was improved to 0.29. Conclusions: A robust electromagnetically guided endoscopy framework was proposed on the basis of an enhanced particle swarm optimization method with using the current observation information and adaptive evolutionary factors. The authors proposed framework greatly reduced the guidance errors from (4.3, 7.8) to (3.0 mm, 5.6°), compared to state-of-the-art methods.« less

New Genetics

MedlinePlus

... Century-Old Evolutionary Puzzle Computing Genetics Model Organisms RNA Interference The New Genetics is a science education ... the basics of DNA and its molecular cousin RNA, and new directions in genetic research. The New ...

Molecular evolutionary rates are not correlated with temperature and latitude in Squamata: an exception to the metabolic theory of ecology?

PubMed

Rolland, Jonathan; Loiseau, Oriane; Romiguier, Jonathan; Salamin, Nicolas

2016-05-20

The metabolic theory of ecology stipulates that molecular evolutionary rates should correlate with temperature and latitude in ectothermic organisms. Previous studies have shown that most groups of vertebrates, such as amphibians, turtles and even endothermic mammals, have higher molecular evolutionary rates in regions where temperature is high. However, the association between molecular evolutionary rates and temperature or latitude has never been tested in Squamata. We used a large dataset including the spatial distributions and environmental variables for 1,651 species of Squamata and compared the contrast of the rates of molecular evolution with the contrast of temperature and latitude between sister species. Using major axis regressions and a new algorithm to choose independent sister species pairs, we found that temperature and absolute latitude were not associated with molecular evolutionary rates. This absence of association in such a diverse ectothermic group questions the mechanisms explaining current pattern of species diversity in Squamata and challenges the presupposed universality of the metabolic theory of ecology.

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.

An Evolutionary Examination of Telemedicine: A Health and Computer-Mediated Communication Perspective

PubMed Central

Breen, Gerald-Mark; Matusitz, Jonathan

2009-01-01

Telemedicine, the use of advanced communication technologies in the healthcare context, has a rich history and a clear evolutionary course. In this paper, the authors identify telemedicine as operationally defined, the services and technologies it comprises, the direction telemedicine has taken, along with its increased acceptance in the healthcare communities. The authors also describe some of the key pitfalls warred with by researchers and activists to advance telemedicine to its full potential and lead to an unobstructed team of technicians to identify telemedicine’s diverse utilities. A discussion and future directions section is included to provide fresh ideas to health communication and computer-mediated scholars wishing to delve into this area and make a difference to enhance public understanding of this field. PMID:20300559

The Chomsky—Place correspondence 1993–1994

PubMed Central

Chomsky, Noam; Place, Ullin T.

2000-01-01

Edited correspondence between Ullin T. Place and Noam Chomsky, which occurred in 1993–1994, is presented. The principal topics are (a) deep versus surface structure; (b) computer modeling of the brain; (c) the evolutionary origins of language; (d) behaviorism; and (e) a dispositional account of language. This correspondence includes Chomsky's denial that he ever characterized deep structure as innate; Chomsky's critique of computer modeling (both traditional and connectionist) of the brain; Place's critique of Chomsky's alleged failure to provide an adequate account of the evolutionary origins of language, and Chomsky's response that such accounts are “pop-Darwinian fairy tales”; and Place's arguments for, and Chomsky's against, the relevance of behaviorism to linguistic theory, especially the relevance of a behavioral approach to language that is buttressed by a dispositional account of sentence construction. PMID:22477211

The Chomsky-Place correspondence 1993-1994.

PubMed

Chomsky, N; Place, U T

2000-01-01

Edited correspondence between Ullin T. Place and Noam Chomsky, which occurred in 1993-1994, is presented. The principal topics are (a) deep versus surface structure; (b) computer modeling of the brain; (c) the evolutionary origins of language; (d) behaviorism; and (e) a dispositional account of language. This correspondence includes Chomsky's denial that he ever characterized deep structure as innate; Chomsky's critique of computer modeling (both traditional and connectionist) of the brain; Place's critique of Chomsky's alleged failure to provide an adequate account of the evolutionary origins of language, and Chomsky's response that such accounts are "pop-Darwinian fairy tales"; and Place's arguments for, and Chomsky's against, the relevance of behaviorism to linguistic theory, especially the relevance of a behavioral approach to language that is buttressed by a dispositional account of sentence construction.

The development of the red giant branch. I - Theoretical evolutionary sequences

NASA Technical Reports Server (NTRS)

Sweigart, Allen V.; Greggio, Laura; Renzini, Alvio

1989-01-01

A grid of 100 evolutionary sequences extending from the zero-age main sequence to the onset of helium burning has been computed for stellar masses between 1.4 and 3.4 solar masses, helium abundances of 0.20 and 0.30, and heavy-element abundances of 0.004, 0.01, and 0.04. Using these computations the transition in the morphology of the red giant branch (RGB) between low-mass stars, which have an extended and luminous first RGB phase prior to helium ignition, and intermediate-mass stars, which do not, is investigated. Extensive tabulations of the numerical results are provided to aid in applying these sequences. The effects of the first dredge-up on the surface helium and CNO abundances of the sequences is discussed.

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.

Development of an Evolutionary Algorithm for the ab Initio Discovery of Two-Dimensional Materials

NASA Astrophysics Data System (ADS)

Revard, Benjamin Charles

Crystal structure prediction is an important first step on the path toward computational materials design. Increasingly robust methods have become available in recent years for computing many materials properties, but because properties are largely a function of crystal structure, the structure must be known before these methods can be brought to bear. In addition, structure prediction is particularly useful for identifying low-energy structures of subperiodic materials, such as two-dimensional (2D) materials, which may adopt unexpected structures that differ from those of the corresponding bulk phases. Evolutionary algorithms, which are heuristics for global optimization inspired by biological evolution, have proven to be a fruitful approach for tackling the problem of crystal structure prediction. This thesis describes the development of an improved evolutionary algorithm for structure prediction and several applications of the algorithm to predict the structures of novel low-energy 2D materials. The first part of this thesis contains an overview of evolutionary algorithms for crystal structure prediction and presents our implementation, including details of extending the algorithm to search for clusters, wires, and 2D materials, improvements to efficiency when running in parallel, improved composition space sampling, and the ability to search for partial phase diagrams. We then present several applications of the evolutionary algorithm to 2D systems, including InP, the C-Si and Sn-S phase diagrams, and several group-IV dioxides. This thesis makes use of the Cornell graduate school's "papers" option. Chapters 1 and 3 correspond to the first-author publications of Refs. [131] and [132], respectively, and chapter 2 will soon be submitted as a first-author publication. The material in chapter 4 is taken from Ref. [144], in which I share joint first-authorship. In this case I have included only my own contributions.

Upon Accounting for the Impact of Isoenzyme Loss, Gene Deletion Costs Anticorrelate with Their Evolutionary Rates.

PubMed

Jacobs, Christopher; Lambourne, Luke; Xia, Yu; Segrè, Daniel

2017-01-01

System-level metabolic network models enable the computation of growth and metabolic phenotypes from an organism's genome. In particular, flux balance approaches have been used to estimate the contribution of individual metabolic genes to organismal fitness, offering the opportunity to test whether such contributions carry information about the evolutionary pressure on the corresponding genes. Previous failure to identify the expected negative correlation between such computed gene-loss cost and sequence-derived evolutionary rates in Saccharomyces cerevisiae has been ascribed to a real biological gap between a gene's fitness contribution to an organism "here and now" and the same gene's historical importance as evidenced by its accumulated mutations over millions of years of evolution. Here we show that this negative correlation does exist, and can be exposed by revisiting a broadly employed assumption of flux balance models. In particular, we introduce a new metric that we call "function-loss cost", which estimates the cost of a gene loss event as the total potential functional impairment caused by that loss. This new metric displays significant negative correlation with evolutionary rate, across several thousand minimal environments. We demonstrate that the improvement gained using function-loss cost over gene-loss cost is explained by replacing the base assumption that isoenzymes provide unlimited capacity for backup with the assumption that isoenzymes are completely non-redundant. We further show that this change of the assumption regarding isoenzymes increases the recall of epistatic interactions predicted by the flux balance model at the cost of a reduction in the precision of the predictions. In addition to suggesting that the gene-to-reaction mapping in genome-scale flux balance models should be used with caution, our analysis provides new evidence that evolutionary gene importance captures much more than strict essentiality.

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.

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.

On the interconnection of stable protein complexes: inter-complex hubs and their conservation in Saccharomyces cerevisiae and Homo sapiens networks.

PubMed

Guerra, Concettina

2015-01-01

Protein complexes are key molecular entities that perform a variety of essential cellular functions. The connectivity of proteins within a complex has been widely investigated with both experimental and computational techniques. We developed a computational approach to identify and characterise proteins that play a role in interconnecting complexes. We computed a measure of inter-complex centrality, the crossroad index, based on disjoint paths connecting proteins in distinct complexes and identified inter-complex hubs as proteins with a high value of the crossroad index. We applied the approach to a set of stable complexes in Saccharomyces cerevisiae and in Homo sapiens. Just as done for hubs, we evaluated the topological and biological properties of inter-complex hubs addressing the following questions. Do inter-complex hubs tend to be evolutionary conserved? What is the relation between crossroad index and essentiality? We found a good correlation between inter-complex hubs and both evolutionary conservation and essentiality.

The Role of "Open" in Strategic Library Planning

ERIC Educational Resources Information Center

Petrides, Lisa; Goger, Letha; Jimes, Cynthia

2016-01-01

Academic libraries are undergoing evolutionary change as emerging technologies and new philosophies about how information is created, distributed, and shared have disrupted traditional operations and services. Additionally, the population that the academic library serves is increasingly distributed due to distance learning opportunities and new…

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.

Rapid, Value-based, Evolutionary Acquisition and Its Application to a USMC Tactical Service Oriented Architecture

DTIC Science & Technology

2009-06-01

Availability C2PC Command and Control Personal Computer CAS Close Air Support CCA Clinger-Cohen Act CDR Critical Design Review CJCSI Chairman of the Joint... kids , Jackie and Anna and my future boy whose name is TBD, I think my time at NPS has made me a better person and hopefully a better father. Thank... can the USMC apply the essential principles of rapid, value-based, evolutionary acquisition to the development and procurement of a TSOA? 4 THIS

Laboratory evolution of protein conformational dynamics.

PubMed

Campbell, Eleanor C; Correy, Galen J; Mabbitt, Peter D; Buckle, Ashley M; Tokuriki, Nobuhiko; Jackson, Colin J

2017-11-08

This review focuses on recent work that has begun to establish specific functional roles for protein conformational dynamics, specifically how the conformational landscapes that proteins can sample can evolve under laboratory based evolutionary selection. We discuss recent technical advances in computational and biophysical chemistry, which have provided us with new ways to dissect evolutionary processes. Finally, we offer some perspectives on the emerging view of conformational dynamics and evolution, and the challenges that we face in rationally engineering conformational dynamics. Copyright © 2017 Elsevier Ltd. All rights reserved.

Aminoacyl-tRNA Synthetases, the Genetic Code, and the Evolutionary Process

PubMed Central

Woese, Carl R.; Olsen, Gary J.; Ibba, Michael; Söll, Dieter

2000-01-01

The aminoacyl-tRNA synthetases (AARSs) and their relationship to the genetic code are examined from the evolutionary perspective. Despite a loose correlation between codon assignments and AARS evolutionary relationships, the code is far too highly structured to have been ordered merely through the evolutionary wanderings of these enzymes. Nevertheless, the AARSs are very informative about the evolutionary process. Examination of the phylogenetic trees for each of the AARSs reveals the following. (i) Their evolutionary relationships mostly conform to established organismal phylogeny: a strong distinction exists between bacterial- and archaeal-type AARSs. (ii) Although the evolutionary profiles of the individual AARSs might be expected to be similar in general respects, they are not. It is argued that these differences in profiles reflect the stages in the evolutionary process when the taxonomic distributions of the individual AARSs became fixed, not the nature of the individual enzymes. (iii) Horizontal transfer of AARS genes between Bacteria and Archaea is asymmetric: transfer of archaeal AARSs to the Bacteria is more prevalent than the reverse, which is seen only for the “gemini group.” (iv) The most far-ranging transfers of AARS genes have tended to occur in the distant evolutionary past, before or during formation of the primary organismal domains. These findings are also used to refine the theory that at the evolutionary stage represented by the root of the universal phylogenetic tree, cells were far more primitive than their modern counterparts and thus exchanged genetic material in far less restricted ways, in effect evolving in a communal sense. PMID:10704480

Human vs. Computer Diagnosis of Students' Natural Selection Knowledge: Testing the Efficacy of Text Analytic Software

ERIC Educational Resources Information Center

Nehm, Ross H.; Haertig, Hendrik

2012-01-01

Our study examines the efficacy of Computer Assisted Scoring (CAS) of open-response text relative to expert human scoring within the complex domain of evolutionary biology. Specifically, we explored whether CAS can diagnose the explanatory elements (or Key Concepts) that comprise undergraduate students' explanatory models of natural selection with…

Modeling evolution of spatially distributed bacterial communities: a simulation with the haploid evolutionary constructor

PubMed Central

2015-01-01

Background Multiscale approaches for integrating submodels of various levels of biological organization into a single model became the major tool of systems biology. In this paper, we have constructed and simulated a set of multiscale models of spatially distributed microbial communities and study an influence of unevenly distributed environmental factors on the genetic diversity and evolution of the community members. Results Haploid Evolutionary Constructor software http://evol-constructor.bionet.nsc.ru/ was expanded by adding the tool for the spatial modeling of a microbial community (1D, 2D and 3D versions). A set of the models of spatially distributed communities was built to demonstrate that the spatial distribution of cells affects both intensity of selection and evolution rate. Conclusion In spatially heterogeneous communities, the change in the direction of the environmental flow might be reflected in local irregular population dynamics, while the genetic structure of populations (frequencies of the alleles) remains stable. Furthermore, in spatially heterogeneous communities, the chemotaxis might dramatically affect the evolution of community members. PMID:25708911

An IUR evolutionary game model on the patent cooperate of Shandong China

NASA Astrophysics Data System (ADS)

Liu, Mengmeng; Ma, Yinghong; Liu, Zhiyuan; You, Xuemei

2017-06-01

Organizations of industries and university & research institutes cooperate to meet their respective needs based on social contacts, trust and share complementary resources. From the perspective of complex network together with the patent data of Shandong province in China, a novel evolutionary game model on patent cooperation network is presented. Two sides in the game model are industries and universities & research institutes respectively. The cooperation is represented by a connection when a new patent is developed together by the two sides. The optimal strategy of the evolutionary game model is quantified by the average positive cooperation probability p ¯ and the average payoff U ¯ . The feasibility of this game model is simulated on the parameters such as the knowledge spillover, the punishment, the development cost and the distribution coefficient of the benefit. The numerical simulations show that the cooperative behaviors are affected by the variation of parameters. The knowledge spillover displays different behaviors when the punishment is larger than the development cost or less than it. Those results indicate that reasonable punishment would improve the positive cooperation. The appropriate punishment will be useful to enhance the big degree nodes positively cooperate with industries and universities & research institutes. And an equitable plan for the distribution of cooperative profits is half-and-half distribution strategy for the two sides in game.

Human genomic disease variants: a neutral evolutionary explanation.

PubMed

Dudley, Joel T; Kim, Yuseob; Liu, Li; Markov, Glenn J; Gerold, Kristyn; Chen, Rong; Butte, Atul J; Kumar, Sudhir

2012-08-01

Many perspectives on the role of evolution in human health include nonempirical assumptions concerning the adaptive evolutionary origins of human diseases. Evolutionary analyses of the increasing wealth of clinical and population genomic data have begun to challenge these presumptions. In order to systematically evaluate such claims, the time has come to build a common framework for an empirical and intellectual unification of evolution and modern medicine. We review the emerging evidence and provide a supporting conceptual framework that establishes the classical neutral theory of molecular evolution (NTME) as the basis for evaluating disease- associated genomic variations in health and medicine. For over a decade, the NTME has already explained the origins and distribution of variants implicated in diseases and has illuminated the power of evolutionary thinking in genomic medicine. We suggest that a majority of disease variants in modern populations will have neutral evolutionary origins (previously neutral), with a relatively smaller fraction exhibiting adaptive evolutionary origins (previously adaptive). This pattern is expected to hold true for common as well as rare disease variants. Ultimately, a neutral evolutionary perspective will provide medicine with an informative and actionable framework that enables objective clinical assessment beyond convenient tendencies to invoke past adaptive events in human history as a root cause of human disease.

Human genomic disease variants: A neutral evolutionary explanation

PubMed Central

Dudley, Joel T.; Kim, Yuseob; Liu, Li; Markov, Glenn J.; Gerold, Kristyn; Chen, Rong; Butte, Atul J.; Kumar, Sudhir

2012-01-01

Many perspectives on the role of evolution in human health include nonempirical assumptions concerning the adaptive evolutionary origins of human diseases. Evolutionary analyses of the increasing wealth of clinical and population genomic data have begun to challenge these presumptions. In order to systematically evaluate such claims, the time has come to build a common framework for an empirical and intellectual unification of evolution and modern medicine. We review the emerging evidence and provide a supporting conceptual framework that establishes the classical neutral theory of molecular evolution (NTME) as the basis for evaluating disease- associated genomic variations in health and medicine. For over a decade, the NTME has already explained the origins and distribution of variants implicated in diseases and has illuminated the power of evolutionary thinking in genomic medicine. We suggest that a majority of disease variants in modern populations will have neutral evolutionary origins (previously neutral), with a relatively smaller fraction exhibiting adaptive evolutionary origins (previously adaptive). This pattern is expected to hold true for common as well as rare disease variants. Ultimately, a neutral evolutionary perspective will provide medicine with an informative and actionable framework that enables objective clinical assessment beyond convenient tendencies to invoke past adaptive events in human history as a root cause of human disease. PMID:22665443

Phylogenetic analyses suggest that diversification and body size evolution are independent in insects.

PubMed

Rainford, James L; Hofreiter, Michael; Mayhew, Peter J

2016-01-08

Skewed body size distributions and the high relative richness of small-bodied taxa are a fundamental property of a wide range of animal clades. The evolutionary processes responsible for generating these distributions are well described in vertebrate model systems but have yet to be explored in detail for other major terrestrial clades. In this study, we explore the macro-evolutionary patterns of body size variation across families of Hexapoda (insects and their close relatives), using recent advances in phylogenetic understanding, with an aim to investigate the link between size and diversity within this ancient and highly diverse lineage. The maximum, minimum and mean-log body lengths of hexapod families are all approximately log-normally distributed, consistent with previous studies at lower taxonomic levels, and contrasting with skewed distributions typical of vertebrate groups. After taking phylogeny and within-tip variation into account, we find no evidence for a negative relationship between diversification rate and body size, suggesting decoupling of the forces controlling these two traits. Likelihood-based modeling of the log-mean body size identifies distinct processes operating within Holometabola and Diptera compared with other hexapod groups, consistent with accelerating rates of size evolution within these clades, while as a whole, hexapod body size evolution is found to be dominated by neutral processes including significant phylogenetic conservatism. Based on our findings we suggest that the use of models derived from well-studied but atypical clades, such as vertebrates may lead to misleading conclusions when applied to other major terrestrial lineages. Our results indicate that within hexapods, and within the limits of current systematic and phylogenetic knowledge, insect diversification is generally unfettered by size-biased macro-evolutionary processes, and that these processes over large timescales tend to converge on apparently neutral evolutionary processes. We also identify limitations on available data within the clade and modeling approaches for the resolution of trees of higher taxa, the resolution of which may collectively enhance our understanding of this key component of terrestrial ecosystems.

Biogeography of photoautotrophs in the high polar biome

PubMed Central

Pointing, Stephen B.; Burkhard Büdel; Convey, Peter; Gillman, Len N.; Körner, Christian; Leuzinger, Sebastian; Vincent, Warwick F.

2015-01-01

The global latitudinal gradient in biodiversity weakens in the high polar biome and so an alternative explanation for distribution of Arctic and Antarctic photoautotrophs is required. Here we identify how temporal, microclimate and evolutionary drivers of biogeography are important, rather than the macroclimate features that drive plant diversity patterns elsewhere. High polar ecosystems are biologically unique, with a more central role for bryophytes, lichens and microbial photoautotrophs over that of vascular plants. Constraints on vascular plants arise mainly due to stature and ontogenetic barriers. Conversely non-vascular plant and microbial photoautotroph distribution is correlated with favorable microclimates and the capacity for poikilohydric dormancy. Contemporary distribution also depends on evolutionary history, with adaptive and dispersal traits as well as legacy influencing biogeography. We highlight the relevance of these findings to predicting future impacts on diversity of polar photoautotrophs and to the current status of plants in Arctic and Antarctic conservation policy frameworks. PMID:26442009

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.

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

Evolutionary Study of Interethnic Cooperation

NASA Astrophysics Data System (ADS)

Kvasnicka, Vladimir; Pospichal, Jiri

The purpose of this communication is to present an evolutionary study of cooperation between two ethnic groups. The used model is stimulated by the seminal paper of J. D. Fearon and D. D. Laitin (Explaining Interethnic Cooperation, American Political Science Review, 90 (1996), pp. 715-735), where the iterated prisoner's dilemma was used to model intra- and interethnic interactions. We reformulated their approach in a form of evolutionary prisoner's dilemma method, where a population of strategies is evolved by applying simple reproduction process with a Darwin metaphor of natural selection (a probability of selection to the reproduction is proportional to a fitness). Our computer simulations show that an application of a principle of collective guilt does not lead to an emergence of an interethnic cooperation. When an administrator is introduced, then an emergence of interethnic cooperation may be observed. Furthermore, if the ethnic groups are of very different sizes, then the principle of collective guilt may be very devastating for smaller group so that intraethnic cooperation is destroyed. The second strategy of cooperation is called the personal responsibility, where agents that defected within interethnic interactions are punished inside of their ethnic groups. It means, unlikely to the principle of collective guilt, that there exists only one type of punishment, loosely speaking, agents are punished "personally." All the substantial computational results were checked and interpreted analytically within the theory of evolutionary stable strategies. Moreover, this theoretical approach offers mechanisms of simple scenarios explaining why some particular strategies are stable or not.

Pareto-optimal phylogenetic tree reconciliation

PubMed Central

Libeskind-Hadas, Ran; Wu, Yi-Chieh; Bansal, Mukul S.; Kellis, Manolis

2014-01-01

Motivation: Phylogenetic tree reconciliation is a widely used method for reconstructing the evolutionary histories of gene families and species, hosts and parasites and other dependent pairs of entities. Reconciliation is typically performed using maximum parsimony, in which each evolutionary event type is assigned a cost and the objective is to find a reconciliation of minimum total cost. It is generally understood that reconciliations are sensitive to event costs, but little is understood about the relationship between event costs and solutions. Moreover, choosing appropriate event costs is a notoriously difficult problem. Results: We address this problem by giving an efficient algorithm for computing Pareto-optimal sets of reconciliations, thus providing the first systematic method for understanding the relationship between event costs and reconciliations. This, in turn, results in new techniques for computing event support values and, for cophylogenetic analyses, performing robust statistical tests. We provide new software tools and demonstrate their use on a number of datasets from evolutionary genomic and cophylogenetic studies. Availability and implementation: Our Python tools are freely available at www.cs.hmc.edu/∼hadas/xscape. Contact: mukul@engr.uconn.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24932009

Computational Evolutionary Methodology for Knowledge Discovery and Forecasting in Epidemiology and Medicine

NASA Astrophysics Data System (ADS)

Rao, Dhananjai M.; Chernyakhovsky, Alexander; Rao, Victoria

2008-05-01

Humanity is facing an increasing number of highly virulent and communicable diseases such as avian influenza. Researchers believe that avian influenza has potential to evolve into one of the deadliest pandemics. Combating these diseases requires in-depth knowledge of their epidemiology. An effective methodology for discovering epidemiological knowledge is to utilize a descriptive, evolutionary, ecological model and use bio-simulations to study and analyze it. These types of bio-simulations fall under the category of computational evolutionary methods because the individual entities participating in the simulation are permitted to evolve in a natural manner by reacting to changes in the simulated ecosystem. This work describes the application of the aforementioned methodology to discover epidemiological knowledge about avian influenza using a novel eco-modeling and bio-simulation environment called SEARUMS. The mathematical principles underlying SEARUMS, its design, and the procedure for using SEARUMS are discussed. The bio-simulations and multi-faceted case studies conducted using SEARUMS elucidate its ability to pinpoint timelines, epicenters, and socio-economic impacts of avian influenza. This knowledge is invaluable for proactive deployment of countermeasures in order to minimize negative socioeconomic impacts, combat the disease, and avert a pandemic.

Computational Evolutionary Methodology for Knowledge Discovery and Forecasting in Epidemiology and Medicine

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

Rao, Dhananjai M.; Chernyakhovsky, Alexander; Rao, Victoria

2008-05-08

Humanity is facing an increasing number of highly virulent and communicable diseases such as avian influenza. Researchers believe that avian influenza has potential to evolve into one of the deadliest pandemics. Combating these diseases requires in-depth knowledge of their epidemiology. An effective methodology for discovering epidemiological knowledge is to utilize a descriptive, evolutionary, ecological model and use bio-simulations to study and analyze it. These types of bio-simulations fall under the category of computational evolutionary methods because the individual entities participating in the simulation are permitted to evolve in a natural manner by reacting to changes in the simulated ecosystem. Thismore » work describes the application of the aforementioned methodology to discover epidemiological knowledge about avian influenza using a novel eco-modeling and bio-simulation environment called SEARUMS. The mathematical principles underlying SEARUMS, its design, and the procedure for using SEARUMS are discussed. The bio-simulations and multi-faceted case studies conducted using SEARUMS elucidate its ability to pinpoint timelines, epicenters, and socio-economic impacts of avian influenza. This knowledge is invaluable for proactive deployment of countermeasures in order to minimize negative socioeconomic impacts, combat the disease, and avert a pandemic.« less

The tangled bank of amino acids.

PubMed

Goldstein, Richard A; Pollock, David D

2016-07-01

The use of amino acid substitution matrices to model protein evolution has yielded important insights into both the evolutionary process and the properties of specific protein families. In order to make these models tractable, standard substitution matrices represent the average results of the evolutionary process rather than the underlying molecular biophysics and population genetics, treating proteins as a set of independently evolving sites rather than as an integrated biomolecular entity. With advances in computing and the increasing availability of sequence data, we now have an opportunity to move beyond current substitution matrices to more interpretable mechanistic models with greater fidelity to the evolutionary process of mutation and selection and the holistic nature of the selective constraints. As part of this endeavour, we consider how epistatic interactions induce spatial and temporal rate heterogeneity, and demonstrate how these generally ignored factors can reconcile standard substitution rate matrices and the underlying biology, allowing us to better understand the meaning of these substitution rates. Using computational simulations of protein evolution, we can demonstrate the importance of both spatial and temporal heterogeneity in modelling protein evolution. © 2016 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Evolving binary classifiers through parallel computation of multiple fitness cases.

PubMed

Cagnoni, Stefano; Bergenti, Federico; Mordonini, Monica; Adorni, Giovanni

2005-06-01

This paper describes two versions of a novel approach to developing binary classifiers, based on two evolutionary computation paradigms: cellular programming and genetic programming. Such an approach achieves high computation efficiency both during evolution and at runtime. Evolution speed is optimized by allowing multiple solutions to be computed in parallel. Runtime performance is optimized explicitly using parallel computation in the case of cellular programming or implicitly taking advantage of the intrinsic parallelism of bitwise operators on standard sequential architectures in the case of genetic programming. The approach was tested on a digit recognition problem and compared with a reference classifier.

Joint evolution of specialization and dispersal in structured metapopulations.

PubMed

Nurmi, Tuomas; Parvinen, Kalle

2011-04-21

We study the joint evolution of dispersal and specialization concerning resource usage in a mechanistically underpinned structured discrete-time metapopulation model. We show that dispersal significantly affects the evolution of specialization and that specialization is a key factor that determines the possibility of evolutionary branching in dispersal propensity. Allowing both dispersal propensity and specialization to evolve as a consequence of natural selection is necessary in order to understand the evolutionary dynamics. The joint evolution of dispersal and specialization forms a natural evolutionary path leading to the coexistence of generalists and specialists. We show that in this process, the number of different patch types and the resource distribution are essential. Copyright © 2011 Elsevier Ltd. All rights reserved.

The contribution of statistical physics to evolutionary biology.

PubMed

de Vladar, Harold P; Barton, Nicholas H

2011-08-01

Evolutionary biology shares many concepts with statistical physics: both deal with populations, whether of molecules or organisms, and both seek to simplify evolution in very many dimensions. Often, methodologies have undergone parallel and independent development, as with stochastic methods in population genetics. Here, we discuss aspects of population genetics that have embraced methods from physics: non-equilibrium statistical mechanics, travelling waves and Monte-Carlo methods, among others, have been used to study polygenic evolution, rates of adaptation and range expansions. These applications indicate that evolutionary biology can further benefit from interactions with other areas of statistical physics; for example, by following the distribution of paths taken by a population through time. Copyright © 2011 Elsevier Ltd. All rights reserved.

An eco-evolutionary IBM improves predictions of future geneticconnectivity for American Pikas (Ochotona princeps) in Crater Lake National Park, Oregon

EPA Science Inventory

In the face of rapid, contemporary climate change, conservationbiologists are relying heavily on species distribution models (SDMs)to predict shifting occupancy and distribution patterns in responseto future conditions. These models are critical tools for assessingvulnerability t...

How has agriculture influenced the geography and genetics of animal parasites?

PubMed

Rosenthal, Benjamin M

2009-02-01

Have farmers inadvertently promoted the distribution, and limited the diversity, of animal parasites? Abundant and broadly distributed livestock hosts evidently harbor exceptionally uniform populations of Trichinella, Taenia, Toxoplasma and Sarcocystis, indicating a fruitful avenue for future research on how we have influenced parasite evolutionary ecology.

Landscape Patterns in Rainforest Phylogenetic Signal: Isolated Islands of Refugia or Structured Continental Distributions?

PubMed Central

Kooyman, Robert M.; Rossetto, Maurizio; Sauquet, Hervé; Laffan, Shawn W.

2013-01-01

Objectives Identify patterns of change in species distributions, diversity, concentrations of evolutionary history, and assembly of Australian rainforests. Methods We used the distribution records of all known rainforest woody species in Australia across their full continental extent. These were analysed using measures of species richness, phylogenetic diversity (PD), phylogenetic endemism (PE) and phylogenetic structure (net relatedness index; NRI). Phylogenetic structure was assessed using both continental and regional species pools. To test the influence of growth-form, freestanding and climbing plants were analysed independently, and in combination. Results Species richness decreased along two generally orthogonal continental axes, corresponding with wet to seasonally dry and tropical to temperate habitats. The PE analyses identified four main areas of substantially restricted phylogenetic diversity, including parts of Cape York, Wet Tropics, Border Ranges, and Tasmania. The continental pool NRI results showed evenness (species less related than expected by chance) in groups of grid cells in coastally aligned areas of species rich tropical and sub-tropical rainforest, and in low diversity moist forest areas in the south-east of the Great Dividing Range and in Tasmania. Monsoon and drier vine forests, and moist forests inland from upland refugia showed phylogenetic clustering, reflecting lower diversity and more relatedness. Signals for evenness in Tasmania and clustering in northern monsoon forests weakened in analyses using regional species pools. For climbing plants, values for NRI by grid cell showed strong spatial structuring, with high diversity and PE concentrated in moist tropical and subtropical regions. Conclusions/Significance Concentrations of rainforest evolutionary history (phylo-diversity) were patchily distributed within a continuum of species distributions. Contrasting with previous concepts of rainforest community distribution, our findings of continuous distributions and continental connectivity have significant implications for interpreting rainforest evolutionary history and current day ecological processes, and for managing rainforest diversity in changing circumstances. PMID:24312493

Computational Intelligence and Its Impact on Future High-Performance Engineering Systems

NASA Technical Reports Server (NTRS)

Noor, Ahmed K. (Compiler)

1996-01-01

This document contains presentations from the joint UVA/NASA Workshop on Computational Intelligence held at the Virginia Consortium of Engineering and Science Universities, Hampton, Virginia, June 27-28, 1995. The presentations addressed activities in the areas of fuzzy logic, neural networks, and evolutionary computations. Workshop attendees represented NASA, the National Science Foundation, the Department of Energy, National Institute of Standards and Technology (NIST), the Jet Propulsion Laboratory, industry, and academia. The workshop objectives were to assess the state of technology in the Computational intelligence area and to provide guidelines for future research.

Pleistocene evolutionary history of the Clouded Apollo (Parnassius mnemosyne): genetic signatures of climate cycles and a 'time-dependent' mitochondrial substitution rate.

PubMed

Gratton, P; Konopiński, M K; Sbordoni, V

2008-10-01

Genetic data are currently providing a large amount of new information on past distribution of species and are contributing to a new vision of Pleistocene ice ages. Nonetheless, an increasing number of studies on the 'time dependency' of mutation rates suggest that date assessments for evolutionary events of the Pleistocene might be overestimated. We analysed mitochondrial (mt) DNA (COI) sequence variation in 225 Parnassius mnemosyne individuals sampled across central and eastern Europe in order to assess (i) the existence of genetic signatures of Pleistocene climate shifts; and (ii) the timescale of demographic and evolutionary events. Our analyses reveal a phylogeographical pattern markedly influenced by the Pleistocene/Holocene climate shifts. Eastern Alpine and Balkan populations display comparatively high mtDNA diversity, suggesting multiple glacial refugia. On the other hand, three widely distributed and spatially segregated lineages occupy most of northern and eastern Europe, indicating postglacial recolonization from different refugial areas. We show that a conventional 'phylogenetic' substitution rate cannot account for the present distribution of genetic variation in this species, and we combine phylogeographical pattern and palaeoecological information in order to determine a suitable intraspecific rate through a Bayesian coalescent approach. We argue that our calibrated 'time-dependent' rate (0.096 substitutions/ million years), offers the most convincing time frame for the evolutionary events inferred from sequence data. When scaled by the new rate, estimates of divergence between Balkan and Alpine lineages point to c. 19 000 years before present (last glacial maximum), and parameters of demographic expansion for northern lineages are consistent with postglacial warming (5-11 000 years before present).

Evolutionary transitions towards eusociality in snapping shrimps.

PubMed

Chak, Solomon Tin Chi; Duffy, J Emmett; Hultgren, Kristin M; Rubenstein, Dustin R

2017-03-20

Animal social organization varies from complex societies where reproduction is dominated by a single individual (eusociality) to those where reproduction is more evenly distributed among group members (communal breeding). Yet, how simple groups transition evolutionarily to more complex societies remains unclear. Competing hypotheses suggest that eusociality and communal breeding are alternative evolutionary endpoints, or that communal breeding is an intermediate stage in the transition towards eusociality. We tested these alternative hypotheses in sponge-dwelling shrimps, Synalpheus spp. Although species varied continuously in reproductive skew, they clustered into pair-forming, communal and eusocial categories based on several demographic traits. Evolutionary transition models suggested that eusocial and communal species are discrete evolutionary endpoints that evolved independently from pair-forming ancestors along alternative paths. This 'family-centred' origin of eusociality parallels observations in insects and vertebrates, reinforcing the role of kin selection in the evolution of eusociality and suggesting a general model of animal social evolution.

Explicit Building Block Multiobjective Evolutionary Computation: Methods and Applications

DTIC Science & Technology

2005-06-16

which is introduced in 1990 by Richard Dawkins in his book ”The Selfish Gene .” [34] 356 E.5.7 Pareto Envelop-based Selection Algorithm I and II...IGC Intelligent Gene Collector . . . . . . . . . . . . . . . . . 59 OED Orthogonal Experimental Design . . . . . . . . . . . . . 59 MED Main Effect...complete one experiment 74 `′ The string length hold within the computer (can be longer than number of genes

The Application of Multiobjective Evolutionary Algorithms to an Educational Computational Model of Science Information Processing: A Computational Experiment in Science Education

ERIC Educational Resources Information Center

Lamb, Richard L.; Firestone, Jonah B.

2017-01-01

Conflicting explanations and unrelated information in science classrooms increase cognitive load and decrease efficiency in learning. This reduced efficiency ultimately limits one's ability to solve reasoning problems in the science. In reasoning, it is the ability of students to sift through and identify critical pieces of information that is of…

Approximate Bayesian Computation Reveals the Crucial Role of Oceanic Islands for the Assembly of Continental Biodiversity.

PubMed

Patiño, Jairo; Carine, Mark; Mardulyn, Patrick; Devos, Nicolas; Mateo, Rubén G; González-Mancebo, Juana M; Shaw, A Jonathan; Vanderpoorten, Alain

2015-07-01

The perceived low levels of genetic diversity, poor interspecific competitive and defensive ability, and loss of dispersal capacities of insular lineages have driven the view that oceanic islands are evolutionary dead ends. Focusing on the Atlantic bryophyte flora distributed across the archipelagos of the Azores, Madeira, the Canary Islands, Western Europe, and northwestern Africa, we used an integrative approach with species distribution modeling and population genetic analyses based on approximate Bayesian computation to determine whether this view applies to organisms with inherent high dispersal capacities. Genetic diversity was found to be higher in island than in continental populations, contributing to mounting evidence that, contrary to theoretical expectations, island populations are not necessarily genetically depauperate. Patterns of genetic variation among island and continental populations consistently fitted those simulated under a scenario of de novo foundation of continental populations from insular ancestors better than those expected if islands would represent a sink or a refugium of continental biodiversity. We, suggest that the northeastern Atlantic archipelagos have played a key role as a stepping stone for transoceanic migrants. Our results challenge the traditional notion that oceanic islands are the end of the colonization road and illustrate the significant role of oceanic islands as reservoirs of novel biodiversity for the assembly of continental floras. © The Author(s) 2015. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Growth Control and Disease Mechanisms in Computational Embryogeny

NASA Technical Reports Server (NTRS)

Shapiro, Andrew A.; Yogev, Or; Antonsson, Erik K.

2008-01-01

This paper presents novel approach to applying growth control and diseases mechanisms in computational embryogeny. Our method, which mimics fundamental processes from biology, enables individuals to reach maturity in a controlled process through a stochastic environment. Three different mechanisms were implemented; disease mechanisms, gene suppression, and thermodynamic balancing. This approach was integrated as part of a structural evolutionary model. The model evolved continuum 3-D structures which support an external load. By using these mechanisms we were able to evolve individuals that reached a fixed size limit through the growth process. The growth process was an integral part of the complete development process. The size of the individuals was determined purely by the evolutionary process where different individuals matured to different sizes. Individuals which evolved with these characteristics have been found to be very robust for supporting a wide range of external loads.

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

The evolution of cranial form and function in theropod dinosaurs: insights from geometric morphometrics.

PubMed

Brusatte, S L; Sakamoto, M; Montanari, S; Harcourt Smith, W E H

2012-02-01

Theropod dinosaurs, an iconic clade of fossil species including Tyrannosaurus and Velociraptor, developed a great diversity of body size, skull form and feeding habits over their 160+ million year evolutionary history. Here, we utilize geometric morphometrics to study broad patterns in theropod skull shape variation and compare the distribution of taxa in cranial morphospace (form) to both phylogeny and quantitative metrics of biting behaviour (function). We find that theropod skulls primarily differ in relative anteroposterior length and snout depth and to a lesser extent in orbit size and depth of the cheek region, and oviraptorosaurs deviate most strongly from the "typical" and ancestral theropod morphologies. Noncarnivorous taxa generally fall out in distinct regions of morphospace and exhibit greater overall disparity than carnivorous taxa, whereas large-bodied carnivores independently converge on the same region of morphospace. The distribution of taxa in morphospace is strongly correlated with phylogeny but only weakly correlated with functional biting behaviour. These results imply that phylogeny, not biting function, was the major determinant of theropod skull shape. © 2011 The Authors. Journal of Evolutionary Biology © 2011 European Society For Evolutionary Biology.

Contrasting evolutionary patterns in two reef-corals and their possible relationship to life history traits

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

Foster, A.B.

1985-01-01

Multivariate statistical analyses have been used to redefine species within two genera of reef-corals (Porites and Montastraea) and to trace their evolutionary patterns through a continuous sequence from late Miocene to early Pliocene time. The material studied consists of populations sampled at regular intervals through four stratigraphic sections in the northern Dominican Republic. The results show that species in the first genus (Porites) have relatively short durations, morphologic stability, and narrow spatial distributions. Their overall evolutionary history is characterized by short periods of radiation and widespread extinction, separated by longer periods of stasis. In contrast, species in the second genusmore » (Montastraea) exhibit various different durations and distributions and directional morphologic trends. These differences in patterns may be related to the dissimilar life histories of the two genera. Patterns in the first genus appear more common in organisms having high larval recruitment, high mortality, high genetic variation, and less morphologic distance between species. Patterns in the second genus occur more frequently in slower growing, phenotypically plastic organisms experiencing less recruitment and mortality and showing more morphologic distance between species.« less

The co-evolutionary dynamics of directed network of spin market agents

NASA Astrophysics Data System (ADS)

Horváth, Denis; Kuscsik, Zoltán; Gmitra, Martin

2006-09-01

The spin market model [S. Bornholdt, Int. J. Mod. Phys. C 12 (2001) 667] is generalized by employing co-evolutionary principles, where strategies of the interacting and competitive traders are represented by local and global couplings between the nodes of dynamic directed stochastic network. The co-evolutionary principles are applied in the frame of Bak-Sneppen self-organized dynamics [P. Bak, K. Sneppen, Phys. Rev. Lett. 71 (1993) 4083] that includes the processes of selection and extinction actuated by the local (node) fitness. The local fitness is related to orientation of spin agent with respect to the instant magnetization. The stationary regime is formed due to the interplay of self-organization and adaptivity effects. The fat tailed distributions of log-price returns are identified numerically. The non-trivial model consequence is the evidence of the long time market memory indicated by the power-law range of the autocorrelation function of volatility with exponent smaller than one. The simulations yield network topology with broad-scale node degree distribution characterized by the range of exponents 1.3<γin<3 coinciding with social networks.

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.

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.

The evolutionary dynamics of language.

PubMed

Steels, Luc; Szathmáry, Eörs

2018-02-01

The well-established framework of evolutionary dynamics can be applied to the fascinating open problems how human brains are able to acquire and adapt language and how languages change in a population. Schemas for handling grammatical constructions are the replicating unit. They emerge and multiply with variation in the brains of individuals and undergo selection based on their contribution to needed expressive power, communicative success and the reduction of cognitive effort. Adopting this perspective has two major benefits. (i) It makes a bridge to neurobiological models of the brain that have also adopted an evolutionary dynamics point of view, thus opening a new horizon for studying how human brains achieve the remarkably complex competence for language. And (ii) it suggests a new foundation for studying cultural language change as an evolutionary dynamics process. The paper sketches this novel perspective, provides references to empirical data and computational experiments, and points to open problems. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

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

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.

Evolutionary Construction of Block-Based Neural Networks in Consideration of Failure

NASA Astrophysics Data System (ADS)

Takamori, Masahito; Koakutsu, Seiichi; Hamagami, Tomoki; Hirata, Hironori

In this paper we propose a modified gene coding and an evolutionary construction in consideration of failure in evolutionary construction of Block-Based Neural Networks. In the modified gene coding, we arrange the genes of weights on a chromosome in consideration of the position relation of the genes of weight and structure. By the modified gene coding, the efficiency of search by crossover is increased. Thereby, it is thought that improvement of the convergence rate of construction and shortening of construction time can be performed. In the evolutionary construction in consideration of failure, the structure which is adapted for failure is built in the state where failure occured. Thereby, it is thought that BBNN can be reconstructed in a short time at the time of failure. To evaluate the proposed method, we apply it to pattern classification and autonomous mobile robot control problems. The computational experiments indicate that the proposed method can improve convergence rate of construction and shorten of construction and reconstruction time.

δ-Similar Elimination to Enhance Search Performance of Multiobjective Evolutionary Algorithms

NASA Astrophysics Data System (ADS)

Aguirre, Hernán; Sato, Masahiko; Tanaka, Kiyoshi

In this paper, we propose δ-similar elimination to improve the search performance of multiobjective evolutionary algorithms in combinatorial optimization problems. This method eliminates similar individuals in objective space to fairly distribute selection among the different regions of the instantaneous Pareto front. We investigate four eliminating methods analyzing their effects using NSGA-II. In addition, we compare the search performance of NSGA-II enhanced by our method and NSGA-II enhanced by controlled elitism.

Implementation of a parallel protein structure alignment service on cloud.

PubMed

Hung, Che-Lun; Lin, Yaw-Ling

2013-01-01

Protein structure alignment has become an important strategy by which to identify evolutionary relationships between protein sequences. Several alignment tools are currently available for online comparison of protein structures. In this paper, we propose a parallel protein structure alignment service based on the Hadoop distribution framework. This service includes a protein structure alignment algorithm, a refinement algorithm, and a MapReduce programming model. The refinement algorithm refines the result of alignment. To process vast numbers of protein structures in parallel, the alignment and refinement algorithms are implemented using MapReduce. We analyzed and compared the structure alignments produced by different methods using a dataset randomly selected from the PDB database. The experimental results verify that the proposed algorithm refines the resulting alignments more accurately than existing algorithms. Meanwhile, the computational performance of the proposed service is proportional to the number of processors used in our cloud platform.

Implementation of a Parallel Protein Structure Alignment Service on Cloud

PubMed Central

Hung, Che-Lun; Lin, Yaw-Ling

2013-01-01

Protein structure alignment has become an important strategy by which to identify evolutionary relationships between protein sequences. Several alignment tools are currently available for online comparison of protein structures. In this paper, we propose a parallel protein structure alignment service based on the Hadoop distribution framework. This service includes a protein structure alignment algorithm, a refinement algorithm, and a MapReduce programming model. The refinement algorithm refines the result of alignment. To process vast numbers of protein structures in parallel, the alignment and refinement algorithms are implemented using MapReduce. We analyzed and compared the structure alignments produced by different methods using a dataset randomly selected from the PDB database. The experimental results verify that the proposed algorithm refines the resulting alignments more accurately than existing algorithms. Meanwhile, the computational performance of the proposed service is proportional to the number of processors used in our cloud platform. PMID:23671842

Stochastic Dynamics through Hierarchically Embedded Markov Chains

NASA Astrophysics Data System (ADS)

Vasconcelos, Vítor V.; Santos, Fernando P.; Santos, Francisco C.; Pacheco, Jorge M.

2017-02-01

Studying dynamical phenomena in finite populations often involves Markov processes of significant mathematical and/or computational complexity, which rapidly becomes prohibitive with increasing population size or an increasing number of individual configuration states. Here, we develop a framework that allows us to define a hierarchy of approximations to the stationary distribution of general systems that can be described as discrete Markov processes with time invariant transition probabilities and (possibly) a large number of states. This results in an efficient method for studying social and biological communities in the presence of stochastic effects—such as mutations in evolutionary dynamics and a random exploration of choices in social systems—including situations where the dynamics encompasses the existence of stable polymorphic configurations, thus overcoming the limitations of existing methods. The present formalism is shown to be general in scope, widely applicable, and of relevance to a variety of interdisciplinary problems.

Evolution of EF-hand calcium-modulated proteins. III. Exon sequences confirm most dendrograms based on protein sequences: calmodulin dendrograms show significant lack of parallelism

NASA Technical Reports Server (NTRS)

Nakayama, S.; Kretsinger, R. H.

1993-01-01

In the first report in this series we presented dendrograms based on 152 individual proteins of the EF-hand family. In the second we used sequences from 228 proteins, containing 835 domains, and showed that eight of the 29 subfamilies are congruent and that the EF-hand domains of the remaining 21 subfamilies have diverse evolutionary histories. In this study we have computed dendrograms within and among the EF-hand subfamilies using the encoding DNA sequences. In most instances the dendrograms based on protein and on DNA sequences are very similar. Significant differences between protein and DNA trees for calmodulin remain unexplained. In our fourth report we evaluate the sequences and the distribution of introns within the EF-hand family and conclude that exon shuffling did not play a significant role in its evolution.

Computer simulations of sympatric speciation in a simple food web

NASA Astrophysics Data System (ADS)

Luz-Burgoa, K.; Dell, Tony; de Oliveira, S. Moss

2005-07-01

Galapagos finches, have motivated much theoretical research aimed at understanding the processes associated with the formation of the species. Inspired by them, in this paper we investigate the process of sympatric speciation in a simple food web model. For that we modify the individual-based Penna model that has been widely used to study aging as well as other evolutionary processes. Initially, our web consists of a primary food source and a single herbivore species that feeds on this resource. Subsequently we introduce a predator that feeds on the herbivore. In both instances we manipulate directly a basal resource distribution and monitor the changes in the populations. Sympatric speciation is obtained for the top species in both cases, and our results suggest that the speciation velocity depends on how far up, in the food chain, the focus population is feeding. Simulations are done with three different sexual imprintinglike mechanisms, in order to discuss adaptation by natural selection.

Stochastic Dynamics through Hierarchically Embedded Markov Chains.

PubMed

Vasconcelos, Vítor V; Santos, Fernando P; Santos, Francisco C; Pacheco, Jorge M

2017-02-03

Studying dynamical phenomena in finite populations often involves Markov processes of significant mathematical and/or computational complexity, which rapidly becomes prohibitive with increasing population size or an increasing number of individual configuration states. Here, we develop a framework that allows us to define a hierarchy of approximations to the stationary distribution of general systems that can be described as discrete Markov processes with time invariant transition probabilities and (possibly) a large number of states. This results in an efficient method for studying social and biological communities in the presence of stochastic effects-such as mutations in evolutionary dynamics and a random exploration of choices in social systems-including situations where the dynamics encompasses the existence of stable polymorphic configurations, thus overcoming the limitations of existing methods. The present formalism is shown to be general in scope, widely applicable, and of relevance to a variety of interdisciplinary problems.

Characterization of irritans mariner-like elements in the olive fruit fly Bactrocera oleae (Diptera: Tephritidae): evolutionary implications.

PubMed

Ben Lazhar-Ajroud, Wafa; Caruso, Aurore; Mezghani, Maha; Bouallegue, Maryem; Tastard, Emmanuelle; Denis, Françoise; Rouault, Jacques-Deric; Makni, Hanem; Capy, Pierre; Chénais, Benoît; Makni, Mohamed; Casse, Nathalie

2016-08-01

Genomic variation among species is commonly driven by transposable element (TE) invasion; thus, the pattern of TEs in a genome allows drawing an evolutionary history of the studied species. This paper reports in vitro and in silico detection and characterization of irritans mariner-like elements (MLEs) in the genome and transcriptome of Bactrocera oleae (Rossi) (Diptera: Tephritidae). Eleven irritans MLE sequences have been isolated in vitro using terminal inverted repeats (TIRs) as primers, and 215 have been extracted in silico from the sequenced genome of B. oleae. Additionally, the sequenced genomes of Bactrocera tryoni (Froggatt) and Bactrocera cucurbitae (Diptera: Tephritidae) have been explored to identify irritans MLEs. A total of 129 sequences from B. tryoni have been extracted, while the genome of B. cucurbitae appears probably devoid of irritans MLEs. All detected irritans MLEs are defective due to several mutations and are clustered together in a monophyletic group suggesting a common ancestor. The evolutionary history and dynamics of these TEs are discussed in relation with the phylogenetic distribution of their hosts. The knowledge on the structure, distribution, dynamic, and evolution of irritans MLEs in Bactrocera species contributes to the understanding of both their evolutionary history and the invasion history of their hosts. This could also be the basis for genetic control strategies using transposable elements.

High Genetic Diversity and Distinctiveness of Rear-Edge Climate Relicts Maintained by Ancient Tetraploidisation for Alnus glutinosa

PubMed Central

Lepais, Olivier; Muller, Serge D.; Ben Saad-Limam, Samia; Benslama, Mohamed; Rhazi, Laila; Belouahem-Abed, Djamila; Daoud-Bouattour, Amina; Gammar, Amor Mokhtar; Ghrabi-Gammar, Zeineb; Bacles, Cécile Fanny Emilie

2013-01-01

Populations located at the rear-edge of a species’ distribution may have disproportionate ecological and evolutionary importance for biodiversity conservation in a changing global environment. Yet genetic studies of such populations remain rare. This study investigates the evolutionary history of North-African low latitude marginal populations of Alnus glutinosa Gaertn., a European tree species that plays a significant ecological role as a keystone of riparian ecosystems. We genotyped 551 adults from 19 populations located across North Africa at 12 microsatellite loci and applied a coalescent-based simulation approach to reconstruct the demographic and evolutionary history of these populations. Surprisingly, Moroccan trees were tetraploids demonstrating a strong distinctiveness of these populations within a species otherwise known as diploid. Best-fitting models of demographic reconstruction revealed the relict nature of Moroccan populations that were found to have withstood past climate change events and to be much older than Algerian and Tunisian populations. This study highlights the complex demographic history that can be encountered in rear-edge distribution margins that here consist of both old stable climate relict and more recent populations, distinctively diverse genetically both quantitatively and qualitatively. We emphasize the high evolutionary and conservation value of marginal rear-edge populations of a keystone riparian species in the context of on-going climate change in the Mediterranean region. PMID:24098677

Global patterns of evolutionary distinct and globally endangered amphibians and mammals.

PubMed

Safi, Kamran; Armour-Marshall, Katrina; Baillie, Jonathan E M; Isaac, Nick J B

2013-01-01

Conservation of phylogenetic diversity allows maximising evolutionary information preserved within fauna and flora. The "EDGE of Existence" programme is the first institutional conservation initiative that prioritises species based on phylogenetic information. Species are ranked in two ways: one according to their evolutionary distinctiveness (ED) and second, by including IUCN extinction status, their evolutionary distinctiveness and global endangerment (EDGE). Here, we describe the global patterns in the spatial distribution of priority ED and EDGE species, in order to identify conservation areas for mammalian and amphibian communities. In addition, we investigate whether environmental conditions can predict the observed spatial pattern in ED and EDGE globally. Priority zones with high concentrations of ED and EDGE scores were defined using two different methods. The overlap between mammal and amphibian zones was very small, reflecting the different phylo-biogeographic histories. Mammal ED zones were predominantly found on the African continent and the neotropical forests, whereas in amphibians, ED zones were concentrated in North America. Mammal EDGE zones were mainly in South-East Asia, southern Africa and Madagascar; for amphibians they were in central and south America. The spatial pattern of ED and EDGE was poorly described by a suite of environmental variables. Mapping the spatial distribution of ED and EDGE provides an important step towards identifying priority areas for the conservation of mammalian and amphibian phylogenetic diversity in the EDGE of existence programme.

SeedVicious: Analysis of microRNA target and near-target sites.

PubMed

Marco, Antonio

2018-01-01

Here I describe seedVicious, a versatile microRNA target site prediction software that can be easily fitted into annotation pipelines and run over custom datasets. SeedVicious finds microRNA canonical sites plus other, less efficient, target sites. Among other novel features, seedVicious can compute evolutionary gains/losses of target sites using maximum parsimony, and also detect near-target sites, which have one nucleotide different from a canonical site. Near-target sites are important to study population variation in microRNA regulation. Some analyses suggest that near-target sites may also be functional sites, although there is no conclusive evidence for that, and they may actually be target alleles segregating in a population. SeedVicious does not aim to outperform but to complement existing microRNA prediction tools. For instance, the precision of TargetScan is almost doubled (from 11% to ~20%) when we filter predictions by the distance between target sites using this program. Interestingly, two adjacent canonical target sites are more likely to be present in bona fide target transcripts than pairs of target sites at slightly longer distances. The software is written in Perl and runs on 64-bit Unix computers (Linux and MacOS X). Users with no computing experience can also run the program in a dedicated web-server by uploading custom data, or browse pre-computed predictions. SeedVicious and its associated web-server and database (SeedBank) are distributed under the GPL/GNU license.

Physical properties of high-mass star-forming clumps in different evolutionary stages from the Bolocam Galactic Plane Survey

NASA Astrophysics Data System (ADS)

Svoboda, Brian; Shirley, Yancy; Rosolowsky, Erik; Dunham, Miranda; Ellsworth-Bowers, Timothy; Ginsburg, Adam

2013-07-01

High mass stars play a key role in the physical and chemical evolution of the interstellar medium, yet the evolutionary sequence for high mass star forming regions is poorly understood. Recent Galactic plane surveys are providing the first systematic view of high-mass star-forming regions in all evolutionary phases across the Milky Way. We present observations of the 22.23 GHz H2O maser transition J(Ka,Kc) = 6(1,6)→5(2,3) transition toward 1398 clumps identified in the Bolocam Galactic Plane Survey using the 100m Green Bank Telescope (GBT). We detect 392 H2O masers, 279 (71%) newly discovered. We show that H2O masers can identify the presence of protostars which were not previously identified by Spitzer/MSX Galactic plane IR surveys: 25% of IR-dark clumps have an H2O maser. We compare the physical properties of the clumps in the Bolocam Galactic Plane Survey (BGPS) with observations of diagnostics of star formation activity: 8 and 24 um YSO candidates, H2O and CH3OH masers, shocked H2, EGOs, and UCHII regions. We identify a sub-sample of 400 clumps with no star formation indicators representing the largest and most robust sample of pre-protocluster candidates from an unbiased survey to date. The different evolutionary stages show strong separations in HCO+ linewidth and integrated intensity, surface mass density, and kinetic temperature. Monte Carlo techniques are applied to distance probability distribution functions (DPDFs) in order to marginalize over the kinematic distance ambiguity and calculate the distribution of derived quantities for clumps in different evolutionary stages. Surface area and dust mass show weak separations above > 2 pc^2 and > 3x10^3 solar masses. An observed breakdown occurs in the size-linewidth relationship with no differentiation by evolutionary stage. Future work includes adding evolutionary indicators (MIPSGAL, HiGal, MMB) and expanding DPDF priors (HI self-absorption, Galactic structure) for more well-resolved KDAs.

Quantifying rates of evolutionary adaptation in response to ocean acidification.

PubMed

Sunday, Jennifer M; Crim, Ryan N; Harley, Christopher D G; Hart, Michael W

2011-01-01

The global acidification of the earth's oceans is predicted to impact biodiversity via physiological effects impacting growth, survival, reproduction, and immunology, leading to changes in species abundances and global distributions. However, the degree to which these changes will play out critically depends on the evolutionary rate at which populations will respond to natural selection imposed by ocean acidification, which remains largely unquantified. Here we measure the potential for an evolutionary response to ocean acidification in larval development rate in two coastal invertebrates using a full-factorial breeding design. We show that the sea urchin species Strongylocentrotus franciscanus has vastly greater levels of phenotypic and genetic variation for larval size in future CO(2) conditions compared to the mussel species Mytilus trossulus. Using these measures we demonstrate that S. franciscanus may have faster evolutionary responses within 50 years of the onset of predicted year-2100 CO(2) conditions despite having lower population turnover rates. Our comparisons suggest that information on genetic variation, phenotypic variation, and key demographic parameters, may lend valuable insight into relative evolutionary potentials across a large number of species.

Stochastic dynamics and stable equilibrium of evolutionary optional public goods game in finite populations

NASA Astrophysics Data System (ADS)

Quan, Ji; Liu, Wei; Chu, Yuqing; Wang, Xianjia

2018-07-01

Continuous noise caused by mutation is widely present in evolutionary systems. Considering the noise effects and under the optional participation mechanism, a stochastic model for evolutionary public goods game in a finite size population is established. The evolutionary process of strategies in the population is described as a multidimensional ergodic and continuous time Markov process. The stochastic stable state of the system is analyzed by the limit distribution of the stochastic process. By numerical experiments, the influences of the fixed income coefficient for non-participants and the investment income coefficient of the public goods on the stochastic stable equilibrium of the system are analyzed. Through the numerical calculation results, we found that the optional participation mechanism can change the evolutionary dynamics and the equilibrium of the public goods game, and there is a range of parameters which can effectively promote the evolution of cooperation. Further, we obtain the accurate quantitative relationship between the parameters and the probabilities for the system to choose different stable equilibriums, which can be used to realize the control of cooperation.

Limited evolutionary rescue of locally adapted populations facing climate change.

PubMed

Schiffers, Katja; Bourne, Elizabeth C; Lavergne, Sébastien; Thuiller, Wilfried; Travis, Justin M J

2013-01-19

Dispersal is a key determinant of a population's evolutionary potential. It facilitates the propagation of beneficial alleles throughout the distributional range of spatially outspread populations and increases the speed of adaptation. However, when habitat is heterogeneous and individuals are locally adapted, dispersal may, at the same time, reduce fitness through increasing maladaptation. Here, we use a spatially explicit, allelic simulation model to quantify how these equivocal effects of dispersal affect a population's evolutionary response to changing climate. Individuals carry a diploid set of chromosomes, with alleles coding for adaptation to non-climatic environmental conditions and climatic conditions, respectively. Our model results demonstrate that the interplay between gene flow and habitat heterogeneity may decrease effective dispersal and population size to such an extent that substantially reduces the likelihood of evolutionary rescue. Importantly, even when evolutionary rescue saves a population from extinction, its spatial range following climate change may be strongly narrowed, that is, the rescue is only partial. These findings emphasize that neglecting the impact of non-climatic, local adaptation might lead to a considerable overestimation of a population's evolvability under rapid environmental change.

Evolution, learning, and cognition

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

Lee, Y.C.

1988-01-01

The book comprises more than fifteen articles in the areas of neural networks and connectionist systems, classifier systems, adaptive network systems, genetic algorithm, cellular automata, artificial immune systems, evolutionary genetics, cognitive science, optical computing, combinatorial optimization, and cybernetics.

Application of high technology in highway transportation.

DOT National Transportation Integrated Search

1985-01-01

Highway and traffic engineering practice is rapidly changing as communications technology and computer systems are being adopted to facilitate the work of the practitioners and expand their capabilities. This field has been an evolutionary one since ...

Large fluctuations in anti-coordination games on scale-free graphs

NASA Astrophysics Data System (ADS)

Sabsovich, Daniel; Mobilia, Mauro; Assaf, Michael

2017-05-01

We study the influence of the complex topology of scale-free graphs on the dynamics of anti-coordination games (e.g. snowdrift games). These reference models are characterized by the coexistence (evolutionary stable mixed strategy) of two competing species, say ‘cooperators’ and ‘defectors’, and, in finite systems, by metastability and large-fluctuation-driven fixation. In this work, we use extensive computer simulations and an effective diffusion approximation (in the weak selection limit) to determine under which circumstances, depending on the individual-based update rules, the topology drastically affects the long-time behavior of anti-coordination games. In particular, we compute the variance of the number of cooperators in the metastable state and the mean fixation time when the dynamics is implemented according to the voter model (death-first/birth-second process) and the link dynamics (birth/death or death/birth at random). For the voter update rule, we show that the scale-free topology effectively renormalizes the population size and as a result the statistics of observables depend on the network’s degree distribution. In contrast, such a renormalization does not occur with the link dynamics update rule and we recover the same behavior as on complete graphs.

Theoretical gravity darkening as a function of optical depth. A first approach to fast rotating stars

NASA Astrophysics Data System (ADS)

Claret, A.

2016-04-01

Aims: Recent observations of very fast rotating stars show systematic deviations from the von Zeipel theorem and pose a challenge to the theory of gravity-darkening exponents (β1). In this paper, we present a new insight into the problem of temperature distribution over distorted stellar surfaces to try to reduce these discrepancies. Methods: We use a variant of the numerical method based on the triangles strategy, which we previously introduced, to evaluate the gravity-darkening exponents. The novelty of the present method is that the theoretical β1 is now computed as a function of the optical depth, that is, β1 ≡ β1(τ). The stellar evolutionary models, which are necessary to obtain the physical conditions of the stellar envelopes/atmospheres inherent to the numerical method, are computed via the code GRANADA. Results: When the resulting theoretical β1(τ) are compared with the best accurate data of very fast rotators, a good agreement for the six systems is simultaneously achieved. In addition, we derive an equation that relates the locus of constant convective efficiency in the Hertzsprung-Russell (HR) diagram with gravity-darkening exponents.

Functional characteristics of the calcium modulated proteins seen from an evolutionary perspective

NASA Technical Reports Server (NTRS)

Kretsinger, R. H.; Nakayama, S.; Moncrief, N. D.

1991-01-01

We have constructed dendrograms relating 173 EF-hand proteins of known amino acid sequence. We aligned all of these proteins by their EF-hand domains, omitting interdomain regions. Initial dendrograms were computed by minimum mutation distance methods. Using these as starting points, we determined the best dendrogram by the method of maximum parsimony, scored by minimum mutation distance. We identified 14 distinct subfamilies as well as 6 unique proteins that are perhaps the sole representatives of other subfamilies. This information is given in tabular form. Within subfamilies one can easily align interdomain regions. The resulting dendrograms are very similar to those computed using domains only. Dendrograms constructed using pairs of domains show general congruence. However, there are enough exceptions to caution against an overly simple scheme in which one pair of gene duplications leads from one domain precurser to a four domain prototype from which all other forms evolved. The ability to bind calcium was lost and acquired several times during evolution. The distribution of introns does not conform to the dendrogram based on amino acid sequences. The rates of evolution appear to be much slower within subfamilies, especially within calmodulin, than those prior to the definition of subfamily.

Investigating host-pathogen behavior and their interaction using genome-scale metabolic network models.

PubMed

Sadhukhan, Priyanka P; Raghunathan, Anu

2014-01-01

Genome Scale Metabolic Modeling methods represent one way to compute whole cell function starting from the genome sequence of an organism and contribute towards understanding and predicting the genotype-phenotype relationship. About 80 models spanning all the kingdoms of life from archaea to eukaryotes have been built till date and used to interrogate cell phenotype under varying conditions. These models have been used to not only understand the flux distribution in evolutionary conserved pathways like glycolysis and the Krebs cycle but also in applications ranging from value added product formation in Escherichia coli to predicting inborn errors of Homo sapiens metabolism. This chapter describes a protocol that delineates the process of genome scale metabolic modeling for analysing host-pathogen behavior and interaction using flux balance analysis (FBA). The steps discussed in the process include (1) reconstruction of a metabolic network from the genome sequence, (2) its representation in a precise mathematical framework, (3) its translation to a model, and (4) the analysis using linear algebra and optimization. The methods for biological interpretations of computed cell phenotypes in the context of individual host and pathogen models and their integration are also discussed.

Ensemble modeling of stochastic unsteady open-channel flow in terms of its time-space evolutionary probability distribution - Part 1: theoretical development

NASA Astrophysics Data System (ADS)

Dib, Alain; Kavvas, M. Levent

2018-03-01

The Saint-Venant equations are commonly used as the governing equations to solve for modeling the spatially varied unsteady flow in open channels. The presence of uncertainties in the channel or flow parameters renders these equations stochastic, thus requiring their solution in a stochastic framework in order to quantify the ensemble behavior and the variability of the process. While the Monte Carlo approach can be used for such a solution, its computational expense and its large number of simulations act to its disadvantage. This study proposes, explains, and derives a new methodology for solving the stochastic Saint-Venant equations in only one shot, without the need for a large number of simulations. The proposed methodology is derived by developing the nonlocal Lagrangian-Eulerian Fokker-Planck equation of the characteristic form of the stochastic Saint-Venant equations for an open-channel flow process, with an uncertain roughness coefficient. A numerical method for its solution is subsequently devised. The application and validation of this methodology are provided in a companion paper, in which the statistical results computed by the proposed methodology are compared against the results obtained by the Monte Carlo approach.

Plant Identification Based on Leaf Midrib Cross-Section Images Using Fractal Descriptors.

PubMed

da Silva, Núbia Rosa; Florindo, João Batista; Gómez, María Cecilia; Rossatto, Davi Rodrigo; Kolb, Rosana Marta; Bruno, Odemir Martinez

2015-01-01

The correct identification of plants is a common necessity not only to researchers but also to the lay public. Recently, computational methods have been employed to facilitate this task, however, there are few studies front of the wide diversity of plants occurring in the world. This study proposes to analyse images obtained from cross-sections of leaf midrib using fractal descriptors. These descriptors are obtained from the fractal dimension of the object computed at a range of scales. In this way, they provide rich information regarding the spatial distribution of the analysed structure and, as a consequence, they measure the multiscale morphology of the object of interest. In Biology, such morphology is of great importance because it is related to evolutionary aspects and is successfully employed to characterize and discriminate among different biological structures. Here, the fractal descriptors are used to identify the species of plants based on the image of their leaves. A large number of samples are examined, being 606 leaf samples of 50 species from Brazilian flora. The results are compared to other imaging methods in the literature and demonstrate that fractal descriptors are precise and reliable in the taxonomic process of plant species identification.

Organization of the secure distributed computing based on multi-agent system

NASA Astrophysics Data System (ADS)

Khovanskov, Sergey; Rumyantsev, Konstantin; Khovanskova, Vera

2018-04-01

Nowadays developing methods for distributed computing is received much attention. One of the methods of distributed computing is using of multi-agent systems. The organization of distributed computing based on the conventional network computers can experience security threats performed by computational processes. Authors have developed the unified agent algorithm of control system of computing network nodes operation. Network PCs is used as computing nodes. The proposed multi-agent control system for the implementation of distributed computing allows in a short time to organize using of the processing power of computers any existing network to solve large-task by creating a distributed computing. Agents based on a computer network can: configure a distributed computing system; to distribute the computational load among computers operated agents; perform optimization distributed computing system according to the computing power of computers on the network. The number of computers connected to the network can be increased by connecting computers to the new computer system, which leads to an increase in overall processing power. Adding multi-agent system in the central agent increases the security of distributed computing. This organization of the distributed computing system reduces the problem solving time and increase fault tolerance (vitality) of computing processes in a changing computing environment (dynamic change of the number of computers on the network). Developed a multi-agent system detects cases of falsification of the results of a distributed system, which may lead to wrong decisions. In addition, the system checks and corrects wrong results.

A Systematic Survey of an Intragenic Epistatic Landscape

PubMed Central

Bank, Claudia; Hietpas, Ryan T.; Jensen, Jeffrey D.; Bolon, Daniel N.A.

2015-01-01

Mutations are the source of evolutionary variation. The interactions of multiple mutations can have important effects on fitness and evolutionary trajectories. We have recently described the distribution of fitness effects of all single mutations for a nine-amino-acid region of yeast Hsp90 (Hsp82) implicated in substrate binding. Here, we report and discuss the distribution of intragenic epistatic effects within this region in seven Hsp90 point mutant backgrounds of neutral to slightly deleterious effect, resulting in an analysis of more than 1,000 double mutants. We find negative epistasis between substitutions to be common, and positive epistasis to be rare—resulting in a pattern that indicates a drastic change in the distribution of fitness effects one step away from the wild type. This can be well explained by a concave relationship between phenotype and genotype (i.e., a concave shape of the local fitness landscape), suggesting mutational robustness intrinsic to the local sequence space. Structural analyses indicate that, in this region, epistatic effects are most pronounced when a solvent-inaccessible position is involved in the interaction. In contrast, all 18 observations of positive epistasis involved at least one mutation at a solvent-exposed position. By combining the analysis of evolutionary and biophysical properties of an epistatic landscape, these results contribute to a more detailed understanding of the complexity of protein evolution. PMID:25371431

Variation in recombination frequency and distribution across eukaryotes: patterns and processes

PubMed Central

Feulner, Philine G. D.; Johnston, Susan E.; Santure, Anna W.; Smadja, Carole M.

2017-01-01

Recombination, the exchange of DNA between maternal and paternal chromosomes during meiosis, is an essential feature of sexual reproduction in nearly all multicellular organisms. While the role of recombination in the evolution of sex has received theoretical and empirical attention, less is known about how recombination rate itself evolves and what influence this has on evolutionary processes within sexually reproducing organisms. Here, we explore the patterns of, and processes governing recombination in eukaryotes. We summarize patterns of variation, integrating current knowledge with an analysis of linkage map data in 353 organisms. We then discuss proximate and ultimate processes governing recombination rate variation and consider how these influence evolutionary processes. Genome-wide recombination rates (cM/Mb) can vary more than tenfold across eukaryotes, and there is large variation in the distribution of recombination events across closely related taxa, populations and individuals. We discuss how variation in rate and distribution relates to genome architecture, genetic and epigenetic mechanisms, sex, environmental perturbations and variable selective pressures. There has been great progress in determining the molecular mechanisms governing recombination, and with the continued development of new modelling and empirical approaches, there is now also great opportunity to further our understanding of how and why recombination rate varies. This article is part of the themed issue ‘Evolutionary causes and consequences of recombination rate variation in sexual organisms’. PMID:29109219

Nutrient addition shifts plant community composition towards earlier flowering species in some prairie ecoregions in the U.S. Central Plains

USDA-ARS?s Scientific Manuscript database

The distribution of flowering across the growing season is governed by each species’ evolutionary history and climatic variability. However, global change factors, such as eutrophication and exotic species invasion, can alter plant community composition and thus change flowering distribution. We ex...

CRYPTIC NEOGENE VICARIANCE AND QUATERNARY DISPERSAL OF THE RED-SPOTTED TOAD (BUFO PUNCTATUS) INSIGHTS ON THE EVOLUTION OF NORTH AMERICAN WARM DESERT BIOTAS

EPA Science Inventory

We define the geographic distributions of embedded evolutionary mitochondrial DNA (mtDNA) lineages (clades) within a broadly distributed, arid- dwelling toad, Bufo punctatus, and evaluate these patterns as they relate to hypothesized vicariant events leading to the formation of b...

Evolutionary dynamics of taxonomic structure

PubMed Central

Foote, Michael

2012-01-01

The distribution of species among genera and higher taxa has largely untapped potential to reveal among-clade variation in rates of origination and extinction. The probability distribution of the number of species within a genus is modelled with a stochastic, time-homogeneous birth–death model having two parameters: the rate of species extinction, μ, and the rate of genus origination, γ, each scaled as a multiple of the rate of within-genus speciation, λ. The distribution is more sensitive to γ than to μ, although μ affects the size of the largest genera. The species : genus ratio depends strongly on both γ and μ, and so is not a good diagnostic of evolutionary dynamics. The proportion of monotypic genera, however, depends mainly on γ, and so may provide an index of the genus origination rate. Application to living marine molluscs of New Zealand shows that bivalves have a higher relative rate of genus origination than gastropods. This is supported by the analysis of palaeontological data. This concordance suggests that analysis of living taxonomic distributions may allow inference of macroevolutionary dynamics even without a fossil record. PMID:21865239

Adiabatic theory for the population distribution in the evolutionary minority game

NASA Astrophysics Data System (ADS)

Chen, Kan; Wang, Bing-Hong; Yuan, Baosheng

2004-02-01

We study the evolutionary minority game (EMG) using a statistical mechanics approach. We derive a theory for the steady-state population distribution of the agents. The theory is based on an “adiabatic approximation” in which short time fluctuations in the population distribution are integrated out to obtain an effective equation governing the steady-state distribution. We discover the mechanism for the transition from segregation (into opposing groups) to clustering (towards cautious behaviors). The transition is determined by two generic factors: the market impact (of the agents’ own actions) and the short time market inefficiency (arbitrage opportunities) due to fluctuations in the numbers of agents using opposite strategies. A large market impact favors “extreme” players who choose fixed opposite strategies, while large market inefficiency favors cautious players. The transition depends on the number of agents (N) and the effective rate of strategy switching. When N is small, the market impact is relatively large; this favors the extreme behaviors. Frequent strategy switching, on the other hand, leads to a clustering of the cautious agents.

Does the evolutionary conservation of microsatellite loci imply function?

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

Shriver, M.D.; Deka, R.; Ferrell, R.E.

Microsatellites are highly polymorphic tandem arrays of short (1-6 bp) sequence motifs which have been found widely distributed in the genomes of all eukaryotes. We have analyzed allele frequency data on 16 microsatellite loci typed in the great apes (human, chimp, orangutan, and gorilla). The majority of these loci (13) were isolated from human genomic libraries; three were cloned from chimpanzee genomic DNA. Most of these loci are not only present in all apes species, but are polymorphic with comparable levels of heterozygosity and have alleles which overlap in size. The extent of divergence of allele frequencies among these fourmore » species were studies using the stepwise-weighted genetic distance (Dsw), which was previously shown to conform to linearity with evolutionary time since divergence for loci where mutations exist in a stepwise fashion. The phylogenetic tree of the great apes constructed from this distance matrix was consistent with the expected topology, with a high bootstrap confidence (82%) for the human/chimp clade. However, the allele frequency distributions of these species are 10 times more similar to each other than expected when they were calibrated with a conservative estimate of the time since separation of humans and the apes. These results are in agreement with sequence-based surveys of microsatellites which have demonstrated that they are highly (90%) conserved over short periods of evolutionary time (< 10 million years) and moderately (30%) conserved over long periods of evolutionary time (> 60-80 million years). This evolutionary conservation has prompted some authors to speculate that there are functional constraints on microsatellite loci. In contrast, the presence of directional bias of mutations with constraints and/or selection against aberrant sized alleles can explain these results.« less

Revisiting the age, evolutionary history and species level diversity of the genus Hydra (Cnidaria: Hydrozoa).

PubMed

Schwentner, Martin; Bosch, Thomas C G

2015-10-01

The genus Hydra has long served as a model system in comparative immunology, developmental and evolutionary biology. Despite its relevance for fundamental research, Hydra's evolutionary origins and species level diversity are not well understood. Detailed previous studies using molecular techniques identified several clades within Hydra, but how these are related to described species remained largely an open question. In the present study, we compiled all published sequence data for three mitochondrial and nuclear genes (COI, 16S and ITS), complemented these with some new sequence data and delimited main genetic lineages (=hypothetical species) objectively by employing two DNA barcoding approaches. Conclusions on the species status of these main lineages were based on inferences of reproductive isolation. Relevant divergence times within Hydra were estimated based on relaxed molecular clock analyses with four genes (COI, 16S, EF1α and 28S) and four cnidarians fossil calibration points All in all, 28 main lineages could be delimited, many more than anticipated from earlier studies. Because allopatric distributions were common, inferences of reproductive isolation often remained ambiguous but reproductive isolation was rarely refuted. Our results support three major conclusions which are central for Hydra research: (1) species level diversity was underestimated by molecular studies; (2) species affiliations of several crucial 'workhorses' of Hydra evolutionary research were wrong and (3) crown group Hydra originated ∼200mya. Our results demonstrate that the taxonomy of Hydra requires a thorough revision and that evolutionary studies need to take this into account when interspecific comparisons are made. Hydra originated on Pangea. Three of four extant groups evolved ∼70mya ago, possibly on the northern landmass of Laurasia. Consequently, Hydra's cosmopolitan distribution is the result of transcontinental and transoceanic dispersal. Copyright © 2015 Elsevier Inc. All rights reserved.

Numerical Control/Computer Aided Manufacturing (NC/CAM), A Descom Study

DTIC Science & Technology

1979-07-01

CAM machines operate directly from computers, but most get instructions in the form of punched tape. The applications of NC/CAM are virtually...Although most NC/CAM equipment is metal working, its applications include electronics manufacturing, glass making, food processing, materiel handling...drafting, woodworking, plastics and inspection, just to name a few. Numerical control, like most technologies, is an advancing and evolutionary process

Supermultiplicative Speedups of Probabilistic Model-Building Genetic Algorithms

DTIC Science & Technology

2009-02-01

physicists as well as practitioners in evolutionary computation. The project was later extended to the one-dimensional SK spin glass with power -law... Brasil ) 10. Yuji Sato (Hosei University, Japan) 11. Shunsukc Saruwatari (Tokyo University, Japan) 12. Jian-Hung Chen (Feng Chia University, Taiwan...scalability. In A. Tiwari, J. Knowlcs, E. Avincri, K. Dahal, and R. Roy (Eds.) Applications of Soft Computing: Recent Trends. Berlin: Springer (2006

Evolution of microgastropods (Ellobioidea, Carychiidae): integrating taxonomic, phylogenetic and evolutionary hypotheses

PubMed Central

2013-01-01

Background Current biodiversity patterns are considered largely the result of past climatic and tectonic changes. In an integrative approach, we combine taxonomic and phylogenetic hypotheses to analyze temporal and geographic diversification of epigean (Carychium) and subterranean (Zospeum) evolutionary lineages in Carychiidae (Eupulmonata, Ellobioidea). We explicitly test three hypotheses: 1) morphospecies encompass unrecognized evolutionary lineages, 2) limited dispersal results in a close genetic relationship of geographical proximally distributed taxa and 3) major climatic and tectonic events had an impact on lineage diversification within Carychiidae. Results Initial morphospecies assignments were investigated by different molecular delimitation approaches (threshold, ABGD, GMYC and SP). Despite a conservative delimitation strategy, carychiid morphospecies comprise a great number of unrecognized evolutionary lineages. We attribute this phenomenon to historic underestimation of morphological stasis and phenotypic variability amongst lineages. The first molecular phylogenetic hypothesis for the Carychiidae (based on COI, 16S and H3) reveals Carychium and Zospeum to be reciprocally monophyletic. Geographical proximally distributed lineages are often closely related. The temporal diversification of Carychiidae is best described by a constant rate model of diversification. The evolution of Carychiidae is characterized by relatively few (long distance) colonization events. We find support for an Asian origin of Carychium. Zospeum may have arrived in Europe before extant members of Carychium. Distantly related Carychium clades inhabit a wide spectrum of the available bioclimatic niche and demonstrate considerable niche overlap. Conclusions Carychiid taxonomy is in dire need of revision. An inferred wide distribution and variable phenotype suggest underestimated diversity in Zospeum. Several Carychium morphospecies are results of past taxonomic lumping. By collecting populations at their type locality, molecular investigations are able to link historic morphospecies assignments to their respective evolutionary lineage. We propose that rare founder populations initially colonized a continent or cave system. Subsequent passive dispersal into adjacent areas led to in situ pan-continental or mountain range diversifications. Major environmental changes did not influence carychiid diversification. However, certain molecular delimitation methods indicated a recent decrease in diversification rate. We attribute this decrease to protracted speciation. PMID:23343473

Building v/s Exploring Models: Comparing Learning of Evolutionary Processes through Agent-based Modeling

NASA Astrophysics Data System (ADS)

Wagh, Aditi

Two strands of work motivate the three studies in this dissertation. Evolutionary change can be viewed as a computational complex system in which a small set of rules operating at the individual level result in different population level outcomes under different conditions. Extensive research has documented students' difficulties with learning about evolutionary change (Rosengren et al., 2012), particularly in terms of levels slippage (Wilensky & Resnick, 1999). Second, though building and using computational models is becoming increasingly common in K-12 science education, we know little about how these two modalities compare. This dissertation adopts agent-based modeling as a representational system to compare these modalities in the conceptual context of micro-evolutionary processes. Drawing on interviews, Study 1 examines middle-school students' productive ways of reasoning about micro-evolutionary processes to find that the specific framing of traits plays a key role in whether slippage explanations are cued. Study 2, which was conducted in 2 schools with about 150 students, forms the crux of the dissertation. It compares learning processes and outcomes when students build their own models or explore a pre-built model. Analysis of Camtasia videos of student pairs reveals that builders' and explorers' ways of accessing rules, and sense-making of observed trends are of a different character. Builders notice rules through available blocks-based primitives, often bypassing their enactment while explorers attend to rules primarily through the enactment. Moreover, builders' sense-making of observed trends is more rule-driven while explorers' is more enactment-driven. Pre and posttests reveal that builders manifest a greater facility with accessing rules, providing explanations manifesting targeted assembly. Explorers use rules to construct explanations manifesting non-targeted assembly. Interviews reveal varying degrees of shifts away from slippage in both modalities, with students who built models not incorporating slippage explanations in responses. Study 3 compares these modalities with a control using traditional activities. Pre and posttests reveal that the two modalities manifested greater facility with accessing and assembling rules than the control. The dissertation offers implications for the design of learning environments for evolutionary change, design of the two modalities based on their strengths and weaknesses, and teacher training for the same.

Evolutionary Games with Randomly Changing Payoff Matrices

NASA Astrophysics Data System (ADS)

Yakushkina, Tatiana; Saakian, David B.; Bratus, Alexander; Hu, Chin-Kun

2015-06-01

Evolutionary games are used in various fields stretching from economics to biology. In most of these games a constant payoff matrix is assumed, although some works also consider dynamic payoff matrices. In this article we assume a possibility of switching the system between two regimes with different sets of payoff matrices. Potentially such a model can qualitatively describe the development of bacterial or cancer cells with a mutator gene present. A finite population evolutionary game is studied. The model describes the simplest version of annealed disorder in the payoff matrix and is exactly solvable at the large population limit. We analyze the dynamics of the model, and derive the equations for both the maximum and the variance of the distribution using the Hamilton-Jacobi equation formalism.

The SW Sex Phenomenon as an Evolutionary Stage of Cataclysmic Variables

NASA Astrophysics Data System (ADS)

Schmidtobreick, L.

From recent large observing campaigns, one finds that nearly all non- or weakly magnetic cataclysmic variables in the orbital period range between 2.8 and 4 hours are of SW Sex type and as such experience very high mass transfer rates. The evolution of cataclysmic variables as for any interacting binary is driven by angular momentum loss which results in a decrease of the orbital period on evolutionary time scales. In particular, all long-period systems need to cross the SW Sex regime of the orbital period distribution before entering the period gap. This makes the SW Sex phenomenon an evolutionary stage in the life of a cataclysmic variable. Here, I present a short overview of the current state of research on these systems.

The role of habitat choice in micro-evolutionary dynamics: An experimental study on the Mediterranean killifish Aphanius fasciatus (Cyprinodontidae).

PubMed

Angeletti, Dario; Sebbio, Claudia; Carlini, Alessandro; Strinati, Claudia; Nascetti, Giuseppe; Carere, Claudio; Cimmaruta, Roberta

2017-12-01

Habitat choice is defined as a nonrandom distribution of genotypes in different microhabitats. Therefore, it could exert a great impact on the genetic variance of natural populations by promoting genetic divergence, local adaptation, and may even lead to sympatric speciation. Despite this potential role in micro- and macro-evolutionary processes, there is little empirical evidence that the various genotypes within a population may differ in habitat choice-related behaviors. Here, we tested whether habitat choice may have contributed to genetic divergence within a local population of the Mediterranean killifish Aphanius fasciatus , which emerged between groups inhabiting microhabitats with different oxygen concentrations during previous field studies. In a first experiment, we studied the distribution of individuals in conditions of hypoxia and normoxia to test whether they had a different ability to shy away from a hypoxic environment; in a second experiment, we analyzed the individual behavior of fish separately in the two conditions, to verify whether they showed peculiar behavioral responses linked to a possible differential distribution. We then analyzed the six allozyme loci, whose allelic and genotypic frequencies were significantly divergent in the previous studies. In the first test, we found that the distribution of the two homozygote genotypes of the glucose-6-phosphate isomerase-1 locus (GPI-1) was significantly different between the hypoxic and the normoxic conditions. During the second test, all individuals were more active in hypoxic conditions, but the two GPI-1 homozygotes showed a significant difference in time spent performing surface breathing, which was consistent with their distribution observed in the first experiment. These results provide evidence that individual behavioral traits, related to genetic features, may lead to a nonrandom distribution of genotypes in heterogeneous although contiguous microhabitats and, consequently, that habitat choice can play a significant role in driving the micro-evolutionary dynamics of this species.

Evolutionary neurobiology and aesthetics.

PubMed

Smith, Christopher Upham

2005-01-01

If aesthetics is a human universal, it should have a neurobiological basis. Although use of all the senses is, as Aristotle noted, pleasurable, the distance senses are primarily involved in aesthetics. The aesthetic response emerges from the central processing of sensory input. This occurs very rapidly, beneath the level of consciousness, and only the feeling of pleasure emerges into the conscious mind. This is exemplified by landscape appreciation, where it is suggested that a computation built into the nervous system during Paleolithic hunter-gathering is at work. Another inbuilt computation leading to an aesthetic response is the part-whole relationship. This, it is argued, may be traced to the predator-prey "arms races" of evolutionary history. Mate selection also may be responsible for part of our response to landscape and visual art. Aesthetics lies at the core of human mentality, and its study is consequently of importance not only to philosophers and art critics but also to neurobiologists.

A hybrid multi-objective evolutionary algorithm for wind-turbine blade optimization

NASA Astrophysics Data System (ADS)

Sessarego, M.; Dixon, K. R.; Rival, D. E.; Wood, D. H.

2015-08-01

A concurrent-hybrid non-dominated sorting genetic algorithm (hybrid NSGA-II) has been developed and applied to the simultaneous optimization of the annual energy production, flapwise root-bending moment and mass of the NREL 5 MW wind-turbine blade. By hybridizing a multi-objective evolutionary algorithm (MOEA) with gradient-based local search, it is believed that the optimal set of blade designs could be achieved in lower computational cost than for a conventional MOEA. To measure the convergence between the hybrid and non-hybrid NSGA-II on a wind-turbine blade optimization problem, a computationally intensive case was performed using the non-hybrid NSGA-II. From this particular case, a three-dimensional surface representing the optimal trade-off between the annual energy production, flapwise root-bending moment and blade mass was achieved. The inclusion of local gradients in the blade optimization, however, shows no improvement in the convergence for this three-objective problem.

Decentralized Grid Scheduling with Evolutionary Fuzzy Systems

NASA Astrophysics Data System (ADS)

Fölling, Alexander; Grimme, Christian; Lepping, Joachim; Papaspyrou, Alexander

In this paper, we address the problem of finding workload exchange policies for decentralized Computational Grids using an Evolutionary Fuzzy System. To this end, we establish a non-invasive collaboration model on the Grid layer which requires minimal information about the participating High Performance and High Throughput Computing (HPC/HTC) centers and which leaves the local resource managers completely untouched. In this environment of fully autonomous sites, independent users are assumed to submit their jobs to the Grid middleware layer of their local site, which in turn decides on the delegation and execution either on the local system or on remote sites in a situation-dependent, adaptive way. We find for different scenarios that the exchange policies show good performance characteristics not only with respect to traditional metrics such as average weighted response time and utilization, but also in terms of robustness and stability in changing environments.

Derivative Trade Optimizing Model Utilizing GP Based on Behavioral Finance Theory

NASA Astrophysics Data System (ADS)

Matsumura, Koki; Kawamoto, Masaru

This paper proposed a new technique which makes the strategy trees for the derivative (option) trading investment decision based on the behavioral finance theory and optimizes it using evolutionary computation, in order to achieve high profitability. The strategy tree uses a technical analysis based on a statistical, experienced technique for the investment decision. The trading model is represented by various technical indexes, and the strategy tree is optimized by the genetic programming(GP) which is one of the evolutionary computations. Moreover, this paper proposed a method using the prospect theory based on the behavioral finance theory to set psychological bias for profit and deficit and attempted to select the appropriate strike price of option for the higher investment efficiency. As a result, this technique produced a good result and found the effectiveness of this trading model by the optimized dealings strategy.

Evolutionary psychology: new perspectives on cognition and motivation.

PubMed

Cosmides, Leda; Tooby, John

2013-01-01

Evolutionary psychology is the second wave of the cognitive revolution. The first wave focused on computational processes that generate knowledge about the world: perception, attention, categorization, reasoning, learning, and memory. The second wave views the brain as composed of evolved computational systems, engineered by natural selection to use information to adaptively regulate physiology and behavior. This shift in focus--from knowledge acquisition to the adaptive regulation of behavior--provides new ways of thinking about every topic in psychology. It suggests a mind populated by a large number of adaptive specializations, each equipped with content-rich representations, concepts, inference systems, and regulatory variables, which are functionally organized to solve the complex problems of survival and reproduction encountered by the ancestral hunter-gatherers from whom we are descended. We present recent empirical examples that illustrate how this approach has been used to discover new features of attention, categorization, reasoning, learning, emotion, and motivation.

Ecological and evolutionary dynamics of interconnectedness and modularity

PubMed Central

Nordbotten, Jan M.; Levin, Simon A.; Szathmáry, Eörs; Stenseth, Nils C.

2018-01-01

In this contribution, we develop a theoretical framework for linking microprocesses (i.e., population dynamics and evolution through natural selection) with macrophenomena (such as interconnectedness and modularity within an ecological system). This is achieved by developing a measure of interconnectedness for population distributions defined on a trait space (generalizing the notion of modularity on graphs), in combination with an evolution equation for the population distribution. With this contribution, we provide a platform for understanding under what environmental, ecological, and evolutionary conditions ecosystems evolve toward being more or less modular. A major contribution of this work is that we are able to decompose the overall driver of changes at the macro level (such as interconnectedness) into three components: (i) ecologically driven change, (ii) evolutionarily driven change, and (iii) environmentally driven change. PMID:29311333

Glassy Dynamics in the Adaptive Immune Response Prevents Autoimmune Disease

NASA Astrophysics Data System (ADS)

Sun, Jun; Deem, Michael

2006-03-01

The immune system normally protects the human host against death by infection. However, when an immune response is mistakenly directed at self antigens, autoimmune disease can occur. We describe a model of protein evolution to simulate the dynamics of the adaptive immune response to antigens. Computer simulations of the dynamics of antibody evolution show that different evolutionary mechanisms, namely gene segment swapping and point mutation, lead to different evolved antibody binding affinities. Although a combination of gene segment swapping and point mutation can yield a greater affinity to a specific antigen than point mutation alone, the antibodies so evolved are highly cross-reactive and would cause autoimmune disease, and this is not the chosen dynamics of the immune system. We suggest that in the immune system a balance has evolved between binding affinity and specificity in the mechanism for searching the amino acid sequence space of antibodies. Our model predicts that chronic infection may lead to autoimmune disease as well due to cross-reactivity and suggests a broad distribution for the time of onset of autoimmune disease due to chronic exposure. The slow search of antibody sequence space by point mutation leads to the broad of distribution times.

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.

WNV Typer: a server for genotyping of West Nile viruses using an alignment-free method based on a return time distribution.

PubMed

Kolekar, Pandurang; Hake, Nilesh; Kale, Mohan; Kulkarni-Kale, Urmila

2014-03-01

West Nile virus (WNV), genus Flavivirus, family Flaviviridae, is a major cause of viral encephalitis with broad host range and global spread. The virus has undergone a series of evolutionary changes with emergence of various genotypic lineages that are known to differ in type and severity of the diseases caused. Currently, genotyping is carried out using molecular phylogeny of complete coding sequences and genotype is assigned based on proximity to reference genotypes in tree topology. Efficient epidemiological surveillance of WNVs demands development of objective criteria for typing. An alignment-free approach based on return time distribution (RTD) of k-mers has been validated for genotyping of WNVs. The RTDs of complete genome sequences at k=7 were found to be optimum for classification of the known lineages of WNVs as well as for genotyping. It provides time and computationally efficient alternative for genome based annotation of WNV lineages. The development of a WNV Typer server based on RTD is described (http://bioinfo.net.in/wnv/homepage.html). Both the method and the server have 100% sensitivity and specificity. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Distributed digital signal processors for multi-body flexible structures

NASA Technical Reports Server (NTRS)

Lee, Gordon K. F.

1992-01-01

Multi-body flexible structures, such as those currently under investigation in spacecraft design, are large scale (high-order) dimensional systems. Controlling and filtering such structures is a computationally complex problem. This is particularly important when many sensors and actuators are located along the structure and need to be processed in real time. This report summarizes research activity focused on solving the signal processing (that is, information processing) issues of multi-body structures. A distributed architecture is developed in which single loop processors are employed for local filtering and control. By implementing such a philosophy with an embedded controller configuration, a supervising controller may be used to process global data and make global decisions as the local devices are processing local information. A hardware testbed, a position controller system for a servo motor, is employed to illustrate the capabilities of the embedded controller structure. Several filtering and control structures which can be modeled as rational functions can be implemented on the system developed in this research effort. Thus the results of the study provide a support tool for many Control/Structure Interaction (CSI) NASA testbeds such as the Evolutionary model and the nine-bay truss structure.

PIGD: a database for intronless genes in the Poaceae.

PubMed

Yan, Hanwei; Jiang, Cuiping; Li, Xiaoyu; Sheng, Lei; Dong, Qing; Peng, Xiaojian; Li, Qian; Zhao, Yang; Jiang, Haiyang; Cheng, Beijiu

2014-10-01

Intronless genes are a feature of prokaryotes; however, they are widespread and unequally distributed among eukaryotes and represent an important resource to study the evolution of gene architecture. Although many databases on exons and introns exist, there is currently no cohesive database that collects intronless genes in plants into a single database. In this study, we present the Poaceae Intronless Genes Database (PIGD), a user-friendly web interface to explore information on intronless genes from different plants. Five Poaceae species, Sorghum bicolor, Zea mays, Setaria italica, Panicum virgatum and Brachypodium distachyon, are included in the current release of PIGD. Gene annotations and sequence data were collected and integrated from different databases. The primary focus of this study was to provide gene descriptions and gene product records. In addition, functional annotations, subcellular localization prediction and taxonomic distribution are reported. PIGD allows users to readily browse, search and download data. BLAST and comparative analyses are also provided through this online database, which is available at http://pigd.ahau.edu.cn/. PIGD provides a solid platform for the collection, integration and analysis of intronless genes in the Poaceae. As such, this database will be useful for subsequent bio-computational analysis in comparative genomics and evolutionary studies.

Computational complexity of ecological and evolutionary spatial dynamics

PubMed Central

Ibsen-Jensen, Rasmus; Chatterjee, Krishnendu; Nowak, Martin A.

2015-01-01

There are deep, yet largely unexplored, connections between computer science and biology. Both disciplines examine how information proliferates in time and space. Central results in computer science describe the complexity of algorithms that solve certain classes of problems. An algorithm is deemed efficient if it can solve a problem in polynomial time, which means the running time of the algorithm is a polynomial function of the length of the input. There are classes of harder problems for which the fastest possible algorithm requires exponential time. Another criterion is the space requirement of the algorithm. There is a crucial distinction between algorithms that can find a solution, verify a solution, or list several distinct solutions in given time and space. The complexity hierarchy that is generated in this way is the foundation of theoretical computer science. Precise complexity results can be notoriously difficult. The famous question whether polynomial time equals nondeterministic polynomial time (i.e., P = NP) is one of the hardest open problems in computer science and all of mathematics. Here, we consider simple processes of ecological and evolutionary spatial dynamics. The basic question is: What is the probability that a new invader (or a new mutant) will take over a resident population? We derive precise complexity results for a variety of scenarios. We therefore show that some fundamental questions in this area cannot be answered by simple equations (assuming that P is not equal to NP). PMID:26644569

Body size distribution of the dinosaurs.

PubMed

O'Gorman, Eoin J; Hone, David W E

2012-01-01

The distribution of species body size is critically important for determining resource use within a group or clade. It is widely known that non-avian dinosaurs were the largest creatures to roam the Earth. There is, however, little understanding of how maximum species body size was distributed among the dinosaurs. Do they share a similar distribution to modern day vertebrate groups in spite of their large size, or did they exhibit fundamentally different distributions due to unique evolutionary pressures and adaptations? Here, we address this question by comparing the distribution of maximum species body size for dinosaurs to an extensive set of extant and extinct vertebrate groups. We also examine the body size distribution of dinosaurs by various sub-groups, time periods and formations. We find that dinosaurs exhibit a strong skew towards larger species, in direct contrast to modern day vertebrates. This pattern is not solely an artefact of bias in the fossil record, as demonstrated by contrasting distributions in two major extinct groups and supports the hypothesis that dinosaurs exhibited a fundamentally different life history strategy to other terrestrial vertebrates. A disparity in the size distribution of the herbivorous Ornithischia and Sauropodomorpha and the largely carnivorous Theropoda suggests that this pattern may have been a product of a divergence in evolutionary strategies: herbivorous dinosaurs rapidly evolved large size to escape predation by carnivores and maximise digestive efficiency; carnivores had sufficient resources among juvenile dinosaurs and non-dinosaurian prey to achieve optimal success at smaller body size.

Body Size Distribution of the Dinosaurs

PubMed Central

O’Gorman, Eoin J.; Hone, David W. E.

2012-01-01

The distribution of species body size is critically important for determining resource use within a group or clade. It is widely known that non-avian dinosaurs were the largest creatures to roam the Earth. There is, however, little understanding of how maximum species body size was distributed among the dinosaurs. Do they share a similar distribution to modern day vertebrate groups in spite of their large size, or did they exhibit fundamentally different distributions due to unique evolutionary pressures and adaptations? Here, we address this question by comparing the distribution of maximum species body size for dinosaurs to an extensive set of extant and extinct vertebrate groups. We also examine the body size distribution of dinosaurs by various sub-groups, time periods and formations. We find that dinosaurs exhibit a strong skew towards larger species, in direct contrast to modern day vertebrates. This pattern is not solely an artefact of bias in the fossil record, as demonstrated by contrasting distributions in two major extinct groups and supports the hypothesis that dinosaurs exhibited a fundamentally different life history strategy to other terrestrial vertebrates. A disparity in the size distribution of the herbivorous Ornithischia and Sauropodomorpha and the largely carnivorous Theropoda suggests that this pattern may have been a product of a divergence in evolutionary strategies: herbivorous dinosaurs rapidly evolved large size to escape predation by carnivores and maximise digestive efficiency; carnivores had sufficient resources among juvenile dinosaurs and non-dinosaurian prey to achieve optimal success at smaller body size. PMID:23284818

The Proposal of a Evolutionary Strategy Generating the Data Structures Based on a Horizontal Tree for the Tests

NASA Astrophysics Data System (ADS)

Żukowicz, Marek; Markiewicz, Michał

2016-09-01

The aim of the article is to present a mathematical definition of the object model, that is known in computer science as TreeList and to show application of this model for design evolutionary algorithm, that purpose is to generate structures based on this object. The first chapter introduces the reader to the problem of presenting data using the TreeList object. The second chapter describes the problem of testing data structures based on TreeList. The third one shows a mathematical model of the object TreeList and the parameters, used in determining the utility of structures created through this model and in evolutionary strategy, that generates these structures for testing purposes. The last chapter provides a brief summary and plans for future research related to the algorithm presented in the article.

Parametric Sensitivity Analysis of Oscillatory Delay Systems with an Application to Gene Regulation.

PubMed

Ingalls, Brian; Mincheva, Maya; Roussel, Marc R

2017-07-01

A parametric sensitivity analysis for periodic solutions of delay-differential equations is developed. Because phase shifts cause the sensitivity coefficients of a periodic orbit to diverge, we focus on sensitivities of the extrema, from which amplitude sensitivities are computed, and of the period. Delay-differential equations are often used to model gene expression networks. In these models, the parametric sensitivities of a particular genotype define the local geometry of the evolutionary landscape. Thus, sensitivities can be used to investigate directions of gradual evolutionary change. An oscillatory protein synthesis model whose properties are modulated by RNA interference is used as an example. This model consists of a set of coupled delay-differential equations involving three delays. Sensitivity analyses are carried out at several operating points. Comments on the evolutionary implications of the results are offered.

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.

Upon accounting for the impact of isoenzyme loss, gene deletion costs anticorrelate with their evolutionary rates

DOE PAGES

Jacobs, Christopher; Lambourne, Luke; Xia, Yu; ...

2017-01-20

Here, system-level metabolic network models enable the computation of growth and metabolic phenotypes from an organism's genome. In particular, flux balance approaches have been used to estimate the contribution of individual metabolic genes to organismal fitness, offering the opportunity to test whether such contributions carry information about the evolutionary pressure on the corresponding genes. Previous failure to identify the expected negative correlation between such computed gene-loss cost and sequence-derived evolutionary rates in Saccharomyces cerevisiae has been ascribed to a real biological gap between a gene's fitness contribution to an organism "here and now"º and the same gene's historical importance asmore » evidenced by its accumulated mutations over millions of years of evolution. Here we show that this negative correlation does exist, and can be exposed by revisiting a broadly employed assumption of flux balance models. In particular, we introduce a new metric that we call "function-loss cost", which estimates the cost of a gene loss event as the total potential functional impairment caused by that loss. This new metric displays significant negative correlation with evolutionary rate, across several thousand minimal environments. We demonstrate that the improvement gained using function-loss cost over gene-loss cost is explained by replacing the base assumption that isoenzymes provide unlimited capacity for backup with the assumption that isoenzymes are completely non-redundant. We further show that this change of the assumption regarding isoenzymes increases the recall of epistatic interactions predicted by the flux balance model at the cost of a reduction in the precision of the predictions. In addition to suggesting that the gene-to-reaction mapping in genome-scale flux balance models should be used with caution, our analysis provides new evidence that evolutionary gene importance captures much more than strict essentiality.« less

Upon accounting for the impact of isoenzyme loss, gene deletion costs anticorrelate with their evolutionary rates

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

Jacobs, Christopher; Lambourne, Luke; Xia, Yu

Here, system-level metabolic network models enable the computation of growth and metabolic phenotypes from an organism's genome. In particular, flux balance approaches have been used to estimate the contribution of individual metabolic genes to organismal fitness, offering the opportunity to test whether such contributions carry information about the evolutionary pressure on the corresponding genes. Previous failure to identify the expected negative correlation between such computed gene-loss cost and sequence-derived evolutionary rates in Saccharomyces cerevisiae has been ascribed to a real biological gap between a gene's fitness contribution to an organism "here and now"º and the same gene's historical importance asmore » evidenced by its accumulated mutations over millions of years of evolution. Here we show that this negative correlation does exist, and can be exposed by revisiting a broadly employed assumption of flux balance models. In particular, we introduce a new metric that we call "function-loss cost", which estimates the cost of a gene loss event as the total potential functional impairment caused by that loss. This new metric displays significant negative correlation with evolutionary rate, across several thousand minimal environments. We demonstrate that the improvement gained using function-loss cost over gene-loss cost is explained by replacing the base assumption that isoenzymes provide unlimited capacity for backup with the assumption that isoenzymes are completely non-redundant. We further show that this change of the assumption regarding isoenzymes increases the recall of epistatic interactions predicted by the flux balance model at the cost of a reduction in the precision of the predictions. In addition to suggesting that the gene-to-reaction mapping in genome-scale flux balance models should be used with caution, our analysis provides new evidence that evolutionary gene importance captures much more than strict essentiality.« less

Faster Evolution of More Multifunctional Logic Circuits

NASA Technical Reports Server (NTRS)

Stoica, Adrian; Zebulum, Ricardo

2005-01-01

A modification in a method of automated evolutionary synthesis of voltage-controlled multifunctional logic circuits makes it possible to synthesize more circuits in less time. Prior to the modification, the computations for synthesizing a four-function logic circuit by this method took about 10 hours. Using the method as modified, it is possible to synthesize a six-function circuit in less than half an hour. The concepts of automated evolutionary synthesis and voltage-controlled multifunctional logic circuits were described in a number of prior NASA Tech Briefs articles. To recapitulate: A circuit is designed to perform one of several different logic functions, depending on the value of an applied control voltage. The circuit design is synthesized following an automated evolutionary approach that is so named because it is modeled partly after the repetitive trial-and-error process of biological evolution. In this process, random populations of integer strings that encode electronic circuits play a role analogous to that of chromosomes. An evolved circuit is tested by computational simulation (prior to testing in real hardware to verify a final design). Then, in a fitness-evaluation step, responses of the circuit are compared with specifications of target responses and circuits are ranked according to how close they come to satisfying specifications. The results of the evaluation provide guidance for refining designs through further iteration.

Cost versus life cycle assessment-based environmental impact optimization of drinking water production plants.

PubMed

Capitanescu, F; Rege, S; Marvuglia, A; Benetto, E; Ahmadi, A; Gutiérrez, T Navarrete; Tiruta-Barna, L

2016-07-15

Empowering decision makers with cost-effective solutions for reducing industrial processes environmental burden, at both design and operation stages, is nowadays a major worldwide concern. The paper addresses this issue for the sector of drinking water production plants (DWPPs), seeking for optimal solutions trading-off operation cost and life cycle assessment (LCA)-based environmental impact while satisfying outlet water quality criteria. This leads to a challenging bi-objective constrained optimization problem, which relies on a computationally expensive intricate process-modelling simulator of the DWPP and has to be solved with limited computational budget. Since mathematical programming methods are unusable in this case, the paper examines the performances in tackling these challenges of six off-the-shelf state-of-the-art global meta-heuristic optimization algorithms, suitable for such simulation-based optimization, namely Strength Pareto Evolutionary Algorithm (SPEA2), Non-dominated Sorting Genetic Algorithm (NSGA-II), Indicator-based Evolutionary Algorithm (IBEA), Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), Differential Evolution (DE), and Particle Swarm Optimization (PSO). The results of optimization reveal that good reduction in both operating cost and environmental impact of the DWPP can be obtained. Furthermore, NSGA-II outperforms the other competing algorithms while MOEA/D and DE perform unexpectedly poorly. Copyright © 2016 Elsevier Ltd. All rights reserved.

Computational methods using weighed-extreme learning machine to predict protein self-interactions with protein evolutionary information.

PubMed

An, Ji-Yong; Zhang, Lei; Zhou, Yong; Zhao, Yu-Jun; Wang, Da-Fu

2017-08-18

Self-interactions Proteins (SIPs) is important for their biological activity owing to the inherent interaction amongst their secondary structures or domains. However, due to the limitations of experimental Self-interactions detection, one major challenge in the study of prediction SIPs is how to exploit computational approaches for SIPs detection based on evolutionary information contained protein sequence. In the work, we presented a novel computational approach named WELM-LAG, which combined the Weighed-Extreme Learning Machine (WELM) classifier with Local Average Group (LAG) to predict SIPs based on protein sequence. The major improvement of our method lies in presenting an effective feature extraction method used to represent candidate Self-interactions proteins by exploring the evolutionary information embedded in PSI-BLAST-constructed position specific scoring matrix (PSSM); and then employing a reliable and robust WELM classifier to carry out classification. In addition, the Principal Component Analysis (PCA) approach is used to reduce the impact of noise. The WELM-LAG method gave very high average accuracies of 92.94 and 96.74% on yeast and human datasets, respectively. Meanwhile, we compared it with the state-of-the-art support vector machine (SVM) classifier and other existing methods on human and yeast datasets, respectively. Comparative results indicated that our approach is very promising and may provide a cost-effective alternative for predicting SIPs. In addition, we developed a freely available web server called WELM-LAG-SIPs to predict SIPs. The web server is available at http://219.219.62.123:8888/WELMLAG/ .

Nature-Inspired Cognitive Evolution to Play MS. Pac-Man

NASA Astrophysics Data System (ADS)

Tan, Tse Guan; Teo, Jason; Anthony, Patricia

Recent developments in nature-inspired computation have heightened the need for research into the three main areas of scientific, engineering and industrial applications. Some approaches have reported that it is able to solve dynamic problems and very useful for improving the performance of various complex systems. So far however, there has been little discussion about the effectiveness of the application of these models to computer and video games in particular. The focus of this research is to explore the hybridization of nature-inspired computation methods for optimization of neural network-based cognition in video games, in this case the combination of a neural network with an evolutionary algorithm. In essence, a neural network is an attempt to mimic the extremely complex human brain system, which is building an artificial brain that is able to self-learn intelligently. On the other hand, an evolutionary algorithm is to simulate the biological evolutionary processes that evolve potential solutions in order to solve the problems or tasks by applying the genetic operators such as crossover, mutation and selection into the solutions. This paper investigates the abilities of Evolution Strategies (ES) to evolve feed-forward artificial neural network's internal parameters (i.e. weight and bias values) for automatically generating Ms. Pac-man controllers. The main objective of this game is to clear a maze of dots while avoiding the ghosts and to achieve the highest possible score. The experimental results show that an ES-based system can be successfully applied to automatically generate artificial intelligence for a complex, dynamic and highly stochastic video game environment.

Variations on a Theme.

ERIC Educational Resources Information Center

Vitali, Julius

1990-01-01

Explains an experimental photographic technique starting with a realistic photograph. Using various media (oil painting, video/computer photography, and multiprint imagery) the artist changes the photograph's compositional elements. Outlines the phases of this evolutionary process. Illustrates four images created by the technique. (DB)

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

We integrated classic and Bayesian phylogeographic tools with a paleodistribution modeling approach to study the historical demographic processes that shaped the distribution of the invasive ant Wasmannia auropunctata in its native South America. We generated mitochondrial Cytochrome Oxidase I seque...

Mammalian Comparative Genomics Reveals Genetic and Epigenetic Features Associated with Genome Reshuffling in Rodentia

PubMed Central

Capilla, Laia; Sánchez-Guillén, Rosa Ana; Farré, Marta; Paytuví-Gallart, Andreu; Malinverni, Roberto; Ventura, Jacint; Larkin, Denis M.

2016-01-01

Abstract Understanding how mammalian genomes have been reshuffled through structural changes is fundamental to the dynamics of its composition, evolutionary relationships between species and, in the long run, speciation. In this work, we reveal the evolutionary genomic landscape in Rodentia, the most diverse and speciose mammalian order, by whole-genome comparisons of six rodent species and six representative outgroup mammalian species. The reconstruction of the evolutionary breakpoint regions across rodent phylogeny shows an increased rate of genome reshuffling that is approximately two orders of magnitude greater than in other mammalian species here considered. We identified novel lineage and clade-specific breakpoint regions within Rodentia and analyzed their gene content, recombination rates and their relationship with constitutive lamina genomic associated domains, DNase I hypersensitivity sites and chromatin modifications. We detected an accumulation of protein-coding genes in evolutionary breakpoint regions, especially genes implicated in reproduction and pheromone detection and mating. Moreover, we found an association of the evolutionary breakpoint regions with active chromatin state landscapes, most probably related to gene enrichment. Our results have two important implications for understanding the mechanisms that govern and constrain mammalian genome evolution. The first is that the presence of genes related to species-specific phenotypes in evolutionary breakpoint regions reinforces the adaptive value of genome reshuffling. Second, that chromatin conformation, an aspect that has been often overlooked in comparative genomic studies, might play a role in modeling the genomic distribution of evolutionary breakpoints. PMID:28175287

Mammalian Comparative Genomics Reveals Genetic and Epigenetic Features Associated with Genome Reshuffling in Rodentia.

PubMed

Capilla, Laia; Sánchez-Guillén, Rosa Ana; Farré, Marta; Paytuví-Gallart, Andreu; Malinverni, Roberto; Ventura, Jacint; Larkin, Denis M; Ruiz-Herrera, Aurora

2016-12-01

Understanding how mammalian genomes have been reshuffled through structural changes is fundamental to the dynamics of its composition, evolutionary relationships between species and, in the long run, speciation. In this work, we reveal the evolutionary genomic landscape in Rodentia, the most diverse and speciose mammalian order, by whole-genome comparisons of six rodent species and six representative outgroup mammalian species. The reconstruction of the evolutionary breakpoint regions across rodent phylogeny shows an increased rate of genome reshuffling that is approximately two orders of magnitude greater than in other mammalian species here considered. We identified novel lineage and clade-specific breakpoint regions within Rodentia and analyzed their gene content, recombination rates and their relationship with constitutive lamina genomic associated domains, DNase I hypersensitivity sites and chromatin modifications. We detected an accumulation of protein-coding genes in evolutionary breakpoint regions, especially genes implicated in reproduction and pheromone detection and mating. Moreover, we found an association of the evolutionary breakpoint regions with active chromatin state landscapes, most probably related to gene enrichment. Our results have two important implications for understanding the mechanisms that govern and constrain mammalian genome evolution. The first is that the presence of genes related to species-specific phenotypes in evolutionary breakpoint regions reinforces the adaptive value of genome reshuffling. Second, that chromatin conformation, an aspect that has been often overlooked in comparative genomic studies, might play a role in modeling the genomic distribution of evolutionary breakpoints.

Effect of the spatial autocorrelation of empty sites on the evolution of cooperation

NASA Astrophysics Data System (ADS)

Zhang, Hui; Wang, Li; Hou, Dongshuang

2016-02-01

An evolutionary game model is constructed to investigate the spatial autocorrelation of empty sites on the evolution of cooperation. Each individual is assumed to imitate the strategy of the one who scores the highest in its neighborhood including itself. Simulation results illustrate that the evolutionary dynamics based on the Prisoner's Dilemma game (PD) depends severely on the initial conditions, while the Snowdrift game (SD) is hardly affected by that. A high degree of autocorrelation of empty sites is beneficial for the evolution of cooperation in the PD, whereas it shows diversification effects depending on the parameter of temptation to defect in the SD. Moreover, for the repeated game with three strategies, 'always defect' (ALLD), 'tit-for-tat' (TFT), and 'always cooperate' (ALLC), simulations reveal that an amazing evolutionary diversity appears for varying of parameters of the temptation to defect and the probability of playing in the next round of the game. The spatial autocorrelation of empty sites can have profound effects on evolutionary dynamics (equilibrium and oscillation) and spatial distribution.

Geography and major host evolutionary transitions shape the resource use of plant parasites

PubMed Central

Calatayud, Joaquín; Hórreo, José Luis; Madrigal-González, Jaime; Migeon, Alain; Rodríguez, Miguel Á.; Magalhães, Sara; Hortal, Joaquín

2016-01-01

The evolution of resource use in herbivores has been conceptualized as an analog of the theory of island biogeography, assuming that plant species are islands separated by phylogenetic distances. Despite its usefulness, this analogy has paradoxically led to neglecting real biogeographical processes in the study of macroevolutionary patterns of herbivore–plant interactions. Here we show that host use is mostly determined by the geographical cooccurrence of hosts and parasites in spider mites (Tetranychidae), a globally distributed group of plant parasites. Strikingly, geography accounts for most of the phylogenetic signal in host use by these parasites. Beyond geography, only evolutionary transitions among major plant lineages (i.e., gymnosperms, commelinids, and eudicots) shape resource use patterns in these herbivores. Still, even these barriers have been repeatedly overcome in evolutionary time, resulting in phylogenetically diverse parasite communities feeding on similar hosts. Therefore, our results imply that patterns of apparent evolutionary conservatism may largely be a byproduct of the geographic cooccurrence of hosts and parasites. PMID:27535932

Geography and major host evolutionary transitions shape the resource use of plant parasites.

PubMed

Calatayud, Joaquín; Hórreo, José Luis; Madrigal-González, Jaime; Migeon, Alain; Rodríguez, Miguel Á; Magalhães, Sara; Hortal, Joaquín

2016-08-30

The evolution of resource use in herbivores has been conceptualized as an analog of the theory of island biogeography, assuming that plant species are islands separated by phylogenetic distances. Despite its usefulness, this analogy has paradoxically led to neglecting real biogeographical processes in the study of macroevolutionary patterns of herbivore-plant interactions. Here we show that host use is mostly determined by the geographical cooccurrence of hosts and parasites in spider mites (Tetranychidae), a globally distributed group of plant parasites. Strikingly, geography accounts for most of the phylogenetic signal in host use by these parasites. Beyond geography, only evolutionary transitions among major plant lineages (i.e., gymnosperms, commelinids, and eudicots) shape resource use patterns in these herbivores. Still, even these barriers have been repeatedly overcome in evolutionary time, resulting in phylogenetically diverse parasite communities feeding on similar hosts. Therefore, our results imply that patterns of apparent evolutionary conservatism may largely be a byproduct of the geographic cooccurrence of hosts and parasites.

Evolutionary Dynamics and Diversity in Microbial Populations

NASA Astrophysics Data System (ADS)

Thompson, Joel; Fisher, Daniel

2013-03-01

Diseases such as flu and cancer adapt at an astonishing rate. In large part, viruses and cancers are so difficult to prevent because they are continually evolving. Controlling such ``evolutionary diseases'' requires a better understanding of the underlying evolutionary dynamics. It is conventionally assumed that adaptive mutations are rare and therefore will occur and sweep through the population in succession. Recent experiments using modern sequencing technologies have illuminated the many ways in which real population sequence data does not conform to the predictions of conventional theory. We consider a very simple model of asexual evolution and perform simulations in a range of parameters thought to be relevant for microbes and cancer. Simulation results reveal complex evolutionary dynamics typified by competition between lineages with different sets of adaptive mutations. This dynamical process leads to a distribution of mutant gene frequencies different than expected under the conventional assumption that adaptive mutations are rare. Simulated gene frequencies share several conspicuous features with data collected from laboratory-evolved yeast and the worldwide population of influenza.

Prevalence of cryptic species in morphologically uniform taxa - fast speciation and evolutionary radiation in Asian toads.

PubMed

Liu, Zuyao; Chen, Guoling; Zhu, Tianqi; Zeng, Zhaochi; Lyu, Zhitong; Wang, Jian; Messenger, Kevin; Greenberg, Anthony J; Guo, Zixiao; Yang, Ziheng; Shi, Suhua; Wang, Yingyong

2018-06-16

Diversity and distributions of cryptic species have long been a vexing issue. Identification of species boundaries is made difficult by the lack of obvious morphological differences. Here, we investigate the cryptic diversity and evolutionary history of an underappreciated group of Asian frog species (Megophrys) to explore the pattern and dynamic of amphibian cryptic species. We sequenced four mitochondrial genes and five nuclear genes and delineated species using multiple approaches, combining DNA and mating-call data. A Bayesian species tree was generated to estimate divergence times and to reconstruct ancestral ranges. Macroevolutionary analyses and hybridization tests were conducted to explore the evolutionary dynamics of this cryptic group. Our phylogenies support the current subgenera. We revealed 43 cryptic species, 158% higher than previously thought. The species-delimitation results were further confirmed by mating-call data and morphological divergence. We found that these Asian frogss entered China from the Sunda Shelf 48 Mya, followed by an ancient radiation event during middle Miocene. We confirmed the efficiency of the multispecies coalescent model for delimitation of species with low morphological diversity. Species diversity of Megophrys is severely underappreciated, and species distributions have been misestimated as a result. Copyright © 2018. Published by Elsevier Inc.

Enhancing Data Assimilation by Evolutionary Particle Filter and Markov Chain Monte Carlo

NASA Astrophysics Data System (ADS)

Moradkhani, H.; Abbaszadeh, P.; Yan, H.

2016-12-01

Particle Filters (PFs) have received increasing attention by the researchers from different disciplines in hydro-geosciences as an effective method to improve model predictions in nonlinear and non-Gaussian dynamical systems. The implication of dual state and parameter estimation by means of data assimilation in hydrology and geoscience has evolved since 2005 from SIR-PF to PF-MCMC and now to the most effective and robust framework through evolutionary PF approach based on Genetic Algorithm (GA) and Markov Chain Monte Carlo (MCMC), the so-called EPF-MCMC. In this framework, the posterior distribution undergoes an evolutionary process to update an ensemble of prior states that more closely resemble realistic posterior probability distribution. The premise of this approach is that the particles move to optimal position using the GA optimization coupled with MCMC increasing the number of effective particles, hence the particle degeneracy is avoided while the particle diversity is improved. The proposed algorithm is applied on a conceptual and highly nonlinear hydrologic model and the effectiveness, robustness and reliability of the method in jointly estimating the states and parameters and also reducing the uncertainty is demonstrated for few river basins across the United States.

Numerical simulation of evolutionary erodible bedforms using the particle finite element method

NASA Astrophysics Data System (ADS)

Bravo, Rafael; Becker, Pablo; Ortiz, Pablo

2017-07-01

This paper presents a numerical strategy for the simulation of flows with evolutionary erodible boundaries. The fluid equations are fully resolved in 3D, while the sediment transport is modelled using the Exner equation and solved with an explicit Lagrangian procedure based on a fixed 2D mesh. Flow and sediment are coupled in geometry by deforming the fluid mesh in the vertical direction and in velocities with the experimental sediment flux computed using the Meyer Peter Müller model. A comparison with real experiments on channels is performed, giving good agreement.

Application of Neural Network Optimized by Mind Evolutionary Computation in Building Energy Prediction

NASA Astrophysics Data System (ADS)

Song, Chen; Zhong-Cheng, Wu; Hong, Lv

2018-03-01

Building Energy forecasting plays an important role in energy management and plan. Using mind evolutionary algorithm to find the optimal network weights and threshold, to optimize the BP neural network, can overcome the problem of the BP neural network into a local minimum point. The optimized network is used for time series prediction, and the same month forecast, to get two predictive values. Then two kinds of predictive values are put into neural network, to get the final forecast value. The effectiveness of the method was verified by experiment with the energy value of three buildings in Hefei.

Geometric morphometrics and virtual anthropology: advances in human evolutionary studies.

PubMed

Rein, Thomas R; Harvati, Katerina

2014-01-01

Geometric morphometric methods have been increasingly used in paleoanthropology in the last two decades, lending greater power to the analysis and interpretation of the human fossil record. More recently the advent of the wide use of computed tomography and surface scanning, implemented in combination with geometric morphometrics (GM), characterizes a new approach, termed Virtual Anthropology (VA). These methodological advances have led to a number of developments in human evolutionary studies. We present some recent examples of GM and VA related research in human evolution with an emphasis on work conducted at the University of Tübingen and other German research institutions.

VizieR Online Data Catalog: Low-mass helium white dwarfs evolutionary models (Istrate+, 2016)

NASA Astrophysics Data System (ADS)

Istrate, A.; Marchant, P.; Tauris, T. M.; Langer, N.; Stancliffe, R. J.; Grassitelli, L.

2016-07-01

Evolutionary models of low-mass helium white dwarfs including element diffusion and rotational mixing. The WDs are produced considering binary evolution through the LMXB channel, with final WDs masses between ~0.16-~0.44. The models are computed using MESA, for different metallicities: Z=0.02, 0.01, 0.001 and 0.0002. For each metallicity, the models are divided in three categories: (1) basic (no diffusion nor rotation are considered) (2) diffusion (element diffusion is considered) (3) rotation+diffusion (both element diffusion and rotational mixing are considered) (4 data files).

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).

A First-Principles Model of Early Evolution: Emergence of Gene Families, Species, and Preferred Protein Folds

PubMed Central

Zeldovich, Konstantin B; Chen, Peiqiu; Shakhnovich, Boris E; Shakhnovich, Eugene I

2007-01-01

In this work we develop a microscopic physical model of early evolution where phenotype—organism life expectancy—is directly related to genotype—the stability of its proteins in their native conformations—which can be determined exactly in the model. Simulating the model on a computer, we consistently observe the “Big Bang” scenario whereby exponential population growth ensues as soon as favorable sequence–structure combinations (precursors of stable proteins) are discovered. Upon that, random diversity of the structural space abruptly collapses into a small set of preferred proteins. We observe that protein folds remain stable and abundant in the population at timescales much greater than mutation or organism lifetime, and the distribution of the lifetimes of dominant folds in a population approximately follows a power law. The separation of evolutionary timescales between discovery of new folds and generation of new sequences gives rise to emergence of protein families and superfamilies whose sizes are power-law distributed, closely matching the same distributions for real proteins. On the population level we observe emergence of species—subpopulations that carry similar genomes. Further, we present a simple theory that relates stability of evolving proteins to the sizes of emerging genomes. Together, these results provide a microscopic first-principles picture of how first-gene families developed in the course of early evolution. PMID:17630830

A first-principles model of early evolution: emergence of gene families, species, and preferred protein folds.

PubMed

Zeldovich, Konstantin B; Chen, Peiqiu; Shakhnovich, Boris E; Shakhnovich, Eugene I

2007-07-01

In this work we develop a microscopic physical model of early evolution where phenotype--organism life expectancy--is directly related to genotype--the stability of its proteins in their native conformations-which can be determined exactly in the model. Simulating the model on a computer, we consistently observe the "Big Bang" scenario whereby exponential population growth ensues as soon as favorable sequence-structure combinations (precursors of stable proteins) are discovered. Upon that, random diversity of the structural space abruptly collapses into a small set of preferred proteins. We observe that protein folds remain stable and abundant in the population at timescales much greater than mutation or organism lifetime, and the distribution of the lifetimes of dominant folds in a population approximately follows a power law. The separation of evolutionary timescales between discovery of new folds and generation of new sequences gives rise to emergence of protein families and superfamilies whose sizes are power-law distributed, closely matching the same distributions for real proteins. On the population level we observe emergence of species--subpopulations that carry similar genomes. Further, we present a simple theory that relates stability of evolving proteins to the sizes of emerging genomes. Together, these results provide a microscopic first-principles picture of how first-gene families developed in the course of early evolution.

Evolutionary Trails of Plant Group II Pyridoxal Phosphate-Dependent Decarboxylase Genes.

PubMed

Kumar, Rahul

2016-01-01

Type II pyridoxal phosphate-dependent decarboxylase (PLP_deC) enzymes play important metabolic roles during nitrogen metabolism. Recent evolutionary profiling of these genes revealed a sharp expansion of histidine decarboxylase genes in the members of Solanaceae family. In spite of the high sequence homology shared by PLP_deC orthologs, these enzymes display remarkable differences in their substrate specificities. Currently, limited information is available on the gene repertoires and substrate specificities of PLP_deCs which renders their precise annotation challenging and offers technical challenges in the immediate identification and biochemical characterization of their full gene complements in plants. Herein, we explored their evolutionary trails in a comprehensive manner by taking advantage of high-throughput data accessibility and computational approaches. We discussed the premise that has enabled an improved reconstruction of their evolutionary lineage and evaluated the factors offering constraints in their rapid functional characterization, till date. We envisage that the synthesized information herein would act as a catalyst for the rapid exploration of their biochemical specificity and physiological roles in more plant species.

Evolutionary design optimization of traffic signals applied to Quito city.

PubMed

Armas, Rolando; Aguirre, Hernán; Daolio, Fabio; Tanaka, Kiyoshi

2017-01-01

This work applies evolutionary computation and machine learning methods to study the transportation system of Quito from a design optimization perspective. It couples an evolutionary algorithm with a microscopic transport simulator and uses the outcome of the optimization process to deepen our understanding of the problem and gain knowledge about the system. The work focuses on the optimization of a large number of traffic lights deployed on a wide area of the city and studies their impact on travel time, emissions and fuel consumption. An evolutionary algorithm with specialized mutation operators is proposed to search effectively in large decision spaces, evolving small populations for a short number of generations. The effects of the operators combined with a varying mutation schedule are studied, and an analysis of the parameters of the algorithm is also included. In addition, hierarchical clustering is performed on the best solutions found in several runs of the algorithm. An analysis of signal clusters and their geolocation, estimation of fuel consumption, spatial analysis of emissions, and an analysis of signal coordination provide an overall picture of the systemic effects of the optimization process.

Evolutionary design optimization of traffic signals applied to Quito city

PubMed Central

2017-01-01

This work applies evolutionary computation and machine learning methods to study the transportation system of Quito from a design optimization perspective. It couples an evolutionary algorithm with a microscopic transport simulator and uses the outcome of the optimization process to deepen our understanding of the problem and gain knowledge about the system. The work focuses on the optimization of a large number of traffic lights deployed on a wide area of the city and studies their impact on travel time, emissions and fuel consumption. An evolutionary algorithm with specialized mutation operators is proposed to search effectively in large decision spaces, evolving small populations for a short number of generations. The effects of the operators combined with a varying mutation schedule are studied, and an analysis of the parameters of the algorithm is also included. In addition, hierarchical clustering is performed on the best solutions found in several runs of the algorithm. An analysis of signal clusters and their geolocation, estimation of fuel consumption, spatial analysis of emissions, and an analysis of signal coordination provide an overall picture of the systemic effects of the optimization process. PMID:29236733

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

Evolutionary game theory using agent-based methods.

PubMed

Adami, Christoph; Schossau, Jory; Hintze, Arend

2016-12-01

Evolutionary game theory is a successful mathematical framework geared towards understanding the selective pressures that affect the evolution of the strategies of agents engaged in interactions with potential conflicts. While a mathematical treatment of the costs and benefits of decisions can predict the optimal strategy in simple settings, more realistic settings such as finite populations, non-vanishing mutations rates, stochastic decisions, communication between agents, and spatial interactions, require agent-based methods where each agent is modeled as an individual, carries its own genes that determine its decisions, and where the evolutionary outcome can only be ascertained by evolving the population of agents forward in time. While highlighting standard mathematical results, we compare those to agent-based methods that can go beyond the limitations of equations and simulate the complexity of heterogeneous populations and an ever-changing set of interactors. We conclude that agent-based methods can predict evolutionary outcomes where purely mathematical treatments cannot tread (for example in the weak selection-strong mutation limit), but that mathematics is crucial to validate the computational simulations. Copyright © 2016 Elsevier B.V. All rights reserved.

Evolution-Inspired Computational Design of Symmetric Proteins.

PubMed

Voet, Arnout R D; Simoncini, David; Tame, Jeremy R H; Zhang, Kam Y J

2017-01-01

Monomeric proteins with a number of identical repeats creating symmetrical structures are potentially very valuable building blocks with a variety of bionanotechnological applications. As such proteins do not occur naturally, the emerging field of computational protein design serves as an excellent tool to create them from nonsymmetrical templates. Existing pseudo-symmetrical proteins are believed to have evolved from oligomeric precursors by duplication and fusion of identical repeats. Here we describe a computational workflow to reverse-engineer this evolutionary process in order to create stable proteins consisting of identical sequence repeats.

Computers in health care for the 21st century.

PubMed

O'Desky, R I; Ball, M J; Ball, E E

1990-03-01

As the world enters the last decade of the 20th Century, there is a great deal of speculation about the effect of computers on the future delivery of health care. In this article, the authors attempt to identify some of the evolving computer technologies and anticipate what effect they will have by the year 2000. Rather than listing potential accomplishments, each of the affected areas: hardware, software, health care systems and communications, are presented in an evolutionary manner so the reader can better appreciate where we have been and where we are going.

Evolutionary and biological metaphors for engineering design

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

Jakiela, M.

1994-12-31

Since computing became generally available, there has been strong interest in using computers to assist and automate engineering design processes. Specifically, for design optimization and automation, nonlinear programming and artificial intelligence techniques have been extensively studied. New computational techniques, based upon the natural processes of evolution, adaptation, and learing, are showing promise because of their generality and robustness. This presentation will describe the use of two such techniques, genetic algorithms and classifier systems, for a variety of engineering design problems. Structural topology optimization, meshing, and general engineering optimization are shown as example applications.

Launching "the evolution of cooperation".

PubMed

Axelrod, Robert

2012-04-21

This article describes three aspects of the author's early work on the evolution of the cooperation. First, it explains how the idea for a computer tournament for the iterated Prisoner's Dilemma was inspired by the artificial intelligence research on computer checkers and computer chess. Second, it shows how the vulnerability of simple reciprocity of misunderstanding or misimplementation can be eliminated with the addition of some degree of generosity or contrition. Third, it recounts the unusual collaboration between the author, a political scientist, and William D. Hamilton, an evolutionary biologist. Copyright © 2011 Elsevier Ltd. 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

Evolutionary radiation of earless frogs in the Andes: molecular phylogenetics and habitat shifts in high-elevation terrestrial breeding frogs

PubMed Central

Lehr, Edgar; Rabosky, Daniel L.

2018-01-01

The loss of hearing structures and loss of advertisement calls in many terrestrial breeding frogs (Strabomantidae) living at high elevations in South America are common and intriguing phenomena. The Andean frog genus Phrynopus Peters, 1873 has undergone an evolutionary radiation in which most species lack the tympanic membrane and tympanic annulus, yet the phylogenetic relationships among species in this group remain largely unknown. Here, we present an expanded molecular phylogeny of Phrynopus that includes 24 nominal species. Our phylogeny includes Phrynopus peruanus, the type species of the genus, and 10 other species for which genetic data were previously unavailable. We found strong support for monophyly of Phrynopus, and that two nominal species—Phrynopus curator and Phrynopus nicoleae—are junior synonyms of Phrynopus tribulosus. Using X-ray computed tomography (CT) imaging, we demonstrate that the absence of external hearing structures is associated with complete loss of the auditory skeletal elements (columella) in at least one member of the genus. We mapped the tympanum condition on to a species tree to infer whether the loss of hearing structures took place once or multiple times. We also assessed whether tympanum condition, body size, and body shape are associated with the elevational distribution and habitat use. We identified a single evolutionary transition that involved the loss of both the tympanic membrane and tympanic annulus, which in turn is correlated with the absence of advertisement calls. We also identified several species pairs where one species inhabits the Andean grassland and the other montane forest. When accounting for phylogenetic relatedness among species, we detected a significant pattern of increasing body size with increasing elevation. Additionally, species at higher elevations tend to develop shorter limbs, shorter head, and shorter snout than species living at lower elevations. Our findings strongly suggest a link between ecological divergence and morphological diversity of terrestrial breeding frogs living in montane gradients. PMID:29492332

Testing for shared biogeographic history in the lower Central American freshwater fish assemblage using comparative phylogeography: concerted, independent, or multiple evolutionary responses?

PubMed Central

Bagley, Justin C; Johnson, Jerald B

2014-01-01

A central goal of comparative phylogeography is determining whether codistributed species experienced (1) concerted evolutionary responses to past geological and climatic events, indicated by congruent spatial and temporal patterns (“concerted-response hypothesis”); (2) independent responses, indicated by spatial incongruence (“independent-response hypothesis”); or (3) multiple responses (“multiple-response hypothesis”), indicated by spatial congruence but temporal incongruence (“pseudocongruence”) or spatial and temporal incongruence (“pseudoincongruence”). We tested these competing hypotheses using DNA sequence data from three livebearing fish species codistributed in the Nicaraguan depression of Central America (Alfaro cultratus, Poecilia gillii, and Xenophallus umbratilis) that we predicted might display congruent responses due to co-occurrence in identical freshwater drainages. Spatial analyses recovered different subdivisions of genetic structure for each species, despite shared finer-scale breaks in northwestern Costa Rica (also supported by phylogenetic results). Isolation-with-migration models estimated incongruent timelines of among-region divergences, with A. cultratus and Xenophallus populations diverging over Miocene–mid-Pleistocene while P. gillii populations diverged over mid-late Pleistocene. Approximate Bayesian computation also lent substantial support to multiple discrete divergences over a model of simultaneous divergence across shared spatial breaks (e.g., Bayes factor [B10] = 4.303 for Ψ [no. of divergences] > 1 vs. Ψ = 1). Thus, the data support phylogeographic pseudoincongruence consistent with the multiple-response hypothesis. Model comparisons also indicated incongruence in historical demography, for example, support for intraspecific late Pleistocene population growth was unique to P. gillii, despite evidence for finer-scale population expansions in the other taxa. Empirical tests for phylogeographic congruence indicate that multiple evolutionary responses to historical events have shaped the population structure of freshwater species codistributed within the complex landscapes in/around the Nicaraguan depression. Recent community assembly through different routes (i.e., different past distributions or colonization routes), and intrinsic ecological differences among species, has likely contributed to the unique phylogeographical patterns displayed by these Neotropical fishes. PMID:24967085

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…

Ecological and evolutionary dynamics of interconnectedness and modularity.

PubMed

Nordbotten, Jan M; Levin, Simon A; Szathmáry, Eörs; Stenseth, Nils C

2018-01-23

In this contribution, we develop a theoretical framework for linking microprocesses (i.e., population dynamics and evolution through natural selection) with macrophenomena (such as interconnectedness and modularity within an ecological system). This is achieved by developing a measure of interconnectedness for population distributions defined on a trait space (generalizing the notion of modularity on graphs), in combination with an evolution equation for the population distribution. With this contribution, we provide a platform for understanding under what environmental, ecological, and evolutionary conditions ecosystems evolve toward being more or less modular. A major contribution of this work is that we are able to decompose the overall driver of changes at the macro level (such as interconnectedness) into three components: ( i ) ecologically driven change, ( ii ) evolutionarily driven change, and ( iii ) environmentally driven change. Copyright © 2018 the Author(s). Published by PNAS.

Evolutionary dynamics of social dilemmas in structured heterogeneous populations.

PubMed

Santos, F C; Pacheco, J M; Lenaerts, Tom

2006-02-28

Real populations have been shown to be heterogeneous, in which some individuals have many more contacts than others. This fact contrasts with the traditional homogeneous setting used in studies of evolutionary game dynamics. We incorporate heterogeneity in the population by studying games on graphs, in which the variability in connectivity ranges from single-scale graphs, for which heterogeneity is small and associated degree distributions exhibit a Gaussian tale, to scale-free graphs, for which heterogeneity is large with degree distributions exhibiting a power-law behavior. We study the evolution of cooperation, modeled in terms of the most popular dilemmas of cooperation. We show that, for all dilemmas, increasing heterogeneity favors the emergence of cooperation, such that long-term cooperative behavior easily resists short-term noncooperative behavior. Moreover, we show how cooperation depends on the intricate ties between individuals in scale-free populations.

Dispersal and vicariance: the complex evolutionary history of boid snakes.

PubMed

Noonan, Brice P; Chippindale, Paul T

2006-08-01

Since the early 1970s, boine snakes (Boidae: Boinae) have served as a prime example of a group whose current distribution was shaped by vicariant events associated with the fragmentation of the supercontinent Gondwana. Early phylogenetic treatments of this group, and what were thought to be closely related groups (Erycinae and Pythoninae) based on morphological features, produced a relatively stable view of relationships that has strongly influenced subsequent molecular-based work. We examined 4307 base pairs (bp) of nucleotide sequence data obtained from five nuclear loci (c-mos, NT3, BDNF, RAG1, and ODC) and one mitochondrial locus (cyt b) for all genera of erycines and boines, plus representatives of other groups, including those previously thought to be closely allied with boines (Ungaliophiidae, Loxocemidae, Xenopeltidae, and Pythoninae). Our results suggest that the Boidae is not monophyletic, and its current division into three subfamilies (Erycinae, Boinae, and Pythoninae) does not accurately reflect evolutionary history. We find that the evolutionary relationships are better reflected by current geographic distributions and tectonic history than by the morphological characters that have long served as the foundation of boid phylogeny. Divergence time estimates suggest that this strong congruence between geography and phylogeny is the result of several vicariant and dispersal events in the Late Cretaceous and Paleocene associated with the fragmentation of the Gondwanan supercontinent. Our results demonstrate the importance of both vicariance and dispersal in shaping the global distributions of terrestrial organisms.

The place of development in mathematical evolutionary theory.

PubMed

Rice, Sean H

2012-09-01

Development plays a critical role in structuring the joint offspring-parent phenotype distribution. It thus must be part of any truly general evolutionary theory. Historically, the offspring-parent distribution has often been treated in such a way as to bury the contribution of development, by distilling from it a single term, either heritability or additive genetic variance, and then working only with this term. I discuss two reasons why this approach is no longer satisfactory. First, the regression of expected offspring phenotype on parent phenotype can easily be nonlinear, and this nonlinearity can have a pronounced impact on the response to selection. Second, even when the offspring-parent regression is linear, it is nearly always a function of the environment, and the precise way that heritability covaries with the environment can have a substantial effect on adaptive evolution. Understanding these complexities of the offspring-parent distribution will require understanding of the developmental processes underlying the traits of interest. I briefly discuss how we can incorporate such complexity into formal evolutionary theory, and why it is likely to be important even for traits that are not traditionally the focus of evo-devo research. Finally, I briefly discuss a topic that is widely seen as being squarely in the domain of evo-devo: novelty. I argue that the same conceptual and mathematical framework that allows us to incorporate developmental complexity into simple models of trait evolution also yields insight into the evolution of novel traits. Copyright © 2011 Wiley Periodicals, Inc., A Wiley Company.

Analysis of optimality in natural and perturbed metabolic networks

PubMed Central

Segrè, Daniel; Vitkup, Dennis; Church, George M.

2002-01-01

An important goal of whole-cell computational modeling is to integrate detailed biochemical information with biological intuition to produce testable predictions. Based on the premise that prokaryotes such as Escherichia coli have maximized their growth performance along evolution, flux balance analysis (FBA) predicts metabolic flux distributions at steady state by using linear programming. Corroborating earlier results, we show that recent intracellular flux data for wild-type E. coli JM101 display excellent agreement with FBA predictions. Although the assumption of optimality for a wild-type bacterium is justifiable, the same argument may not be valid for genetically engineered knockouts or other bacterial strains that were not exposed to long-term evolutionary pressure. We address this point by introducing the method of minimization of metabolic adjustment (MOMA), whereby we test the hypothesis that knockout metabolic fluxes undergo a minimal redistribution with respect to the flux configuration of the wild type. MOMA employs quadratic programming to identify a point in flux space, which is closest to the wild-type point, compatibly with the gene deletion constraint. Comparing MOMA and FBA predictions to experimental flux data for E. coli pyruvate kinase mutant PB25, we find that MOMA displays a significantly higher correlation than FBA. Our method is further supported by experimental data for E. coli knockout growth rates. It can therefore be used for predicting the behavior of perturbed metabolic networks, whose growth performance is in general suboptimal. MOMA and its possible future extensions may be useful in understanding the evolutionary optimization of metabolism. PMID:12415116

Historical connectivity, contemporary isolation and local adaptation in a widespread but discontinuously distributed species endemic to Taiwan, Rhododendron oldhamii (Ericaceae)

PubMed Central

Hsieh, Y-C; Chung, J-D; Wang, C-N; Chang, C-T; Chen, C-Y; Hwang, S-Y

2013-01-01

Elucidation of the evolutionary processes that constrain or facilitate adaptive divergence is a central goal in evolutionary biology, especially in non-model organisms. We tested whether changes in dynamics of gene flow (historical vs contemporary) caused population isolation and examined local adaptation in response to environmental selective forces in fragmented Rhododendron oldhamii populations. Variation in 26 expressed sequence tag-simple sequence repeat loci from 18 populations in Taiwan was investigated by examining patterns of genetic diversity, inbreeding, geographic structure, recent bottlenecks, and historical and contemporary gene flow. Selection associated with environmental variables was also examined. Bayesian clustering analysis revealed four regional population groups of north, central, south and southeast with significant genetic differentiation. Historical bottlenecks beginning 9168–13,092 years ago and ending 1584–3504 years ago were revealed by estimates using approximate Bayesian computation for all four regional samples analyzed. Recent migration within and across geographic regions was limited. However, major dispersal sources were found within geographic regions. Altitudinal clines of allelic frequencies of environmentally associated positively selected outliers were found, indicating adaptive divergence. Our results point to a transition from historical population connectivity toward contemporary population isolation and divergence on a regional scale. Spatial and temporal dispersal differences may have resulted in regional population divergence and local adaptation associated with environmental variables, which may have played roles as selective forces at a regional scale. PMID:23591517

PROTECTED POLYMORPHISMS AND EVOLUTIONARY STABILITY OF PATCH-SELECTION STRATEGIES IN STOCHASTIC ENVIRONMENTS

PubMed Central

EVANS, STEVEN N.; HENING, ALEXANDRU; SCHREIBER, SEBASTIAN J.

2015-01-01

We consider a population living in a patchy environment that varies stochastically in space and time. The population is composed of two morphs (that is, individuals of the same species with different genotypes). In terms of survival and reproductive success, the associated phenotypes differ only in their habitat selection strategies. We compute invasion rates corresponding to the rates at which the abundance of an initially rare morph increases in the presence of the other morph established at equilibrium. If both morphs have positive invasion rates when rare, then there is an equilibrium distribution such that the two morphs coexist; that is, there is a protected polymorphism for habitat selection. Alternatively, if one morph has a negative invasion rate when rare, then it is asymptotically displaced by the other morph under all initial conditions where both morphs are present. We refine the characterization of an evolutionary stable strategy for habitat selection from [Schreiber, 2012] in a mathematically rigorous manner. We provide a necessary and sufficient condition for the existence of an ESS that uses all patches and determine when using a single patch is an ESS. We also provide an explicit formula for the ESS when there are two habitat types. We show that adding environmental stochasticity results in an ESS that, when compared to the ESS for the corresponding model without stochasticity, spends less time in patches with larger carrying capacities and possibly makes use of sink patches, thereby practicing a spatial form of bet hedging. PMID:25151369

Contemporary genetic structure and postglacial demographic history of the black scorpionfish, Scorpaena porcus, in the Mediterranean and the Black Seas.

PubMed

Boissin, E; Micu, D; Janczyszyn-Le Goff, M; Neglia, V; Bat, L; Todorova, V; Panayotova, M; Kruschel, C; Macic, V; Milchakova, N; Keskin, Ç; Anastasopoulou, A; Nasto, I; Zane, L; Planes, S

2016-05-01

Understanding the distribution of genetic diversity in the light of past demographic events linked with climatic shifts will help to forecast evolutionary trajectories of ecosystems within the current context of climate change. In this study, mitochondrial sequences and microsatellite loci were analysed using traditional population genetic approaches together with Bayesian dating and the more recent approximate Bayesian computation scenario testing. The genetic structure and demographic history of a commercial fish, the black scorpionfish, Scorpaena porcus, was investigated throughout the Mediterranean and Black Seas. The results suggest that the species recently underwent population expansions, in both seas, likely concomitant with the warming period following the Last Glacial Maximum, 20 000 years ago. A weak contemporaneous genetic differentiation was identified between the Black Sea and the Mediterranean Sea. However, the genetic diversity was similar for populations of the two seas, suggesting a high number of colonizers entered the Black Sea during the interglacial period and/or the presence of a refugial population in the Black Sea during the glacial period. Finally, within seas, an east/west genetic differentiation in the Adriatic seems to prevail, whereas the Black Sea does not show any structured spatial genetic pattern of its population. Overall, these results suggest that the Black Sea is not that isolated from the Mediterranean, and both seas revealed similar evolutionary patterns related to climate change and changes in sea level. © 2016 John Wiley & Sons Ltd.

Cloud computing task scheduling strategy based on improved differential evolution algorithm

NASA Astrophysics Data System (ADS)

Ge, Junwei; He, Qian; Fang, Yiqiu

2017-04-01

In order to optimize the cloud computing task scheduling scheme, an improved differential evolution algorithm for cloud computing task scheduling is proposed. Firstly, the cloud computing task scheduling model, according to the model of the fitness function, and then used improved optimization calculation of the fitness function of the evolutionary algorithm, according to the evolution of generation of dynamic selection strategy through dynamic mutation strategy to ensure the global and local search ability. The performance test experiment was carried out in the CloudSim simulation platform, the experimental results show that the improved differential evolution algorithm can reduce the cloud computing task execution time and user cost saving, good implementation of the optimal scheduling of cloud computing tasks.

Visions of the past and dreams of the future in the Orient: the Irano-Turanian region from classical botany to evolutionary studies.

PubMed

Manafzadeh, Sara; Staedler, Yannick M; Conti, Elena

2017-08-01

Ever since the 19th century, the immense arid lands of the Orient, now called the Irano-Turanian (IT) floristic region, attracted the interest of European naturalists with their tremendous plant biodiversity. Covering approximately 30% of the surface of Eurasia (16000000 km 2 ), the IT region is one of the largest floristic regions of the world. The IT region represents one of the hotspots of evolutionary and biological diversity in the Old World, and serves as a source of xerophytic taxa for neighbouring regions. Moreover, it is the cradle of the numerous species domesticated in the Fertile Crescent. Over the last 200 years, naturalists outlined different borders for the IT region. Yet, the delimitation and evolutionary history of this area remain one of the least well-understood fields of global biogeography, even though it is crucial to explaining the distribution of life in Eurasia. No comprehensive review of the biogeographical delimitations nor of the role of geological and climatic changes in the evolution of the IT region is currently available. After considering the key role of floristic regions in biogeography, we review the history of evolving concepts about the borders and composition of the IT region over the past 200 years and outline a tentative circumscription for it. We also summarise current knowledge on the geological and climatic history of the IT region. We then use this knowledge to generate specific evolutionary hypotheses to explain how different geological, palaeoclimatic, and ecological factors contributed to range expansion and contraction, thus shaping patterns of speciation in the IT region over time and space. Both historical and ecological biogeography should be applied to understand better the floristic diversification of the region. This will ultimately require evolutionary comparative analyses based on integrative phylogenetic, geological, climatic, ecological, and species distribution studies on the region. Furthermore, an understanding of evolutionary and ecological processes will play a major role in regional planning for protecting biodiversity of the IT region in facing climatic change. With this review, we aim to introduce the IT floristic region to a broader audience of evolutionary, ecological and systematic biologists, thus promoting cutting-edge research on this area and raising awareness of this vast and diverse, yet understudied, part of the world. © 2016 Cambridge Philosophical Society.

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

Application of evolutionary games to modeling carcinogenesis.

PubMed

Swierniak, Andrzej; Krzeslak, Michal

2013-06-01

We review a quite large volume of literature concerning mathematical modelling of processes related to carcinogenesis and the growth of cancer cell populations based on the theory of evolutionary games. This review, although partly idiosyncratic, covers such major areas of cancer-related phenomena as production of cytotoxins, avoidance of apoptosis, production of growth factors, motility and invasion, and intra- and extracellular signaling. We discuss the results of other authors and append to them some additional results of our own simulations dealing with the possible dynamics and/or spatial distribution of the processes discussed.

Williams' paradox and the role of phenotypic plasticity in sexual systems.

PubMed

Leonard, Janet L

2013-10-01

As George Williams pointed out in 1975, although evolutionary explanations, based on selection acting on individuals, have been developed for the advantages of simultaneous hermaphroditism, sequential hermaphroditism and gonochorism, none of these evolutionary explanations adequately explains the current distribution of these sexual systems within the Metazoa (Williams' Paradox). As Williams further pointed out, the current distribution of sexual systems is explained largely by phylogeny. Since 1975, we have made a great deal of empirical and theoretical progress in understanding sexual systems. However, we still lack a theory that explains the current distribution of sexual systems in animals and we do not understand the evolutionary transitions between hermaphroditism and gonochorism. Empirical data, collected over the past 40 years, demonstrate that gender may have more phenotypic plasticity than was previously realized. We know that not only sequential hermaphrodites, but also simultaneous hermaphrodites have phenotypic plasticity that alters sex allocation in response to social and environmental conditions. A focus on phenotypic plasticity suggests that one sees a continuum in animals between genetically determined gonochorism on the one hand and simultaneous hermaphroditism on the other, with various types of sequential hermaphroditism and environmental sex determination as points along the spectrum. Here I suggest that perhaps the reason we have been unable to resolve Williams' Paradox is because the problem was not correctly framed. First, because, for example, simultaneous hermaphroditism provides reproductive assurance or dioecy ensures outcrossing does not mean that there are no other evolutionary paths that can provide adaptive responses to those selective pressures. Second, perhaps the question we need to ask is: What selective forces favor increased versus reduced phenotypic plasticity in gender expression? It is time to begin to look at the question of sexual system as one of understanding the timing and degree of phenotypic plasticity in gender expression in the life history in terms of selection acting on a continuum, rather than on a set of discrete sexual systems.

Evolutionary History of Lagomorphs in Response to Global Environmental Change

PubMed Central

Ge, Deyan; Wen, Zhixin; Xia, Lin; Zhang, Zhaoqun; Erbajeva, Margarita; Huang, Chengming; Yang, Qisen

2013-01-01

Although species within Lagomorpha are derived from a common ancestor, the distribution range and body size of its two extant groups, ochotonids and leporids, are quite differentiated. It is unclear what has driven their disparate evolutionary history. In this study, we compile and update all fossil records of Lagomorpha for the first time, to trace the evolutionary processes and infer their evolutionary history using mitochondrial genes, body length and distribution of extant species. We also compare the forage selection of extant species, which offers an insight into their future prospects. The earliest lagomorphs originated in Asia and later diversified in different continents. Within ochotonids, more than 20 genera occupied the period from the early Miocene to middle Miocene, whereas most of them became extinct during the transition from the Miocene to Pliocene. The peak diversity of the leporids occurred during the Miocene to Pliocene transition, while their diversity dramatically decreased in the late Quaternary. Mantel tests identified a positive correlation between body length and phylogenetic distance of lagomorphs. The body length of extant ochotonids shows a normal distribution, while the body length of extant leporids displays a non-normal pattern. We also find that the forage selection of extant pikas features a strong preference for C3 plants, while for the diet of leporids, more than 16% of plant species are identified as C4 (31% species are from Poaceae). The ability of several leporid species to consume C4 plants is likely to result in their size increase and range expansion, most notably in Lepus. Expansion of C4 plants in the late Miocene, the so-called ‘nature’s green revolution’, induced by global environmental change, is suggested to be one of the major ‘ecological opportunities’, which probably drove large-scale extinction and range contraction of ochotonids, but inversely promoted diversification and range expansion of leporids. PMID:23573205

Toward an evolutionary-predictive foundation for creativity : Commentary on "Human creativity, evolutionary algorithms, and predictive representations: The mechanics of thought trials" by Arne Dietrich and Hilde Haider, 2014 (Accepted pending minor revisions for publication in Psychonomic Bulletin & Review).

PubMed

Gabora, Liane; Kauffman, Stuart

2016-04-01

Dietrich and Haider (Psychonomic Bulletin & Review, 21 (5), 897-915, 2014) justify their integrative framework for creativity founded on evolutionary theory and prediction research on the grounds that "theories and approaches guiding empirical research on creativity have not been supported by the neuroimaging evidence." Although this justification is controversial, the general direction holds promise. This commentary clarifies points of disagreement and unresolved issues, and addresses mis-applications of evolutionary theory that lead the authors to adopt a Darwinian (versus Lamarckian) approach. To say that creativity is Darwinian is not to say that it consists of variation plus selection - in the everyday sense of the term - as the authors imply; it is to say that evolution is occurring because selection is affecting the distribution of randomly generated heritable variation across generations. In creative thought the distribution of variants is not key, i.e., one is not inclined toward idea A because 60 % of one's candidate ideas are variants of A while only 40 % are variants of B; one is inclined toward whichever seems best. The authors concede that creative variation is partly directed; however, the greater the extent to which variants are generated non-randomly, the greater the extent to which the distribution of variants can reflect not selection but the initial generation bias. Since each thought in a creative process can alter the selective criteria against which the next is evaluated, there is no demarcation into generations as assumed in a Darwinian model. We address the authors' claim that reduced variability and individuality are more characteristic of Lamarckism than Darwinian evolution, and note that a Lamarckian approach to creativity has addressed the challenge of modeling the emergent features associated with insight.