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Sample records for san-specific genetic program

  1. Applications of Genetic Programming

    DEFF Research Database (Denmark)

    Gaunholt, Hans; Toma, Laura

    1996-01-01

    In this report a study of genetic programming (GP) has been performed with respect to a number of applications such as Symbolic function regression, Solving Symbolic Differential Equations, Image encoding, the ant problem etc.......In this report a study of genetic programming (GP) has been performed with respect to a number of applications such as Symbolic function regression, Solving Symbolic Differential Equations, Image encoding, the ant problem etc....

  2. Applications of Genetic Programming

    DEFF Research Database (Denmark)

    Gaunholt, Hans; Toma, Laura

    1996-01-01

    In this report a study of genetic programming (GP) has been performed with respect to a number of applications such as Symbolic function regression, Solving Symbolic Differential Equations, Image encoding, the ant problem etc.......In this report a study of genetic programming (GP) has been performed with respect to a number of applications such as Symbolic function regression, Solving Symbolic Differential Equations, Image encoding, the ant problem etc....

  3. Cartesian genetic programming

    CERN Document Server

    Miller, Julian F

    2011-01-01

    Cartesian Genetic Programming (CGP) is a highly effective and increasingly popular form of genetic programming. It represents programs in the form of directed graphs, and a particular characteristic is that it has a highly redundant genotype - phenotype mapping, in that genes can be noncoding. It has spawned a number of new forms, each improving on the efficiency, among them modular, or embedded, CGP, and self-modifying CGP. It has been applied to many problems in both computer science and applied sciences. This book contains chapters written by the leading figures in the development and appli

  4. Behavioral program synthesis with genetic programming

    CERN Document Server

    Krawiec, Krzysztof

    2016-01-01

    Genetic programming (GP) is a popular heuristic methodology of program synthesis with origins in evolutionary computation. In this generate-and-test approach, candidate programs are iteratively produced and evaluated. The latter involves running programs on tests, where they exhibit complex behaviors reflected in changes of variables, registers, or memory. That behavior not only ultimately determines program output, but may also reveal its `hidden qualities' and important characteristics of the considered synthesis problem. However, the conventional GP is oblivious to most of that information and usually cares only about the number of tests passed by a program. This `evaluation bottleneck' leaves search algorithm underinformed about the actual and potential qualities of candidate programs. This book proposes behavioral program synthesis, a conceptual framework that opens GP to detailed information on program behavior in order to make program synthesis more efficient. Several existing and novel mechanisms subs...

  5. Genetic Programming and Genetic Algorithms for Propositions

    Directory of Open Access Journals (Sweden)

    Nabil M. HEWAHI

    2012-01-01

    Full Text Available In this paper we propose a mechanism to discover the compound proposition solutions for a given truth table without knowing the compound propositions that lead to the truth table results. The approach is based on two proposed algorithms, the first is called Producing Formula (PF algorithm which is based on the genetic programming idea, to find out the compound proposition solutions for the given truth table. The second algorithm is called the Solutions Optimization (SO algorithm which is based on genetic algorithms idea, to find a list of the optimum compound propositions that can solve the truth table. The obtained list will depend on the solutions obtained from the PF algorithm. Various types of genetic operators have been introduced to obtain the solutions either within the PF algorithm or SO algorithm.

  6. Scientific discovery using genetic programming

    DEFF Research Database (Denmark)

    Keijzer, Maarten

    2001-01-01

    programming paradigm. The induction of mathematical expressions based on data is called symbolic regression. In this work, genetic programming is extended to not just fit the data i.e., get the numbers right, but also to get the dimensions right. For this units of measurement are used. The main contribution...... in this work can be summarized as: The symbolic expressions produced by genetic programming can be made suitable for analysis and interpretation by using units of measurements to guide or restrict the search. To achieve this, the following has been accomplished: A standard genetic programming system...... that are numerically stable and correct. A case study using four real-world problems in the induction of dimensionally correct empirical equations on data using the two different methods is presented to illustrate to use and limitations of these methods in a framework of scientific discovery....

  7. Genetic Programming with Simple Loops

    Institute of Scientific and Technical Information of China (English)

    QI Yuesheng; WANG Baozhong; KANG Lishan

    1999-01-01

    A kind of loop function LoopN inGenetic Programming (GP) is proposed.Different from other forms of loopfunction, such as While-Do and Repeat-Until, LoopNtakes only oneargument as its loop body and makes its loop body simply run N times,soinfinite loops will never happen. The problem of how to avoid too manylayers ofloops in Genetic Programming is also solved. The advantage ofLoopN in GP is shown bythe computational results in solving the mowerproblem.

  8. Dynamical genetic programming in XCSF.

    Science.gov (United States)

    Preen, Richard J; Bull, Larry

    2013-01-01

    A number of representation schemes have been presented for use within learning classifier systems, ranging from binary encodings to artificial neural networks. This paper presents results from an investigation into using a temporally dynamic symbolic representation within the XCSF learning classifier system. In particular, dynamical arithmetic networks are used to represent the traditional condition-action production system rules to solve continuous-valued reinforcement learning problems and to perform symbolic regression, finding competitive performance with traditional genetic programming on a number of composite polynomial tasks. In addition, the network outputs are later repeatedly sampled at varying temporal intervals to perform multistep-ahead predictions of a financial time series.

  9. Atmospheric Downscaling using Genetic Programming

    Science.gov (United States)

    Zerenner, Tanja; Venema, Victor; Simmer, Clemens

    2013-04-01

    Coupling models for the different components of the Soil-Vegetation-Atmosphere-System requires up-and downscaling procedures. Subject of our work is the downscaling scheme used to derive high resolution forcing data for land-surface and subsurface models from coarser atmospheric model output. The current downscaling scheme [Schomburg et. al. 2010, 2012] combines a bi-quadratic spline interpolation, deterministic rules and autoregressive noise. For the development of the scheme, training and validation data sets have been created by carrying out high-resolution runs of the atmospheric model. The deterministic rules in this scheme are partly based on known physical relations and partly determined by an automated search for linear relationships between the high resolution fields of the atmospheric model output and high resolution data on surface characteristics. Up to now deterministic rules are available for downscaling surface pressure and partially, depending on the prevailing weather conditions, for near surface temperature and radiation. Aim of our work is to improve those rules and to find deterministic rules for the remaining variables, which require downscaling, e.g. precipitation or near surface specifc humidity. To accomplish that, we broaden the search by allowing for interdependencies between different atmospheric parameters, non-linear relations, non-local and time-lagged relations. To cope with the vast number of possible solutions, we use genetic programming, a method from machine learning, which is based on the principles of natural evolution. We are currently working with GPLAB, a Genetic Programming toolbox for Matlab. At first we have tested the GP system to retrieve the known physical rule for downscaling surface pressure, i.e. the hydrostatic equation, from our training data. We have found this to be a simple task to the GP system. Furthermore we have improved accuracy and efficiency of the GP solution by implementing constant variation and

  10. Genetic programming theory and practice XII

    CERN Document Server

    Riolo, Rick; Kotanchek, Mark

    2015-01-01

    These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Topics in this volume include: gene expression regulation, novel genetic models for glaucoma, inheritable epigenetics, combinators in genetic programming, sequential symbolic regression, system dynamics, sliding window symbolic regression, large feature problems, alignment in the error space, HUMIE winners, Boolean multiplexer funct

  11. Recognition of Objects by Using Genetic Programming

    Directory of Open Access Journals (Sweden)

    Nerses Safaryan

    2013-01-01

    Full Text Available This document is devoted to the task of object detection and recognition in digital images by using genetic programming. The goal was to improve and simplify existing approaches. The detection and recognition are achieved by means of extracting the features. A genetic program is used to extract and classify features of objects. Simple features and primitive operators are processed in genetic programming operations. We are trying to detect and to recognize objects in SAR images. Due to the new approach described in this article, five and seven types of objects were recognized with good recognition results.

  12. Applied genetic programming and machine learning

    CERN Document Server

    Iba, Hitoshi; Paul, Topon Kumar

    2009-01-01

    What do financial data prediction, day-trading rule development, and bio-marker selection have in common? They are just a few of the tasks that could potentially be resolved with genetic programming and machine learning techniques. Written by leaders in this field, Applied Genetic Programming and Machine Learning delineates the extension of Genetic Programming (GP) for practical applications. Reflecting rapidly developing concepts and emerging paradigms, this book outlines how to use machine learning techniques, make learning operators that efficiently sample a search space, navigate the searc

  13. Genetic Parallel Programming: design and implementation.

    Science.gov (United States)

    Cheang, Sin Man; Leung, Kwong Sak; Lee, Kin Hong

    2006-01-01

    This paper presents a novel Genetic Parallel Programming (GPP) paradigm for evolving parallel programs running on a Multi-Arithmetic-Logic-Unit (Multi-ALU) Processor (MAP). The MAP is a Multiple Instruction-streams, Multiple Data-streams (MIMD), general-purpose register machine that can be implemented on modern Very Large-Scale Integrated Circuits (VLSIs) in order to evaluate genetic programs at high speed. For human programmers, writing parallel programs is more difficult than writing sequential programs. However, experimental results show that GPP evolves parallel programs with less computational effort than that of their sequential counterparts. It creates a new approach to evolving a feasible problem solution in parallel program form and then serializes it into a sequential program if required. The effectiveness and efficiency of GPP are investigated using a suite of 14 well-studied benchmark problems. Experimental results show that GPP speeds up evolution substantially.

  14. Programming cells: towards an automated 'Genetic Compiler'.

    Science.gov (United States)

    Clancy, Kevin; Voigt, Christopher A

    2010-08-01

    One of the visions of synthetic biology is to be able to program cells using a language that is similar to that used to program computers or robotics. For large genetic programs, keeping track of the DNA on the level of nucleotides becomes tedious and error prone, requiring a new generation of computer-aided design (CAD) software. To push the size of projects, it is important to abstract the designer from the process of part selection and optimization. The vision is to specify genetic programs in a higher-level language, which a genetic compiler could automatically convert into a DNA sequence. Steps towards this goal include: defining the semantics of the higher-level language, algorithms to select and assemble parts, and biophysical methods to link DNA sequence to function. These will be coupled to graphic design interfaces and simulation packages to aid in the prediction of program dynamics, optimize genes, and scan projects for errors.

  15. Evolving evolutionary algorithms using linear genetic programming.

    Science.gov (United States)

    Oltean, Mihai

    2005-01-01

    A new model for evolving Evolutionary Algorithms is proposed in this paper. The model is based on the Linear Genetic Programming (LGP) technique. Every LGP chromosome encodes an EA which is used for solving a particular problem. Several Evolutionary Algorithms for function optimization, the Traveling Salesman Problem and the Quadratic Assignment Problem are evolved by using the considered model. Numerical experiments show that the evolved Evolutionary Algorithms perform similarly and sometimes even better than standard approaches for several well-known benchmarking problems.

  16. Genetic Programming Framework for Fingerprint Matching

    CERN Document Server

    Ismail, Ismail A; Abd-ElWahid, Mohammed A; ElKafrawy, Passent M; Nasef, Mohammed M

    2009-01-01

    A fingerprint matching is a very difficult problem. Minutiae based matching is the most popular and widely used technique for fingerprint matching. The minutiae points considered in automatic identification systems are based normally on termination and bifurcation points. In this paper we propose a new technique for fingerprint matching using minutiae points and genetic programming. The goal of this paper is extracting the mathematical formula that defines the minutiae points.

  17. Deterministic Pattern Classifier Based on Genetic Programming

    Institute of Scientific and Technical Information of China (English)

    LI Jian-wu; LI Min-qiang; KOU Ji-song

    2001-01-01

    This paper proposes a supervised training-test method with Genetic Programming (GP) for pattern classification. Compared and contrasted with traditional methods with regard to deterministic pattern classifiers, this method is true for both linear separable problems and linear non-separable problems. For specific training samples, it can formulate the expression of discriminate function well without any prior knowledge. At last, an experiment is conducted, and the result reveals that this system is effective and practical.

  18. Genetic programming theory and practice X

    CERN Document Server

    Riolo, Rick; Ritchie, Marylyn D; Moore, Jason H

    2013-01-01

    These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Topics in this volume include: evolutionary constraints, relaxation of selection mechanisms, diversity preservation strategies, flexing fitness evaluation, evolution in dynamic environments, multi-objective and multi-modal selection, foundations of evolvability, evolvable and adaptive evolutionary operators, foundation of  injecting

  19. Grammar Based Genetic Programming Using Linear Representations

    Institute of Scientific and Technical Information of China (English)

    ZHANGHong; LUYinan; WANGFei

    2003-01-01

    In recent years,there has been a great interest in genetic programming(GP),which is used to solve many applications such as data mining,electronic engineering and pattern recognition etc.. Genetic programming paradigm as a from of adaptive learning is a functional approach to many problems that require a nonfixed representation and GP typically operates on a population of parse which usually represent computer programs whose nodes have single data type.In this paper GP using context-free grammars(CFGs) is described.This technique separates search space from solution space through a genotype to phenotype mapping.The genotypes and phenotypes of the individuals both act on different linear representations.A phenotype is postfix expression,a new method of representing which is described by making use of the definition and related features of a context-free grammar,i.e.a genotype is a variable length,linear valid genome determined by a simplifled derivation tree(SDT) generated from a context-free grammar.A CFG is used to specify how the possible solutions are created according to experiential knowledge and to direct legal crossover(ormutation)operations without any explicit reference to the process of program generation and parsing,and automatically ensuring typing and syntax correctness.Some related definitions involving genetic operators are described.Fitness evaluation is given.This technique is applied to a symbol regression problem-the identification of nonlinear dynamic characteristics of cushioning packaging.Experimental results show this method can flnd good relations between variables and is better than basic GP without a grammar.Future research on it is outlined.

  20. Functional Localization of Genetic Network Programming

    Science.gov (United States)

    Eto, Shinji; Hirasawa, Kotaro; Hu, Jinglu

    According to the knowledge of brain science, it is suggested that there exists cerebral functional localization, which means that a specific part of the cerebrum is activated depending on various kinds of information human receives. The aim of this paper is to build an artificial model to realize functional localization based on Genetic Network Programming (GNP), a new evolutionary computation method recently developed. GNP has a directed graph structure suitable for realizing functional localization. We studied the basic characteristics of the proposed system by making GNP work in a functionally localized way.

  1. Bias-variance decomposition in Genetic Programming

    Directory of Open Access Journals (Sweden)

    Kowaliw Taras

    2016-01-01

    Full Text Available We study properties of Linear Genetic Programming (LGP through several regression and classification benchmarks. In each problem, we decompose the results into bias and variance components, and explore the effect of varying certain key parameters on the overall error and its decomposed contributions. These parameters are the maximum program size, the initial population, and the function set used. We confirm and quantify several insights into the practical usage of GP, most notably that (a the variance between runs is primarily due to initialization rather than the selection of training samples, (b parameters can be reasonably optimized to obtain gains in efficacy, and (c functions detrimental to evolvability are easily eliminated, while functions well-suited to the problem can greatly improve performance—therefore, larger and more diverse function sets are always preferable.

  2. LIGO detector characterization with genetic programming

    Science.gov (United States)

    Cavaglia, Marco; Staats, Kai; Errico, Luciano; Mogushi, Kentaro; Gabbard, Hunter

    2017-01-01

    Genetic Programming (GP) is a supervised approach to Machine Learning. GP has for two decades been applied to a diversity of problems, from predictive and financial modelling to data mining, from code repair to optical character recognition and product design. GP uses a stochastic search, tournament, and fitness function to explore a solution space. GP evolves a population of individual programs, through multiple generations, following the principals of biological evolution (mutation and reproduction) to discover a model that best fits or categorizes features in a given data set. We apply GP to categorization of LIGO noise and show that it can effectively be used to characterize the detector non-astrophysical noise both in low latency and offline searches. National Science Foundation award PHY-1404139.

  3. Improving Search Properties in Genetic Programming

    Science.gov (United States)

    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

  4. On Using Surrogates with Genetic Programming.

    Science.gov (United States)

    Hildebrandt, Torsten; Branke, Jürgen

    2015-01-01

    One way to accelerate evolutionary algorithms with expensive fitness evaluations is to combine them with surrogate models. Surrogate models are efficiently computable approximations of the fitness function, derived by means of statistical or machine learning techniques from samples of fully evaluated solutions. But these models usually require a numerical representation, and therefore cannot be used with the tree representation of genetic programming (GP). In this paper, we present a new way to use surrogate models with GP. Rather than using the genotype directly as input to the surrogate model, we propose using a phenotypic characterization. This phenotypic characterization can be computed efficiently and allows us to define approximate measures of equivalence and similarity. Using a stochastic, dynamic job shop scenario as an example of simulation-based GP with an expensive fitness evaluation, we show how these ideas can be used to construct surrogate models and improve the convergence speed and solution quality of GP.

  5. Genetic Programming Transforms in Linear Regression Situations

    Science.gov (United States)

    Castillo, Flor; Kordon, Arthur; Villa, Carlos

    The chapter summarizes the use of Genetic Programming (GP) inMultiple Linear Regression (MLR) to address multicollinearity and Lack of Fit (LOF). The basis of the proposed method is applying appropriate input transforms (model respecification) that deal with these issues while preserving the information content of the original variables. The transforms are selected from symbolic regression models with optimal trade-off between accuracy of prediction and expressional complexity, generated by multiobjective Pareto-front GP. The chapter includes a comparative study of the GP-generated transforms with Ridge Regression, a variant of ordinary Multiple Linear Regression, which has been a useful and commonly employed approach for reducing multicollinearity. The advantages of GP-generated model respecification are clearly defined and demonstrated. Some recommendations for transforms selection are given as well. The application benefits of the proposed approach are illustrated with a real industrial application in one of the broadest empirical modeling areas in manufacturing - robust inferential sensors. The chapter contributes to increasing the awareness of the potential of GP in statistical model building by MLR.

  6. Improved Evolvability in Genetic Programming with Polyandry

    Directory of Open Access Journals (Sweden)

    Anisa Waganda Ragalo

    2013-12-01

    Full Text Available This paper proposes Polyandry, a new nature-inspired modification to canonical Genetic Programming (GP. Polyandry aims to improve evolvability in GP. Evolvability is a critically important GP trait, the maintenance of which determines the arrival of the GP at the global optimum solution. Specifically evolvability is defined as the ability of the genetic operators employed in GP to produce offspring that are fitter than their parents. When GP fails to exhibit evolvability, further adaptation of the GP individuals towards the global optimum solution becomes impossible. Polyandry improves evolvability by improving the typically disruptive standard GP crossover operator. The algorithm employs a dual strategy towards this goal. The chief part of this strategy is an incorporation of genetic material from multiple mating partners into broods of offspring. Given such a brood, the offspring in the brood then compete according to a culling function, which we make equivalent to the main GP fitness function. Polyandry’s incorporation of genetic material from multiple GP individuals into broods of offspring represents a more aggressive search for building block information. This characteristic of the algorithm leads to an advanced explorative capability in both GP structural space and fitness space. The second component of the Polyandry strategy is an attempt at multiple crossover points, in order to find crossover points that minimize building block disruption from parents to offspring. This strategy is employed by a similar algorithm, Brood Recombination. We conduct experiments to compare Polyandry with the canonical GP. Our experiments demonstrate that Polyandry consistently exhibits better evolvability than the canonical GP. As a consequence, Polyandry achieves higher success rates and finds solutions faster than the latter. The result of these observations is that given certain brood size settings, Polyandry requires less computational effort to

  7. Solving Classification Problems Using Genetic Programming Algorithms on GPUs

    Science.gov (United States)

    Cano, Alberto; Zafra, Amelia; Ventura, Sebastián

    Genetic Programming is very efficient in problem solving compared to other proposals but its performance is very slow when the size of the data increases. This paper proposes a model for multi-threaded Genetic Programming classification evaluation using a NVIDIA CUDA GPUs programming model to parallelize the evaluation phase and reduce computational time. Three different well-known Genetic Programming classification algorithms are evaluated using the parallel evaluation model proposed. Experimental results using UCI Machine Learning data sets compare the performance of the three classification algorithms in single and multithreaded Java, C and CUDA GPU code. Results show that our proposal is much more efficient.

  8. Genetic Programming for Automatic Hydrological Modelling

    Science.gov (United States)

    Chadalawada, Jayashree; Babovic, Vladan

    2017-04-01

    One of the recent challenges for the hydrologic research community is the need for the development of coupled systems that involves the integration of hydrologic, atmospheric and socio-economic relationships. This poses a requirement for novel modelling frameworks that can accurately represent complex systems, given, the limited understanding of underlying processes, increasing volume of data and high levels of uncertainity. Each of the existing hydrological models vary in terms of conceptualization and process representation and is the best suited to capture the environmental dynamics of a particular hydrological system. Data driven approaches can be used in the integration of alternative process hypotheses in order to achieve a unified theory at catchment scale. The key steps in the implementation of integrated modelling framework that is influenced by prior understanding and data, include, choice of the technique for the induction of knowledge from data, identification of alternative structural hypotheses, definition of rules, constraints for meaningful, intelligent combination of model component hypotheses and definition of evaluation metrics. This study aims at defining a Genetic Programming based modelling framework that test different conceptual model constructs based on wide range of objective functions and evolves accurate and parsimonious models that capture dominant hydrological processes at catchment scale. In this paper, GP initializes the evolutionary process using the modelling decisions inspired from the Superflex framework [Fenicia et al., 2011] and automatically combines them into model structures that are scrutinized against observed data using statistical, hydrological and flow duration curve based performance metrics. The collaboration between data driven and physical, conceptual modelling paradigms improves the ability to model and manage hydrologic systems. Fenicia, F., D. Kavetski, and H. H. Savenije (2011), Elements of a flexible approach

  9. Adaptable Constrained Genetic Programming: Extensions and Applications

    Science.gov (United States)

    Janikow, Cezary Z.

    2005-01-01

    An evolutionary algorithm applies evolution-based principles to problem solving. To solve a problem, the user defines the space of potential solutions, the representation space. Sample solutions are encoded in a chromosome-like structure. The algorithm maintains a population of such samples, which undergo simulated evolution by means of mutation, crossover, and survival of the fittest principles. Genetic Programming (GP) uses tree-like chromosomes, providing very rich representation suitable for many problems of interest. GP has been successfully applied to a number of practical problems such as learning Boolean functions and designing hardware circuits. To apply GP to a problem, the user needs to define the actual representation space, by defining the atomic functions and terminals labeling the actual trees. The sufficiency principle requires that the label set be sufficient to build the desired solution trees. The closure principle allows the labels to mix in any arity-consistent manner. To satisfy both principles, the user is often forced to provide a large label set, with ad hoc interpretations or penalties to deal with undesired local contexts. This unfortunately enlarges the actual representation space, and thus usually slows down the search. In the past few years, three different methodologies have been proposed to allow the user to alleviate the closure principle by providing means to define, and to process, constraints on mixing the labels in the trees. Last summer we proposed a new methodology to further alleviate the problem by discovering local heuristics for building quality solution trees. A pilot system was implemented last summer and tested throughout the year. This summer we have implemented a new revision, and produced a User's Manual so that the pilot system can be made available to other practitioners and researchers. We have also designed, and partly implemented, a larger system capable of dealing with much more powerful heuristics.

  10. Alternative Living Kidney Donation Programs Boost Genetically Unrelated Donation

    Directory of Open Access Journals (Sweden)

    Rosalie A. Poldervaart

    2015-01-01

    Full Text Available Donor-recipient ABO and/or HLA incompatibility used to lead to donor decline. Development of alternative transplantation programs enabled transplantation of incompatible couples. How did that influence couple characteristics? Between 2000 and 2014, 1232 living donor transplantations have been performed. In conventional and ABO-incompatible transplantation the willing donor becomes an actual donor for the intended recipient. In kidney-exchange and domino-donation the donor donates indirectly to the intended recipient. The relationship between the donor and intended recipient was studied. There were 935 conventional and 297 alternative program transplantations. There were 66 ABO-incompatible, 68 domino-paired, 62 kidney-exchange, and 104 altruistic donor transplantations. Waiting list recipients (n=101 were excluded as they did not bring a living donor. 1131 couples remained of whom 196 participated in alternative programs. Genetically unrelated donors (486 were primarily partners. Genetically related donors (645 were siblings, parents, children, and others. Compared to genetically related couples, almost three times as many genetically unrelated couples were incompatible and participated in alternative programs (P<0.001. 62% of couples were genetically related in the conventional donation program versus 32% in alternative programs (P<0.001. Patient and graft survival were not significantly different between recipient programs. Alternative donation programs increase the number of transplantations by enabling genetically unrelated donors to donate.

  11. Using genetic programming to discover nonlinear variable interactions.

    Science.gov (United States)

    Westbury, Chris; Buchanan, Lori; Sanderson, Michael; Rhemtulla, Mijke; Phillips, Leah

    2003-05-01

    Psychology has to deal with many interacting variables. The analyses usually used to uncover such relationships have many constraints that limit their utility. We briefly discuss these and describe recent work that uses genetic programming to evolve equations to combine variables in nonlinear ways in a number of different domains. We focus on four studies of interactions from lexical access experiments and psychometric problems. In all cases, genetic programming described nonlinear combinations of items in a manner that was subsequently independently verified. We discuss the general implications of genetic programming and related computational methods for multivariate problems in psychology.

  12. Genetic Programming Approach for Predicting Surface Subsidence Induced by Mining

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    The surface subsidence induced by mining is a complex problem, which is related with many complex and uncertain factors.Genetic programming (GP) has a good ability to deal with complex and nonlinear problems, therefore genetic programming approach is proposed to predict mining induced surface subsidence in this article.First genetic programming technique is introduced, second, surface subsidence genetic programming model is set up by selecting its main affective factors and training relating to practical engineering data, and finally, predictions are made by the testing of data, whose results show that the relative error is approximately less than 10%, which can meet the engineering needs, and therefore, this proposed approach is valid and applicable in predicting mining induced surface subsidence.The model offers a novel method to predict surface subsidence in mining.

  13. Biotech 101: an educational outreach program in genetics and biotechnology.

    Science.gov (United States)

    East, Kelly M; Hott, Adam M; Callanan, Nancy P; Lamb, Neil E

    2012-10-01

    Recent advances in research and biotechnology are making genetics and genomics increasingly relevant to the lives and health of the general public. For the public to make informed healthcare and public policy decisions relating to genetic information, there is a need for increased genetic literacy. Biotech 101 is a free, short-course for the local community introducing participants to topics in genetics, genomics, and biotechnology, created at the HudsonAlpha Institute for Biotechnology. This study evaluated the effectiveness of Biotech 101 in increasing the genetic literacy of program participants through pre-and-post surveys. Genetic literacy was measured through increases in self-perceived knowledge for each content area covered through the course and the self-reported impact the course had on various aspects of participants' lives. Three hundred ninety-two individuals attended Biotech 101 during the first three course offerings. Participants reported a significant increase in self-perceived knowledge for each content area (p biotechnology.

  14. The "Genetic Program": Behind the Genesis of an Influential Metaphor.

    Science.gov (United States)

    Peluffo, Alexandre E

    2015-07-01

    The metaphor of the "genetic program," indicating the genome as a set of instructions required to build a phenotype, has been very influential in biology despite various criticisms over the years. This metaphor, first published in 1961, is thought to have been invented independently in two different articles, one by Ernst Mayr and the other by François Jacob and Jacques Monod. Here, after a detailed analysis of what both parties meant by "genetic program," I show, using unpublished archives, the strong resemblance between the ideas of Mayr and Monod and suggest that their idea of genetic program probably shares a common origin. I explore the possibility that the two men met before 1961 and also exchanged their ideas through common friends and colleagues in the field of molecular biology. Based on unpublished correspondence of Jacob and Monod, I highlight the important events that influenced the preparation of their influential paper, which introduced the concept of the genetic program. Finally, I suggest that the genetic program metaphor may have preceded both papers and that it was probably used informally before 1961.

  15. Genetic programming and serial processing for time series classification.

    Science.gov (United States)

    Alfaro-Cid, Eva; Sharman, Ken; Esparcia-Alcázar, Anna I

    2014-01-01

    This work describes an approach devised by the authors for time series classification. In our approach genetic programming is used in combination with a serial processing of data, where the last output is the result of the classification. The use of genetic programming for classification, although still a field where more research in needed, is not new. However, the application of genetic programming to classification tasks is normally done by considering the input data as a feature vector. That is, to the best of our knowledge, there are not examples in the genetic programming literature of approaches where the time series data are processed serially and the last output is considered as the classification result. The serial processing approach presented here fills a gap in the existing literature. This approach was tested in three different problems. Two of them are real world problems whose data were gathered for online or conference competitions. As there are published results of these two problems this gives us the chance to compare the performance of our approach against top performing methods. The serial processing of data in combination with genetic programming obtained competitive results in both competitions, showing its potential for solving time series classification problems. The main advantage of our serial processing approach is that it can easily handle very large datasets.

  16. Mendelian Genetics: Paradigm, Conjecture, or Research Program.

    Science.gov (United States)

    Oldham, V.; Brouwer, W.

    1984-01-01

    Applies Kuhn's model of the structure of scientific revolutions, Popper's hypothetic-deductive model of science, and Lakatos' methodology of competing research programs to a historical biological episode. Suggests using Kuhn's model (emphasizing the nonrational basis of science) and Popper's model (emphasizing the rational basis of science) in…

  17. Mendelian Genetics: Paradigm, Conjecture, or Research Program.

    Science.gov (United States)

    Oldham, V.; Brouwer, W.

    1984-01-01

    Applies Kuhn's model of the structure of scientific revolutions, Popper's hypothetic-deductive model of science, and Lakatos' methodology of competing research programs to a historical biological episode. Suggests using Kuhn's model (emphasizing the nonrational basis of science) and Popper's model (emphasizing the rational basis of science) in…

  18. Primer on Molecular Genetics; DOE Human Genome Program

    Science.gov (United States)

    1992-04-01

    This report is taken from the April 1992 draft of the DOE Human Genome 1991--1992 Program Report, which is expected to be published in May 1992. The primer is intended to be an introduction to basic principles of molecular genetics pertaining to the genome project. The material contained herein is not final and may be incomplete. Techniques of genetic mapping and DNA sequencing are described.

  19. Primer on molecular genetics. DOE Human Genome Program

    Energy Technology Data Exchange (ETDEWEB)

    1992-04-01

    This report is taken from the April 1992 draft of the DOE Human Genome 1991--1992 Program Report, which is expected to be published in May 1992. The primer is intended to be an introduction to basic principles of molecular genetics pertaining to the genome project. The material contained herein is not final and may be incomplete. Techniques of genetic mapping and DNA sequencing are described.

  20. An adaptive genetic algorithm for solving bilevel linear programming problem

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Bilevel linear programming, which consists of the objective functions of the upper level and lower level, is a useful tool for modeling decentralized decision problems.Various methods are proposed for solving this problem. Of all the algorithms, the genetic algorithm is an alternative to conventional approaches to find the solution of the bilevel linear programming. In this paper, we describe an adaptive genetic algorithm for solving the bilevel linear programming problem to overcome the difficulty of determining the probabilities of crossover and mutation. In addition, some techniques are adopted not only to deal with the difficulty that most of the chromosomes may be infeasible in solving constrained optimization problem with genetic algorithm but also to improve the efficiency of the algorithm. The performance of this proposed algorithm is illustrated by the examples from references.

  1. Manufacturing Resource Planning Technology Based on Genetic Programming Simulation

    Institute of Scientific and Technical Information of China (English)

    GAO Shiwen; LIAO Wenhe; GUO Yu; LIU Jinshan; SU Yan

    2009-01-01

    Network-based manufacturing is a kind of distributed system, which enables manufacturers to finish production tasks as well as to grasp the opportunities in the market, even if manufacturing resources are insufficient. One of the main problems in network-based manufacturing is the allocation of resources and the assignment of tasks rationally, according to flexible resource distribution. The mapping rules and relations between production techniques and resources are proposed, followed by the definition of the resource unit. Ultimately, the genetic programming method for the optimization of the manufacturing system is put forward. A set of software for the optimization system of simulation process using genetic programming techniques has been developed, and the problems of manufacturing resource planning in network-based manufacturing are solved with the simulation of optimizing methods by genetic programming. The optimum proposal of hardware planning, selection of company and scheduling will be obtained in theory to help company managers in scientific decision-making.

  2. Polyglot programming in applications used for genetic data analysis.

    Science.gov (United States)

    Nowak, Robert M

    2014-01-01

    Applications used for the analysis of genetic data process large volumes of data with complex algorithms. High performance, flexibility, and a user interface with a web browser are required by these solutions, which can be achieved by using multiple programming languages. In this study, I developed a freely available framework for building software to analyze genetic data, which uses C++, Python, JavaScript, and several libraries. This system was used to build a number of genetic data processing applications and it reduced the time and costs of development.

  3. Genetic Programming for Medicinal Plant Family Identification System

    Directory of Open Access Journals (Sweden)

    Indra Laksmana

    2014-11-01

    Full Text Available Information about medicinal plants that is available in text documents is generally quite easy to access, however, one needs some efforts to use it. This research was aimed at utilizing crucial information taken from a text document to identify the family of several species of medicinal plants using a heuristic approach, i.e. genetic programming. Each of the species has its unique features. The genetic program puts the characteristics or special features of each family into a tree form. There are a number of processes involved in the investigated method, i.e. data acquisition, booleanization, grouping of training and test data, evaluation, and analysis. The genetic program uses a training process to select the best individual, initializes a generate-rule process to create several individuals and then executes a fitness evaluation. The next procedure is a genetic operation process, which consists of tournament selection to choose the best individual based on a fitness value, the crossover operation and the mutation operation. These operations have the purpose of complementing the individual. The best individual acquired is the expected solution, which is a rule for classifying medicinal plants. This process produced three rules, one for each plant family, displaying a feature structure that distinguishes each of the families from each other. The genetic program then used these rules to identify the medicinal plants, achieving an average accuracy of 86.47%.

  4. Genetic Evolution of Shape-Altering Programs for Supersonic Aerodynamics

    Science.gov (United States)

    Kennelly, Robert A., Jr.; Bencze, Daniel P. (Technical Monitor)

    2002-01-01

    Two constrained shape optimization problems relevant to aerodynamics are solved by genetic programming, in which a population of computer programs evolves automatically under pressure of fitness-driven reproduction and genetic crossover. Known optimal solutions are recovered using a small, naive set of elementary operations. Effectiveness is improved through use of automatically defined functions, especially when one of them is capable of a variable number of iterations, even though the test problems lack obvious exploitable regularities. An attempt at evolving new elementary operations was only partially successful.

  5. Template learning of cellular neural network using genetic programming.

    Science.gov (United States)

    Radwan, Elsayed; Tazaki, Eiichiro

    2004-08-01

    A new learning algorithm for space invariant Uncoupled Cellular Neural Network is introduced. Learning is formulated as an optimization problem. Genetic Programming has been selected for creating new knowledge because they allow the system to find new rules both near to good ones and far from them, looking for unknown good control actions. According to the lattice Cellular Neural Network architecture, Genetic Programming will be used in deriving the Cloning Template. Exploration of any stable domain is possible by the current approach. Details of the algorithm are discussed and several application results are shown.

  6. Genetic program based data mining to reverse engineer digital logic

    Science.gov (United States)

    Smith, James F., III; Nguyen, Thanh Vu H.

    2006-04-01

    A data mining based procedure for automated reverse engineering and defect discovery has been developed. The data mining algorithm for reverse engineering uses a genetic program (GP) as a data mining function. A genetic program is an algorithm based on the theory of evolution that automatically evolves populations of computer programs or mathematical expressions, eventually selecting one that is optimal in the sense it maximizes a measure of effectiveness, referred to as a fitness function. The system to be reverse engineered is typically a sensor. Design documents for the sensor are not available and conditions prevent the sensor from being taken apart. The sensor is used to create a database of input signals and output measurements. Rules about the likely design properties of the sensor are collected from experts. The rules are used to create a fitness function for the genetic program. Genetic program based data mining is then conducted. This procedure incorporates not only the experts' rules into the fitness function, but also the information in the database. The information extracted through this process is the internal design specifications of the sensor. Uncertainty related to the input-output database and the expert based rule set can significantly alter the reverse engineering results. Significant experimental and theoretical results related to GP based data mining for reverse engineering will be provided. Methods of quantifying uncertainty and its effects will be presented. Finally methods for reducing the uncertainty will be examined.

  7. Genetic programming applied to RFI mitigation in radio astronomy

    Science.gov (United States)

    Staats, K.

    2016-12-01

    Genetic Programming is a type of machine learning that employs a stochastic search of a solutions space, genetic operators, a fitness function, and multiple generations of evolved programs to resolve a user-defined task, such as the classification of data. At the time of this research, the application of machine learning to radio astronomy was relatively new, with a limited number of publications on the subject. Genetic Programming had never been applied, and as such, was a novel approach to this challenging arena. Foundational to this body of research, the application Karoo GP was developed in the programming language Python following the fundamentals of tree-based Genetic Programming described in "A Field Guide to Genetic Programming" by Poli, et al. Karoo GP was tasked with the classification of data points as signal or radio frequency interference (RFI) generated by instruments and machinery which makes challenging astronomers' ability to discern the desired targets. The training data was derived from the output of an observation run of the KAT-7 radio telescope array built by the South African Square Kilometre Array (SKA-SA). Karoo GP, kNN, and SVM were comparatively employed, the outcome of which provided noteworthy correlations between input parameters, the complexity of the evolved hypotheses, and performance of raw data versus engineered features. This dissertation includes description of novel approaches to GP, such as upper and lower limits to the size of syntax trees, an auto-scaling multiclass classifier, and a Numpy array element manager. In addition to the research conducted at the SKA-SA, it is described how Karoo GP was applied to fine-tuning parameters of a weather prediction model at the South African Astronomical Observatory (SAAO), to glitch classification at the Laser Interferometer Gravitational-wave Observatory (LIGO), and to astro-particle physics at The Ohio State University.

  8. Feature extraction from multiple data sources using genetic programming.

    Energy Technology Data Exchange (ETDEWEB)

    Szymanski, J. J. (John J.); Brumby, Steven P.; Pope, P. A. (Paul A.); Eads, D. R. (Damian R.); Galassi, M. C. (Mark C.); Harvey, N. R. (Neal R.); Perkins, S. J. (Simon J.); Porter, R. B. (Reid B.); Theiler, J. P. (James P.); Young, A. C. (Aaron Cody); Bloch, J. J. (Jeffrey J.); David, N. A. (Nancy A.); Esch-Mosher, D. M. (Diana M.)

    2002-01-01

    Feature extration from imagery is an important and long-standing problem in remote sensing. In this paper, we report on work using genetic programming to perform feature extraction simultaneously from multispectral and digital elevation model (DEM) data. The tool used is the GENetic Imagery Exploitation (GENIE) software, which produces image-processing software that inherently combines spatial and spectral processing. GENIE is particularly useful in exploratory studies of imagery, such as one often does in combining data from multiple sources. The user trains the software by painting the feature of interest with a simple graphical user interface. GENIE then uses genetic programming techniques to produce an image-processing pipeline. Here, we demonstrate evolution of image processing algorithms that extract a range of land-cover features including towns, grasslands, wild fire burn scars, and several types of forest. We use imagery from the DOE/NNSA Multispectral Thermal Imager (MTI) spacecraft, fused with USGS 1:24000 scale DEM data.

  9. Considering genetic characteristics in German Holstein breeding programs.

    Science.gov (United States)

    Segelke, D; Täubert, H; Reinhardt, F; Thaller, G

    2016-01-01

    Recently, several research groups have demonstrated that several haplotypes may cause embryonic loss in the homozygous state. Up to now, carriers of genetic disorders were often excluded from mating, resulting in a decrease of genetic gain and a reduced number of sires available for the breeding program. Ongoing research is very likely to identify additional genetic defects causing embryonic loss and calf mortality by genotyping a large proportion of the female cattle population and sequencing key ancestors. Hence, a clear demand is present to develop a method combining selection against recessive defects (e.g., Holstein haplotypes HH1-HH5) with selection for economically beneficial traits (e.g., polled) for mating decisions. Our proposed method is a genetic index that accounts for the allele frequencies in the population and the economic value of the genetic characteristic without excluding carriers from breeding schemes. Fertility phenotypes from routine genetic evaluations were used to determine the economic value per embryo lost. Previous research has shown that embryo loss caused by HH1 and HH2 occurs later than the loss for HH3, HH4, and HH5. Therefore, an economic value of € 97 was used against HH1 and HH2 and € 70 against HH3, HH4, and HH5. For polled, € 7 per polled calf was considered. Minor allele frequencies of the defects ranged between 0.8 and 3.3%. The polled allele has a frequency of 4.1% in the German Holstein population. A genomic breeding program was simulated to study the effect of changing the selection criteria from assortative mating based on breeding values to selecting the females using the genetic index. Selection for a genetic index on the female path is a useful method to control the allele frequencies by reducing undesirable alleles and simultaneously increasing economical beneficial characteristics maintaining most of the genetic gain in production and functional traits. Additionally, we applied the genetic index to real data and

  10. Initialization Method for Grammar-Guided Genetic Programming

    Science.gov (United States)

    García-Arnau, M.; Manrique, D.; Ríos, J.; Rodríguez-Patón, A.

    This paper proposes a new tree-generation algorithm for grammarguided genetic programming that includes a parameter to control the maximum size of the trees to be generated. An important feature of this algorithm is that the initial populations generated are adequately distributed in terms of tree size and distribution within the search space. Consequently, genetic programming systems starting from the initial populations generated by the proposed method have a higher convergence speed. Two different problems have been chosen to carry out the experiments: a laboratory test involving searching for arithmetical equalities and the real-world task of breast cancer prognosis. In both problems, comparisons have been made to another five important initialization methods.

  11. Multigene Genetic Programming for Estimation of Elastic Modulus of Concrete

    Directory of Open Access Journals (Sweden)

    Alireza Mohammadi Bayazidi

    2014-01-01

    Full Text Available This paper presents a new multigene genetic programming (MGGP approach for estimation of elastic modulus of concrete. The MGGP technique models the elastic modulus behavior by integrating the capabilities of standard genetic programming and classical regression. The main aim is to derive precise relationships between the tangent elastic moduli of normal and high strength concrete and the corresponding compressive strength values. Another important contribution of this study is to develop a generalized prediction model for the elastic moduli of both normal and high strength concrete. Numerous concrete compressive strength test results are obtained from the literature to develop the models. A comprehensive comparative study is conducted to verify the performance of the models. The proposed models perform superior to the existing traditional models, as well as those derived using other powerful soft computing tools.

  12. Genetic variability of broodstocks of restocking programs in Brazil

    Directory of Open Access Journals (Sweden)

    Nelson Lopera-Barrero

    2015-09-01

    Full Text Available Objective. The aim of this study was evaluate the genetic diversity of the following broodstocks: piapara (Leporinus elongatus, dourado (Salminus brasiliensis, jundiá (Rhamdia quelen and cachara (Pseudoplatystoma fasciatum already useful for restocking programs in the Paranapanema, Iguaçu and Paraná Brazilian Rivers. Materials and methods. Samples from the caudal fin of 122 fish were analyzed. DNA was extracted by NaCl protocol. PCR products were separated by a horizontal agarose gel electrophoresis. The fragments were visualized by staining with ethidium bromide. Results. The amplification of 25 primers generated different fragments in studied species that allowed characterizing 440 fragments of 100-2900 bp. High percentage of polymorphic fragments (66.67 to 86.29, Shannon index (0.365 to 0.486 and genetic diversity of Nei (0.248 to 0.331 were detected. Conclusions. The level of genetic variability in the broodstocks was adequate for allowing their use in restocking programs in the studied Rivers. However, periodical monitoring studies of genetic variability in these stocks, the mating system, reproductive system and general management must be made to guarantee the preservation of wild populations.

  13. Finding Approximate Analytic Solutions to Differential Equations by Seed Selection Genetic Programming

    Institute of Scientific and Technical Information of China (English)

    侯进军

    2007-01-01

    @@ 1 Seed Selection Genetic Programming In Genetic Programming, each tree in population shows an algebraic or surmounting expression, and each algebraic or surmounting expression shows an approximate analytic solution to differential equations.

  14. Genetic regulation of programmed cell death in Drosophila

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Programmed cell death plays an important role in maintaining homeostasis during animal development, and has been conserved in animals as different as nematodes and humans. Recent studies of Drosophila have provided valuable information toward our understanding of genetic regulation of death. Different signals trigger the novel death regulators rpr, hid, and grim, that utilize the evolutionarily conserved iap and ark genes to modulate caspase function. Subsequent removal of dying cells also appears to be accomplished by conserved mechanisms. The similarity between Drosophila and human in cell death signaling pathways illustrate the promise of fruit flies as a model system to elucidate the mechanisms underlying regulation of programmed cell death.

  15. Genetic programming-based chaotic time series modeling

    Institute of Scientific and Technical Information of China (English)

    张伟; 吴智铭; 杨根科

    2004-01-01

    This paper proposes a Genetic Programming-Based Modeling (GPM) algorithm on chaotic time series. GP is used here to search for appropriate model structures in function space, and the Particle Swarm Optimization (PSO) algorithm is used for Nonlinear Parameter Estimation (NPE) of dynamic model structures. In addition, GPM integrates the results of Nonlinear Time Series Analysis (NTSA) to adjust the parameters and takes them as the criteria of established models. Experiments showed the effectiveness of such improvements on chaotic time series modeling.

  16. Long Term Energy Consumption Forecasting Using Genetic Programming

    OpenAIRE

    KARABULUT, Korhan; Alkan, Ahmet; YILMAZ, Ahmet

    2008-01-01

    Managing electrical energy supply is a complex task. The most important part of electric utility resource planning is forecasting of the future load demand in the regional or national service area. This is usually achieved by constructing models on relative information, such as climate and previous load demand data. In this paper, a genetic programming approach is proposed to forecast long term electrical power consumption in the area covered by a utility situated in the southeast of Turkey. ...

  17. Tracking the Genetic Stability of a Honey Bee (Hymenoptera: Apidae) Breeding Program With Genetic Markers.

    Science.gov (United States)

    Bourgeois, Lelania; Beaman, Lorraine

    2017-08-01

    A genetic stock identification (GSI) assay was developed in 2008 to distinguish Russian honey bees from other honey bee stocks that are commercially produced in the United States. Probability of assignment (POA) values have been collected and maintained since the stock release in 2008 to the Russian Honey Bee Breeders Association. These data were used to assess stability of the breeding program and the diversity levels of the contemporary breeding stock through comparison of POA values and genetic diversity parameters from the initial release to current values. POA values fluctuated throughout 2010-2016, but have recovered to statistically similar levels in 2016 (POA(2010) = 0.82, POA(2016) = 0.74; P = 0.33). Genetic diversity parameters (i.e., allelic richness and gene diversity) in 2016 also remained at similar levels when compared to those in 2010. Estimates of genetic structure revealed stability (FST(2009/2016) = 0.0058) with a small increase in the estimate of the inbreeding coefficient (FIS(2010) = 0.078, FIS(2016) = 0.149). The relationship among breeding lines, based on genetic distance measurement, was similar in 2008 and 2016 populations, but with increased homogeneity among lines (i.e., decreased genetic distance). This was expected based on the closed breeding system used for Russian honey bees. The successful application of the GSI assay in a commercial breeding program demonstrates the utility and stability of such technology to contribute to and monitor the genetic integrity of a breeding stock of an insect species. Published by Oxford University Press on behalf of Entomological Society of America 2017. This work is written by US Government employees and is in the public domain in the US.

  18. Genetic Programming Modeling and Complexity Analysis of the Magnetoencephalogram of Epileptic Patients

    Science.gov (United States)

    Georgopoulos, Efstratios F.; Adamopoulos, Adam V.; Likothanassis, Spiridon D.

    In this work MagnetoEncephaloGram (MEG) recordings of epileptic patients are modeled using a genetic programming approach. This is the first time that genetic programming is used to model MEG signal. Numerous experiments were conducted giving highly successful results. It is demonstrated that genetic programming can produce very simple nonlinear models that fit with great accuracy the observed data of MEG.

  19. Genetic Programming Neural Networks: A Powerful Bioinformatics Tool for Human Genetics.

    Science.gov (United States)

    Ritchie, Marylyn D; Motsinger, Alison A; Bush, William S; Coffey, Christopher S; Moore, Jason H

    2007-01-01

    The identification of genes that influence the risk of common, complex disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. This challenge is partly due to the limitations of parametric statistical methods for detecting genetic effects that are dependent solely or partially on interactions. We have previously introduced a genetic programming neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of genetic and gene-environment combinations associated with disease risk. Previous empirical studies suggest GPNN has excellent power for identifying gene-gene and gene-environment interactions. The goal of this study was to compare the power of GPNN to stepwise logistic regression (SLR) and classification and regression trees (CART) for identifying gene-gene and gene-environment interactions. SLR and CART are standard methods of analysis for genetic association studies. Using simulated data, we show that GPNN has higher power to identify gene-gene and gene-environment interactions than SLR and CART. These results indicate that GPNN may be a useful pattern recognition approach for detecting gene-gene and gene-environment interactions in studies of human disease.

  20. Feedback Control of Turbulent Shear Flows by Genetic Programming

    CERN Document Server

    Duriez, Thomas; von Krbek, Kai; Bonnet, Jean-Paul; Cordier, Laurent; Noack, Bernd R; Segond, Marc; Abel, Markus; Gautier, Nicolas; Aider, Jean-Luc; Raibaudo, Cedric; Cuvier, Christophe; Stanislas, Michel; Debien, Antoine; Mazellier, Nicolas; Kourta, Azeddine; Brunton, Steven L

    2015-01-01

    Turbulent shear flows have triggered fundamental research in nonlinear dynamics, like transition scenarios, pattern formation and dynamical modeling. In particular, the control of nonlinear dynamics is subject of research since decades. In this publication, actuated turbulent shear flows serve as test-bed for a nonlinear feedback control strategy which can optimize an arbitrary cost function in an automatic self-learning manner. This is facilitated by genetic programming providing an analytically treatable control law. Unlike control based on PID laws or neural networks, no structure of the control law needs to be specified in advance. The strategy is first applied to low-dimensional dynamical systems featuring aspects of turbulence and for which linear control methods fail. This includes stabilizing an unstable fixed point of a nonlinearly coupled oscillator model and maximizing mixing, i.e.\\ the Lyapunov exponent, for forced Lorenz equations. For the first time, we demonstrate the applicability of genetic p...

  1. Stream Flow Prediction by Remote Sensing and Genetic Programming

    Science.gov (United States)

    Chang, Ni-Bin

    2009-01-01

    A genetic programming (GP)-based, nonlinear modeling structure relates soil moisture with synthetic-aperture-radar (SAR) images to present representative soil moisture estimates at the watershed scale. Surface soil moisture measurement is difficult to obtain over a large area due to a variety of soil permeability values and soil textures. Point measurements can be used on a small-scale area, but it is impossible to acquire such information effectively in large-scale watersheds. This model exhibits the capacity to assimilate SAR images and relevant geoenvironmental parameters to measure soil moisture.

  2. Genetic programming-based chaotic time series modeling

    Institute of Scientific and Technical Information of China (English)

    张伟; 吴智铭; 杨根科

    2004-01-01

    This paper proposes a Genetic Programming-Based Modeling(GPM)algorithm on chaotic time series. GP is used here to search for appropriate model structures in function space,and the Particle Swarm Optimization(PSO)algorithm is used for Nonlinear Parameter Estimation(NPE)of dynamic model structures. In addition,GPM integrates the results of Nonlinear Time Series Analysis(NTSA)to adjust the parameters and takes them as the criteria of established models.Experiments showed the effectiveness of such improvements on chaotic time series modeling.

  3. Combining classifiers generated by multi-gene genetic programming for protein fold recognition using genetic algorithm.

    Science.gov (United States)

    Bardsiri, Mahshid Khatibi; Eftekhari, Mahdi; Mousavi, Reza

    2015-01-01

    In this study the problem of protein fold recognition, that is a classification task, is solved via a hybrid of evolutionary algorithms namely multi-gene Genetic Programming (GP) and Genetic Algorithm (GA). Our proposed method consists of two main stages and is performed on three datasets taken from the literature. Each dataset contains different feature groups and classes. In the first step, multi-gene GP is used for producing binary classifiers based on various feature groups for each class. Then, different classifiers obtained for each class are combined via weighted voting so that the weights are determined through GA. At the end of the first step, there is a separate binary classifier for each class. In the second stage, the obtained binary classifiers are combined via GA weighting in order to generate the overall classifier. The final obtained classifier is superior to the previous works found in the literature in terms of classification accuracy.

  4. EVOLVING RETRIEVAL ALGORITHMS WITH A GENETIC PROGRAMMING SCHEME

    Energy Technology Data Exchange (ETDEWEB)

    J. THEILER; ET AL

    1999-06-01

    The retrieval of scene properties (surface temperature, material type, vegetation health, etc.) from remotely sensed data is the ultimate goal of many earth observing satellites. The algorithms that have been developed for these retrievals are informed by physical models of how the raw data were generated. This includes models of radiation as emitted and/or rejected by the scene, propagated through the atmosphere, collected by the optics, detected by the sensor, and digitized by the electronics. To some extent, the retrieval is the inverse of this ''forward'' modeling problem. But in contrast to this forward modeling, the practical task of making inferences about the original scene usually requires some ad hoc assumptions, good physical intuition, and a healthy dose of trial and error. The standard MTI data processing pipeline will employ algorithms developed with this traditional approach. But we will discuss some preliminary research on the use of a genetic programming scheme to ''evolve'' retrieval algorithms. Such a scheme cannot compete with the physical intuition of a remote sensing scientist, but it may be able to automate some of the trial and error. In this scenario, a training set is used, which consists of multispectral image data and the associated ''ground truth;'' that is, a registered map of the desired retrieval quantity. The genetic programming scheme attempts to combine a core set of image processing primitives to produce an IDL (Interactive Data Language) program which estimates this retrieval quantity from the raw data.

  5. A new crossover operator in genetic programming for object classification.

    Science.gov (United States)

    Zhang, Mengjie; Gao, Xiaoying; Lou, Weijun

    2007-10-01

    The crossover operator has been considered "the centre of the storm" in genetic programming (GP). However, many existing GP approaches to object recognition suggest that the standard GP crossover is not sufficiently powerful in producing good child programs due to the totally random choice of the crossover points. To deal with this problem, this paper introduces an approach with a new crossover operator in GP for object recognition, particularly object classification. In this approach, a local hill-climbing search is used in constructing good building blocks, a weight called looseness is introduced to identify the good building blocks in individual programs, and the looseness values are used as heuristics in choosing appropriate crossover points to preserve good building blocks. This approach is examined and compared with the standard crossover operator and the headless chicken crossover (HCC) method on a sequence of object classification problems. The results suggest that this approach outperforms the HCC, the standard crossover, and the standard crossover operator with hill climbing on all of these problems in terms of the classification accuracy. Although this approach spends a bit longer time than the standard crossover operator, it significantly improves the system efficiency over the HCC method.

  6. Genetic counseling services and development of training programs in Malaysia.

    Science.gov (United States)

    Lee, Juliana Mei-Har; Thong, Meow-Keong

    2013-12-01

    Genetic counseling service is urgently required in developing countries. In Malaysia, the first medical genetic service was introduced in 1994 at one of the main teaching hospitals in Kuala Lumpur. Two decades later, the medical genetic services have improved with the availability of genetic counseling, genetic testing and diagnosis, for both paediatric conditions and adult-onset inherited conditions, at four main centers of medical genetic services in Malaysia. Prenatal diagnosis services and assisted reproductive technologies are available at tertiary centres and private medical facilities. Positive developments include governmental recognition of Clinical Genetics as a subspecialty, increased funding for genetics services, development of medical ethics guidelines, and establishment of support groups. However, the country lacked qualified genetic counselors. Proposals were presented to policy-makers to develop genetic counseling courses. Challenges encountered included limited resources and public awareness, ethical dilemmas such as religious and social issues and inadequate genetic health professionals especially genetic counselors.

  7. Practice-based competencies for accreditation of and training in graduate programs in genetic counseling.

    Science.gov (United States)

    Fine, B A; Baker, D L; Fiddler, M B

    1996-09-01

    In January 1996, the American Board of Genetic Counseling (ABGC) adopted 27 practice-based competencies as a standard for assessing the training of graduate students in genetic counseling. These competencies were identified and refined through a collective, narrative process that took place from January through November 1994, and included directors of graduate programs in genetic counseling, ABGC board members and expert consultants. These competencies now form the basis of the document "Requirements for Graduate Programs in Genetic Counseling Seeking Accreditation by the American Board of Genetic Counseling" (American Board of Genetic Counseling, 1996). The competencies are organized into four domains and are presented and discussed in this article.

  8. Integer programming model for optimizing bus timetable using genetic algorithm

    Science.gov (United States)

    Wihartiko, F. D.; Buono, A.; Silalahi, B. P.

    2017-01-01

    Bus timetable gave an information for passengers to ensure the availability of bus services. Timetable optimal condition happened when bus trips frequency could adapt and suit with passenger demand. In the peak time, the number of bus trips would be larger than the off-peak time. If the number of bus trips were more frequent than the optimal condition, it would make a high operating cost for bus operator. Conversely, if the number of trip was less than optimal condition, it would make a bad quality service for passengers. In this paper, the bus timetabling problem would be solved by integer programming model with modified genetic algorithm. Modification was placed in the chromosomes design, initial population recovery technique, chromosomes reconstruction and chromosomes extermination on specific generation. The result of this model gave the optimal solution with accuracy 99.1%.

  9. GENETIC PROGRAMMING TO PREDICT SKI-JUMP BUCKET SPILLWAY SCOUR

    Institute of Scientific and Technical Information of China (English)

    AZAMATHULLA H. MD; GHANI A. AB; ZAKARIA N. A; LAI S. H; CHANG C. K; LEOW C. S; ABUHASAN Z

    2008-01-01

    Researchers in the past had noticed that application of Artificial Neural Networks (ANN) in place of conventional statistics on the basis of data mining techniques predicts more accurate results in hydraulic predictions. Mostly these works pertained to applications of ANN. Recently, another tool of soft computing, namely, Genetic Programming (GP) has caught the attention of researchers in civil engineering computing. This article examines the usefulness of the GP based approach to predict the relative scour depth downstream of a common type of ski-jump bucket spillway. Actual field measurements were used to develop the GP model. The GP based estimations were found to be equally and more accurate than the ANN based ones, especially, when the underlying cause-effect relationship became more uncertain to model.

  10. Reversible circuit synthesis by genetic programming using dynamic gate libraries

    Science.gov (United States)

    Abubakar, Mustapha Y.; Jung, Low Tang; Zakaria, Nordin; Younes, Ahmed; Abdel-Aty, Abdel-Haleem

    2017-06-01

    We have defined a new method for automatic construction of reversible logic circuits by using the genetic programming approach. The choice of the gate library is 100% dynamic. The algorithm is capable of accepting all possible combinations of the following gate types: NOT TOFFOLI, NOT PERES, NOT CNOT TOFFOLI, NOT CNOT SWAP FREDKIN, NOT CNOT TOFFOLI SWAP FREDKIN, NOT CNOT PERES, NOT CNOT SWAP FREDKIN PERES, NOT CNOT TOFFOLI PERES and NOT CNOT TOFFOLI SWAP FREDKIN PERES. Our method produced near optimum circuits in some cases when a particular subset of gate types was used in the library. Meanwhile, in some cases, optimal circuits were produced due to the heuristic nature of the algorithm. We compared the outcomes of our method with several existing synthesis methods, and it was shown that our algorithm performed relatively well compared to the previous synthesis methods in terms of the output efficiency of the algorithm and execution time as well.

  11. A Comparison of Genetic Programming Variants for Hyper-Heuristics

    Energy Technology Data Exchange (ETDEWEB)

    Harris, Sean [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-03-01

    Modern society is faced with ever more complex problems, many of which can be formulated as generate-and-test optimization problems. General-purpose optimization algorithms are not well suited for real-world scenarios where many instances of the same problem class need to be repeatedly and efficiently solved, such as routing vehicles over highways with constantly changing traffic flows, because they are not targeted to a particular scenario. Hyper-heuristics automate the design of algorithms to create a custom algorithm for a particular scenario. Hyper-heuristics typically employ Genetic Programming (GP) and this project has investigated the relationship between the choice of GP and performance in Hyper-heuristics. Results are presented demonstrating the existence of problems for which there is a statistically significant performance differential between the use of different types of GP.

  12. Forecasting tourist arrivals to balearic islands using genetic programming

    Directory of Open Access Journals (Sweden)

    Rosselló-Nadal, Jaume

    2007-01-01

    Full Text Available Traditionally, univariate time-series models have largely dominated forecasting for international tourism demand. In this paper, the ability of a Genetic Program (GP to predict monthly tourist arrivals from UK and Germany to Balearic Islands (Spain is explored. GP has already been employed satisfactorily in different scientific areas, including economics. The technique shows different advantages regarding to other forecasting methods. Firstly, it does not assume a priori a rigid functional form of the model. Secondly, it is more robust and easy-to-use than other non-parametric methods. Finally, it provides explicitly a mathematical equation which allows a simple ad hoc interpretation of the results. Comparing the performance of the proposed technique against other method commonly used in tourism forecasting (no-change model, Moving Average and ARIMA, the empirical results reveal that GP can be a valuable tool in this field.

  13. Comprehensive bidding strategies with genetic programming/finite state automata

    Energy Technology Data Exchange (ETDEWEB)

    Richter, C.W. Jr.; Sheble, G.B.; Ashlock, D.

    1999-11-01

    This research is an extension of the authors' previous work in double auctions aimed at developing bidding strategies for electric utilities which trade electricity competitively. The improvements detailed in this paper come from using data structures which combine genetic programming and finite state automata termed GP-Automata. The strategies developed by the method described here are adaptive--reacting to inputs--whereas the previously developed strategies were only suitable in the particular scenario for which they had been designed. The strategies encoded in the GP-Automata are tested in an auction simulator. The simulator pits them against other distribution companies (distcos) and generation companies (gencos), buying and selling power via double auctions implemented in regional commodity exchanges. The GP-Automata are evolved with a genetic algorithm so that they possess certain characteristics. In addition to designing successful bidding strategies (whose usage would result in higher profits) the resulting strategies can also be designed to imitate certain types of trading behaviors. The resulting strategies can be implemented directly in on-line trading, or can be used as realistic competitors in an off-line trading simulator.

  14. Accurate construction of consensus genetic maps via integer linear programming.

    Science.gov (United States)

    Wu, Yonghui; Close, Timothy J; Lonardi, Stefano

    2011-01-01

    We study the problem of merging genetic maps, when the individual genetic maps are given as directed acyclic graphs. The computational problem is to build a consensus map, which is a directed graph that includes and is consistent with all (or, the vast majority of) the markers in the input maps. However, when markers in the individual maps have ordering conflicts, the resulting consensus map will contain cycles. Here, we formulate the problem of resolving cycles in the context of a parsimonious paradigm that takes into account two types of errors that may be present in the input maps, namely, local reshuffles and global displacements. The resulting combinatorial optimization problem is, in turn, expressed as an integer linear program. A fast approximation algorithm is proposed, and an additional speedup heuristic is developed. Our algorithms were implemented in a software tool named MERGEMAP which is freely available for academic use. An extensive set of experiments shows that MERGEMAP consistently outperforms JOINMAP, which is the most popular tool currently available for this task, both in terms of accuracy and running time. MERGEMAP is available for download at http://www.cs.ucr.edu/~yonghui/mgmap.html.

  15. A novel genetic programming approach for epileptic seizure detection.

    Science.gov (United States)

    Bhardwaj, Arpit; Tiwari, Aruna; Krishna, Ramesh; Varma, Vishaal

    2016-02-01

    The human brain is a delicate mix of neurons (brain cells), electrical impulses and chemicals, known as neurotransmitters. Any damage has the potential to disrupt the workings of the brain and cause seizures. These epileptic seizures are the manifestations of epilepsy. The electroencephalograph (EEG) signals register average neuronal activity from the cerebral cortex and label changes in activity over large areas. A detailed analysis of these electroencephalograph (EEG) signals provides valuable insights into the mechanisms instigating epileptic disorders. Moreover, the detection of interictal spikes and epileptic seizures in an EEG signal plays an important role in the diagnosis of epilepsy. Automatic seizure detection methods are required, as these epileptic seizures are volatile and unpredictable. This paper deals with an automated detection of epileptic seizures in EEG signals using empirical mode decomposition (EMD) for feature extraction and proposes a novel genetic programming (GP) approach for classifying the EEG signals. Improvements in the standard GP approach are made using a Constructive Genetic Programming (CGP) in which constructive crossover and constructive subtree mutation operators are introduced. A hill climbing search is integrated in crossover and mutation operators to remove the destructive nature of these operators. A new concept of selecting the Globally Prime offspring is also presented to select the best fitness offspring generated during crossover. To decrease the time complexity of GP, a new dynamic fitness value computation (DFVC) is employed to increase the computational speed. We conducted five different sets of experiments to evaluate the performance of the proposed model in the classification of different mixtures of normal, interictal and ictal signals, and the accuracies achieved are outstandingly high. The experimental results are compared with the existing methods on same datasets, and these results affirm the potential use of

  16. Multi-Center Genetic Study of Hypertension: The Family Blood Pressure Program (FBPP)

    National Research Council Canada - National Science Library

    The FBPP Investigators

    2002-01-01

    The Family Blood Pressure Program (FBPP) consists of 4 independently established multicenter networks of investigators who have complementary approaches to the genetics of blood pressure levels and hypertension...

  17. Structural health monitoring feature design by genetic programming

    Science.gov (United States)

    Harvey, Dustin Y.; Todd, Michael D.

    2014-09-01

    Structural health monitoring (SHM) systems provide real-time damage and performance information for civil, aerospace, and other high-capital or life-safety critical structures. Conventional data processing involves pre-processing and extraction of low-dimensional features from in situ time series measurements. The features are then input to a statistical pattern recognition algorithm to perform the relevant classification or regression task necessary to facilitate decisions by the SHM system. Traditional design of signal processing and feature extraction algorithms can be an expensive and time-consuming process requiring extensive system knowledge and domain expertise. Genetic programming, a heuristic program search method from evolutionary computation, was recently adapted by the authors to perform automated, data-driven design of signal processing and feature extraction algorithms for statistical pattern recognition applications. The proposed method, called Autofead, is particularly suitable to handle the challenges inherent in algorithm design for SHM problems where the manifestation of damage in structural response measurements is often unclear or unknown. Autofead mines a training database of response measurements to discover information-rich features specific to the problem at hand. This study provides experimental validation on three SHM applications including ultrasonic damage detection, bearing damage classification for rotating machinery, and vibration-based structural health monitoring. Performance comparisons with common feature choices for each problem area are provided demonstrating the versatility of Autofead to produce significant algorithm improvements on a wide range of problems.

  18. Empirical valence bond models for reactive potential energy surfaces: a parallel multilevel genetic program approach.

    Science.gov (United States)

    Bellucci, Michael A; Coker, David F

    2011-07-28

    We describe a new method for constructing empirical valence bond potential energy surfaces using a parallel multilevel genetic program (PMLGP). Genetic programs can be used to perform an efficient search through function space and parameter space to find the best functions and sets of parameters that fit energies obtained by ab initio electronic structure calculations. Building on the traditional genetic program approach, the PMLGP utilizes a hierarchy of genetic programming on two different levels. The lower level genetic programs are used to optimize coevolving populations in parallel while the higher level genetic program (HLGP) is used to optimize the genetic operator probabilities of the lower level genetic programs. The HLGP allows the algorithm to dynamically learn the mutation or combination of mutations that most effectively increase the fitness of the populations, causing a significant increase in the algorithm's accuracy and efficiency. The algorithm's accuracy and efficiency is tested against a standard parallel genetic program with a variety of one-dimensional test cases. Subsequently, the PMLGP is utilized to obtain an accurate empirical valence bond model for proton transfer in 3-hydroxy-gamma-pyrone in gas phase and protic solvent.

  19. Modeling the MagnetoencephaloGram (MEG) Of Epileptic Patients Using Genetic Programming and Minimizing the Derived Models Using Genetic Algorithms

    Science.gov (United States)

    Theofilatos, Konstantinos; Georgopoulos, Efstratios; Likothanassis, Spiridon

    2009-09-01

    In this paper, a variation of traditional Genetic Programming(GP) is used to model the MagnetoencephaloGram(MEG) of Epileptic Patients. This variation is Linear Genetic Programming(LGP). LGP is a particular subset of GP wherein computer programs in population are represented as a sequence of instructions from imperative programming language or machine language. The derived models from this method were simplified using genetic algorithms. The proposed method was used to model the MEG signal of epileptic patients using 6 different datasets. Each dataset uses different number of previous values of MEG to predict the next value. The models were tested in datasets different from the ones which were used to produce them and the results were very promising.

  20. Population genetics analysis using R and the Geneland program

    DEFF Research Database (Denmark)

    Guillot, Gilles; Santos, Filipe; Estoup, Arnaud

    2011-01-01

    Geneland program documentation 2011 Program distributed under GNU license as an R package on the Comprehensive R Archive Network.......Geneland program documentation 2011 Program distributed under GNU license as an R package on the Comprehensive R Archive Network....

  1. Genetic programming approach to evaluate complexity of texture images

    Science.gov (United States)

    Ciocca, Gianluigi; Corchs, Silvia; Gasparini, Francesca

    2016-11-01

    We adopt genetic programming (GP) to define a measure that can predict complexity perception of texture images. We perform psychophysical experiments on three different datasets to collect data on the perceived complexity. The subjective data are used for training, validation, and test of the proposed measure. These data are also used to evaluate several possible candidate measures of texture complexity related to both low level and high level image features. We select four of them (namely roughness, number of regions, chroma variance, and memorability) to be combined in a GP framework. This approach allows a nonlinear combination of the measures and could give hints on how the related image features interact in complexity perception. The proposed complexity measure M exhibits Pearson correlation coefficients of 0.890 on the training set, 0.728 on the validation set, and 0.724 on the test set. M outperforms each of all the single measures considered. From the statistical analysis of different GP candidate solutions, we found that the roughness measure evaluated on the gray level image is the most dominant one, followed by the memorability, the number of regions, and finally the chroma variance.

  2. Automating the packing heuristic design process with genetic programming.

    Science.gov (United States)

    Burke, Edmund K; Hyde, Matthew R; Kendall, Graham; Woodward, John

    2012-01-01

    The literature shows that one-, two-, and three-dimensional bin packing and knapsack packing are difficult problems in operational research. Many techniques, including exact, heuristic, and metaheuristic approaches, have been investigated to solve these problems and it is often not clear which method to use when presented with a new instance. This paper presents an approach which is motivated by the goal of building computer systems which can design heuristic methods. The overall aim is to explore the possibilities for automating the heuristic design process. We present a genetic programming system to automatically generate a good quality heuristic for each instance. It is not necessary to change the methodology depending on the problem type (one-, two-, or three-dimensional knapsack and bin packing problems), and it therefore has a level of generality unmatched by other systems in the literature. We carry out an extensive suite of experiments and compare with the best human designed heuristics in the literature. Note that our heuristic design methodology uses the same parameters for all the experiments. The contribution of this paper is to present a more general packing methodology than those currently available, and to show that, by using this methodology, it is possible for a computer system to design heuristics which are competitive with the human designed heuristics from the literature. This represents the first packing algorithm in the literature able to claim human competitive results in such a wide variety of packing domains.

  3. Genetic Programming Based Ensemble System for Microarray Data Classification

    Directory of Open Access Journals (Sweden)

    Kun-Hong Liu

    2015-01-01

    Full Text Available Recently, more and more machine learning techniques have been applied to microarray data analysis. The aim of this study is to propose a genetic programming (GP based new ensemble system (named GPES, which can be used to effectively classify different types of cancers. Decision trees are deployed as base classifiers in this ensemble framework with three operators: Min, Max, and Average. Each individual of the GP is an ensemble system, and they become more and more accurate in the evolutionary process. The feature selection technique and balanced subsampling technique are applied to increase the diversity in each ensemble system. The final ensemble committee is selected by a forward search algorithm, which is shown to be capable of fitting data automatically. The performance of GPES is evaluated using five binary class and six multiclass microarray datasets, and results show that the algorithm can achieve better results in most cases compared with some other ensemble systems. By using elaborate base classifiers or applying other sampling techniques, the performance of GPES may be further improved.

  4. Estimating soil wetting patterns for drip irrigation using genetic programming

    Energy Technology Data Exchange (ETDEWEB)

    Samadianfard, S.; Sadraddini, A. A.; Nazemi, A. H.; Provenzano, G.; Kisi, O.

    2012-07-01

    Drip irrigation is considered as one of the most efficient irrigation systems. Knowledge of the soil wetted perimeter arising from infiltration of water from drippers is important in the design and management of efficient irrigation systems. To this aim, numerical models can represent a powerful tool to analyze the evolution of the wetting pattern during irrigation, in order to explore drip irrigation management strategies, to set up the duration of irrigation, and finally to optimize water use efficiency. This paper examines the potential of genetic programming (GP) in simulating wetting patterns of drip irrigation. First by considering 12 different soil textures of USDA-SCS soil texture triangle, different emitter discharge and duration of irrigation, soil wetting patterns have been simulated by using HYDRUS 2D software. Then using the calculated values of depth and radius of wetting pattern as target outputs, two different GP models have been considered. Finally, the capability of GP for simulating wetting patterns was analyzed using some values of data set that were not used in training. Results showed that the GP method had good agreement with results of HYDRUS 2D software in the case of considering full set of operators with R{sup 2} of 0.99 and 0.99 and root mean squared error of 2.88 and 4.94 in estimation of radius and depth of wetting patterns, respectively. Also, field experimental results in a sandy loam soil with emitter discharge of 4 L h{sup -}1 showed reasonable agreement with GP results. As a conclusion, the results of the study demonstrate the usefulness of the GP method for estimating wetting patterns of drip irrigation. (Author) 40 refs.

  5. Mathematical Modeling of Intestinal Iron Absorption Using Genetic Programming

    Science.gov (United States)

    Colins, Andrea; Gerdtzen, Ziomara P.; Nuñez, Marco T.; Salgado, J. Cristian

    2017-01-01

    Iron is a trace metal, key for the development of living organisms. Its absorption process is complex and highly regulated at the transcriptional, translational and systemic levels. Recently, the internalization of the DMT1 transporter has been proposed as an additional regulatory mechanism at the intestinal level, associated to the mucosal block phenomenon. The short-term effect of iron exposure in apical uptake and initial absorption rates was studied in Caco-2 cells at different apical iron concentrations, using both an experimental approach and a mathematical modeling framework. This is the first report of short-term studies for this system. A non-linear behavior in the apical uptake dynamics was observed, which does not follow the classic saturation dynamics of traditional biochemical models. We propose a method for developing mathematical models for complex systems, based on a genetic programming algorithm. The algorithm is aimed at obtaining models with a high predictive capacity, and considers an additional parameter fitting stage and an additional Jackknife stage for estimating the generalization error. We developed a model for the iron uptake system with a higher predictive capacity than classic biochemical models. This was observed both with the apical uptake dataset used for generating the model and with an independent initial rates dataset used to test the predictive capacity of the model. The model obtained is a function of time and the initial apical iron concentration, with a linear component that captures the global tendency of the system, and a non-linear component that can be associated to the movement of DMT1 transporters. The model presented in this paper allows the detailed analysis, interpretation of experimental data, and identification of key relevant components for this complex biological process. This general method holds great potential for application to the elucidation of biological mechanisms and their key components in other complex

  6. A genetic programming approach to oral cancer prognosis

    Directory of Open Access Journals (Sweden)

    Mei Sze Tan

    2016-09-01

    Full Text Available Background The potential of genetic programming (GP on various fields has been attained in recent years. In bio-medical field, many researches in GP are focused on the recognition of cancerous cells and also on gene expression profiling data. In this research, the aim is to study the performance of GP on the survival prediction of a small sample size of oral cancer prognosis dataset, which is the first study in the field of oral cancer prognosis. Method GP is applied on an oral cancer dataset that contains 31 cases collected from the Malaysia Oral Cancer Database and Tissue Bank System (MOCDTBS. The feature subsets that is automatically selected through GP were noted and the influences of this subset on the results of GP were recorded. In addition, a comparison between the GP performance and that of the Support Vector Machine (SVM and logistic regression (LR are also done in order to verify the predictive capabilities of the GP. Result The result shows that GP performed the best (average accuracy of 83.87% and average AUROC of 0.8341 when the features selected are smoking, drinking, chewing, histological differentiation of SCC, and oncogene p63. In addition, based on the comparison results, we found that the GP outperformed the SVM and LR in oral cancer prognosis. Discussion Some of the features in the dataset are found to be statistically co-related. This is because the accuracy of the GP prediction drops when one of the feature in the best feature subset is excluded. Thus, GP provides an automatic feature selection function, which chooses features that are highly correlated to the prognosis of oral cancer. This makes GP an ideal prediction model for cancer clinical and genomic data that can be used to aid physicians in their decision making stage of diagnosis or prognosis.

  7. A Domain-Independent Window Approach to Multiclass Object Detection Using Genetic Programming

    Directory of Open Access Journals (Sweden)

    Mengjie Zhang

    2003-07-01

    Full Text Available This paper describes a domain-independent approach to the use of genetic programming for object detection problems in which the locations of small objects of multiple classes in large images must be found. The evolved program is scanned over the large images to locate the objects of interest. The paper develops three terminal sets based on domain-independent pixel statistics and considers two different function sets. The fitness function is based on the detection rate and the false alarm rate. We have tested the method on three object detection problems of increasing difficulty. This work not only extends genetic programming to multiclass-object detection problems, but also shows how to use a single evolved genetic program for both object classification and localisation. The object classification map developed in this approach can be used as a general classification strategy in genetic programming for multiple-class classification problems.

  8. Genetic programming as alternative for predicting development effort of individual software projects.

    Directory of Open Access Journals (Sweden)

    Arturo Chavoya

    Full Text Available Statistical and genetic programming techniques have been used to predict the software development effort of large software projects. In this paper, a genetic programming model was used for predicting the effort required in individually developed projects. Accuracy obtained from a genetic programming model was compared against one generated from the application of a statistical regression model. A sample of 219 projects developed by 71 practitioners was used for generating the two models, whereas another sample of 130 projects developed by 38 practitioners was used for validating them. The models used two kinds of lines of code as well as programming language experience as independent variables. Accuracy results from the model obtained with genetic programming suggest that it could be used to predict the software development effort of individual projects when these projects have been developed in a disciplined manner within a development-controlled environment.

  9. CDPOP: A spatially explicit cost distance population genetics program

    Science.gov (United States)

    Erin L. Landguth; S. A. Cushman

    2010-01-01

    Spatially explicit simulation of gene flow in complex landscapes is essential to explain observed population responses and provide a foundation for landscape genetics. To address this need, we wrote a spatially explicit, individual-based population genetics model (CDPOP). The model implements individual-based population modelling with Mendelian inheritance and k-allele...

  10. SAM: The "Search and Match" Computer Program of the Escherichia coli Genetic Stock Center

    Science.gov (United States)

    Bachmann, B. J.; And Others

    1973-01-01

    Describes a computer program used at a genetic stock center to locate particular strains of bacteria. The program can match up to 30 strain descriptions requested by a researcher with the records on file. Uses of this particular program can be made in many fields. (PS)

  11. A Genetic-Algorithms-Based Approach for Programming Linear and Quadratic Optimization Problems with Uncertainty

    Directory of Open Access Journals (Sweden)

    Weihua Jin

    2013-01-01

    Full Text Available This paper proposes a genetic-algorithms-based approach as an all-purpose problem-solving method for operation programming problems under uncertainty. The proposed method was applied for management of a municipal solid waste treatment system. Compared to the traditional interactive binary analysis, this approach has fewer limitations and is able to reduce the complexity in solving the inexact linear programming problems and inexact quadratic programming problems. The implementation of this approach was performed using the Genetic Algorithm Solver of MATLAB (trademark of MathWorks. The paper explains the genetic-algorithms-based method and presents details on the computation procedures for each type of inexact operation programming problems. A comparison of the results generated by the proposed method based on genetic algorithms with those produced by the traditional interactive binary analysis method is also presented.

  12. Developing close combat behaviors for simulated soldiers using genetic programming techniques.

    Energy Technology Data Exchange (ETDEWEB)

    Pryor, Richard J.; Schaller, Mark J.

    2003-10-01

    Genetic programming is a powerful methodology for automatically producing solutions to problems in a variety of domains. It has been used successfully to develop behaviors for RoboCup soccer players and simple combat agents. We will attempt to use genetic programming to solve a problem in the domain of strategic combat, keeping in mind the end goal of developing sophisticated behaviors for compound defense and infiltration. The simplified problem at hand is that of two armed agents in a small room, containing obstacles, fighting against each other for survival. The base case and three changes are considered: a memory of positions using stacks, context-dependent genetic programming, and strongly typed genetic programming. Our work demonstrates slight improvements from the first two techniques, and no significant improvement from the last.

  13. Evolving Rule-Based Systems in two Medical Domains using Genetic Programming

    DEFF Research Database (Denmark)

    Tsakonas, A.; Dounias, G.; Jantzen, Jan

    2004-01-01

    We demonstrate, compare and discuss the application of two genetic programming methodologies for the construction of rule-based systems in two medical domains: the diagnosis of Aphasia's subtypes and the classification of Pap-Smear Test examinations. The first approach consists of a scheme...... that combines genetic programming and heuristic hierarchical crisp rule-base construction. The second model is composed by a grammar driven genetic programming system for the generation of fuzzy rule-based systems. Results are also compared for their efficiency, accuracy and comprehensibility, to those...... of a standard entropy based machine learning approach and to those of a standard genetic programming symbolic expression approach. In the diagnosis of subtypes of Aphasia, two models for crisp rule-bases are presented. The first one discriminates between four major types and the second attempts...

  14. National Survey of Genetics Content in Basic Nursing Preparatory Programs in the United States.

    Science.gov (United States)

    Hetteberg, Carol G.; Prows, Cynthia A.; Deets, Carol; Monsen, Rita B.; Kenner, Carole A.

    1999-01-01

    A sample of 879 basic nursing programs was used to identify the type and amount of genetics content in curricula. Recommendations were made for increasing genetics content as a result of the synthesis of the survey data with previously collected data. (25 references) (Author/JOW)

  15. Effects of genotype x environment interaction on genetic gain in breeding programs

    NARCIS (Netherlands)

    Mulder, H.A.; Bijma, P.

    2005-01-01

    Genotype x environment interaction (G x E) is increasingly important, because breeding programs tend to be more internationally oriented. The aim of this theoretical study was to investigate the effects of G x E on genetic gain in sib-testing and progeny-testing schemes. Loss of genetic gain due to

  16. Design of Autonomous Navigation Controllers for Unmanned Aerial Vehicles Using Multi-Objective Genetic Programming

    Science.gov (United States)

    2004-03-01

    In Genetic Programming 1997: Proceedings of the Second Annual Conference, pages 398–406, 1997. [23] Emilio Frazzoli. Maneuver-based motion planning...Evolutionary approaches to neural control of rolling, walking, swimming and flying animats or robots. In Richard J. Duro, Jose Santos, and Manuel Grana...objective genetic programming. In Proceedings of the Congress on Evolutionary Computation, Portland, OR, June 2004. [66] Peter Pacheco . Parallel

  17. The potential use of genetics to increase the effectiveness of treatment programs for criminal offenders.

    Science.gov (United States)

    Beaver, Kevin M; Jackson, Dylan B; Flesher, Dillon

    2014-01-01

    During the past couple of decades, the amount of research examining the genetic underpinnings to antisocial behaviors, including crime, has exploded. Findings from this body of work have generated a great deal of information linking genetics to criminal involvement. As a partial result, there is now a considerable amount of interest in how these findings should be integrated into the criminal justice system. In the current paper, we outline the potential ways that genetic information can be used to increase the effectiveness of treatment programs designed to reduce recidivism among offenders. We conclude by drawing attention to how genetic information can be used by rehabilitation programs to increase program effectiveness, reduce offender recidivism rates, and enhance public safety.

  18. Human-competitive evolution of quantum computing artefacts by Genetic Programming.

    Science.gov (United States)

    Massey, Paul; Clark, John A; Stepney, Susan

    2006-01-01

    We show how Genetic Programming (GP) can be used to evolve useful quantum computing artefacts of increasing sophistication and usefulness: firstly specific quantum circuits, then quantum programs, and finally system-independent quantum algorithms. We conclude the paper by presenting a human-competitive Quantum Fourier Transform (QFT) algorithm evolved by GP.

  19. Artificial intelligence programming with LabVIEW: genetic algorithms for instrumentation control and optimization.

    Science.gov (United States)

    Moore, J H

    1995-06-01

    A genetic algorithm for instrumentation control and optimization was developed using the LabVIEW graphical programming environment. The usefulness of this methodology for the optimization of a closed loop control instrument is demonstrated with minimal complexity and the programming is presented in detail to facilitate its adaptation to other LabVIEW applications. Closed loop control instruments have variety of applications in the biomedical sciences including the regulation of physiological processes such as blood pressure. The program presented here should provide a useful starting point for those wishing to incorporate genetic algorithm approaches to LabVIEW mediated optimization of closed loop control instruments.

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

    Science.gov (United States)

    Catania, Francesco; Schmitz, Jürgen

    2015-01-01

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

  1. Forecasting Shaharchay River Flow in Lake Urmia Basin using Genetic Programming and M5 Model Tree

    Directory of Open Access Journals (Sweden)

    S. Samadianfard

    2017-01-01

    Full Text Available Introduction: Precise prediction of river flows is the key factor for proper planning and management of water resources. Thus, obtaining the reliable methods for predicting river flows has great importance in water resource engineering. In the recent years, applications of intelligent methods such as artificial neural networks, fuzzy systems and genetic programming in water science and engineering have been grown extensively. These mentioned methods are able to model nonlinear process of river flows without any need to geometric properties. A huge number of studies have been reported in the field of using intelligent methods in water resource engineering. For example, Noorani and Salehi (23 presented a model for predicting runoff in Lighvan basin using adaptive neuro-fuzzy network and compared the performance of it with neural network and fuzzy inference methods in east Azerbaijan, Iran. Nabizadeh et al. (21 used fuzzy inference system and adaptive neuro-fuzzy inference system in order to predict river flow in Lighvan river. Khalili et al. (13 proposed a BL-ARCH method for prediction of flows in Shaharchay River in Urmia. Khu et al. (16 used genetic programming for runoff prediction in Orgeval catchment in France. Firat and Gungor (11 evaluated the fuzzy-neural model for predicting Mendes river flow in Turkey. The goal of present study is comparing the performance of genetic programming and M5 model trees for prediction of Shaharchay river flow in the basin of Lake Urmia and obtaining a comprehensive insight of their abilities. Materials and Methods: Shaharchay river as a main source of providing drinking water of Urmia city and agricultural needs of surrounding lands and finally one of the main input sources of Lake Urmia is quite important in the region. For obtaining the predetermined goals of present study, average monthly flows of Shaharchay River in Band hydrometric station has been gathered from 1951 to 2011. Then, two third of mentioned

  2. A novel holistic framework for genetic-based captive-breeding and reintroduction programs.

    Science.gov (United States)

    Attard, C R M; Möller, L M; Sasaki, M; Hammer, M P; Bice, C M; Brauer, C J; Carvalho, D C; Harris, J O; Beheregaray, L B

    2016-10-01

    Research in reintroduction biology has provided a greater understanding of the often limited success of species reintroductions and highlighted the need for scientifically rigorous approaches in reintroduction programs. We examined the recent genetic-based captive-breeding and reintroduction literature to showcase the underuse of the genetic data gathered. We devised a framework that takes full advantage of the genetic data through assessment of the genetic makeup of populations before (past component of the framework), during (present component), and after (future component) captive-breeding and reintroduction events to understand their conservation potential and maximize their success. We empirically applied our framework to two small fishes: Yarra pygmy perch (Nannoperca obscura) and southern pygmy perch (Nannoperca australis). Each of these species has a locally adapted and geographically isolated lineage that is endemic to the highly threatened lower Murray-Darling Basin in Australia. These two populations were rescued during Australia's recent decade-long Millennium Drought, when their persistence became entirely dependent on captive-breeding and subsequent reintroduction efforts. Using historical demographic analyses, we found differences and similarities between the species in the genetic impacts of past natural and anthropogenic events that occurred in situ, such as European settlement (past component). Subsequently, successful maintenance of genetic diversity in captivity-despite skewed brooder contribution to offspring-was achieved through carefully managed genetic-based breeding (present component). Finally, genetic monitoring revealed the survival and recruitment of released captive-bred offspring in the wild (future component). Our holistic framework often requires no additional data collection to that typically gathered in genetic-based breeding programs, is applicable to a wide range of species, advances the genetic considerations of reintroduction

  3. Solution for integer linear bilevel programming problems using orthogonal genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    Hong Li; Li Zhang; Yongchang Jiao

    2014-01-01

    An integer linear bilevel programming problem is firstly transformed into a binary linear bilevel programming problem, and then converted into a single-level binary implicit program-ming. An orthogonal genetic algorithm is developed for solving the binary linear implicit programming problem based on the ortho-gonal design. The orthogonal design with the factor analysis, an experimental design method is applied to the genetic algorithm to make the algorithm more robust, statistical y sound and quickly convergent. A crossover operator formed by the orthogonal array and the factor analysis is presented. First, this crossover operator can generate a smal but representative sample of points as off-spring. After al of the better genes of these offspring are selected, a best combination among these offspring is then generated. The simulation results show the effectiveness of the proposed algo-rithm.

  4. Academic training: From Evolution Theory to Parallel and Distributed Genetic Programming

    CERN Multimedia

    2007-01-01

    2006-2007 ACADEMIC TRAINING PROGRAMME LECTURE SERIES 15, 16 March From 11:00 to 12:00 - Main Auditorium, bldg. 500 From Evolution Theory to Parallel and Distributed Genetic Programming F. FERNANDEZ DE VEGA / Univ. of Extremadura, SP Lecture No. 1: From Evolution Theory to Evolutionary Computation Evolutionary computation is a subfield of artificial intelligence (more particularly computational intelligence) involving combinatorial optimization problems, which are based to some degree on the evolution of biological life in the natural world. In this tutorial we will review the source of inspiration for this metaheuristic and its capability for solving problems. We will show the main flavours within the field, and different problems that have been successfully solved employing this kind of techniques. Lecture No. 2: Parallel and Distributed Genetic Programming The successful application of Genetic Programming (GP, one of the available Evolutionary Algorithms) to optimization problems has encouraged an ...

  5. Selecting the Best Forecasting-Implied Volatility Model Using Genetic Programming

    Directory of Open Access Journals (Sweden)

    Wafa Abdelmalek

    2009-01-01

    Full Text Available The volatility is a crucial variable in option pricing and hedging strategies. The aim of this paper is to provide some initial evidence of the empirical relevance of genetic programming to volatility's forecasting. By using real data from S&P500 index options, the genetic programming's ability to forecast Black and Scholes-implied volatility is compared between time series samples and moneyness-time to maturity classes. Total and out-of-sample mean squared errors are used as forecasting's performance measures. Comparisons reveal that the time series model seems to be more accurate in forecasting-implied volatility than moneyness time to maturity models. Overall, results are strongly encouraging and suggest that the genetic programming approach works well in solving financial problems.

  6. Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer

    Directory of Open Access Journals (Sweden)

    Mauro Castelli

    2015-01-01

    Full Text Available Energy consumption forecasting (ECF is an important policy issue in today’s economies. An accurate ECF has great benefits for electric utilities and both negative and positive errors lead to increased operating costs. The paper proposes a semantic based genetic programming framework to address the ECF problem. In particular, we propose a system that finds (quasi-perfect solutions with high probability and that generates models able to produce near optimal predictions also on unseen data. The framework blends a recently developed version of genetic programming that integrates semantic genetic operators with a local search method. The main idea in combining semantic genetic programming and a local searcher is to couple the exploration ability of the former with the exploitation ability of the latter. Experimental results confirm the suitability of the proposed method in predicting the energy consumption. In particular, the system produces a lower error with respect to the existing state-of-the art techniques used on the same dataset. More importantly, this case study has shown that including a local searcher in the geometric semantic genetic programming system can speed up the search process and can result in fitter models that are able to produce an accurate forecasting also on unseen data.

  7. Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer.

    Science.gov (United States)

    Castelli, Mauro; Trujillo, Leonardo; Vanneschi, Leonardo

    2015-01-01

    Energy consumption forecasting (ECF) is an important policy issue in today's economies. An accurate ECF has great benefits for electric utilities and both negative and positive errors lead to increased operating costs. The paper proposes a semantic based genetic programming framework to address the ECF problem. In particular, we propose a system that finds (quasi-)perfect solutions with high probability and that generates models able to produce near optimal predictions also on unseen data. The framework blends a recently developed version of genetic programming that integrates semantic genetic operators with a local search method. The main idea in combining semantic genetic programming and a local searcher is to couple the exploration ability of the former with the exploitation ability of the latter. Experimental results confirm the suitability of the proposed method in predicting the energy consumption. In particular, the system produces a lower error with respect to the existing state-of-the art techniques used on the same dataset. More importantly, this case study has shown that including a local searcher in the geometric semantic genetic programming system can speed up the search process and can result in fitter models that are able to produce an accurate forecasting also on unseen data.

  8. Analysis of genetic structure and relationship among nine indigenous Chinese chicken populations by the Structure program

    Indian Academy of Sciences (India)

    H. F. Li; W. Han; Y. F. Zhu; J. T. Shu; X. Y. Zhang; K. W. Chen

    2009-08-01

    The multi-locus model-based clustering method Structure program was used to infer the genetic structure of nine indigenous Chinese chicken (Gallus gallus) populations based on 16 microsatellite markers. Twenty runs were carried out at each chosen value of predefined cluster numbers $(K)$ under admixture model. The Structure program properly inferred the presence of genetic structure with 0.999 probabilities. The genetic structure not only indicated that the nine kinds of chicken populations were defined actually by their locations, phenotypes or culture, but also reflected the underlying genetic variations. At $K = 2$, nine chicken populations were divided into two main clusters, one light-body type, including Chahua chicken (CHA), Tibet chicken (TIB), Xianju chicken (XIA), Gushi chicken (GUS) and Baier chicken (BAI); and the other heavy-body type, including Beijing You chicken (YOU), Xiaoshan chicken (XIA), Luyuan chicken (LUY) and Dagu chicken (DAG). GUS and DAG were divided into independent clusters respectively when equaled 4, 5, or 6. XIA and BIA chicken, XIA and LUY chicken, TIB and CHA chicken still clustered together when equaled 6, 7, and 8, respectively. These clustering results were consistent with the breeding directions of the nine chicken populations. The Structure program also identified migrants or admixed individuals. The admixed individuals were distributed in all the nine chicken populations, while migrants were only distributed in TIB, XIA and LUY populations. These results indicated that the clustering analysis using the Structure program might provide an accurate representation of the genetic relationship among the breeds.

  9. Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer

    Science.gov (United States)

    Vanneschi, Leonardo

    2015-01-01

    Energy consumption forecasting (ECF) is an important policy issue in today's economies. An accurate ECF has great benefits for electric utilities and both negative and positive errors lead to increased operating costs. The paper proposes a semantic based genetic programming framework to address the ECF problem. In particular, we propose a system that finds (quasi-)perfect solutions with high probability and that generates models able to produce near optimal predictions also on unseen data. The framework blends a recently developed version of genetic programming that integrates semantic genetic operators with a local search method. The main idea in combining semantic genetic programming and a local searcher is to couple the exploration ability of the former with the exploitation ability of the latter. Experimental results confirm the suitability of the proposed method in predicting the energy consumption. In particular, the system produces a lower error with respect to the existing state-of-the art techniques used on the same dataset. More importantly, this case study has shown that including a local searcher in the geometric semantic genetic programming system can speed up the search process and can result in fitter models that are able to produce an accurate forecasting also on unseen data. PMID:26106410

  10. A survey of application: genomics and genetic programming, a new frontier.

    Science.gov (United States)

    Khan, Mohammad Wahab; Alam, Mansaf

    2012-08-01

    The aim of this paper is to provide an introduction to the rapidly developing field of genetic programming (GP). Particular emphasis is placed on the application of GP to genomics. First, the basic methodology of GP is introduced. This is followed by a review of applications in the areas of gene network inference, gene expression data analysis, SNP analysis, epistasis analysis and gene annotation. Finally this paper concluded by suggesting potential avenues of possible future research on genetic programming, opportunities to extend the technique, and areas for possible practical applications.

  11. Genetic testing and Alzheimer disease: recommendations of the Stanford Program in Genomics, Ethics, and Society.

    Science.gov (United States)

    McConnell, L M; Koenig, B A; Greely, H T; Raffin, T A

    1999-01-01

    Several genes associated with Alzheimer disease (AD) have been localized and cloned; two genetic tests are already commercially available, and new tests are being developed. Genetic testing for AD--either for disease prediction or for diagnosis--raises critical ethical concerns. The multidisciplinary Alzheimer Disease Working Group of the Stanford Program in Genomics, Ethics, and Society (PGES) presents comprehensive recommendations on genetic testing for AD. The Group concludes that under current conditions, genetic testing for AD prediction or diagnosis is only rarely appropriate. Criteria for judging the readiness of a test for introduction into routine clinical practice typically rely heavily on evaluation of technical efficacy. PGES recommends a broader and more comprehensive approach, considering: 1) the unique social and historical meanings of AD; 2) the availability of procedures to promote good surrogate decision making for incompetent patients and to safeguard confidentiality; 3) access to sophisticated genetic counselors able to communicate complex risk information and effectively convey the social costs and psychological burdens of testing, such as unintentional disclosure of predictive genetic information to family members; 4) protection from inappropriate advertising and marketing of genetic tests; and 5) recognition of the need for public education about the meaning and usefulness of predictive and diagnostic tests for AD. In this special issue of Genetic Testing, the PGES recommendations are published along with comprehensive background papers authored by Working Group members.

  12. Genetics

    Science.gov (United States)

    ... Inheritance; Heterozygous; Inheritance patterns; Heredity and disease; Heritable; Genetic markers ... The chromosomes are made up of strands of genetic information called DNA. Each chromosome contains sections of ...

  13. A CAL Program to Teach the Basic Principles of Genetic Engineering--A Change from the Traditional Approach.

    Science.gov (United States)

    Dewhurst, D. G.; And Others

    1989-01-01

    An interactive computer-assisted learning program written for the BBC microcomputer to teach the basic principles of genetic engineering is described. Discussed are the hardware requirements software, use of the program, and assessment. (Author/CW)

  14. A CAL Program to Teach the Basic Principles of Genetic Engineering--A Change from the Traditional Approach.

    Science.gov (United States)

    Dewhurst, D. G.; And Others

    1989-01-01

    An interactive computer-assisted learning program written for the BBC microcomputer to teach the basic principles of genetic engineering is described. Discussed are the hardware requirements software, use of the program, and assessment. (Author/CW)

  15. Genetic algorithms and genetic programming for multiscale modeling: Applications in materials science and chemistry and advances in scalability

    Science.gov (United States)

    Sastry, Kumara Narasimha

    2007-03-01

    Effective and efficient rnultiscale modeling is essential to advance both the science and synthesis in a, wide array of fields such as physics, chemistry, materials science; biology, biotechnology and pharmacology. This study investigates the efficacy and potential of rising genetic algorithms for rnultiscale materials modeling and addresses some of the challenges involved in designing competent algorithms that solve hard problems quickly, reliably and accurately. In particular, this thesis demonstrates the use of genetic algorithms (GAs) and genetic programming (GP) in multiscale modeling with the help of two non-trivial case studies in materials science and chemistry. The first case study explores the utility of genetic programming (GP) in multi-timescaling alloy kinetics simulations. In essence, GP is used to bridge molecular dynamics and kinetic Monte Carlo methods to span orders-of-magnitude in simulation time. Specifically, GP is used to regress symbolically an inline barrier function from a limited set of molecular dynamics simulations to enable kinetic Monte Carlo that simulate seconds of real time. Results on a non-trivial example of vacancy-assisted migration on a surface of a face-centered cubic (fcc) Copper-Cobalt (CuxCo 1-x) alloy show that GP predicts all barriers with 0.1% error from calculations for less than 3% of active configurations, independent of type of potentials used to obtain the learning set of barriers via molecular dynamics. The resulting method enables 2--9 orders-of-magnitude increase in real-time dynamics simulations taking 4--7 orders-of-magnitude less CPU time. The second case study presents the application of multiobjective genetic algorithms (MOGAs) in multiscaling quantum chemistry simulations. Specifically, MOGAs are used to bridge high-level quantum chemistry and semiempirical methods to provide accurate representation of complex molecular excited-state and ground-state behavior. Results on ethylene and benzene---two common

  16. Genetic Algorithm Based on Duality Principle for Bilevel Programming Problem in Steel-making Production

    Institute of Scientific and Technical Information of China (English)

    Shuo Lin; Fangjun Luan; Zhonghua Han; Xisheng Lü; Xiaofeng Zhou; Wei Liu

    2014-01-01

    Steel-making and continuous/ingot casting are the key processes of modern iron and steel enterprises. Bilevel programming problems (BLPPs) are the optimization problems with hierarchical structure. In steel-making pro-duction, the plan is not only decided by the steel-making scheduling, but also by the transportation equipment. This paper proposes a genetic algorithm to solve continuous and ingot casting scheduling problems. Based on the characteristics of the problems involved, a genetic algorithm is proposed for solving the bilevel programming problem in steel-making production. Furthermore, based on the simplex method, a new crossover operator is designed to improve the efficiency of the genetic algorithm. Finally, the convergence is analyzed. Using actual data the validity of the proposed algorithm is proved and the application results in the steel plant are analyzed.

  17. Innate and adaptive immunity in bacteria: mechanisms of programmed genetic variation to fight bacteriophages.

    Science.gov (United States)

    Bikard, David; Marraffini, Luciano A

    2012-02-01

    Bacteria are constantly challenged by bacteriophages (viruses that infect bacteria), the most abundant microorganism on earth. Bacteria have evolved a variety of immunity mechanisms to resist bacteriophage infection. In response, bacteriophages can evolve counter-resistance mechanisms and launch a 'virus versus host' evolutionary arms race. In this context, rapid evolution is fundamental for the survival of the bacterial cell. Programmed genetic variation mechanisms at loci involved in immunity against bacteriophages generate diversity at a much faster rate than random point mutation and enable bacteria to quickly adapt and repel infection. Diversity-generating retroelements (DGRs) and phase variation mechanisms enhance the generic (innate) immune response against bacteriophages. On the other hand, the integration of small bacteriophage sequences in CRISPR loci provide bacteria with a virus-specific and sequence-specific adaptive immune response. Therefore, although using different molecular mechanisms, both prokaryotes and higher organisms rely on programmed genetic variation to increase genetic diversity and fight rapidly evolving infectious agents.

  18. Optimization of Turning Operations by Using a Hybrid Genetic Algorithm with Sequential Quadratic Programming

    Directory of Open Access Journals (Sweden)

    A. Belloufi*

    2013-01-01

    Full Text Available The determination of optimal cutting parameters is one of the most important elements in any process planning ofmetal parts. In this paper, a new hybrid genetic algorithm by using sequential quadratic programming is used for theoptimization of cutting conditions. It is used for the resolution of a multipass turning optimization case by minimizingthe production cost under a set of machining constraints. The genetic algorithm (GA is the main optimizer of thisalgorithm whereas SQP Is used to fine tune the results obtained from the GA. Furthermore, the convergencecharacteristics and robustness of the proposed method have been explored through comparisons with resultsreported in literature. The obtained results indicate that the proposed hybrid genetic algorithm by using a sequentialquadratic programming is effective compared to other techniques carried out by different researchers.

  19. Model-based problem solving through symbolic regression via pareto genetic programming

    NARCIS (Netherlands)

    Vladislavleva, E.

    2008-01-01

    Pareto genetic programming methodology is extended by additional generic model selection and generation strategies that (1) drive the modeling engine to creation of models of reduced non-linearity and increased generalization capabilities, and (2) improve the effectiveness of the search for robust m

  20. Application of Genetic Programming in Predicting Infinite Dilution Activity Coefficients of Organic Compounds in Water

    Institute of Scientific and Technical Information of China (English)

    Yi Lin CAO; Huan Ying LI

    2003-01-01

    In this paper, we calculated 37 structural descriptors of 174 organic compounds. The154 molecules were used to derive quantitative structure-infinite dilution activity coefficientrelationship by genetic programming, the other 20 compounds were used to test the model. Theresult showed that molecular partition property and three-dimensional structural descriptors havesignificant influence on the infinite dilution activity coefficients.

  1. Genetic Diversity of Some Tomato Cultivars and Breeding Lines Commonly Used in Pakistani Breeding Program

    Directory of Open Access Journals (Sweden)

    Muhammad Azhar Shah

    2014-10-01

    Full Text Available Genetic diversity present in gene pool is an important determination for breeding programs, and characterization is useful of building crop plant collections primarily based on the knowledge of the presence of valuable genes and traits. Developing successful varieties for increasing the future yield and quality of tomato depend mainly on the genetic diversity of parents used in the breeding program. Molecular characterization of 21 tomato genotypes used in in Pakistani breeding program was studied using random amplified polymorphic DNA (RAPD markers. Total 102 bands were amplified among 21 genotypes using 20 RAPD primers. Overall 73.5% polymorphism was shown as 75 out of 102 loci were polymorphic. High degree of divergence between varieties was indicated by low level of monomorphic bands. The number of PCR products per primer varied from 2-8 with an average of 5.1 bands per primer. Primer GL J-20 and GL C-09 produced maximum number of bands whereas the primers GL A-09 produced the lowest. The polymorphism per RAPD primer ranged from 50% to 100% with an average of 73.5%. The accumulative analysis of amplified products generated by RAPD’s was enough to assess the genetic diversity among the genotypes. The information would be helpful for formulating future breeding and genome mapping programs. This study will also work as an indicator for tomato breeders to evolve varieties with genetic diverse back ground to achieve sustainability in tomato production in the country.

  2. Behaviour of genetically modified amylose free potato clones as progenitors in a breeding program.

    NARCIS (Netherlands)

    Heeres, P.; Jacobsen, E.; Visser, R.G.F.

    1997-01-01

    Three amylose-free genetically modified potato clones were used both as male and female parents in a breeding program with non-GMO potato clones. Segregation data on the expression of the inserted antisense gene construct in tubers of progeny plants were in agreement with previous molecular analysis

  3. Dynamic Programming and Genetic Algorithm for Business Processes Optimisation

    Directory of Open Access Journals (Sweden)

    Mateusz Wibig

    2012-12-01

    Full Text Available There are many business process modelling techniques, which allow to capture features of those processes, but graphical, diagrammatic models seems to be used most in companies and organizations. Although the modelling notations are more and more mature and can be used not only to visualise the process idea but also to implement it in the workflow solution and although modern software allows us to gather a lot of data for analysis purposes, there is still not much commercial used business process optimisation methods. In this paper the scheduling / optimisation method for automatic task scheduling in business processes models is described. The Petri Net model is used, but it can be easily applied to any other modelling notation, where the process is presented as a set of tasks, i.e. BPMN (Business Process Modelling Notation. The method uses Petri Nets’, business processes’ scalability and dynamic programming concept to reduce the necessary computations, by revising only those parts of the model, to which the change was applied.

  4. Telegenetics: application of a tele-education program in genetic syndromes for Brazilian students.

    Science.gov (United States)

    Maximino, Luciana Paula; Picolini-Pereira, Mirela Machado; Carvalho, José Luiz Brito

    2014-01-01

    With the high occurrence of genetic anomalies in Brazil and the manifestations of communication disorders associated with these conditions, the development of educative actions that comprise these illnesses can bring unique benefits in the identification and appropriate treatment of these clinical pictures. Objective The aim of this study was to develop and analyze an educational program in genetic syndromes for elementary students applied in two Brazilian states, using an Interactive Tele-education model. Material and Methods The study was carried out in 4 schools: two in the state of São Paulo, Southeast Region, Brazil, and two in the state of Amazonas, North Region, Brazil. Forty-five students, both genders, aged between 13 and 14 years, of the 9th grade of the basic education of both public and private system, were divided into two groups: 21 of São Paulo Group (SPG) and 24 of Amazonas Group (AMG). The educational program lasted about 3 months and was divided into two stages including both classroom and distance activities on genetic syndromes. The classroom activity was carried out separately in each school, with expository lessons, graphs and audiovisual contents. In the activity at a distance the educational content was presented to students by means of the Interactive Tele-education model. In this stage, the students had access a Cybertutor, using the Young Doctor Project methodology. In order to measure the effectiveness of the educational program, the Problem Situation Questionnaire (PSQ) and the Web Site Motivational Analysis Checklist adapted (FPM) were used. Results The program developed was effective for knowledge acquisition in 80% of the groups. FPM showed a high satisfaction index from the participants in relation to the Interactive Tele-education, evaluating the program as "awesome course". No statistically significant differences between the groups regarding type of school or state were observed. Conclusion Thus, the Tele-Education Program can

  5. Potential of gene drives with genome editing to increase genetic gain in livestock breeding programs.

    Science.gov (United States)

    Gonen, Serap; Jenko, Janez; Gorjanc, Gregor; Mileham, Alan J; Whitelaw, C Bruce A; Hickey, John M

    2017-01-04

    This paper uses simulation to explore how gene drives can increase genetic gain in livestock breeding programs. Gene drives are naturally occurring phenomena that cause a mutation on one chromosome to copy itself onto its homologous chromosome. We simulated nine different breeding and editing scenarios with a common overall structure. Each scenario began with 21 generations of selection, followed by 20 generations of selection based on true breeding values where the breeder used selection alone, selection in combination with genome editing, or selection with genome editing and gene drives. In the scenarios that used gene drives, we varied the probability of successfully incorporating the gene drive. For each scenario, we evaluated genetic gain, genetic variance [Formula: see text], rate of change in inbreeding ([Formula: see text]), number of distinct quantitative trait nucleotides (QTN) edited, rate of increase in favourable allele frequencies of edited QTN and the time to fix favourable alleles. Gene drives enhanced the benefits of genome editing in seven ways: (1) they amplified the increase in genetic gain brought about by genome editing; (2) they amplified the rate of increase in the frequency of favourable alleles and reduced the time it took to fix them; (3) they enabled more rapid targeting of QTN with lesser effect for genome editing; (4) they distributed fixed editing resources across a larger number of distinct QTN across generations; (5) they focussed editing on a smaller number of QTN within a given generation; (6) they reduced the level of inbreeding when editing a subset of the sires; and (7) they increased the efficiency of converting genetic variation into genetic gain. Genome editing in livestock breeding results in short-, medium- and long-term increases in genetic gain. The increase in genetic gain occurs because editing increases the frequency of favourable alleles in the population. Gene drives accelerate the increase in allele frequency

  6. Multi-gene genetic programming based predictive models for municipal solid waste gasification in a fluidized bed gasifier.

    Science.gov (United States)

    Pandey, Daya Shankar; Pan, Indranil; Das, Saptarshi; Leahy, James J; Kwapinski, Witold

    2015-03-01

    A multi-gene genetic programming technique is proposed as a new method to predict syngas yield production and the lower heating value for municipal solid waste gasification in a fluidized bed gasifier. The study shows that the predicted outputs of the municipal solid waste gasification process are in good agreement with the experimental dataset and also generalise well to validation (untrained) data. Published experimental datasets are used for model training and validation purposes. The results show the effectiveness of the genetic programming technique for solving complex nonlinear regression problems. The multi-gene genetic programming are also compared with a single-gene genetic programming model to show the relative merits and demerits of the technique. This study demonstrates that the genetic programming based data-driven modelling strategy can be a good candidate for developing models for other types of fuels as well.

  7. Potential benefits of genomic selection on genetic gain of small ruminant breeding programs.

    Science.gov (United States)

    Shumbusho, F; Raoul, J; Astruc, J M; Palhiere, I; Elsen, J M

    2013-08-01

    In conventional small ruminant breeding programs, only pedigree and phenotype records are used to make selection decisions but prospects of including genomic information are now under consideration. The objective of this study was to assess the potential benefits of genomic selection on the genetic gain in French sheep and goat breeding designs of today. Traditional and genomic scenarios were modeled with deterministic methods for 3 breeding programs. The models included decisional variables related to male selection candidates, progeny testing capacity, and economic weights that were optimized to maximize annual genetic gain (AGG) of i) a meat sheep breeding program that improved a meat trait of heritability (h(2)) = 0.30 and a maternal trait of h(2) = 0.09 and ii) dairy sheep and goat breeding programs that improved a milk trait of h(2) = 0.30. Values of ±0.20 of genetic correlation between meat and maternal traits were considered to study their effects on AGG. The Bulmer effect was accounted for and the results presented here are the averages of AGG after 10 generations of selection. Results showed that current traditional breeding programs provide an AGG of 0.095 genetic standard deviation (σa) for meat and 0.061 σa for maternal trait in meat breed and 0.147 σa and 0.120 σa in sheep and goat dairy breeds, respectively. By optimizing decisional variables, the AGG with traditional selection methods increased to 0.139 σa for meat and 0.096 σa for maternal traits in meat breeding programs and to 0.174 σa and 0.183 σa in dairy sheep and goat breeding programs, respectively. With a medium-sized reference population (nref) of 2,000 individuals, the best genomic scenarios gave an AGG that was 17.9% greater than with traditional selection methods with optimized values of decisional variables for combined meat and maternal traits in meat sheep, 51.7% in dairy sheep, and 26.2% in dairy goats. The superiority of genomic schemes increased with the size of the

  8. Multi-Objective Genetic Programming with Redundancy-Regulations for Automatic Construction of Image Feature Extractors

    Science.gov (United States)

    Watchareeruetai, Ukrit; Matsumoto, Tetsuya; Takeuchi, Yoshinori; Kudo, Hiroaki; Ohnishi, Noboru

    We propose a new multi-objective genetic programming (MOGP) for automatic construction of image feature extraction programs (FEPs). The proposed method was originated from a well known multi-objective evolutionary algorithm (MOEA), i.e., NSGA-II. The key differences are that redundancy-regulation mechanisms are applied in three main processes of the MOGP, i.e., population truncation, sampling, and offspring generation, to improve population diversity as well as convergence rate. Experimental results indicate that the proposed MOGP-based FEP construction system outperforms the two conventional MOEAs (i.e., NSGA-II and SPEA2) for a test problem. Moreover, we compared the programs constructed by the proposed MOGP with four human-designed object recognition programs. The results show that the constructed programs are better than two human-designed methods and are comparable with the other two human-designed methods for the test problem.

  9. National Swine Genetic Improvement: An overview of essential program components and organizational structure needed for success

    Institute of Scientific and Technical Information of China (English)

    John; MABRY

    2005-01-01

    The swine industry in China is a thrivingand evolving industry that has shown phenome-nal growth over the past10years.Newand mod-ern swine farms have been started in locationsacross the country.Genetics has been importedfrom many different countries in an effort to up-grade the quality and efficiency of the traditionalbreeds of swine.But to insure long term successand viability in a worldwide competitive industrysuch as pork,there is need for a National SwineGenetic Improvement Program.This programneeds to ...

  10. Dynamic Simulations of Nonlinear Multi-Domain Systems Based on Genetic Programming and Bond Graphs

    Institute of Scientific and Technical Information of China (English)

    DI Wenhui; SUN Bo; XU Lixin

    2009-01-01

    A dynamic simulation method for non-linear systems based on genetic programming (GP) and bond graphs (BG) was developed to improve the design of nonlinear multi-domain energy conversion sys-tems. The genetic operators enable the embryo bond graph to evolve towards the target graph according to the fitness function. Better simulation requires analysis of the optimization of the eigenvalue and the filter circuit evolution. The open topological design and space search ability of this method not only gives a more optimized convergence for the operation, but also reduces the generation time for the new circuit graph for the design of nonlinear multi-domain systems.

  11. wisepair: a computer program for individual matching in genetic tracking studies.

    Science.gov (United States)

    Rothstein, Andrew P; McLaughlin, Ryan; Acevedo-Gutiérrez, Alejandro; Schwarz, Dietmar

    2017-03-01

    Individual-based data sets tracking organisms over space and time are fundamental to answering broad questions in ecology and evolution. A 'permanent' genetic tag circumvents a need to invasively mark or tag animals, especially if there are little phenotypic differences among individuals. However, genetic tracking of individuals does not come without its limits; correctly matching genotypes and error rates associated with laboratory work can make it difficult to parse out matched individuals. In addition, defining a sampling design that effectively matches individuals in the wild can be a challenge for researchers. Here, we combine the two objectives of defining sampling design and reducing genotyping error through an efficient Python-based computer-modelling program, wisepair. We describe the methods used to develop the computer program and assess its effectiveness through three empirical data sets, with and without reference genotypes. Our results show that wisepair outperformed similar genotype matching programs using previously published from reference genotype data of diurnal poison frogs (Allobates femoralis) and without-reference (faecal) genotype sample data sets of harbour seals (Phoca vitulina) and Eurasian otters (Lutra lutra). In addition, due to limited sampling effort in the harbour seal data, we present optimal sampling designs for future projects. wisepair allows for minimal sacrifice in the available methods as it incorporates sample rerun error data, allelic pairwise comparisons and probabilistic simulations to determine matching thresholds. Our program is the lone tool available to researchers to define parameters a priori for genetic tracking studies.

  12. The genetic diversity of triticale genotypes involved in Polish breeding programs.

    Science.gov (United States)

    Niedziela, Agnieszka; Orłowska, Renata; Machczyńska, Joanna; Bednarek, Piotr T

    2016-01-01

    Genetic diversity analysis of triticale populations is useful for breeding programs, as it helps to select appropriate genetic material for classifying the parental lines, heterotic groups and predicting hybrid performance. In our study 232 breeding forms were analyzed using diversity arrays technology markers. Principal coordinate analysis followed by model-based Bayesian analysis of population structure revealed the presence of weak data structuring with three groups of data. In the first group, 17 spring and 17 winter forms were clustered. The second and the third groups were represented by 101 and 26 winter forms, respectively. Polymorphic information content values, as well as Shannon's Information Index, were higher for the first (0.319) and second (0.309) than for third (0.234) group. AMOVA analysis demonstrated a higher level of within variation (86 %) than among populations (14 %). This study provides the basic information on the presence of structure within a genetic pool of triticale breeding forms.

  13. Interactive computer program for learning genetic principles of segregation and independent assortment through meiosis.

    Science.gov (United States)

    Yang, Xiaoli; Ge, Rong; Yang, Yufei; Shen, Hao; Li, Yingjie; Tseng, Charles C

    2009-01-01

    Teaching fundamental principles of genetics such as segregation and independent assortment of genes could be challenging for high school and college biology instructors. Students without thorough knowledge in meiosis often end up of frustration and failure in genetics courses. Although all textbooks and laboratory manuals have excellent graphic demonstrations and photographs of meiotic process, students may not always master the concept due to the lack of hands-on exercise. In response to the need for an effective lab exercise to understand the segregation of allelic genes and the independent assortment of the unlinked genes, we developed an interactive program for students to manually manipulate chromosome models and visualize each major step of meiosis so that these two genetic principles can be thoroughly understood.

  14. Using AFLP markers and the Geneland program for the inference of population genetic structure

    DEFF Research Database (Denmark)

    Guillot, Gilles; Santos, Filipe

    2010-01-01

    The use of dominant markers such as amplified fragment length polymorphism (AFLP) for population genetics analyses is often impeded by the lack of appropriate computer programs and rarely motivated by objective considerations. The point of the present note is twofold: (i) we describe how the comp......The use of dominant markers such as amplified fragment length polymorphism (AFLP) for population genetics analyses is often impeded by the lack of appropriate computer programs and rarely motivated by objective considerations. The point of the present note is twofold: (i) we describe how...... such as single nucleotide polymorphisms (SNP) markers but this difference becomes negligible for data sets of common size (number of individuals n≥100, number of markers L≥200). The latest Geneland version (3.2.1) handling dominant markers is freely available as an R package with a fully clickable graphical...

  15. Extracting classification rules from an informatic security incidents repository by genetic programming

    Directory of Open Access Journals (Sweden)

    Carlos Javier Carvajal Montealegre

    2015-04-01

    Full Text Available This paper describes the data mining process to obtain classification rules over an information security incident data collection, explaining in detail the use of genetic programming as a mean to model the incidents behavior and representing such rules as decision trees. The described mining process includes several tasks, such as the GP (Genetic Programming approach evaluation, the individual's representation and the algorithm parameters tuning to upgrade the performance. The paper concludes with the result analysis and the description of the rules obtained, suggesting measures to avoid the occurrence of new informatics attacks. This paper is a part of the thesis work degree: Information Security Incident Analytics by Data Mining for Behavioral Modeling and Pattern Recognition (Carvajal, 2012.

  16. The influence of genetic background versus commercial breeding programs on chicken immunocompetence.

    Science.gov (United States)

    Emam, Mehdi; Mehrabani-Yeganeh, Hassan; Barjesteh, Neda; Nikbakht, Gholamreza; Thompson-Crispi, Kathleen; Charkhkar, Saeid; Mallard, Bonnie

    2014-01-01

    Immunocompetence of livestock plays an important role in farm profitability because it directly affects health maintenance. Genetics significantly influences the immune system, and the genotypic structure of modern fast-growing chickens has been changed, particularly after decades of breeding for higher production. Therefore, this study was designed to help determine if intensive breeding programs have adversely affected immunocompetence or whether the immune response profiles are controlled to greater extent by genetic background. Thus, 3 indigenous chicken populations from different genetic backgrounds and 2 globally available modern broiler strains, Ross 308 and Cobb 500, were evaluated for various aspects of immune response. These included antibody responses against sheep red blood cells and Brucella abortus antigen, as well as some aspects of cell-mediated immunocompetence by toe web swelling test and in vitro blood mononuclear cell proliferation. Significant differences (P chickens is most likely due to differences in the genetic background between each strain of chicken rather than by commercial selection programs for high production.

  17. An integrated biochemistry and genetics outreach program designed for elementary school students.

    Science.gov (United States)

    Ross, Eric D; Lee, Sarah K; Radebaugh, Catherine A; Stargell, Laurie A

    2012-02-01

    Exposure to genetic and biochemical experiments typically occurs late in one's academic career. By the time students have the opportunity to select specialized courses in these areas, many have already developed negative attitudes toward the sciences. Given little or no direct experience with the fields of genetics and biochemistry, it is likely that many young people rule these out as potential areas of study or career path. To address this problem, we developed a 7-week (~1 hr/week) hands-on course to introduce fifth grade students to basic concepts in genetics and biochemistry. These young students performed a series of investigations (ranging from examining phenotypic variation, in vitro enzymatic assays, and yeast genetic experiments) to explore scientific reasoning through direct experimentation. Despite the challenging material, the vast majority of students successfully completed each experiment, and most students reported that the experience increased their interest in science. Additionally, the experiments within the 7-week program are easily performed by instructors with basic skills in biological sciences. As such, this program can be implemented by others motivated to achieve a broader impact by increasing the accessibility of their university and communicating to a young audience a positive impression of the sciences and the potential for science as a career.

  18. Prediction of Compressive Strength of Concrete Using Artificial Neural Network and Genetic Programming

    OpenAIRE

    Palika Chopra; Rajendra Kumar Sharma; Maneek Kumar

    2016-01-01

    An effort has been made to develop concrete compressive strength prediction models with the help of two emerging data mining techniques, namely, Artificial Neural Networks (ANNs) and Genetic Programming (GP). The data for analysis and model development was collected at 28-, 56-, and 91-day curing periods through experiments conducted in the laboratory under standard controlled conditions. The developed models have also been tested on in situ concrete data taken from literature. A comparison o...

  19. Prediction of jet engine parameters for control design using genetic programming

    OpenAIRE

    Martínez-Arellano, G; Cant, R; Nolle, L

    2014-01-01

    The simulation of a jet engine behavior is widely used in many different aspects of the engine development and maintenance. Achieving high quality jet engine control systems requires the iterative use of these simulations to virtually test the performance of the engine avoiding any possible damage on the real engine. Jet engine simulations involve the use of mathematical models which are complex and may not always be available. This paper introduces an approach based on Genetic Programming (G...

  20. Lasing from Escherichia coli bacteria genetically programmed to express green fluorescent protein

    Science.gov (United States)

    Gather, Malte C.; Yun, Seok Hyun

    2011-08-01

    We report on lasing action from colonies of Escherichia coli bacteria that are genetically programmed to synthesize the green fluorescent protein (GFP). When embedded in a Fabry--Perot type cavity and excited by ns-pulses of blue light (465nm), the bacteria generate green laser emission (˜520nm). Broad illumination of pump light yields simultaneous lasing over a large area in bacterial colonies.

  1. Statistical studies in genetic toxicology: a perspective from the U.S. National Toxicology Program.

    OpenAIRE

    Margolin, B H

    1985-01-01

    This paper surveys recent, as yet unpublished, statistical studies arising from research in genetic toxicology within the U.S. National Toxicology Program (NTP). These studies all involve analyses of data from Ames Salmonella/microsome mutagenicity tests, but the statistical methodologies are broadly applicable. Three issues are addressed: First, what is a tenable sampling model for Ames test data, and how does one best test the adequacy of the Poisson sampling assumption? Second, given that ...

  2. A High Precision Comprehensive Evaluation Method for Flood Disaster Loss Based on Improved Genetic Programming

    Institute of Scientific and Technical Information of China (English)

    ZHOU Yuliang; LU Guihua; JIN Juliang; TONG Fang; ZHOU Ping

    2006-01-01

    Precise comprehensive evaluation of flood disaster loss is significant for the prevention and mitigation of flood disasters. Here, one of the difficulties involved is how to establish a model capable of describing the complex relation between the input and output data of the system of flood disaster loss. Genetic programming (GP) solves problems by using ideas from genetic algorithm and generates computer programs automatically. In this study a new method named the evaluation of the grade of flood disaster loss (EGFD) on the basis of improved genetic programming (IGP) is presented (IGPEGFD). The flood disaster area and the direct economic loss are taken as the evaluation indexes of flood disaster loss. Obviously that the larger the evaluation index value, the larger the corresponding value of the grade of flood disaster loss is. Consequently the IGP code is designed to make the value of the grade of flood disaster be an increasing function of the index value. The result of the application of the IGP-EGFD model to Henan Province shows that a good function expression can be obtained within a bigger searched function space; and the model is of high precision and considerable practical significance.Thus, IGP-EGFD can be widely used in automatic modeling and other evaluation systems.

  3. Modeling the Isentropic Head Value of Centrifugal Gas Compressor using Genetic Programming

    Directory of Open Access Journals (Sweden)

    Safiyullah Ferozkhan

    2016-01-01

    Full Text Available Gas compressor performance is vital in oil and gas industry because of the equipment criticality which requires continuous operations. Plant operators often face difficulties in predicting appropriate time for maintenance and would usually rely on time based predictive maintenance intervals as recommended by original equipment manufacturer (OEM. The objective of this work is to develop the computational model to find the isentropic head value using genetic programming. The isentropic head value is calculated from the OEM performance chart. Inlet mass flow rate and speed of the compressor are taken as the input value. The obtained results from the GP computational models show good agreement with experimental and target data with the average prediction error of 1.318%. The genetic programming computational model will assist machinery engineers to quantify performance deterioration of gas compressor and the results from this study will be then utilized to estimate future maintenance requirements based on the historical data. In general, this genetic programming modelling provides a powerful solution for gas compressor operators to realize predictive maintenance approach in their operations.

  4. Genetic variability and population structure of Salvia lachnostachys: implications for breeding and conservation programs.

    Science.gov (United States)

    Erbano, Marianna; Schühli, Guilherme Schnell E; Santos, Élide Pereira Dos

    2015-04-08

    The genetic diversity and population structure of Salvia lachnostachys Benth were assessed. Inter Simple Sequence Repeat (ISSR) molecular markers were used to investigate the restricted distribution of S. lachnostachys in Parana State, Brazil. Leaves of 73 individuals representing three populations were collected. DNA was extracted and submitted to PCR-ISSR amplification with nine tested primers. Genetic diversity parameters were evaluated. Our analysis indicated 95.6% polymorphic loci (stress value 0.02) with a 0.79 average Simpson's index. The Nei-Li distance dendrogram and principal component analysis largely recovered the geographical origin of each sample. Four major clusters were recognized representing each collected population. Nei's gene diversity and Shannon's information index were 0.25 and 0.40 respectively. As is typical for outcrossing herbs, the majority of genetic variation occurred at the population level (81.76%). A high gene flow (Nm = 2.48) was observed with a correspondingly low fixation index. These values were generally similar to previous studies on congeneric species. The results of principal coordinate analysis (PCA) and of arithmetic average (UPGMA) were consistent and all three populations appear distinct as in STRUCTURE analysis. In addition, this analysis indicated a majority intrapopulation genetic variation. Despite the human pressure on natural populations our study found high levels of genetic diversity for S. lachnostachys. This was the first molecular assessment for this endemic species with medicinal proprieties and the results can guide for subsequent bioprospection, breeding programs or conservation actions.

  5. Concept of automatic programming of NC machine for metal plate cutting by genetic algorithm method

    Directory of Open Access Journals (Sweden)

    B. Vaupotic

    2005-12-01

    Full Text Available Purpose: In this paper the concept of automatic programs of the NC machine for metal plate cutting by genetic algorithm method has been presented.Design/methodology/approach: The paper was limited to automatic creation of NC programs for two-dimensional cutting of material by means of adaptive heuristic search algorithms.Findings: Automatic creation of NC programs in laser cutting of materials combines the CAD concepts, the recognition of features and creation and optimization of NC programs. The proposed intelligent system is capable to recognize automatically the nesting of products in the layout, to determine the incisions and sequences of cuts forming the laid out products. Position of incisions is determined at the relevant places on the cut. The system is capable to find the shortest path between individual cuts and to record the NC program.Research limitations/implications: It would be appropriate to orient future researches towards conceiving an improved system for three-dimensional cutting with optional determination of positions of incisions, with the capability to sense collisions and with optimization of the speed and acceleration during cutting.Practical implications: The proposed system assures automatic preparation of NC program without NC programer.Originality/value: The proposed concept shows a high degree of universality, efficiency and reliability and it can be simply adapted to other NC-machines.

  6. Telegenetics: application of a tele-education program in genetic syndromes for Brazilian students

    Directory of Open Access Journals (Sweden)

    Luciana Paula MAXIMINO

    2014-12-01

    Full Text Available With the high occurrence of genetic anomalies in Brazil and the manifestations of communication disorders associated with these conditions, the development of educative actions that comprise these illnesses can bring unique benefits in the identification and appropriate treatment of these clinical pictures. Objective The aim of this study was to develop and analyze an educational program in genetic syndromes for elementary students applied in two Brazilian states, using an Interactive Tele-education model. Material and Methods The study was carried out in 4 schools: two in the state of São Paulo, Southeast Region, Brazil, and two in the state of Amazonas, North Region, Brazil. Forty-five students, both genders, aged between 13 and 14 years, of the 9th grade of the basic education of both public and private system, were divided into two groups: 21 of São Paulo Group (SPG and 24 of Amazonas Group (AMG. The educational program lasted about 3 months and was divided into two stages including both classroom and distance activities on genetic syndromes. The classroom activity was carried out separately in each school, with expository lessons, graphs and audiovisual contents. In the activity at a distance the educational content was presented to students by means of the Interactive Tele-education model. In this stage, the students had access a Cybertutor, using the Young Doctor Project methodology. In order to measure the effectiveness of the educational program, the Problem Situation Questionnaire (PSQ and the Web Site Motivational Analysis Checklist adapted (FPM were used. Results The program developed was effective for knowledge acquisition in 80% of the groups. FPM showed a high satisfaction index from the participants in relation to the Interactive Tele-education, evaluating the program as "awesome course". No statistically significant differences between the groups regarding type of school or state were observed. Conclusion Thus, the Tele

  7. The Mouse House: A brief history of the ORNL mouse-genetics program, 1947–2009

    Energy Technology Data Exchange (ETDEWEB)

    Russell, Liane B.

    2013-10-01

    The large mouse genetics program at the Oak Ridge National Lab is often re-membered chiefly for the germ-cell mutation-rate data it generated and their uses in estimating the risk of heritable radiation damage. In fact, it soon became a multi-faceted research effort that, over a period of almost 60 years, generated a wealth of information in the areas of mammalian mutagenesis, basic genetics (later enriched by molecular techniques), cytogenetics, reproductive biology, biochemistry of germ cells, and teratology. Research in the area of germ-cell mutagenesis explored the important physical and biological factors that affect the frequency and nature of induced mutations and made several unexpected discoveries, such as the major importance of the perigametic interval (the zygote stage) for the origin of spontaneous mutations and for the sensitivity to induced genetic change. Of practical value was the discovery that ethylnitrosourea was a supermutagen for point mutations, making high-efficiency mutagenesis in the mouse feasible worldwide. Teratogenesis findings resulted in recommendations still generally accepted in radiological practice. Studies supporting the mutagenesis research added whole bodies of information about mammalian germ-cell development and about molecular targets in germ cells. The early decision to not merely count but propagate genetic variants of all sorts made possible further discoveries, such as the Y-Chromosome s importance in mammalian sex determination and the identification of rare X-autosome translocations, which, in turn, led to the formulation of the single-active-X hypothesis and provided tools for studies of functional mosaicism for autosomal genes, male sterility, and chromosome-pairing mechanism. Extensive genetic and then molecular analyses of large numbers of induced specific-locus mutants resulted in fine-structure physical and correlated functional mapping of significant portions of the mouse genome and constituted a valuable

  8. Exponential distribution-based genetic algorithm for solving mixed-integer bilevel programming problems

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Two classes of mixed-integer nonlinear bilevel programming problems are discussed. One is that the follower's functions are separable with respect to the follower's variables, and the other is that the follower's functions are convex if the follower's variables are not restricted to integers. A genetic algorithm based on an exponential distribution is proposed for the aforementioned problems. First, for each fixed leader's variable x, it is proved that the optimal solution y of the follower's mixed-integer programming can be obtained by solving associated relaxed problems, and according to the convexity of the functions involved, a simplified branch and bound approach is given to solve the follower's programming for the second class of problems. Furthermore, based on an exponential distribution with a parameter A, a new crossover operator is designed in which the best individuals are used to generate better offspring of crossover. The simulation results illustrate that the proposed algorithm is efficient and robust.

  9. A Genetic Programming Method for the Identification of Signal Peptides and Prediction of Their Cleavage Sites

    Directory of Open Access Journals (Sweden)

    David Lennartsson

    2004-01-01

    Full Text Available A novel approach to signal peptide identification is presented. We use an evolutionary algorithm for automatic evolution of classification programs, so-called programmatic motifs. The variant of evolutionary algorithm used is called genetic programming where a population of solution candidates in the form of full computer programs is evolved, based on training examples consisting of signal peptide sequences. The method is compared with a previous work using artificial neural network (ANN approaches. Some advantages compared to ANNs are noted. The programmatic motif can perform computational tasks beyond that of feed-forward neural networks and has also other advantages such as readability. The best motif evolved was analyzed and shown to detect the h-region of the signal peptide. A powerful parallel computer cluster was used for the experiment.

  10. Genetic Programming for the Generation of Crisp and Fuzzy Rule Bases in Classification and Diagnosis of Medical Data

    DEFF Research Database (Denmark)

    Dounias, George; Tsakonas, Athanasios; Jantzen, Jan

    2002-01-01

    This paper demonstrates two methodologies for the construction of rule-based systems in medical decision making. The first approach consists of a method combining genetic programming and heuristic hierarchical rule-base construction. The second model is composed by a strongly-typed genetic progra...

  11. DNAStat, version 2.1--a computer program for processing genetic profile databases and biostatistical calculations.

    Science.gov (United States)

    Berent, Jarosław

    2010-01-01

    This paper presents the new DNAStat version 2.1 for processing genetic profile databases and biostatistical calculations. The popularization of DNA studies employed in the judicial system has led to the necessity of developing appropriate computer programs. Such programs must, above all, address two critical problems, i.e. the broadly understood data processing and data storage, and biostatistical calculations. Moreover, in case of terrorist attacks and mass natural disasters, the ability to identify victims by searching related individuals is very important. DNAStat version 2.1 is an adequate program for such purposes. The DNAStat version 1.0 was launched in 2005. In 2006, the program was updated to 1.1 and 1.2 versions. There were, however, slight differences between those versions and the original one. The DNAStat version 2.0 was launched in 2007 and the major program improvement was an introduction of the group calculation options with the potential application to personal identification of mass disasters and terrorism victims. The last 2.1 version has the option of language selection--Polish or English, which will enhance the usage and application of the program also in other countries.

  12. On the Calibration of Multigene Genetic Programming to Simulate Low Flows in the Moselle River

    Directory of Open Access Journals (Sweden)

    Ali DANANDEH MEHR

    2016-12-01

    Full Text Available The aim of this paper is to calibrate a data-driven model to simulate Moselle River flows and compare the performance with three different hydrologic models from a previous study. For consistency a similar set up and error metric are used to evaluate the model results. Precipitation, potential evapotranspiration and streamflow from previous day have been used as inputs. Based on the calibration and validation results, the proposed multigene genetic programming model is the best performing model among four models. The timing and the magnitude of extreme low flow events could be captured even when we use root mean squared error as the objective function for model calibration. Although the model is developed and calibrated for Moselle River flows, the multigene genetic algorithm offers a great opportunity for hydrologic prediction and forecast problems in the river basins with scarce data issues.

  13. Real Time Updating Genetic Network Programming for Adapting to the Change of Stock Prices

    Science.gov (United States)

    Chen, Yan; Mabu, Shingo; Shimada, Kaoru; Hirasawa, Kotaro

    The key in stock trading model is to take the right actions for trading at the right time, primarily based on the accurate forecast of future stock trends. Since an effective trading with given information of stock prices needs an intelligent strategy for the decision making, we applied Genetic Network Programming (GNP) to creating a stock trading model. In this paper, we propose a new method called Real Time Updating Genetic Network Programming (RTU-GNP) for adapting to the change of stock prices. There are three important points in this paper: First, the RTU-GNP method makes a stock trading decision considering both the recommendable information of technical indices and the candlestick charts according to the real time stock prices. Second, we combine RTU-GNP with a Sarsa learning algorithm to create the programs efficiently. Also, sub-nodes are introduced in each judgment and processing node to determine appropriate actions (buying/selling) and to select appropriate stock price information depending on the situation. Third, a Real Time Updating system has been firstly introduced in our paper considering the change of the trend of stock prices. The experimental results on the Japanese stock market show that the trading model with the proposed RTU-GNP method outperforms other models without real time updating. We also compared the experimental results using the proposed method with Buy&Hold method to confirm its effectiveness, and it is clarified that the proposed trading model can obtain much higher profits than Buy&Hold method.

  14. Optimal in silico target gene deletion through nonlinear programming for genetic engineering.

    Science.gov (United States)

    Hong, Chung-Chien; Song, Mingzhou

    2010-02-24

    Optimal selection of multiple regulatory genes, known as targets, for deletion to enhance or suppress the activities of downstream genes or metabolites is an important problem in genetic engineering. Such problems become more feasible to address in silico due to the availability of more realistic dynamical system models of gene regulatory and metabolic networks. The goal of the computational problem is to search for a subset of genes to knock out so that the activity of a downstream gene or a metabolite is optimized. Based on discrete dynamical system modeling of gene regulatory networks, an integer programming problem is formulated for the optimal in silico target gene deletion problem. In the first result, the integer programming problem is proved to be NP-hard and equivalent to a nonlinear programming problem. In the second result, a heuristic algorithm, called GKONP, is designed to approximate the optimal solution, involving an approach to prune insignificant terms in the objective function, and the parallel differential evolution algorithm. In the third result, the effectiveness of the GKONP algorithm is demonstrated by applying it to a discrete dynamical system model of the yeast pheromone pathways. The empirical accuracy and time efficiency are assessed in comparison to an optimal, but exhaustive search strategy. Although the in silico target gene deletion problem has enormous potential applications in genetic engineering, one must overcome the computational challenge due to its NP-hardness. The presented solution, which has been demonstrated to approximate the optimal solution in a practical amount of time, is among the few that address the computational challenge. In the experiment on the yeast pheromone pathways, the identified best subset of genes for deletion showed advantage over genes that were selected empirically. Once validated in vivo, the optimal target genes are expected to achieve higher genetic engineering effectiveness than a trial

  15. Optimal in silico target gene deletion through nonlinear programming for genetic engineering.

    Directory of Open Access Journals (Sweden)

    Chung-Chien Hong

    Full Text Available BACKGROUND: Optimal selection of multiple regulatory genes, known as targets, for deletion to enhance or suppress the activities of downstream genes or metabolites is an important problem in genetic engineering. Such problems become more feasible to address in silico due to the availability of more realistic dynamical system models of gene regulatory and metabolic networks. The goal of the computational problem is to search for a subset of genes to knock out so that the activity of a downstream gene or a metabolite is optimized. METHODOLOGY/PRINCIPAL FINDINGS: Based on discrete dynamical system modeling of gene regulatory networks, an integer programming problem is formulated for the optimal in silico target gene deletion problem. In the first result, the integer programming problem is proved to be NP-hard and equivalent to a nonlinear programming problem. In the second result, a heuristic algorithm, called GKONP, is designed to approximate the optimal solution, involving an approach to prune insignificant terms in the objective function, and the parallel differential evolution algorithm. In the third result, the effectiveness of the GKONP algorithm is demonstrated by applying it to a discrete dynamical system model of the yeast pheromone pathways. The empirical accuracy and time efficiency are assessed in comparison to an optimal, but exhaustive search strategy. SIGNIFICANCE: Although the in silico target gene deletion problem has enormous potential applications in genetic engineering, one must overcome the computational challenge due to its NP-hardness. The presented solution, which has been demonstrated to approximate the optimal solution in a practical amount of time, is among the few that address the computational challenge. In the experiment on the yeast pheromone pathways, the identified best subset of genes for deletion showed advantage over genes that were selected empirically. Once validated in vivo, the optimal target genes are

  16. Mini core germplasm collections for infusing genetic diversity in plant breeding programs

    Directory of Open Access Journals (Sweden)

    Hari D Upadhyaya*, Devvart Yadav, Naresh Dronavalli, CLL Gowda, and Sube Singh

    2010-07-01

    Full Text Available Plant genetic resources are essential components to meet future food security needs of world. Crop germplasm diversitycontributes to developing improved crop cultivars aimed at increasing crop productivity. The large size of germplasmcollections, coupled with unavailability of detailed data and information, has resulted in low use (<1% of germplasmleading to a narrow genetic base in many crops. The miniaturization of crop collections with almost full representation ofgenetic diversity in the form of mini core (~1% of the entire collection approach is an effective methodology to enrichand enhance crop improvement programs. The concept and process of developing mini core at The International CropsResearch Institute for the Semi-Arid Tropics (ICRISAT has been recognized worldwide as an “International PublicGood” (IPG. The mini core provides a means for accessing the larger collections for further exploration and also helps inproper assessment of genetic diversity and population structure and for association mapping and targeted gene mining.Use of mini core approach will lead to greater utilization of diverse germplasm for developing broad-based cultivars,especially in the context of climate change. Many national programs have shown immense interest in evaluating minicore as reflected by the supply of 114 sets of mini core of chickpea, groundnut, pigeonpea, sorghum, pearl millet, foxtailmillet and finger millet to researchers in 14 countries. Scientists have been able to identify new and diverse sources ofvariation for morpho-agronomic, quality, biotic, and abiotic stress resistance traits in various crops. The molecularcharacterization of the mini core will further enhance its use in plant breeding programs.

  17. Genetic Variability and Population Structure of Salvia lachnostachys: Implications for Breeding and Conservation Programs

    Directory of Open Access Journals (Sweden)

    Marianna Erbano

    2015-04-01

    Full Text Available The genetic diversity and population structure of Salvia lachnostachys Benth were assessed. Inter Simple Sequence Repeat (ISSR molecular markers were used to investigate the restricted distribution of S. lachnostachys in Parana State, Brazil. Leaves of 73 individuals representing three populations were collected. DNA was extracted and submitted to PCR-ISSR amplification with nine tested primers. Genetic diversity parameters were evaluated. Our analysis indicated 95.6% polymorphic loci (stress value 0.02 with a 0.79 average Simpson’s index. The Nei-Li distance dendrogram and principal component analysis largely recovered the geographical origin of each sample. Four major clusters were recognized representing each collected population. Nei’s gene diversity and Shannon’s information index were 0.25 and 0.40 respectively. As is typical for outcrossing herbs, the majority of genetic variation occurred at the population level (81.76%. A high gene flow (Nm = 2.48 was observed with a correspondingly low fixation index. These values were generally similar to previous studies on congeneric species. The results of principal coordinate analysis (PCA and of arithmetic average (UPGMA were consistent and all three populations appear distinct as in STRUCTURE analysis. In addition, this analysis indicated a majority intrapopulation genetic variation. Despite the human pressure on natural populations our study found high levels of genetic diversity for S. lachnostachys. This was the first molecular assessment for this endemic species with medicinal proprieties and the results can guide for subsequent bioprospection, breeding programs or conservation actions.

  18. System Response Analysis and Model Order Reduction, Using Conventional Method, Bond Graph Technique and Genetic Programming

    Directory of Open Access Journals (Sweden)

    Lubna Moin

    2009-04-01

    Full Text Available This research paper basically explores and compares the different modeling and analysis techniques and than it also explores the model order reduction approach and significance. The traditional modeling and simulation techniques for dynamic systems are generally adequate for single-domain systems only, but the Bond Graph technique provides new strategies for reliable solutions of multi-domain system. They are also used for analyzing linear and non linear dynamic production system, artificial intelligence, image processing, robotics and industrial automation. This paper describes a unique technique of generating the Genetic design from the tree structured transfer function obtained from Bond Graph. This research work combines bond graphs for model representation with Genetic programming for exploring different ideas on design space tree structured transfer function result from replacing typical bond graph element with their impedance equivalent specifying impedance lows for Bond Graph multiport. This tree structured form thus obtained from Bond Graph is applied for generating the Genetic Tree. Application studies will identify key issues and importance for advancing this approach towards becoming on effective and efficient design tool for synthesizing design for Electrical system. In the first phase, the system is modeled using Bond Graph technique. Its system response and transfer function with conventional and Bond Graph method is analyzed and then a approach towards model order reduction is observed. The suggested algorithm and other known modern model order reduction techniques are applied to a 11th order high pass filter [1], with different approach. The model order reduction technique developed in this paper has least reduction errors and secondly the final model retains structural information. The system response and the stability analysis of the system transfer function taken by conventional and by Bond Graph method is compared and

  19. System Response Analysis and Model Order Reduction, Using Conventional Method, Bond Graph Technique and Genetic Programming

    Directory of Open Access Journals (Sweden)

    Shahid Ali

    2009-04-01

    Full Text Available This research paper basically explores and compares the different modeling and analysis techniques and than it also explores the model order reduction approach and significance. The traditional modeling and simulation techniques for dynamic systems are generally adequate for single-domain systems only, but the Bond Graph technique provides new strategies for reliable solutions of multi-domain system. They are also used for analyzing linear and non linear dynamic production system, artificial intelligence, image processing, robotics and industrial automation. This paper describes a unique technique of generating the Genetic design from the tree structured transfer function obtained from Bond Graph. This research work combines bond graphs for model representation with Genetic programming for exploring different ideas on design space tree structured transfer function result from replacing typical bond graph element with their impedance equivalent specifying impedance lows for Bond Graph multiport. This tree structured form thus obtained from Bond Graph is applied for generating the Genetic Tree. Application studies will identify key issues and importance for advancing this approach towards becoming on effective and efficient design tool for synthesizing design for Electrical system. In the first phase, the system is modeled using Bond Graph technique. Its system response and transfer function with conventional and Bond Graph method is analyzed and then a approach towards model order reduction is observed. The suggested algorithm and other known modern model order reduction techniques are applied to a 11th order high pass filter [1], with different approach. The model order reduction technique developed in this paper has least reduction errors and secondly the final model retains structural information. The system response and the stability analysis of the system transfer function taken by conventional and by Bond Graph method is compared and

  20. Buying and Selling Stocks of Multi Brands Using Genetic Network Programming with Control Nodes

    Science.gov (United States)

    Ohkawa, Etsushi; Chen, Yan; Bao, Zhiguo; Mabu, Shingo; Shimada, Kaoru; Hirasawa, Kotaro

    A new evolutionary method named “Genetic Network Programming with control nodes, GNPcn” has been applied to determine the timing of buying or selling stocks. GNPcn represents its solutions as directed graph structures which has some useful features inherently. For example, GNPcn has an implicit memory function which memorizes the past action sequences of agents and GNPcn can re-use nodes repeatedly in the network flow, so very compact graph structures can be made. GNPcn can determine the strategy of buying and selling stocks of multi issues. The effectiveness of the proposed method is confirmed by simulations.

  1. Better-than-classical circuits for OR and AND/OR found using genetic programming

    CERN Document Server

    Barnum, H N; Spector, L; Barnum, Howard; Bernstein, Herbert J.; Spector, Lee

    1999-01-01

    We present a quantum circuit evolved using genetic programming. From it we derive the first better-than-classical one-query bounded-error circuit for OR of one-bit black-box functions. The larger evolved circuit calculates, with error probability lower than any possible classical one-query algorithm, the property defined by a depth-two binary AND/OR tree with the four possible function input values as leaves. We analyze it as a kind of recursive application of the OR circuit. Since the OR and AND/OR trees have fan-in 2, these circuits may be useful in investigating the uniform binary AND/OR tree in the large-N asymptotic regime, a problem whose classical query complexity is completely understood and which has applications in game tree evaluation, logic programming, theorem-proving, and many other areas.

  2. Learning to solve planning problems efficiently by means of genetic programming.

    Science.gov (United States)

    Aler, R; Borrajo, D; Isasi, P

    2001-01-01

    Declarative problem solving, such as planning, poses interesting challenges for Genetic Programming (GP). There have been recent attempts to apply GP to planning that fit two approaches: (a) using GP to search in plan space or (b) to evolve a planner. In this article, we propose to evolve only the heuristics to make a particular planner more efficient. This approach is more feasible than (b) because it does not have to build a planner from scratch but can take advantage of already existing planning systems. It is also more efficient than (a) because once the heuristics have been evolved, they can be used to solve a whole class of different planning problems in a planning domain, instead of running GP for every new planning problem. Empirical results show that our approach (EvoCK) is able to evolve heuristics in two planning domains (the blocks world and the logistics domain) that improve PRODIGY4.0 performance. Additionally, we experiment with a new genetic operator --Instance-Based Crossover--that is able to use traces of the base planner as raw genetic material to be injected into the evolving population.

  3. Wavelet-linear genetic programming: A new approach for modeling monthly streamflow

    Science.gov (United States)

    Ravansalar, Masoud; Rajaee, Taher; Kisi, Ozgur

    2017-06-01

    The streamflows are important and effective factors in stream ecosystems and its accurate prediction is an essential and important issue in water resources and environmental engineering systems. A hybrid wavelet-linear genetic programming (WLGP) model, which includes a discrete wavelet transform (DWT) and a linear genetic programming (LGP) to predict the monthly streamflow (Q) in two gauging stations, Pataveh and Shahmokhtar, on the Beshar River at the Yasuj, Iran were used in this study. In the proposed WLGP model, the wavelet analysis was linked to the LGP model where the original time series of streamflow were decomposed into the sub-time series comprising wavelet coefficients. The results were compared with the single LGP, artificial neural network (ANN), a hybrid wavelet-ANN (WANN) and Multi Linear Regression (MLR) models. The comparisons were done by some of the commonly utilized relevant physical statistics. The Nash coefficients (E) were found as 0.877 and 0.817 for the WLGP model, for the Pataveh and Shahmokhtar stations, respectively. The comparison of the results showed that the WLGP model could significantly increase the streamflow prediction accuracy in both stations. Since, the results demonstrate a closer approximation of the peak streamflow values by the WLGP model, this model could be utilized for the simulation of cumulative streamflow data prediction in one month ahead.

  4. Multiobjective Genetic Algorithms Program for the Optimization of an OTA for Front-End Electronics

    Directory of Open Access Journals (Sweden)

    Abdelghani Dendouga

    2014-01-01

    Full Text Available The design of an interface to a specific sensor induces costs and design time mainly related to the analog part. So to reduce these costs, it should have been standardized like digital electronics. The aim of the present work is the elaboration of a method based on multiobjectives genetic algorithms (MOGAs to allow automated synthesis of analog and mixed systems. This proposed methodology is used to find the optimal dimensional transistor parameters (length and width in order to obtain operational amplifier performances for analog and mixed CMOS-(complementary metal oxide semiconductor- based circuit applications. Six performances are considered in this study, direct current (DC gain, unity-gain bandwidth (GBW, phase margin (PM, power consumption (P, area (A, and slew rate (SR. We used the Matlab optimization toolbox to implement the program. Also, by using variables obtained from genetic algorithms, the operational transconductance amplifier (OTA is simulated by using Cadence Virtuoso Spectre circuit simulator in standard TSMC (Taiwan Semiconductor Manufacturing Company RF 0.18 μm CMOS technology. A good agreement is observed between the program optimization and electric simulation.

  5. Coregulation of genetic programs by the transcription factors NFIB and STAT5.

    Science.gov (United States)

    Robinson, Gertraud W; Kang, Keunsoo; Yoo, Kyung Hyun; Tang, Yong; Zhu, Bing-Mei; Yamaji, Daisuke; Colditz, Vera; Jang, Seung Jian; Gronostajski, Richard M; Hennighausen, Lothar

    2014-05-01

    Mammary-specific genetic programs are activated during pregnancy by the common transcription factor signal transducer and activator of transcription (STAT) 5. More than one third of these genes carry nuclear factor I/B (NFIB) binding motifs that coincide with STAT5 in vivo binding, suggesting functional synergy between these two transcription factors. The role of NFIB in this governance was investigated in mice from which Nfib had been inactivated in mammary stem cells or in differentiating alveolar epithelium. Although NFIB was not required for alveolar expansion, the combined absence of NFIB and STAT5 prevented the formation of functional alveoli. NFIB controlled the expression of mammary-specific and STAT5-regulated genes and chromatin immunoprecipitation-sequencing established STAT5 and NFIB binding at composite regulatory elements containing histone H3 lysine dimethylation enhancer marks and progesterone receptor binding. By integrating previously published chromatin immunoprecipitation-sequencing data sets, the presence of NFIB-STAT5 modules in other cell types was investigated. Notably, genomic sites bound by NFIB in hair follicle stem cells were also occupied by STAT5 in mammary epithelium and coincided with enhancer marks. Many of these genes were under NFIB control in both hair follicle stem cells and mammary alveolar epithelium. We propose that NFIB-STAT5 modules, possibly in conjunction with other transcription factors, control cell-specific genetic programs.

  6. A wavelet-linear genetic programming model for sodium (Na+) concentration forecasting in rivers

    Science.gov (United States)

    Ravansalar, Masoud; Rajaee, Taher; Zounemat-Kermani, Mohammad

    2016-06-01

    The prediction of water quality parameters in water resources such as rivers is of importance issue that needs to be considered in better management of irrigation systems and water supplies. In this respect, this study proposes a new hybrid wavelet-linear genetic programming (WLGP) model for prediction of monthly sodium (Na+) concentration. The 23-year monthly data used in this study, were measured from the Asi River at the Demirköprü gauging station located in Antakya, Turkey. At first, the measured discharge (Q) and Na+ datasets are initially decomposed into several sub-series using discrete wavelet transform (DWT). Then, these new sub-series are imposed to the ad hoc linear genetic programming (LGP) model as input patterns to predict monthly Na+ one month ahead. The results of the new proposed WLGP model are compared with LGP, WANN and ANN models. Comparison of the models represents the superiority of the WLGP model over the LGP, WANN and ANN models such that the Nash-Sutcliffe efficiencies (NSE) for WLGP, WANN, LGP and ANN models were 0.984, 0.904, 0.484 and 0.351, respectively. The achieved results even points to the superiority of the single LGP model than the ANN model. Continuously, the capability of the proposed WLGP model in terms of prediction of the Na+ peak values is also presented in this study.

  7. Drag reduction of a car model by linear genetic programming control

    Science.gov (United States)

    Li, Ruiying; Noack, Bernd R.; Cordier, Laurent; Borée, Jacques; Harambat, Fabien

    2017-08-01

    We investigate open- and closed-loop active control for aerodynamic drag reduction of a car model. Turbulent flow around a blunt-edged Ahmed body is examined at ReH≈ 3× 105 based on body height. The actuation is performed with pulsed jets at all trailing edges (multiple inputs) combined with a Coanda deflection surface. The flow is monitored with 16 pressure sensors distributed at the rear side (multiple outputs). We apply a recently developed model-free control strategy building on genetic programming in Dracopoulos and Kent (Neural Comput Appl 6:214-228, 1997) and Gautier et al. (J Fluid Mech 770:424-441, 2015). The optimized control laws comprise periodic forcing, multi-frequency forcing and sensor-based feedback including also time-history information feedback and combinations thereof. Key enabler is linear genetic programming (LGP) as powerful regression technique for optimizing the multiple-input multiple-output control laws. The proposed LGP control can select the best open- or closed-loop control in an unsupervised manner. Approximately 33% base pressure recovery associated with 22% drag reduction is achieved in all considered classes of control laws. Intriguingly, the feedback actuation emulates periodic high-frequency forcing. In addition, the control identified automatically the only sensor which listens to high-frequency flow components with good signal to noise ratio. Our control strategy is, in principle, applicable to all multiple actuators and sensors experiments.

  8. Linear genetic programming for time-series modelling of daily flow rate

    Indian Academy of Sciences (India)

    Aytac Guven

    2009-04-01

    In this study linear genetic programming (LGP),which is a variant of Genetic Programming,and two versions of Neural Networks (NNs)are used in predicting time-series of daily flow rates at a station on Schuylkill River at Berne,PA,USA.Daily flow rate at present is being predicted based on different time-series scenarios.For this purpose,various LGP and NN models are calibrated with training sets and validated by testing sets.Additionally,the robustness of the proposed LGP and NN models are evaluated by application data,which are used neither in training nor at testing stage.The results showed that both techniques predicted the flow rate data in quite good agreement with the observed ones,and the predictions of LGP and NN are challenging.The performance of LGP,which was moderately better than NN,is very promising and hence supports the use of LGP in predicting of river flow data.

  9. A Constraint programming-based genetic algorithm for capacity output optimization

    Directory of Open Access Journals (Sweden)

    Kate Ean Nee Goh

    2014-10-01

    Full Text Available Purpose: The manuscript presents an investigation into a constraint programming-based genetic algorithm for capacity output optimization in a back-end semiconductor manufacturing company.Design/methodology/approach: In the first stage, constraint programming defining the relationships between variables was formulated into the objective function. A genetic algorithm model was created in the second stage to optimize capacity output. Three demand scenarios were applied to test the robustness of the proposed algorithm.Findings: CPGA improved both the machine utilization and capacity output once the minimum requirements of a demand scenario were fulfilled. Capacity outputs of the three scenarios were improved by 157%, 7%, and 69%, respectively.Research limitations/implications: The work relates to aggregate planning of machine capacity in a single case study. The constraints and constructed scenarios were therefore industry-specific.Practical implications: Capacity planning in a semiconductor manufacturing facility need to consider multiple mutually influenced constraints in resource availability, process flow and product demand. The findings prove that CPGA is a practical and an efficient alternative to optimize the capacity output and to allow the company to review its capacity with quick feedback.Originality/value: The work integrates two contemporary computational methods for a real industry application conventionally reliant on human judgement.

  10. Drag reduction of a car model by linear genetic programming control

    CERN Document Server

    Li, Ruiying; Cordier, Laurent; Borée, Jacques; Harambat, Fabien; Kaiser, Eurika; Duriez, Thomas

    2016-01-01

    We investigate open- and closed-loop active control for aerodynamic drag reduction of a car model. Turbulent flow around a blunt-edged Ahmed body is examined at $Re_{H}\\approx3\\times10^{5}$ based on body height. The actuation is performed with pulsed jets at all trailing edges combined with a Coanda deflection surface. The flow is monitored with pressure sensors distributed at the rear side. We apply a model-free control strategy building on Dracopoulos & Kent (Neural Comput. & Applic., vol. 6, 1997, pp. 214-228) and Gautier et al. (J. Fluid Mech., vol. 770, 2015, pp. 442-457). The optimized control laws comprise periodic forcing, multi-frequency forcing and sensor-based feedback including also time-history information feedback and combination thereof. Key enabler is linear genetic programming as simple and efficient framework for multiple inputs (actuators) and multiple outputs (sensors). The proposed linear genetic programming control can select the best open- or closed-loop control in an unsupervis...

  11. Generating Stock Trading Rules Using Genetic Network Programming with Flag Nodes and Adjustment of Importance Indexes

    Science.gov (United States)

    Mabu, Shingo; Chen, Yan; Hirasawa, Kotaro

    Genetic Network Programming (GNP) is an evolutionary algorithm which represents its solutions using graph structures. Since GNP can create quite compact programs and has an implicit memory function, GNP works well especially in dynamic environments. In addition, a study on creating trading rules on stock markets using GNP with Importance Index (GNP-IMX) has been done. IMX is one of the criterions for decision making. However, the values of IMXs must be deteminined by our experience/knowledge. Therefore in this paper, IMXs are adjusted appropriately during the stock trading in order to predict the rise and fall of the stocks. Moreover, newly defined flag nodes are introduced to GNP, which can appropriately judge the current situation of the stock prices, and also contributes to the use of many kinds of nodes in GNP program. In the simulation, programs are evolved using the stock prices of 20 companies. Then the generalization ability is tested and compared with GNP without flag nodes, GNP without IMX adjustment and Buy&Hold.

  12. Trading Rules on Stock Markets Using Genetic Network Programming with Reinforcement Learning and Importance Index

    Science.gov (United States)

    Mabu, Shingo; Hirasawa, Kotaro; Furuzuki, Takayuki

    Genetic Network Programming (GNP) is an evolutionary computation which represents its solutions using graph structures. Since GNP can create quite compact programs and has an implicit memory function, it has been clarified that GNP works well especially in dynamic environments. In addition, a study on creating trading rules on stock markets using GNP with Importance Index (GNP-IMX) has been done. IMX is a new element which is a criterion for decision making. In this paper, we combined GNP-IMX with Actor-Critic (GNP-IMX&AC) and create trading rules on stock markets. Evolution-based methods evolve their programs after enough period of time because they must calculate fitness values, however reinforcement learning can change programs during the period, therefore the trading rules can be created efficiently. In the simulation, the proposed method is trained using the stock prices of 10 brands in 2002 and 2003. Then the generalization ability is tested using the stock prices in 2004. The simulation results show that the proposed method can obtain larger profits than GNP-IMX without AC and Buy&Hold.

  13. The Features of Genetic Prion Diseases Based on Chinese Surveillance Program.

    Directory of Open Access Journals (Sweden)

    Qi Shi

    Full Text Available To identify the features of Chinese genetic prion diseases.Suspected Creutzfeldt-Jakob disease (CJD cases that were reported under CJD surveillance were diagnosed and subtyped using the diagnostic criteria issued by the WHO. The general information concerning the patient, their clinical, MRI and EEG data, and the results of CSF 14-3-3 and PRNP sequencing were carefully collected from the database of the national CJD surveillance program and analyzed using the SPSS 11.5 statistical software program.Since 2006, 69 patients were diagnosed with genetic prion diseases and as having 15 different mutations. The median age of the 69 patients at disease onset was 53.5 years, varying from 19 to 80 years. The majority of patients displaying clinical symptoms were in the 50-59 years of age. FFI, T188K gCJD and E200K were the three most common subtypes. The disease appeared in the family histories of 43.48% of the patients. The clinical manifestations varied considerably among the various diseases. Patients who carried mutations in the N-terminus displayed a younger age of onset, were CSF 14-3-3 negative, had a family history of the condition, and experienced a longer duration of the condition. The clinical courses of T188K were significantly shorter than those of FFI and E200K gCJD, while the symptoms in the FFI group appeared at a younger age and for a longer duration. Moreover, the time intervals between the initial neurologist visit to the final diagnosis were similar among patients with FFI, T188K gCJD, E200K gCJD and other diseases.The features of Chinese genetic prion diseases are different from those seen in Europe and other Asian countries.

  14. Genetics

    DEFF Research Database (Denmark)

    Christensen, Kaare; McGue, Matt

    2016-01-01

    The sequenced genomes of individuals aged ≥80 years, who were highly educated, self-referred volunteers and with no self-reported chronic diseases were compared to young controls. In these data, healthy ageing is a distinct phenotype from exceptional longevity and genetic factors that protect...

  15. A Pareto-optimal moving average multigene genetic programming model for daily streamflow prediction

    Science.gov (United States)

    Danandeh Mehr, Ali; Kahya, Ercan

    2017-06-01

    Genetic programming (GP) is able to systematically explore alternative model structures of different accuracy and complexity from observed input and output data. The effectiveness of GP in hydrological system identification has been recognized in recent studies. However, selecting a parsimonious (accurate and simple) model from such alternatives still remains a question. This paper proposes a Pareto-optimal moving average multigene genetic programming (MA-MGGP) approach to develop a parsimonious model for single-station streamflow prediction. The three main components of the approach that take us from observed data to a validated model are: (1) data pre-processing, (2) system identification and (3) system simplification. The data pre-processing ingredient uses a simple moving average filter to diminish the lagged prediction effect of stand-alone data-driven models. The multigene ingredient of the model tends to identify the underlying nonlinear system with expressions simpler than classical monolithic GP and, eventually simplification component exploits Pareto front plot to select a parsimonious model through an interactive complexity-efficiency trade-off. The approach was tested using the daily streamflow records from a station on Senoz Stream, Turkey. Comparing to the efficiency results of stand-alone GP, MGGP, and conventional multi linear regression prediction models as benchmarks, the proposed Pareto-optimal MA-MGGP model put forward a parsimonious solution, which has a noteworthy importance of being applied in practice. In addition, the approach allows the user to enter human insight into the problem to examine evolved models and pick the best performing programs out for further analysis.

  16. Competent Geometric Semantic Genetic Programming for Symbolic Regression and Boolean Function Synthesis.

    Science.gov (United States)

    Pawlak, Tomasz P; Krawiec, Krzysztof

    2017-02-16

    Program semantics is a promising recent research thread in Genetic Programming (GP). Over a dozen of semantic-aware search, selection, and initialization operators for GP have been proposed to date. Some of those operators are designed to exploit the geometric properties of semantic space, while some others focus on making offspring effective, i.e., semantically different from their parents. Only a small fraction of previous works aimed at addressing both these features simultaneously. In this paper, we propose a suite of competent operators that combine effectiveness with geometry for population initialization, mate selection, mutation and crossover. We present a theoretical rationale behind these operators and compare them experimentally to operators known from literature on symbolic regression and Boolean function synthesis benchmarks. We analyze each operator in isolation as well as verify how they fare together in an evolutionary run, concluding that the competent operators are superior on a wide range of performance indicators, including best-of-run fitness, test-set fitness, and program size.

  17. Binary Image Classification: A Genetic Programming Approach to the Problem of Limited Training Instances.

    Science.gov (United States)

    Al-Sahaf, Harith; Zhang, Mengjie; Johnston, Mark

    2016-01-01

    In the computer vision and pattern recognition fields, image classification represents an important yet difficult task. It is a challenge to build effective computer models to replicate the remarkable ability of the human visual system, which relies on only one or a few instances to learn a completely new class or an object of a class. Recently we proposed two genetic programming (GP) methods, one-shot GP and compound-GP, that aim to evolve a program for the task of binary classification in images. The two methods are designed to use only one or a few instances per class to evolve the model. In this study, we investigate these two methods in terms of performance, robustness, and complexity of the evolved programs. We use ten data sets that vary in difficulty to evaluate these two methods. We also compare them with two other GP and six non-GP methods. The results show that one-shot GP and compound-GP outperform or achieve results comparable to competitor methods. Moreover, the features extracted by these two methods improve the performance of other classifiers with handcrafted features and those extracted by a recently developed GP-based method in most cases.

  18. On the Predictability of Risk Box Approach by Genetic Programming Method for Bankruptcy Prediction

    Directory of Open Access Journals (Sweden)

    Alireza Bahiraie

    2009-01-01

    Full Text Available Problem statement: Theoretical based data representation is an important tool for model selection and interpretations in bankruptcy analysis since the numerical representation are much less transparent. Some methodological problems concerning financial ratios such as non-proportionality, non-asymetricity, non-scalicity are solved in this study and we presented a complementary technique for empirical analysis of financial ratios and bankruptcy risk. Approach: This study presented new geometric technique for empirical analysis of bankruptcy risk using financial ratios. Within this framework, we proposed the use of a new ratio representation which named Risk Box measure (RB. We demonstrated the application of this geometric approach for variable representation, data visualization and financial ratios at different stages of corporate bankruptcy prediction models based on financial balance sheet ratios. These stages were the selection of variables (predictors, accuracy of each estimation model and the representation of each model for transformed and common ratios. Results: We provided evidence of extent to which changes in values of this index were associated with changes in each axis values and how this may alter our economic interpretation of changes in the patterns and direction of risk components. Results of Genetic Programming (GP models were compared as different classification models and results showed the classifiers outperform by modified ratios. Conclusion/Recommendations: In this study, a new dimension to risk measurement and data representation with the advent of the Share Risk method (SR was proposed. Genetic programming method is substantially superior to the traditional methods such as MDA or Logistic method. It was strongly suggested the use of SR methodology for ratio analysis, which provided a conceptual and complimentary methodological solution to many problems associated with the use of ratios. Respectively, GP will provide

  19. Genetic Programming for the Generation of Crisp and Fuzzy Rule Bases in Classification and Diagnosis of Medical Data

    DEFF Research Database (Denmark)

    Dounias, George; Tsakonas, Athanasios; Jantzen, Jan;

    2002-01-01

    This paper demonstrates two methodologies for the construction of rule-based systems in medical decision making. The first approach consists of a method combining genetic programming and heuristic hierarchical rule-base construction. The second model is composed by a strongly-typed genetic progra...... systems. Comparisons on the system's comprehensibility and the transparency are included. These comparisons include for the Aphasia domain, previous work consisted of two neural network models....

  20. Automated synthesis of both the topology and numerical parameters for seven patented optical lens systems using genetic programming

    Science.gov (United States)

    Jones, Lee W.; Al-Sakran, Sameer H.; Koza, John R.

    2005-08-01

    This paper describes how genetic programming was used as an automated invention machine to synthesize both the topology and numerical parameters for seven previously patented optical lens systems, including one aspherical system and one issued in the 21st-century. Two of the evolved optical lens systems infringe the claims of the patents and the others are novel solutions that satisfy the design goals stated in the patent. The automatic synthesis was done "from scratch"--that is, without starting from a pre-existing good design and without pre-specifying the number of lenses, the topological layout of the lenses, or the numerical parameters of the lenses. Genetic programming is a form of evolutionary computation used to automatically solve problems. It starts from a high-level statement of what needs to be done and progressively breeds a population of candidate individuals over many generations using the principle of Darwinian natural selection and genetic recombination. The paper describes how genetic programming created eyepieces that duplicated the functionality of seven previously patented lens systems. The seven designs were created in a substantially similar and routine way, suggesting that the use of genetic programming in the automated design of both the topology and numerical parameters for optical lens systems may have widespread utility.

  1. Using Fuzzy Gaussian Inference and Genetic Programming to Classify 3D Human Motions

    Science.gov (United States)

    Khoury, Mehdi; Liu, Honghai

    This research introduces and builds on the concept of Fuzzy Gaussian Inference (FGI) (Khoury and Liu in Proceedings of UKCI, 2008 and IEEE Workshop on Robotic Intelligence in Informationally Structured Space (RiiSS 2009), 2009) as a novel way to build Fuzzy Membership Functions that map to hidden Probability Distributions underlying human motions. This method is now combined with a Genetic Programming Fuzzy rule-based system in order to classify boxing moves from natural human Motion Capture data. In this experiment, FGI alone is able to recognise seven different boxing stances simultaneously with an accuracy superior to a GMM-based classifier. Results seem to indicate that adding an evolutionary Fuzzy Inference Engine on top of FGI improves the accuracy of the classifier in a consistent way.

  2. Prediction of Compressive Strength of Concrete Using Artificial Neural Network and Genetic Programming

    Directory of Open Access Journals (Sweden)

    Palika Chopra

    2016-01-01

    Full Text Available An effort has been made to develop concrete compressive strength prediction models with the help of two emerging data mining techniques, namely, Artificial Neural Networks (ANNs and Genetic Programming (GP. The data for analysis and model development was collected at 28-, 56-, and 91-day curing periods through experiments conducted in the laboratory under standard controlled conditions. The developed models have also been tested on in situ concrete data taken from literature. A comparison of the prediction results obtained using both the models is presented and it can be inferred that the ANN model with the training function Levenberg-Marquardt (LM for the prediction of concrete compressive strength is the best prediction tool.

  3. Modeling of Drilling Forces Based on Twist Drill Point Angles Using Multigene Genetic Programming

    Directory of Open Access Journals (Sweden)

    Myong-Il Kim

    2016-01-01

    Full Text Available The mathematical model was developed for predicting the influence of the drill point angles on the cutting forces in drilling with the twist drills, which was used to optimize those angles for reducing drilling forces. The approach was based on multigene genetic programming, for the training data, the grinding tests of twist drill were firstly conducted for the different drill point angles in Biglide parallel machine, and then drilling tests were performed on carbon fiber reinforced plastics using the grinded drills. The effectiveness of the proposed approach was verified through comparing with published data. It was found that the proposed model agreed well with the experimental data and was useful for improving the performance of twist drill.

  4. Genetic programming:  a novel method for the quantitative analysis of pyrolysis mass spectral data.

    Science.gov (United States)

    Gilbert, R J; Goodacre, R; Woodward, A M; Kell, D B

    1997-11-01

    A technique for the analysis of multivariate data by genetic programming (GP) is described, with particular reference to the quantitative analysis of orange juice adulteration data collected by pyrolysis mass spectrometry (PyMS). The dimensionality of the input space was reduced by ranking variables according to product moment correlation or mutual information with the outputs. The GP technique as described gives predictive errors equivalent to, if not better than, more widespread methods such as partial least squares and artificial neural networks but additionally can provide a means for easing the interpretation of the correlation between input and output variables. The described application demonstrates that by using the GP method for analyzing PyMS data the adulteration of orange juice with 10% sucrose solution can be quantified reliably over a 0-20% range with an RMS error in the estimate of ∼1%.

  5. Estimation of hydraulic jump on corrugated bed using artificial neural networks and genetic programming

    Institute of Scientific and Technical Information of China (English)

    Akram ABBASPOUR; Davood FARSADIZADEH; Mohammad Ali GHORBANI

    2013-01-01

    Artificial neural networks (ANNs) and genetic programming (GP) have recently been used for the estimation of hydraulic data. In this study, they were used as alternative tools to estimate the characteristics of hydraulic jumps, such as the free surface location and energy dissipation. The dimensionless hydraulic parameters, including jump depth, jump length, and energy dissipation, were determined as functions of the Froude number and the height and length of corrugations. The estimations of the ANN and GP models were found to be in good agreement with the measured data. The results of the ANN model were compared with those of the GP model, showing that the proposed ANN models are much more accurate than the GP models.

  6. Performance of Cost Assessment on Reusable Components for Software Development using Genetic Programming

    Directory of Open Access Journals (Sweden)

    T.Tejaswini

    2015-08-01

    Full Text Available Reusability is the quality of a piece of software, which enables it to be used again, be it partial, modified or complete. A wide range of modeling techniques have been proposed and applied for software quality predictions. Complexity and size metrics have been used to predict the number of defects in software components. Estimation of cost is important, during the process of software development. There are two main types of cost estimation approaches: algorithmic methods and non-algorithmic methods. In this work, using genetic programming which is a branch of evolutionary algorithms, a new algorithmic method is presented for software development cost estimation, using the implementation of this method; new formulas were obtained for software development cost estimation in which reusability of components is given priority. After evaluation of these formulas, the mean and standard deviation of the magnitude of relative error is better than related algorithmic methods such as COCOMO formulas.

  7. Statistical studies in genetic toxicology: a perspective from the U.S. National Toxicology Program.

    Science.gov (United States)

    Margolin, B H

    1985-11-01

    This paper surveys recent, as yet unpublished, statistical studies arising from research in genetic toxicology within the U.S. National Toxicology Program (NTP). These studies all involve analyses of data from Ames Salmonella/microsome mutagenicity tests, but the statistical methodologies are broadly applicable. Three issues are addressed: First, what is a tenable sampling model for Ames test data, and how does one best test the adequacy of the Poisson sampling assumption? Second, given that nonmonotone dose-response curves are fairly common in the Salmonella assay, what new statistical techniques or modifications of existing ones seem appropriate to accommodate to this reality? Finally, an intriguing question: How can the extensive NTP Ames test data base be used to assess the characteristics of any mutagen-nonmutagen decision rule? The last issue is illustrated with the commonly used "two-times background" rule.

  8. Evolving Rule-Based Systems in two Medical Domains using Genetic Programming

    DEFF Research Database (Denmark)

    Tsakonas, A.; Dounias, G.; Jantzen, Jan;

    2004-01-01

    We demonstrate, compare and discuss the application of two genetic programming methodologies for the construction of rule-based systems in two medical domains: the diagnosis of Aphasia's subtypes and the classification of Pap-Smear Test examinations. The first approach consists of a scheme...... the classification between all common types. A third model consisting of a GP-generated fuzzy rule-based system is tested on the same field. In the classification of Pap-Smear Test examinations, a crisp rule-based system is constructed. Results denote the effectiveness of the proposed systems. Comments...... and comparisons are made between the proposed methods and previous attempts on the selected fields of application....

  9. On the Performance of Different Genetic Programming Approaches for the SORTING Problem.

    Science.gov (United States)

    Wagner, Markus; Neumann, Frank; Urli, Tommaso

    2015-01-01

    In genetic programming, the size of a solution is typically not specified in advance, and solutions of larger size may have a larger benefit. The flexibility often comes at the cost of the so-called bloat problem: individuals grow without providing additional benefit to the quality of solutions, and the additional elements can block the optimization process. Consequently, problems that are relatively easy to optimize cannot be handled by variable-length evolutionary algorithms. In this article, we analyze different single- and multiobjective algorithms on the sorting problem, a problem that typically lacks independent and additive fitness structures. We complement the theoretical results with comprehensive experiments to indicate the tightness of existing bounds, and to indicate bounds where theoretical results are missing.

  10. Genetic and epigenetic catalysts in early-life programming of adult cardiometabolic disorders

    Directory of Open Access Journals (Sweden)

    Estampador AC

    2014-12-01

    Full Text Available Angela C Estampador,1,2 Paul W Franks1,3,4 1Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Skåne University Hospital Malmö, Malmö, Sweden; 2Department of Endocrinology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark; 3Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden; 4Department of Nutrition, Harvard School of Public Health, Boston, MA, USA Abstract: Evidence has emerged across the past few decades that the lifetime risk of developing morbidities like type 2 diabetes, obesity, and cardiovascular disease may be influenced by exposures that occur in utero and in childhood. Developmental abnormalities are known to occur at various stages in fetal growth. Epidemiological and mechanistic studies have sought to delineate developmental processes and plausible risk factors influencing pregnancy outcomes and later health. Whether these observations reflect causal processes or are confounded by genetic and social factors remains unclear, although animal (and some human studies suggest that epigenetic programming events may be involved. Regardless of the causal basis to observations of early-life risk factors and later disease risk, the fact that such associations exist and that they are of a fairly large magnitude justifies further research around this topic. Furthermore, additional information is needed to substantiate public health guidelines on lifestyle behaviors during pregnancy to improve infant health outcomes. Indeed, lifestyle intervention clinical trials in pregnancy are now coming online, where materials and data are being collected that should facilitate understanding of the causal nature of intrauterine exposures related with gestational weight gain, such as elevated maternal blood glucose concentrations. In this review, we provide an overview of these concepts. Keywords: early-life, epigenetic, programming, pregnancy, cardiometabolic

  11. Genetic Programming Applied to Base-Metal Prospectivity Mapping in the Aravalli Province, India

    Science.gov (United States)

    Lewkowski, Christopher; Porwal, Alok; González-Álvarez, Ignacio

    2010-05-01

    Genetic Programming Applied to Base-Metal Prospectivity Mapping in the Aravalli Province, India Mineral prospectivity mapping of an area involves demarcation of potentially mineralized zones based on geologic features associated with the targeted mineral deposits. These features are sometimes directly observable and mapped; more often, their presence is inferred from their responses in various geoscience datasets, which are appropriately processed, generally in a GIS software environment, to derive their spatial proxies, also called predictor maps layers. Most approaches to mineral prospectivity mapping use mathematical models to approximate the relation between predictor map layers and the presence (or absence) of the targeted mineral deposits and to label unique combinations of spatially coincident predictor map layers as mineralized or barren. Essentially, the procedure involves recognizing and distinguishing the patterns of predictor map layers associated with mineralized locations from those associated with barren locations. Machine learning algorithms such as neural networks, support vector machines, and Bayesian classifiers are highly efficient pattern recognizers and classifiers. They are being increasingly applied to mineral prospectivity mapping, within or outside a GIS environment. However, most of these algorithms have a black-box-type implementation, that is, the output of these models do not generate new conceptual geological knowledge about the relative importance of various variables and their mutual relationships. Genetic Programming (GP) is a category of machine learning algorithms that address this problem effectively. In addition to generating the output classification map, GP also generates a set of rules that reveal the mutual relationships of the predictor variables, based on empirical analyses. These rules can be used to validate conceptual knowledge against empirical data, and also reveal new patterns in the data, resulting in new

  12. Disaggregating sorghum yield reductions under warming scenarios exposes narrow genetic diversity in US breeding programs.

    Science.gov (United States)

    Tack, Jesse; Lingenfelser, Jane; Jagadish, S V Krishna

    2017-08-29

    Historical adaptation of sorghum production to arid and semiarid conditions has provided promise regarding its sustained productivity under future warming scenarios. Using Kansas field-trial sorghum data collected from 1985 to 2014 and spanning 408 hybrid cultivars, we show that sorghum productivity under increasing warming scenarios breaks down. Through extensive regression modeling, we identify a temperature threshold of 33 °C, beyond which yields start to decline. We show that this decline is robust across both field-trial and on-farm data. Moderate and higher warming scenarios of 2 °C and 4 °C resulted in roughly 17% and 44% yield reductions, respectively. The average reduction across warming scenarios from 1 to 5 °C is 10% per degree Celsius. Breeding efforts over the last few decades have developed high-yielding cultivars with considerable variability in heat resilience, but even the most tolerant cultivars did not offer much resilience to warming temperatures. This outcome points to two concerns regarding adaption to global warming, the first being that adaptation will not be as simple as producers' switching among currently available cultivars and the second being that there is currently narrow genetic diversity for heat resilience in US breeding programs. Using observed flowering dates and disaggregating heat-stress impacts, both pre- and postflowering stages were identified to be equally important for overall yields. These findings suggest the adaptation potential for sorghum under climate change would be greatly facilitated by introducing wider genetic diversity for heat resilience into ongoing breeding programs, and that there should be additional efforts to improve resilience during the preflowering phase.

  13. Genetic modulation of lipid profiles following lifestyle modification or metformin treatment: the Diabetes Prevention Program.

    Directory of Open Access Journals (Sweden)

    Toni I Pollin

    Full Text Available Weight-loss interventions generally improve lipid profiles and reduce cardiovascular disease risk, but effects are variable and may depend on genetic factors. We performed a genetic association analysis of data from 2,993 participants in the Diabetes Prevention Program to test the hypotheses that a genetic risk score (GRS based on deleterious alleles at 32 lipid-associated single-nucleotide polymorphisms modifies the effects of lifestyle and/or metformin interventions on lipid levels and nuclear magnetic resonance (NMR lipoprotein subfraction size and number. Twenty-three loci previously associated with fasting LDL-C, HDL-C, or triglycerides replicated (P = 0.04-1 × 10(-17. Except for total HDL particles (r = -0.03, P = 0.26, all components of the lipid profile correlated with the GRS (partial |r| = 0.07-0.17, P = 5 × 10(-5-1 10(-19. The GRS was associated with higher baseline-adjusted 1-year LDL cholesterol levels (β = +0.87, SEE ± 0.22 mg/dl/allele, P = 8 × 10(-5, P(interaction = 0.02 in the lifestyle intervention group, but not in the placebo (β = +0.20, SEE ± 0.22 mg/dl/allele, P = 0.35 or metformin (β = -0.03, SEE ± 0.22 mg/dl/allele, P = 0.90; P(interaction = 0.64 groups. Similarly, a higher GRS predicted a greater number of baseline-adjusted small LDL particles at 1 year in the lifestyle intervention arm (β = +0.30, SEE ± 0.012 ln nmol/L/allele, P = 0.01, P(interaction = 0.01 but not in the placebo (β = -0.002, SEE ± 0.008 ln nmol/L/allele, P = 0.74 or metformin (β = +0.013, SEE ± 0.008 nmol/L/allele, P = 0.12; P(interaction = 0.24 groups. Our findings suggest that a high genetic burden confers an adverse lipid profile and predicts attenuated response in LDL-C levels and small LDL particle number to dietary and physical activity interventions aimed at weight loss.

  14. Genetic modulation of lipid profiles following lifestyle modification or metformin treatment: the Diabetes Prevention Program.

    Science.gov (United States)

    Pollin, Toni I; Isakova, Tamara; Jablonski, Kathleen A; de Bakker, Paul I W; Taylor, Andrew; McAteer, Jarred; Pan, Qing; Horton, Edward S; Delahanty, Linda M; Altshuler, David; Shuldiner, Alan R; Goldberg, Ronald B; Florez, Jose C; Franks, Paul W

    2012-01-01

    Weight-loss interventions generally improve lipid profiles and reduce cardiovascular disease risk, but effects are variable and may depend on genetic factors. We performed a genetic association analysis of data from 2,993 participants in the Diabetes Prevention Program to test the hypotheses that a genetic risk score (GRS) based on deleterious alleles at 32 lipid-associated single-nucleotide polymorphisms modifies the effects of lifestyle and/or metformin interventions on lipid levels and nuclear magnetic resonance (NMR) lipoprotein subfraction size and number. Twenty-three loci previously associated with fasting LDL-C, HDL-C, or triglycerides replicated (P = 0.04-1 × 10(-17)). Except for total HDL particles (r = -0.03, P = 0.26), all components of the lipid profile correlated with the GRS (partial |r| = 0.07-0.17, P = 5 × 10(-5)-1 10(-19)). The GRS was associated with higher baseline-adjusted 1-year LDL cholesterol levels (β = +0.87, SEE ± 0.22 mg/dl/allele, P = 8 × 10(-5), P(interaction) = 0.02) in the lifestyle intervention group, but not in the placebo (β = +0.20, SEE ± 0.22 mg/dl/allele, P = 0.35) or metformin (β = -0.03, SEE ± 0.22 mg/dl/allele, P = 0.90; P(interaction) = 0.64) groups. Similarly, a higher GRS predicted a greater number of baseline-adjusted small LDL particles at 1 year in the lifestyle intervention arm (β = +0.30, SEE ± 0.012 ln nmol/L/allele, P = 0.01, P(interaction) = 0.01) but not in the placebo (β = -0.002, SEE ± 0.008 ln nmol/L/allele, P = 0.74) or metformin (β = +0.013, SEE ± 0.008 nmol/L/allele, P = 0.12; P(interaction) = 0.24) groups. Our findings suggest that a high genetic burden confers an adverse lipid profile and predicts attenuated response in LDL-C levels and small LDL particle number to dietary and physical activity interventions aimed at weight loss.

  15. Genetic Modulation of Lipid Profiles following Lifestyle Modification or Metformin Treatment: The Diabetes Prevention Program

    Science.gov (United States)

    Jablonski, Kathleen A.; de Bakker, Paul I. W.; Taylor, Andrew; McAteer, Jarred; Pan, Qing; Horton, Edward S.; Delahanty, Linda M.; Altshuler, David; Shuldiner, Alan R.; Goldberg, Ronald B.; Florez, Jose C.; Bray, George A.; Culbert, Iris W.; Champagne, Catherine M.; Eberhardt, Barbara; Greenway, Frank; Guillory, Fonda G.; Herbert, April A.; Jeffirs, Michael L.; Kennedy, Betty M.; Lovejoy, Jennifer C.; Morris, Laura H.; Melancon, Lee E.; Ryan, Donna; Sanford, Deborah A.; Smith, Kenneth G.; Smith, Lisa L.; Amant, Julia A. St.; Tulley, Richard T.; Vicknair, Paula C.; Williamson, Donald; Zachwieja, Jeffery J.; Polonsky, Kenneth S.; Tobian, Janet; Ehrmann, David; Matulik, Margaret J.; Clark, Bart; Czech, Kirsten; DeSandre, Catherine; Hilbrich, Ruthanne; McNabb, Wylie; Semenske, Ann R.; Caro, Jose F.; Watson, Pamela G.; Goldstein, Barry J.; Smith, Kellie A.; Mendoza, Jewel; Liberoni, Renee; Pepe, Constance; Spandorfer, John; Donahue, Richard P.; Goldberg, Ronald B.; Prineas, Ronald; Rowe, Patricia; Calles, Jeanette; Cassanova-Romero, Paul; Florez, Hermes J.; Giannella, Anna; Kirby, Lascelles; Larreal, Carmen; McLymont, Valerie; Mendez, Jadell; Ojito, Juliet; Perry, Arlette; Saab, Patrice; Haffner, Steven M.; Montez, Maria G.; Lorenzo, Carlos; Martinez, Arlene; Hamman, Richard F.; Nash, Patricia V.; Testaverde, Lisa; Anderson, Denise R.; Ballonoff, Larry B.; Bouffard, Alexis; Calonge, B. Ned; Delve, Lynne; Farago, Martha; Hill, James O.; Hoyer, Shelley R.; Jortberg, Bonnie T.; Lenz, Dione; Miller, Marsha; Price, David W.; Regensteiner, Judith G.; Seagle, Helen; Smith, Carissa M.; Steinke, Sheila C.; VanDorsten, Brent; Horton, Edward S.; Lawton, Kathleen E.; Arky, Ronald A.; Bryant, Marybeth; Burke, Jacqueline P.; Caballero, Enrique; Callaphan, Karen M.; Ganda, Om P.; Franklin, Therese; Jackson, Sharon D.; Jacobsen, Alan M.; Jacobsen, Alan M.; Kula, Lyn M.; Kocal, Margaret; Malloy, Maureen A.; Nicosia, Maryanne; Oldmixon, Cathryn F.; Pan, Jocelyn; Quitingon, Marizel; Rubtchinsky, Stacy; Seely, Ellen W.; Schweizer, Dana; Simonson, Donald; Smith, Fannie; Solomon, Caren G.; Warram, James; Kahn, Steven E.; Montgomery, Brenda K.; Fujimoto, Wilfred; Knopp, Robert H.; Lipkin, Edward W.; Marr, Michelle; Trence, Dace; Kitabchi, Abbas E.; Murphy, Mary E.; Applegate, William B.; Bryer-Ash, Michael; Frieson, Sandra L.; Imseis, Raed; Lambeth, Helen; Lichtermann, Lynne C.; Oktaei, Hooman; Rutledge, Lily M.K.; Sherman, Amy R.; Smith, Clara M.; Soberman, Judith E.; Williams-Cleaves, Beverly; Metzger, Boyd E.; Johnson, Mariana K.; Behrends, Catherine; Cook, Michelle; Fitzgibbon, Marian; Giles, Mimi M.; Heard, Deloris; Johnson, Cheryl K.H.; Larsen, Diane; Lowe, Anne; Lyman, Megan; McPherson, David; Molitch, Mark E.; Pitts, Thomas; Reinhart, Renee; Roston, Susan; Schinleber, Pamela A.; Nathan, David M.; McKitrick, Charles; Turgeon, Heather; Abbott, Kathy; Anderson, Ellen; Bissett, Laurie; Cagliero, Enrico; Florez, Jose C.; Delahanty, Linda; Goldman, Valerie; Poulos, Alexandra; Olefsky, Jerrold M.; Carrion-Petersen, Mary Lou; Barrett-Connor, Elizabeth; Edelman, Steven V.; Henry, Robert R.; Horne, Javiva; Janesch, Simona Szerdi; Leos, Diana; Mudaliar, Sundar; Polonsky, William; Smith, Jean; Vejvoda, Karen; Pi-Sunyer, F. Xavier; Lee, Jane E.; Allison, David B.; Aronoff, Nancy J.; Crandall, Jill P.; Foo, Sandra T.; Pal, Carmen; Parkes, Kathy; Pena, Mary Beth; Rooney, Ellen S.; Wye, Gretchen E.H. Van; Viscovich, Kristine A.; Marrero, David G.; Prince, Melvin J.; Kelly, Susie M.; Dotson, Yolanda F.; Fineberg, Edwin S.; Guare, John C; Hadden, Angela M.; Ignaut, James M.; Jackson, Marcia L.; Kirkman, Marion S.; Mather, Kieren J.; Porter, Beverly D.; Roach, Paris J.; Rowland, Nancy D.; Wheeler, Madelyn L.; Ratner, Robert E.; Youssef, Gretchen; Shapiro, Sue; Bavido-Arrage, Catherine; Boggs, Geraldine; Bronsord, Marjorie; Brown, Ernestine; Cheatham, Wayman W.; Cola, Susan; Evans, Cindy; Gibbs, Peggy; Kellum, Tracy; Levatan, Claresa; Nair, Asha K.; Passaro, Maureen; Uwaifo, Gabriel; Saad, Mohammed F.; Budget, Maria; Jinagouda, Sujata; Akbar, Khan; Conzues, Claudia; Magpuri, Perpetua; Ngo, Kathy; Rassam, Amer; Waters, Debra; Xapthalamous, Kathy; Santiago, Julio V.; Dagogo-Jack, Samuel; White, Neil H.; Das, Samia; Santiago, Ana; Brown, Angela; Fisher, Edwin; Hurt, Emma; Jones, Tracy; Kerr, Michelle; Ryder, Lucy; Wernimont, Cormarie; Saudek, Christopher D.; Bradley, Vanessa; Sullivan, Emily; Whittington, Tracy; Abbas, Caroline; Brancati, Frederick L.; Clark, Jeanne M.; Charleston, Jeanne B.; Freel, Janice; Horak, Katherine; Jiggetts, Dawn; Johnson, Deloris; Joseph, Hope; Loman, Kimberly; Mosley, Henry; Rubin, Richard R.; Samuels, Alafia; Stewart, Kerry J.; Williamson, Paula; Schade, David S.; Adams, Karwyn S.; Johannes, Carolyn; Atler, Leslie F.; Boyle, Patrick J.; Burge, Mark R.; Canady, Janene L.; Chai, Lisa; Gonzales, Ysela; Hernandez-McGinnis, Doris A.; Katz, Patricia; King, Carolyn; Rassam, Amer; Rubinchik, Sofya; Senter, Willette; Waters, Debra; Shamoon, Harry; Brown, Janet O.; Adorno, Elsie; Cox, Liane; Crandall, Jill; Duffy, Helena; Engel, Samuel; Friedler, Allison; Howard-Century, Crystal J.; Kloiber, Stacey; Longchamp, Nadege; Martinez, Helen; Pompi, Dorothy; Scheindlin, Jonathan; Violino, Elissa; Walker, Elizabeth; Wylie-Rosett, Judith; Zimmerman, Elise; Zonszein, Joel; Orchard, Trevor; Wing, Rena R.; Koenning, Gaye; Kramer, M. Kaye; Barr, Susan; Boraz, Miriam; Clifford, Lisa; Culyba, Rebecca; Frazier, Marlene; Gilligan, Ryan; Harrier, Susan; Harris, Louann; Jeffries, Susan; Kriska, Andrea; Manjoo, Qurashia; Mullen, Monica; Noel, Alicia; Otto, Amy; Semler, Linda; Smith, Cheryl F.; Smith, Marie; Venditti, Elizabeth; Weinzierl, Valarie; Williams, Katherine V.; Wilson, Tara; Arakaki, Richard F.; Latimer, Renee W.; Baker-Ladao, Narleen K.; Beddow, Ralph; Dias, Lorna; Inouye, Jillian; Mau, Marjorie K.; Mikami, Kathy; Mohideen, Pharis; Odom, Sharon K.; Perry, Raynette U.; Knowler, William C.; Cooeyate, Norman; Hoskin, Mary A.; Percy, Carol A.; Acton, Kelly J.; Andre, Vickie L.; Barber, Rosalyn; Begay, Shandiin; Bennett, Peter H.; Benson, Mary Beth; Bird, Evelyn C.; Broussard, Brenda A.; Chavez, Marcella; Dacawyma, Tara; Doughty, Matthew S.; Duncan, Roberta; Edgerton, Cyndy; Ghahate, Jacqueline M.; Glass, Justin; Glass, Martia; Gohdes, Dorothy; Grant, Wendy; Hanson, Robert L.; Horse, Ellie; Ingraham, Louise E.; Jackson, Merry; Jay, Priscilla; Kaskalla, Roylen S.; Kessler, David; Kobus, Kathleen M.; Krakoff, Jonathan; Manus, Catherine; Michaels, Sara; Morgan, Tina; Nashboo, Yolanda; Nelson, Julie A.; Poirier, Steven; Polczynski, Evette; Reidy, Mike; Roumain, Jeanine; Rowse, Debra; Sangster, Sandra; Sewenemewa, Janet; Tonemah, Darryl; Wilson, Charlton; Yazzie, Michelle; Bain, Raymond; Fowler, Sarah; Brenneman, Tina; Abebe, Solome; Bamdad, Julie; Callaghan, Jackie; Edelstein, Sharon L.; Gao, Yuping; Grimes, Kristina L.; Grover, Nisha; Haffner, Lori; Jones, Steve; Jones, Tara L.; Katz, Richard; Lachin, John M.; Mucik, Pamela; Orlosky, Robert; Rochon, James; Sapozhnikova, Alla; Sherif, Hanna; Stimpson, Charlotte; Temprosa, Marinella; Walker-Murray, Fredricka; Marcovina, Santica; Strylewicz, Greg; Aldrich, F. Alan; O'Leary, Dan; Stamm, Elizabeth; Rautaharju, Pentti; Prineas, Ronald J.; Alexander, Teresa; Campbell, Charles; Hall, Sharon; Li, Yabing; Mills, Margaret; Pemberton, Nancy; Rautaharju, Farida; Zhang, Zhuming; Mayer-Davis, Elizabeth; Moran, Robert R.; Ganiats, Ted; David, Kristin; Sarkin, Andrew J.; Eastman, R.; Fradkin, Judith; Garfield, Sanford; Gregg, Edward; Zhang, Ping; Herman, William; Florez, Jose C.; Altshuler, David; de Bakker, Paul I.W.; Franks, Paul W.; Hanson, Robert L.; Jablonski, Kathleen; Knowler, William C.; McAteer, Jarred B.; Pollin, Toni I.; Shuldiner, Alan R.

    2012-01-01

    Weight-loss interventions generally improve lipid profiles and reduce cardiovascular disease risk, but effects are variable and may depend on genetic factors. We performed a genetic association analysis of data from 2,993 participants in the Diabetes Prevention Program to test the hypotheses that a genetic risk score (GRS) based on deleterious alleles at 32 lipid-associated single-nucleotide polymorphisms modifies the effects of lifestyle and/or metformin interventions on lipid levels and nuclear magnetic resonance (NMR) lipoprotein subfraction size and number. Twenty-three loci previously associated with fasting LDL-C, HDL-C, or triglycerides replicated (P = 0.04–1×10−17). Except for total HDL particles (r = −0.03, P = 0.26), all components of the lipid profile correlated with the GRS (partial |r| = 0.07–0.17, P = 5×10−5–1×10−19). The GRS was associated with higher baseline-adjusted 1-year LDL cholesterol levels (β = +0.87, SEE±0.22 mg/dl/allele, P = 8×10−5, P interaction = 0.02) in the lifestyle intervention group, but not in the placebo (β = +0.20, SEE±0.22 mg/dl/allele, P = 0.35) or metformin (β = −0.03, SEE±0.22 mg/dl/allele, P = 0.90; P interaction = 0.64) groups. Similarly, a higher GRS predicted a greater number of baseline-adjusted small LDL particles at 1 year in the lifestyle intervention arm (β = +0.30, SEE±0.012 ln nmol/L/allele, P = 0.01, P interaction = 0.01) but not in the placebo (β = −0.002, SEE±0.008 ln nmol/L/allele, P = 0.74) or metformin (β = +0.013, SEE±0.008 nmol/L/allele, P = 0.12; P interaction = 0.24) groups. Our findings suggest that a high genetic burden confers an adverse lipid profile and predicts attenuated response in LDL-C levels and small LDL particle number to dietary and physical activity interventions aimed at weight loss. PMID:22951888

  16. Useful genetic sources of economic importance and their utlization in wheat-breeding programs in Pakistan.

    Science.gov (United States)

    Qureshi, S A

    Wheat breeders the world over have been utilizing genetic sources to tailor the varieties to meet ever-changing requirements. In the late 1940s Dr. Borlaug at CIMMYT recognized that further increase in yield would be possible only if lodging in the existing wheat varieties could be avoided, for which he began to look for a suitable source for dwarfness. The Japanese had developed semidwarf Norin strains through a series of crosses involving a local line, Daruma; American soft red winter variety, Fultz; and American hard red winter variety, Turkey Red. One of the Norin strains, Norin-10, was used in the breeding programs, first in Italy and then in the United States where Dr. Orville Vogel developed two to three semidwarf varieties. In 1953 Dr. Vogel supplied some F2 seeds of Norin-10 Brevor to the CIMMYT program in Mexico, where this source was employed extensively in the breeding rogram; a large number of varieties were developed, some of which worth mentioning are Pitic, Penjamo, Lerma, Sonora, Inia, Tobari, and Siete Cerros.

  17. Effects of genetic variants previously associated with fasting glucose and insulin in the Diabetes Prevention Program.

    Directory of Open Access Journals (Sweden)

    Jose C Florez

    Full Text Available Common genetic variants have been recently associated with fasting glucose and insulin levels in white populations. Whether these associations replicate in pre-diabetes is not known. We extended these findings to the Diabetes Prevention Program, a clinical trial in which participants at high risk for diabetes were randomized to placebo, lifestyle modification or metformin for diabetes prevention. We genotyped previously reported polymorphisms (or their proxies in/near G6PC2, MTNR1B, GCK, DGKB, GCKR, ADCY5, MADD, CRY2, ADRA2A, FADS1, PROX1, SLC2A2, GLIS3, C2CD4B, IGF1, and IRS1 in 3,548 Diabetes Prevention Program participants. We analyzed variants for association with baseline glycemic traits, incident diabetes and their interaction with response to metformin or lifestyle intervention. We replicated associations with fasting glucose at MTNR1B (P<0.001, G6PC2 (P = 0.002 and GCKR (P = 0.001. We noted impaired β-cell function in carriers of glucose-raising alleles at MTNR1B (P<0.001, and an increase in the insulinogenic index for the glucose-raising allele at G6PC2 (P<0.001. The association of MTNR1B with fasting glucose and impaired β-cell function persisted at 1 year despite adjustment for the baseline trait, indicating a sustained deleterious effect at this locus. We also replicated the association of MADD with fasting proinsulin levels (P<0.001. We detected no significant impact of these variants on diabetes incidence or interaction with preventive interventions. The association of several polymorphisms with quantitative glycemic traits is replicated in a cohort of high-risk persons. These variants do not have a detectable impact on diabetes incidence or response to metformin or lifestyle modification in the Diabetes Prevention Program.

  18. Effects of genetic variants previously associated with fasting glucose and insulin in the Diabetes Prevention Program.

    Science.gov (United States)

    Florez, Jose C; Jablonski, Kathleen A; McAteer, Jarred B; Franks, Paul W; Mason, Clinton C; Mather, Kieren; Horton, Edward; Goldberg, Ronald; Dabelea, Dana; Kahn, Steven E; Arakaki, Richard F; Shuldiner, Alan R; Knowler, William C

    2012-01-01

    Common genetic variants have been recently associated with fasting glucose and insulin levels in white populations. Whether these associations replicate in pre-diabetes is not known. We extended these findings to the Diabetes Prevention Program, a clinical trial in which participants at high risk for diabetes were randomized to placebo, lifestyle modification or metformin for diabetes prevention. We genotyped previously reported polymorphisms (or their proxies) in/near G6PC2, MTNR1B, GCK, DGKB, GCKR, ADCY5, MADD, CRY2, ADRA2A, FADS1, PROX1, SLC2A2, GLIS3, C2CD4B, IGF1, and IRS1 in 3,548 Diabetes Prevention Program participants. We analyzed variants for association with baseline glycemic traits, incident diabetes and their interaction with response to metformin or lifestyle intervention. We replicated associations with fasting glucose at MTNR1B (P<0.001), G6PC2 (P = 0.002) and GCKR (P = 0.001). We noted impaired β-cell function in carriers of glucose-raising alleles at MTNR1B (P<0.001), and an increase in the insulinogenic index for the glucose-raising allele at G6PC2 (P<0.001). The association of MTNR1B with fasting glucose and impaired β-cell function persisted at 1 year despite adjustment for the baseline trait, indicating a sustained deleterious effect at this locus. We also replicated the association of MADD with fasting proinsulin levels (P<0.001). We detected no significant impact of these variants on diabetes incidence or interaction with preventive interventions. The association of several polymorphisms with quantitative glycemic traits is replicated in a cohort of high-risk persons. These variants do not have a detectable impact on diabetes incidence or response to metformin or lifestyle modification in the Diabetes Prevention Program.

  19. Functional Genetic Screen to Identify Interneurons Governing Behaviorally Distinct Aspects of Drosophila Larval Motor Programs

    Directory of Open Access Journals (Sweden)

    Matt Q. Clark

    2016-07-01

    Full Text Available Drosophila larval crawling is an attractive system to study rhythmic motor output at the level of animal behavior. Larval crawling consists of waves of muscle contractions generating forward or reverse locomotion. In addition, larvae undergo additional behaviors, including head casts, turning, and feeding. It is likely that some neurons (e.g., motor neurons are used in all these behaviors, but the identity (or even existence of neurons dedicated to specific aspects of behavior is unclear. To identify neurons that regulate specific aspects of larval locomotion, we performed a genetic screen to identify neurons that, when activated, could elicit distinct motor programs. We used 165 Janelia CRM-Gal4 lines—chosen for sparse neuronal expression—to ectopically express the warmth-inducible neuronal activator TrpA1, and screened for locomotor defects. The primary screen measured forward locomotion velocity, and we identified 63 lines that had locomotion velocities significantly slower than controls following TrpA1 activation (28°. A secondary screen was performed on these lines, revealing multiple discrete behavioral phenotypes, including slow forward locomotion, excessive reverse locomotion, excessive turning, excessive feeding, immobile, rigid paralysis, and delayed paralysis. While many of the Gal4 lines had motor, sensory, or muscle expression that may account for some or all of the phenotype, some lines showed specific expression in a sparse pattern of interneurons. Our results show that distinct motor programs utilize distinct subsets of interneurons, and provide an entry point for characterizing interneurons governing different elements of the larval motor program.

  20. Genetic Program Based Data Mining of Fuzzy Decision Trees and Methods of Improving Convergence and Reducing Bloat

    Science.gov (United States)

    2007-04-01

    A data mining procedure for automatic determination of fuzzy decision tree structure using a genetic program (GP) is discussed. A GP is an algorithm...that evolves other algorithms or mathematical expressions. Innovative methods for accelerating convergence of the data mining procedure and reducing...Finally, additional methods that have been used to validate the data mining algorithm are referenced.

  1. System network planning expansion using mathematical programming, genetic algorithms and tabu search

    Energy Technology Data Exchange (ETDEWEB)

    Sadegheih, A. [Department of Industrial Engineering, University of Yazd, P.O. Box 89195-741, Yazd (Iran); Drake, P.R. [E-Business and Operations Management Division, University of Liverpool Management School, University of Liverpool, Liverpool (United Kingdom)

    2008-06-15

    In this paper, system network planning expansion is formulated for mixed integer programming, a genetic algorithm (GA) and tabu search (TS). Compared with other optimization methods, GAs are suitable for traversing large search spaces, since they can do this relatively rapidly and because the use of mutation diverts the method away from local minima, which will tend to become more common as the search space increases in size. GA's give an excellent trade off between solution quality and computing time and flexibility for taking into account specific constraints in real situations. TS has emerged as a new, highly efficient, search paradigm for finding quality solutions to combinatorial problems. It is characterized by gathering knowledge during the search and subsequently profiting from this knowledge. The attractiveness of the technique comes from its ability to escape local optimality. The cost function of this problem consists of the capital investment cost in discrete form, the cost of transmission losses and the power generation costs. The DC load flow equations for the network are embedded in the constraints of the mathematical model to avoid sub-optimal solutions that can arise if the enforcement of such constraints is done in an indirect way. The solution of the model gives the best line additions and also provides information regarding the optimal generation at each generation point. This method of solution is demonstrated on the expansion of a 10 bus bar system to 18 bus bars. Finally, a steady-state genetic algorithm is employed rather than generational replacement, also uniform crossover is used. (author)

  2. Automatic Generation of English-Japanese Translation Pattern Utilizing Genetic Programming Technique

    Science.gov (United States)

    Matsumura, Koki; Tamekuni, Yuji; Kimura, Shuhei

    There are a lot of constructional differences in an English-Japanese phrase template, and that often makes the act of translation difficult. Moreover, there exist various and tremendous phrase templates and sentence to be refered to. It is not easy to prepare the corpus that covers the all. Therefore, it is very significant to generate the translation pattern of the sentence pattern automatically from a viewpoint of the translation success rate and the capacity of the pattern dictionary. Then, for the purpose of realizing the automatic generation of the translation pattern, this paper proposed the new method for the generation of the translation pattern by using the genetic programming technique (GP). The technique tries to generate the translation pattern of various sentences which are not registered in the phrase template dictionary automatically by giving the genetic operation to the parsing tree of a basic pattern. The tree consists of the pair of the English-Japanese sentence generated as the first stage population. The analysis tree data base with 50,100,150,200 pairs was prepared as the first stage population. And this system was applied and executed for an English input of 1,555 sentences. As a result, the analysis tree increases from 200 to 517, and the accuracy rate of the translation pattern has improved from 42.57% to 70.10%. And, 86.71% of the generated translations was successfully done, whose meanings are enough acceptable and understandable. It seemed that this proposal technique became a clue to raise the translation success rate, and to find the possibility of the reduction of the analysis tree data base.

  3. Hierarchical On-line Scheduling of Multiproduct Batch Plants with a Combined Approach of Mathematical Programming and Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    陈理; 王克峰; 徐霄羽; 姚平经

    2004-01-01

    In this contribution we present an online scheduling algorithm for a real world multiproduct batch plant. The overall mixed integer nonlinear programming (MINLP) problem is hierarchically structured into a mixed integer linear programming (MILP) problem first and then a reduced dimensional MINLP problem, which are optimized by mathematical programming (MP) and genetic algorithm (GA) respectively. The basis idea relies on combining MP with GA to exploit their complementary capacity. The key features of the hierarchical model are explained and illustrated with some real world cases from the multiproduct batch plants.

  4. Heterozygosities and genetic relationship of tea cultivars revealed by simple sequence repeat markers and implications for breeding and genetic mapping programs.

    Science.gov (United States)

    Tan, L Q; Zhang, C C; Qi, G N; Wang, L Y; Wei, K; Chen, S X; Zou, Y; Wu, L Y; Cheng, H

    2015-03-06

    Genetic maps are essential tools for quantitative trait locus analysis and marker-assisted selection breeding. In order to select parents that are highly heterozygous for genetic mapping, the heterozygosity (HS) of 24 tea cultivars (Camellia sinensis) was analyzed with 72 simple sequence repeat markers. In total, 359 alleles were obtained with an average of 4.99 per marker. The HS varied greatly from 37.5 to 71.0% with an average of 51.3%. On average, tea cultivars from Fujian Province showed a higher level of heterozygosity (59.8%) than those from Zhejiang (48.5%) and Yunnan (44.5%), and the 12 national tea cultivars were generally more heterozygous than the 12 provincial cultivars. Unweighted pair-group analysis using the arithmetic average grouping divided the 24 cultivars into 2 groups that are consistent with the morphological classification. All dual combinations of the 24 cultivars were studied to calculate the percentage of mappable markers when using pseudo-testcross mapping strategy, and results showed that this value also varied greatly from 51.4 to 90.3%. The genetic relationships and HS differences among different cultivars were discussed, and tea cultivars with high HS were recommended as cross parents for genetic mapping programs.

  5. Automatic Compilation from High-Level Biologically-Oriented Programming Language to Genetic Regulatory Networks

    Science.gov (United States)

    Beal, Jacob; Lu, Ting; Weiss, Ron

    2011-01-01

    Background The field of synthetic biology promises to revolutionize our ability to engineer biological systems, providing important benefits for a variety of applications. Recent advances in DNA synthesis and automated DNA assembly technologies suggest that it is now possible to construct synthetic systems of significant complexity. However, while a variety of novel genetic devices and small engineered gene networks have been successfully demonstrated, the regulatory complexity of synthetic systems that have been reported recently has somewhat plateaued due to a variety of factors, including the complexity of biology itself and the lag in our ability to design and optimize sophisticated biological circuitry. Methodology/Principal Findings To address the gap between DNA synthesis and circuit design capabilities, we present a platform that enables synthetic biologists to express desired behavior using a convenient high-level biologically-oriented programming language, Proto. The high level specification is compiled, using a regulatory motif based mechanism, to a gene network, optimized, and then converted to a computational simulation for numerical verification. Through several example programs we illustrate the automated process of biological system design with our platform, and show that our compiler optimizations can yield significant reductions in the number of genes () and latency of the optimized engineered gene networks. Conclusions/Significance Our platform provides a convenient and accessible tool for the automated design of sophisticated synthetic biological systems, bridging an important gap between DNA synthesis and circuit design capabilities. Our platform is user-friendly and features biologically relevant compiler optimizations, providing an important foundation for the development of sophisticated biological systems. PMID:21850228

  6. Semantic Search-Based Genetic Programming and the Effect of Intron Deletion.

    Science.gov (United States)

    Castelli, Mauro; Vanneschi, Leonardo; Silva, Sara

    2014-01-01

    The concept of semantics (in the sense of input-output behavior of solutions on training data) has been the subject of a noteworthy interest in the genetic programming (GP) research community over the past few years. In this paper, we present a new GP system that uses the concept of semantics to improve search effectiveness. It maintains a distribution of different semantic behaviors and biases the search toward solutions that have similar semantics to the best solutions that have been found so far. We present experimental evidence of the fact that the new semantics-based GP system outperforms the standard GP and the well-known bacterial GP on a set of test functions, showing particularly interesting results for noncontinuous (i.e., generally harder to optimize) test functions. We also observe that the solutions generated by the proposed GP system often have a larger size than the ones returned by standard GP and bacterial GP and contain an elevated number of introns, i.e., parts of code that do not have any effect on the semantics. Nevertheless, we show that the deletion of introns during the evolution does not affect the performance of the proposed method.

  7. Genetic and epigenetic catalysts in early-life programming of adult cardiometabolic disorders.

    Science.gov (United States)

    Estampador, Angela C; Franks, Paul W

    2014-01-01

    Evidence has emerged across the past few decades that the lifetime risk of developing morbidities like type 2 diabetes, obesity, and cardiovascular disease may be influenced by exposures that occur in utero and in childhood. Developmental abnormalities are known to occur at various stages in fetal growth. Epidemiological and mechanistic studies have sought to delineate developmental processes and plausible risk factors influencing pregnancy outcomes and later health. Whether these observations reflect causal processes or are confounded by genetic and social factors remains unclear, although animal (and some human) studies suggest that epigenetic programming events may be involved. Regardless of the causal basis to observations of early-life risk factors and later disease risk, the fact that such associations exist and that they are of a fairly large magnitude justifies further research around this topic. Furthermore, additional information is needed to substantiate public health guidelines on lifestyle behaviors during pregnancy to improve infant health outcomes. Indeed, lifestyle intervention clinical trials in pregnancy are now coming online, where materials and data are being collected that should facilitate understanding of the causal nature of intrauterine exposures related with gestational weight gain, such as elevated maternal blood glucose concentrations. In this review, we provide an overview of these concepts.

  8. Application of genetic programming in shape optimization of concrete gravity dams by metaheuristics

    Directory of Open Access Journals (Sweden)

    Abdolhossein Baghlani

    2014-12-01

    Full Text Available A gravity dam maintains its stability against the external loads by its massive size. Hence, minimization of the weight of the dam can remarkably reduce the construction costs. In this paper, a procedure for finding optimal shape of concrete gravity dams with a computationally efficient approach is introduced. Genetic programming (GP in conjunction with metaheuristics is used for this purpose. As a case study, shape optimization of the Bluestone dam is presented. Pseudo-dynamic analysis is carried out on a total number of 322 models in order to establish a database of the results. This database is then used to find appropriate relations based on GP for design criteria of the dam. This procedure eliminates the necessity of the time-consuming process of structural analyses in evolutionary optimization methods. The method is hybridized with three different metaheuristics, including particle swarm optimization, firefly algorithm (FA, and teaching–learning-based optimization, and a comparison is made. The results show that although all algorithms are very suitable, FA is slightly superior to other two algorithms in finding a lighter structure in less number of iterations. The proposed method reduces the weight of dam up to 14.6% with very low computational effort.

  9. Genetic Programming for the Downscaling of Extreme Rainfall Events on the East Coast of Peninsular Malaysia

    Directory of Open Access Journals (Sweden)

    Sahar Hadi Pour

    2014-11-01

    Full Text Available A genetic programming (GP-based logistic regression method is proposed in the present study for the downscaling of extreme rainfall indices on the east coast of Peninsular Malaysia, which is considered one of the zones in Malaysia most vulnerable to climate change. A National Centre for Environmental Prediction reanalysis dataset at 42 grid points surrounding the study area was used to select the predictors. GP models were developed for the downscaling of three extreme rainfall indices: days with larger than or equal to the 90th percentile of rainfall during the north-east monsoon; consecutive wet days; and consecutive dry days in a year. Daily rainfall data for the time periods 1961–1990 and 1991–2000 were used for the calibration and validation of models, respectively. The results are compared with those obtained using the multilayer perceptron neural network (ANN and linear regression-based statistical downscaling model (SDSM. It was found that models derived using GP can predict both annual and seasonal extreme rainfall indices more accurately compared to ANN and SDSM.

  10. Evolving Software Effort Estimation Models Using Multigene Symbolic Regression Genetic Programming

    Directory of Open Access Journals (Sweden)

    Sultan Aljahdali

    2013-12-01

    Full Text Available Software has played an essential role in engineering, economic development, stock market growth and military applications. Mature software industry count on highly predictive software effort estimation models. Correct estimation of software effort lead to correct estimation of budget and development time. It also allows companies to develop appropriate time plan for marketing campaign. Now a day it became a great challenge to get these estimates due to the increasing number of attributes which affect the software development life cycle. Software cost estimation models should be able to provide sufficient confidence on its prediction capabilities. Recently, Computational Intelligence (CI paradigms were explored to handle the software effort estimation problem with promising results. In this paper we evolve two new models for software effort estimation using Multigene Symbolic Regression Genetic Programming (GP. One model utilizes the Source Line Of Code (SLOC as input variable to estimate the Effort (E; while the second model utilize the Inputs, Outputs, Files, and User Inquiries to estimate the Function Point (FP. The proposed GP models show better estimation capabilities compared to other reported models in the literature. The validation results are accepted based Albrecht data set.

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

    Science.gov (United States)

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

    2009-01-01

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

  12. Discovering link communities in complex networks by an integer programming model and a genetic algorithm.

    Science.gov (United States)

    Li, Zhenping; Zhang, Xiang-Sun; Wang, Rui-Sheng; Liu, Hongwei; Zhang, Shihua

    2013-01-01

    Identification of communities in complex networks is an important topic and issue in many fields such as sociology, biology, and computer science. Communities are often defined as groups of related nodes or links that correspond to functional subunits in the corresponding complex systems. While most conventional approaches have focused on discovering communities of nodes, some recent studies start partitioning links to find overlapping communities straightforwardly. In this paper, we propose a new quantity function for link community identification in complex networks. Based on this quantity function we formulate the link community partition problem into an integer programming model which allows us to partition a complex network into overlapping communities. We further propose a genetic algorithm for link community detection which can partition a network into overlapping communities without knowing the number of communities. We test our model and algorithm on both artificial networks and real-world networks. The results demonstrate that the model and algorithm are efficient in detecting overlapping community structure in complex networks.

  13. Genetic programming-based approach to elucidate biochemical interaction networks from data.

    Science.gov (United States)

    Kandpal, Manoj; Kalyan, Chakravarthy Mynampati; Samavedham, Lakshminarayanan

    2013-02-01

    Biochemical systems are characterised by cyclic/reversible reciprocal actions, non-linear interactions and a mixed relationship structures (linear and non-linear; static and dynamic). Deciphering the architecture of such systems using measured data to provide quantitative information regarding the nature of relationships that exist between the measured variables is a challenging proposition. Causality detection is one of the methodologies that are applied to elucidate biochemical networks from such data. Autoregressive-based modelling approach such as granger causality, partial directed coherence, directed transfer function and canonical variate analysis have been applied on different systems for deciphering such interactions, but with limited success. In this study, the authors propose a genetic programming-based causality detection (GPCD) methodology which blends evolutionary computation-based procedures along with parameter estimation methods to derive a mathematical model of the system. Application of the GPCD methodology on five data sets that contained the different challenges mentioned above indicated that GPCD performs better than the other methods in uncovering the exact structure with less false positives. On a glycolysis data set, GPCD was able to fill the 'interaction gaps' which were missed by other methods.

  14. Elevator Group Supervisory Control System Using Genetic Network Programming with Macro Nodes and Reinforcement Learning

    Science.gov (United States)

    Zhou, Jin; Yu, Lu; Mabu, Shingo; Hirasawa, Kotaro; Hu, Jinglu; Markon, Sandor

    Elevator Group Supervisory Control System (EGSCS) is a very large scale stochastic dynamic optimization problem. Due to its vast state space, significant uncertainty and numerous resource constraints such as finite car capacities and registered hall/car calls, it is hard to manage EGSCS using conventional control methods. Recently, many solutions for EGSCS using Artificial Intelligence (AI) technologies have been reported. Genetic Network Programming (GNP), which is proposed as a new evolutionary computation method several years ago, is also proved to be efficient when applied to EGSCS problem. In this paper, we propose an extended algorithm for EGSCS by introducing Reinforcement Learning (RL) into GNP framework, and an improvement of the EGSCS' performances is expected since the efficiency of GNP with RL has been clarified in some other studies like tile-world problem. Simulation tests using traffic flows in a typical office building have been made, and the results show an actual improvement of the EGSCS' performances comparing to the algorithms using original GNP and conventional control methods. Furthermore, as a further study, an importance weight optimization algorithm is employed based on GNP with RL and its efficiency is also verified with the better performances.

  15. Soil temperature modeling at different depths using neuro-fuzzy, neural network, and genetic programming techniques

    Science.gov (United States)

    Kisi, Ozgur; Sanikhani, Hadi; Cobaner, Murat

    2016-05-01

    The applicability of artificial neural networks (ANN), adaptive neuro-fuzzy inference system (ANFIS), and genetic programming (GP) techniques in estimating soil temperatures (ST) at different depths is investigated in this study. Weather data from two stations, Mersin and Adana, Turkey, were used as inputs to the applied models in order to model monthly STs. The first part of the study focused on comparison of ANN, ANFIS, and GP models in modeling ST of two stations at the depths of 10, 50, and 100 cm. GP was found to perform better than the ANN and ANFIS-SC in estimating monthly ST. The effect of periodicity (month of the year) on models' accuracy was also investigated. Including periodicity component in models' inputs considerably increased their accuracies. The root mean square error (RMSE) of ANN models was respectively decreased by 34 and 27 % for the depths of 10 and 100 cm adding the periodicity input. In the second part of the study, the accuracies of the ANN, ANFIS, and GP models were compared in estimating ST of Mersin Station using the climatic data of Adana Station. The ANN models generally performed better than the ANFIS-SC and GP in modeling ST of Mersin Station without local climatic inputs.

  16. Object detection via feature synthesis using MDL-based genetic programming.

    Science.gov (United States)

    Lin, Yingqiang; Bhanu, Bir

    2005-06-01

    In this paper, we use genetic programming (GP) to synthesize composite operators and composite features from combinations of primitive operations and primitive features for object detection. The motivation for using GP is to overcome the human experts' limitations of focusing only on conventional combinations of primitive image processing operations in the feature synthesis. GP attempts many unconventional combinations that in some cases yield exceptionally good results. To improve the efficiency of GP and prevent its well-known code bloat problem without imposing severe restriction on the GP search, we design a new fitness function based on minimum description length principle to incorporate both the pixel labeling error and the size of a composite operator into the fitness evaluation process. To further improve the efficiency of GP, smart crossover, smart mutation and a public library ideas are incorporated to identify and keep the effective components of composite operators. Our experiments, which are performed on selected training regions of a training image to reduce the training time, show that compared to normal GP, our GP algorithm finds effective composite operators more quickly and the learned composite operators can be applied to the whole training image and other similar testing images. Also, compared to a traditional region-of-interest extraction algorithm, the composite operators learned by GP are more effective and efficient for object detection.

  17. Genetic Algorithm Combination of Boolean Constraint Programming for Solving Course of Action Optimization in Influence Nets

    Directory of Open Access Journals (Sweden)

    Yanguang Zhu

    2011-06-01

    Full Text Available A military decision maker is typically confronted by the task of determining optimal course of action under some constraints in complex uncertain situation. Thus, a new class of Combinational Constraint Optimization Problem (CCOP is formalized, that is utilized to solve this complex Operation Optimization Problem. The object function of CCOP is modeled by Influence net, and the constraints of CCOP relate to resource and collaboration. These constraints are expressed by Pseudo-Boolean and Boolean constraints. Thus CCOP holds a complex mathematical configuration, which is expressed as a 0 1 integer optimization problem with compositional constraints and unobvious optimal object function. A novel method of Genetic Algorithm (GA combination of Boolean Constraint Programming (BCP is proposed to solve CCOP. The constraints of CCOP can be easily reduced and transformed into Disjunctive Normal Form (DNF by BCP. The DNF representation then can be used to drive GA so as to solve CCOP. Finally, a numerical experiment is given to demonstrate the effectiveness of above method.

  18. Soil temperature modeling at different depths using neuro-fuzzy, neural network, and genetic programming techniques

    Science.gov (United States)

    Kisi, Ozgur; Sanikhani, Hadi; Cobaner, Murat

    2017-08-01

    The applicability of artificial neural networks (ANN), adaptive neuro-fuzzy inference system (ANFIS), and genetic programming (GP) techniques in estimating soil temperatures (ST) at different depths is investigated in this study. Weather data from two stations, Mersin and Adana, Turkey, were used as inputs to the applied models in order to model monthly STs. The first part of the study focused on comparison of ANN, ANFIS, and GP models in modeling ST of two stations at the depths of 10, 50, and 100 cm. GP was found to perform better than the ANN and ANFIS-SC in estimating monthly ST. The effect of periodicity (month of the year) on models' accuracy was also investigated. Including periodicity component in models' inputs considerably increased their accuracies. The root mean square error (RMSE) of ANN models was respectively decreased by 34 and 27 % for the depths of 10 and 100 cm adding the periodicity input. In the second part of the study, the accuracies of the ANN, ANFIS, and GP models were compared in estimating ST of Mersin Station using the climatic data of Adana Station. The ANN models generally performed better than the ANFIS-SC and GP in modeling ST of Mersin Station without local climatic inputs.

  19. Real Time Wave Forecasting Using Wind Time History and Genetic Programming

    Directory of Open Access Journals (Sweden)

    A.R. Kambekar

    2014-12-01

    Full Text Available The significant wave height and average wave period form an essential input for operational activities in ocean and coastal areas. Such information is important in issuing appropriate warnings to people planning any construction or instillation works in the oceanic environment. Many countries over the world routinely collect wave and wind data through a network of wave rider buoys. The data collecting agencies transmit the resulting information online to their registered users through an internet or a web-based system. Operational wave forecasts in addition to the measured data are also made and supplied online to the users. This paper discusses operational wave forecasting in real time mode at locations where wind rather than wave data are continuously recorded. It is based on the time series modeling and incorporates an artificial intelligence technique of genetic programming. The significant wave height and average wave period values are forecasted over a period of 96 hr in future from the observations of wind speed and directions extending to a similar time scale in the past. Wind measurements made by floating buoys at eight different locations around India over a period varying from 1.5 yr to 9.0 yr were considered. The platform of Matlab and C++ was used to develop a graphical user interface that will extend an internet based user-friendly access of the forecasts to any registered user of the data dissemination authority.

  20. Improving probabilistic flood forecasting through a data assimilation scheme based on genetic programming

    Directory of Open Access Journals (Sweden)

    L. Mediero

    2012-12-01

    Full Text Available Opportunities offered by high performance computing provide a significant degree of promise in the enhancement of the performance of real-time flood forecasting systems. In this paper, a real-time framework for probabilistic flood forecasting through data assimilation is presented. The distributed rainfall-runoff real-time interactive basin simulator (RIBS model is selected to simulate the hydrological process in the basin. Although the RIBS model is deterministic, it is run in a probabilistic way through the results of calibration developed in a previous work performed by the authors that identifies the probability distribution functions that best characterise the most relevant model parameters. Adaptive techniques improve the result of flood forecasts because the model can be adapted to observations in real time as new information is available. The new adaptive forecast model based on genetic programming as a data assimilation technique is compared with the previously developed flood forecast model based on the calibration results. Both models are probabilistic as they generate an ensemble of hydrographs, taking the different uncertainties inherent in any forecast process into account. The Manzanares River basin was selected as a case study, with the process being computationally intensive as it requires simulation of many replicas of the ensemble in real time.

  1. Genetic characterization of physical activity behaviours in university students enrolled in kinesiology degree programs.

    Science.gov (United States)

    Many, Gina M; Kendrick, Zachary; Deschamps, Chelsea L; Sprouse, Courtney; Tosi, Laura L; Devaney, Joseph M; Gordish-Dressman, Heather; Barfield, Whitney; Hoffman, Eric P; Houmard, Joseph A; Pescatello, Linda S; Vogel, Hans J; Shearer, Jane; Hittel, Dustin S

    2017-03-01

    Studies of physical activity behaviours have increasingly shown the importance of heritable factors such as genetic variation. Nonsynonymous polymorphisms of alpha-actinin 3 (ACTN3) and the β-adrenergic receptors 1 and 3 (ADRB1 and ADRB3) have been previously associated with exercise capacity and cardiometabolic health. We thus hypothesized that these polymorphisms are also related to physical activity behaviours in young adults. To test this hypothesis we examined relationships between ACTN3 (R577X), ARDB1 (Arg389Gly), ADRB3 (Trp64Arg), and physical activity behaviours in university students. We stratified for student enrollment in kinesiology degree programs compared with nonmajors as we previously found this to be a predictor of physical activity. We did not identify novel associations between physical activity and ACTN3. However, the minor alleles of ADRB1 and ADRB3 were significantly underrepresented in kinesiology students compared with nonmajors. Furthermore, carriers of the ADRB1 minor allele reported reduced participation in moderate physical activity and increased afternoon fatigue compared with ancestral allele homozygotes. Together, these findings suggest that the heritability of physical activity behaviours in young adults may be linked to nonsynonymous polymorphisms within β-adrenergic receptors.

  2. Designing A Nonlinear Integer Programming Model For A Cross-Dock By A Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Bahareh Vaisi

    2015-03-01

    Full Text Available Abstract This paper presents a non-linear integer programming model for a cross-dock problem that considers the total transportation cost of inbound and outbound trucks from an origin to a destination and the total cost of assigning strip and stack doors to trucks based on their number of trips and the distance between doors in cross-dock. In previous studies these two cost-based problems are modeled separately however it is more realistic and practical to use both of them as an integrated cross-docking model. Additionally this model is solved for a randomly generated numerical example with three suppliers and two customers by the use of a genetic algorithm. By comparing two different parameter levels i.e. low and high numbers of populations the optimum solution is obtained considering a high level population size. A number of strip and stack doors are equal to a number of inbound and outbound trucks in the same sequence as 4 and 6 respectively. Finally the conclusion is presented.

  3. Closed-loop separation control over a sharp edge ramp using Genetic Programming

    CERN Document Server

    Debien, Antoine; Mazellier, Nicolas; Duriez, Thomas; Cordier, Laurent; Noack, Bernd R; Abel, Markus W; Kourta, Azeddine

    2015-01-01

    We experimentally perform open and closed-loop control of a separating turbulent boundary layer downstream from a sharp edge ramp. The turbulent boundary layer just above the separation point has a Reynolds number $Re_{\\theta}\\approx 3\\,500$ based on momentum thickness. The goal of the control is to mitigate separation and early re-attachment. The forcing employs a spanwise array of active vortex generators. The flow state is monitored with skin-friction sensors downstream of the actuators. The feedback control law is obtained using model-free genetic programming control (GPC) (Gautier et al. 2015). The resulting flow is assessed using the momentum coefficient, pressure distribution and skin friction over the ramp and stereo PIV. The PIV yields vector field statistics, e.g. shear layer growth, the backflow area and vortex region. GPC is benchmarked against the best periodic forcing. While open-loop control achieves separation reduction by locking-on the shedding mode, GPC gives rise to similar benefits by acc...

  4. Premarital Screening and Genetic Counseling program: knowledge, attitude, and satisfaction of attendees of governmental outpatient clinics in Jeddah.

    Science.gov (United States)

    Ibrahim, Nahla Khamis; Bashawri, Jamel; Al Bar, Hussein; Al Ahmadi, Jawaher; Al Bar, Adnan; Qadi, Mahdi; Milaat, Waleed; Feda, Hashim

    2013-02-01

    Premarital care (PMC) is a worldwide activity that aims to diagnose and treat unrecognized disorders and reduce the transmission of diseases to couples and children. To assess the knowledge and attitude of individuals attending governmental outpatient clinics regarding the Premarital Screening and Genetic Counseling (PMSGC) programs, to identify predictors of high knowledge scores and to determine the satisfaction and recommendations of clients of the program. A cross-sectional study was conducted from January to April 2009. Individuals who attended three governmental hospital outpatient clinics on the day of the interview and agreed to participate in the study were recruited. The three hospitals were the two hospitals in Jeddah that offer the PMSGC programs and the King Abdulaziz University Hospital. Ethical considerations were followed and data were collected through an interview questionnaire that had been constructed for the study. The questionnaire asked for personal and socio-demographic data and for responses, on a 5-point Likert scale, to 30 knowledge items and 14 attitude statements. Individuals who participated in the PMSGC program were asked questions regarding the services and activities of the program to ascertain their satisfaction with the program and their recommendations for program improvement. The statistical analysis was performed using SPSS version 16 (SPSS Inc., Chicago, IL). The sample included 655 participants, of whom 38.8% completed the PMSGC program. The participants' knowledge about the program was generally low. Education was the first predictor of a high knowledge score; individuals having ≥ university degree obtained a higher score (aOR=2.73; 95% CI: 1.77-4.20). The second predictor was the nationality of the participants, with Saudis gaining a higher score (aOR=2.04; 95% CI: 1.002-4.16). The third predictor was monthly income. Regarding attitudes, the vast majority of participants (96.0%) strongly agreed on the importance of the

  5. Mass Releases of Genetically Modified Insects in Area-Wide Pest Control Programs and Their Impact on Organic Farmers

    Directory of Open Access Journals (Sweden)

    R. Guy Reeves

    2017-01-01

    Full Text Available The mass release of irradiated insects to reduce the size of agricultural pest populations of the same species has a more than 50-year record of success. Using these techniques, insect pests can be suppressed without necessarily dispersing chemical insecticides into the environment. Ongoing release programs include the suppression of medfly at numerous locations around the globe (e.g., California, Chile and Israel and the pink bollworm eradication program across the southern USA and northern Mexico. These, and other successful area-wide programs, encompass a large number of diverse organic farms without incident. More recently, mass release techniques have been proposed that involve the release of genetically modified insects. Given that the intentional use of genetically modified organisms by farmers will in many jurisdictions preclude organic certification, this prohibits the deliberate use of this technology by organic farmers. However, mass releases of flying insects are not generally conducted by individual farmers but are done on a regional basis, often without the explicit consent of all situated farms (frequently under the auspices of government agencies or growers’ collectives. Consequently, there exists the realistic prospect of organic farms becoming involved in genetically modified insect releases as part of area-wide programs or experiments. Herein, we describe genetically modified insects engineered for mass release and examine their potential impacts on organic farmers, both intended and unintended. This is done both generally and also focusing on a hypothetical organic farm located near an approved experimental release of genetically modified (GM diamondback moths in New York State (USA.

  6. The U.S. National Sheep Improvement Program: across-flock genetic evaluations and new trait development.

    Science.gov (United States)

    Notter, D R

    1998-09-01

    The U.S. National Sheep Improvement Program (NSIP) began in 1987 to provide within-flock genetic evaluations for the American sheep industry. An evaluation of operating procedures and methodology for NSIP began in 1993 and has resulted in across-flock, multiple-trait EPD for three breeds: Targhee, Suffolk, and Polypay. Traits reported in the across-flock analyses included direct and maternal effects on weaning weight in all breeds, postweaning weight at 120 d in Suffolk and Polypay and at 365 d in Targhee, greasy fleece weight in Targhee and Polypay, and wool fiber diameter in Targhee. Number born per ewe lambing was also evaluated in single-trait analyses for all breeds. Genetic parameters were derived separately for each breed. Important genetic antagonisms include an unfavorable genetic correlation of .51 between fleece weight and fiber diameter in Targhee and a genetic correlation of -.55 between direct and maternal effects on weaning weight in Polypay. Estimates of genetic trends between 1987 and 1995 were consistent with perceived breed roles. In Targhee, direct and maternal effects on body weights increased, fiber diameter declined, fleece weight was maintained, and number born declined. In Suffolk, direct effects on body weight increased, but number born and maternal effects on weaning weight did not change. In Polypay, number born and maternal contributions to weaning weight increased, but direct genetic merit for body weight declined. Prospective enhancements to NSIP include methods for genetic evaluation of performance in accelerated lambing and of carcass leanness and development of breeding objectives and selection aids for various production systems.

  7. Genetic differences between wild and hatchery populations of Diplodus sargus and D. vulgaris inferred from RAPD markers: implications for production and restocking programs design.

    Science.gov (United States)

    Pereira, J C; Lino, P G; Leitão, A; Joaquim, S; Chaves, R; Pousão-Ferreira, P; Guedes-Pinto, H; dos Santos, M Neves

    2010-01-01

    Restocking and stock enhancement programs are now recognized as an important tool for the management of fishery resources. It is important, however, to have an adequate knowledge on the genetic population structure of both the released stock and the wild population before carrying out such programs. In this study, random amplified polymorphic DNA (RAPD) markers were applied to assess genetic diversity and population structure of wild and hatchery populations of the white seabream Diplodus sargus and the common two-banded seabream D. vulgaris (Sparidae). The estimated values for intrapopulation genetic variation, measured using the percentage of polymorphic loci (%P), Shannon index (H'), and Nei's gene diversity (h), showed high values for all populations. The percentage of genetic variation within D. sargus and D. vulgaris populations, based on coefficient of gene differentiation, reached 82.5% and 90% of the total genetic variation, respectively. An undeniable decrease in genetic variation was found in both hatchery populations, particularly in D. sargus, compared to the wild ones. However, the high values of variation within all populations and the low levels of genetic variation among populations did not indicate inbreeding or depression effects, thus indicating a fairly proper hatchery management. Nevertheless, the results of this study highlight the importance of monitoring the genetic variation of hatchery populations, particularly those to be used in restocking programs. The creation of a genetic baseline database will contribute to a more efficient conservation management and to the design of genetically sustainable restocking programs.

  8. Pedigree analysis: One teaching strategy to incorporate genetics into a full FNP program.

    Science.gov (United States)

    Schumacher, Gretchen; Conway, Alice E; Sparlin, Judith A

    2006-05-01

    The successful completion of the genome project in April 2003 and explosion of genetic knowledge is impacting healthcare at a dramatic rate. All healthcare providers need to update themselves on genetics in order to provide comprehensive care. This article describes a national grant obtained to educate faculty regarding incorporating genetics into courses. It also presents an innovate method for incorporating genetics into a full Family Nurse Practitioner (FNP) curriculum. Student responses and guidelines for one assignment are included. Utilizing this type of assignment in FNP courses is beneficial to both students and faculty. With more FNPs assessing patterns for illness in families, primary prevention and earlier intervention in primary care can be achieved.

  9. Genetic programming approach on evaporation losses and its effect on climate change for Vaipar Basin

    Directory of Open Access Journals (Sweden)

    K.S.Kasiviswanathan

    2011-09-01

    Full Text Available Climate change is the major problem that every human being is facing over the world. The rise in fossil fuel usage increases the emission of `greenhouse' gases, particularly carbon dioxide continuously into the earth's atmosphere. This causes a rise in the amount of heat from the sun withheld in the earth's atmosphere that would normally radiated back into space. This increase in heat has led to the greenhouse effect, resulting in climate change and rise in temperature along with other climatological parameters directly affects evaporation losses. Accurate modelling and forecasting of these evaporation losses are important for preventing further effects due to climate change. Evaporation is purely non-linear and varying both spatially and temporally. This needs suitable data driven approach to model and should have the ability to take care of all these non-linear behaviour of the system. As such, though there are many empirical and analytical models suggested in the literature for the estimation of evaporation losses, such models should be used with care and caution. Further, difficulties arise in obtaining all the climatological data used in a given analytical or empirical model. Genetic programming (GP is one such technique applied where the non-linearity exist. GP has the flexible mathematical structure which is capable of identifying the non-linear relationship between input and output data sets. Thus, it is easy to construct 'local' models for estimating evaporation losses. The performance of GP model is compared with Thornthwaite method, and results from the study indicate that the GP model performed better than the Thornthwaite method. Forecasting of meteorological parameters such as temperature, relative humidity and wind velocity has been performed using Markovian chain series analysis subsequently it is used to estimate the future evaporation losses using developed GP model. Finally the effect of possible future climate change on

  10. Genetic programming based quantitative structure-retention relationships for the prediction of Kovats retention indices.

    Science.gov (United States)

    Goel, Purva; Bapat, Sanket; Vyas, Renu; Tambe, Amruta; Tambe, Sanjeev S

    2015-11-13

    The development of quantitative structure-retention relationships (QSRR) aims at constructing an appropriate linear/nonlinear model for the prediction of the retention behavior (such as Kovats retention index) of a solute on a chromatographic column. Commonly, multi-linear regression and artificial neural networks are used in the QSRR development in the gas chromatography (GC). In this study, an artificial intelligence based data-driven modeling formalism, namely genetic programming (GP), has been introduced for the development of quantitative structure based models predicting Kovats retention indices (KRI). The novelty of the GP formalism is that given an example dataset, it searches and optimizes both the form (structure) and the parameters of an appropriate linear/nonlinear data-fitting model. Thus, it is not necessary to pre-specify the form of the data-fitting model in the GP-based modeling. These models are also less complex, simple to understand, and easy to deploy. The effectiveness of GP in constructing QSRRs has been demonstrated by developing models predicting KRIs of light hydrocarbons (case study-I) and adamantane derivatives (case study-II). In each case study, two-, three- and four-descriptor models have been developed using the KRI data available in the literature. The results of these studies clearly indicate that the GP-based models possess an excellent KRI prediction accuracy and generalization capability. Specifically, the best performing four-descriptor models in both the case studies have yielded high (>0.9) values of the coefficient of determination (R(2)) and low values of root mean squared error (RMSE) and mean absolute percent error (MAPE) for training, test and validation set data. The characteristic feature of this study is that it introduces a practical and an effective GP-based method for developing QSRRs in gas chromatography that can be gainfully utilized for developing other types of data-driven models in chromatography science.

  11. Diversity and genetic stability in banana genotypes in a breeding program using inter simple sequence repeats (ISSR) markers.

    Science.gov (United States)

    Silva, A V C; Nascimento, A L S; Vitória, M F; Rabbani, A R C; Soares, A N R; Lédo, A S

    2017-02-23

    Banana (Musa spp) is a fruit species frequently cultivated and consumed worldwide. Molecular markers are important for estimating genetic diversity in germplasm and between genotypes in breeding programs. The objective of this study was to analyze the genetic diversity of 21 banana genotypes (FHIA 23, PA42-44, Maçã, Pacovan Ken, Bucaneiro, YB42-47, Grand Naine, Tropical, FHIA 18, PA94-01, YB42-17, Enxerto, Japira, Pacovã, Prata-Anã, Maravilha, PV79-34, Caipira, Princesa, Garantida, and Thap Maeo), by using inter-simple sequence repeat (ISSR) markers. Material was generated from the banana breeding program of Embrapa Cassava & Fruits and evaluated at Embrapa Coastal Tablelands. The 12 primers used in this study generated 97.5% polymorphism. Four clusters were identified among the different genotypes studied, and the sum of the first two principal components was 48.91%. From the Unweighted Pair Group Method using Arithmetic averages (UPGMA) dendrogram, it was possible to identify two main clusters and subclusters. Two genotypes (Garantida and Thap Maeo) remained isolated from the others, both in the UPGMA clustering and in the principal cordinate analysis (PCoA). Using ISSR markers, we could analyze the genetic diversity of the studied material and state that these markers were efficient at detecting sufficient polymorphism to estimate the genetic variability in banana genotypes.

  12. GESP: A computer program for modeling genetic effective population size, inbreeding, and divergence in substructured populations.

    Science.gov (United States)

    Olsson, Fredrik; Laikre, Linda; Hössjer, Ola; Ryman, Nils

    2017-03-24

    The genetically effective population size (Ne) is of key importance for quantifying rates of inbreeding and genetic drift, and is often used in conservation management to set targets for genetic viability. The concept was developed for single, isolated populations and the mathematical means for analyzing the expected Ne in complex, subdivided populations have previously not been available. We recently developed such analytical theory and central parts of that work have now been incorporated into a freely available software tool presented here. GESP (Genetic Effective population size, inbreeding, and divergence in Substructured Populations) is R-based and designed to model short and long term patterns of genetic differentiation and effective population size of subdivided populations. The algorithms performed by GESP allow exact computation of global and local inbreeding and eigenvalue effective population size, predictions of genetic divergence among populations (GST) as well as departures from random mating (FIS, FIT) while varying i) subpopulation census and effective size, separately or including trend of the global population size, ii) rate and direction of migration between all pairs of subpopulations, iii) degree of relatedness and divergence among subpopulations, iv) ploidy (haploid or diploid), and v) degree of selfing. Here, we describe GESP and exemplify its use in conservation genetics modeling. This article is protected by copyright. All rights reserved.

  13. Genetic evaluation of the Association of Zoos and Aquariums Matschie's tree kangaroo (Dendrolagus matschiei) captive breeding program.

    Science.gov (United States)

    McGreevy, Thomas J; Dabek, Lisa; Husband, Thomas P

    2011-01-01

    Matschie's tree kangaroo (Dendrolagus matschiei) is an endangered species that has been bred in captivity since the 1970s. In 1992, the Tree Kangaroo Species Survival Plan(®) (TKSSP) was established to coordinate the captive management of Association of Zoos and Aquariums (AZA) D. matschiei. The TKSSP makes annual breeding recommendations primarily based on the mean kinship (MK) strategy. Captive breeding programs often use the MK strategy to preserve genetic diversity in small populations-to avoid the negative consequences of inbreeding and retain their adaptive potential. The ability of a captive breeding program to retain the population's genetic diversity over time can be evaluated by comparing the genetic diversity of the captive population to wild populations. We analyzed DNA extracted from blood and fecal samples from AZA (n = 71), captive (n = 28), and wild (n = 22) D. matschiei using eight microsatellite markers and sequenced the partial mitochondrial DNA control region gene. AZA D. matschiei had a similar expected heterozygosity (H(e) = 0.595 ± 0.184) compared with wild D. matschiei (H(e) = 0.628 ± 0.143), but they had different allelic frequencies (F(ST) = 0.126; P < 0.001). AZA D. matschiei haplotype diversity was almost two times lower than wild D. matschiei Ĥ = 0.740 ± 0.063. These data will assist management of AZA D. matschiei and serve as a baseline for AZA and wild D. matschiei genetic diversity values that could be used to monitor future changes in their genetic diversity. © 2010 Wiley Periodicals, Inc.

  14. [Prenatal diagnosis. I: Prenatal diagnosis program at the Medical Genetics Unit of the Universidad de Zulia, Maracaibo, Venezuela].

    Science.gov (United States)

    Prieto-Carrasquero, M; Molero, A; Carrasquero, N; Paz, V; González, S; Pineda-Del Villar, L; Del Villar, A; Rojas-Atencio, A; Quintero, M; Fulcado, W; Mena, R; Morales-Machin, A

    1998-06-01

    The Prenatal Diagnosis Program of the Medical Genetic Unit of University of Zulia has the following objectives: Identification of Genetic Risk Factors (GRF) in those couples who attend to the Prenatal Genetic Clinic, application of different prenatal diagnostic procedures (PDP), and providing adequate genetic counseling. The goal of this paper is to show preliminary results obtained between January 1993 and December 1996. Three hundred and twenty one pregnant women were analyzed by determining the GRF and taking into account the genetic clinical history. The GRF analyzed were: Advanced maternal age (AMA), congenital malformation history (CMH), previous child with chromosomic anomalies (PCCA), defects of neural tube history (DNTH), congenital heart disease history (CHDH), any parent carrier of chromosomic anomaly (PCA), habitual abortion (HA), abnormal fetal echography (AFE), altered maternal serum levels of alpha-feto-protein (AMSAFP) and OTHERS: exposure to teratogenic agents, history of Mendelian diseases, maternal systemic diseases and anxiety in the mother or in her partner. The PDP was designed according to the GRF, which included fetal echography (FE), fetal echocardiography (FEc), amniocentesis (AMN), chordocentesis (CCT) and AMSAFP. Results showed that 58.4% of the expectant mothers asked for counseling during the 2nd trimester, 70% of the total showed only one GRF, and AMA was the most frequent GRF found (40.3%), followed by PCCA, AFE, CHDH, HA, DNTH, PCA, and OTHERS in that order. The specific PDP applied to the identified GRF allowed a health evaluation of the fetus. The GRF identification gave the opportunity of establishing a Prenatal Diagnostic Program producing a response to the couple's needs and showed the utility of an integral and multidisciplinary management directed to any expecting mother in order to identify any high GRF.

  15. Six-year outcome of the national premarital screening and genetic counseling program for sickle cell disease and β-thalassemia in Saudi Arabia

    National Research Council Canada - National Science Library

    Memish, Ziad Ahmed; Saeedi, Mohammad Y

    2011-01-01

    Saudi Arabia has a high prevalence of hereditary hemoglobin disorders. Data has been collected by the Saudi Premarital Screening and Genetic Counseling Program on the prevalence of sickle cell disease and β...

  16. Genetic associations with intimate partner violence in a sample of hazardous drinking men in batterer intervention programs.

    Science.gov (United States)

    Stuart, Gregory L; McGeary, John E; Shorey, Ryan C; Knopik, Valerie S; Beaucage, Kayla; Temple, Jeff R

    2014-04-01

    The etiology of intimate partner violence (IPV) is multifactorial. However, etiological theories of IPV have rarely included potential genetic factors. The purpose of the present study was to examine whether a cumulative genetic score (CGS) containing the monoamine oxidase A (MAOA) and the human serotonin transporter gene linked polymorphism (5-HTTLPR) was associated with IPV perpetration after accounting for the effects of alcohol problems, drug problems, age, and length of relationship. We obtained DNA from 97 men in batterer intervention programs in the state of Rhode Island. In the full sample, the CGS was significantly associated with physical and psychological aggression and injuries caused to one's partner, even after controlling for the effects of alcohol problems, drug problems, age, and length of relationship. Two of the men in the sample likely had Klinefelter's syndrome, and analyses were repeated excluding these two individuals, leading to similar results. The implications of the genetic findings for the etiology and treatment of IPV among men in batterer intervention programs are briefly discussed.

  17. Controlling inbreeding and maximizing genetic gain using semi-definite programming with pedigree-based and genomic relationships.

    Science.gov (United States)

    Schierenbeck, S; Pimentel, E C G; Tietze, M; Körte, J; Reents, R; Reinhardt, F; Simianer, H; König, S

    2011-12-01

    Because of the relatively high levels of genetic relationships among potential bull sires and bull dams, innovative selection tools should consider both genetic gain and genetic relationships in a long-term perspective. Optimum genetic contribution theory using official estimated breeding values for a moderately heritable trait (production index, Index-PROD), and a lowly heritable functional trait (index for somatic cell score, Index-SCS) was applied to find optimal allocations of bull dams and bull sires. In contrast to previous practical applications using optimizations based on Lagrange multipliers, we focused on semi-definite programming (SDP). The SDP methodology was combined with either pedigree (a(ij)) or genomic relationships (f(ij)) among selection candidates. Selection candidates were 484 genotyped bulls, and 499 preselected genotyped bull dams completing a central test on station. In different scenarios separately for PROD and SCS, constraints on the average pedigree relationships among future progeny were varied from a(ij)=0.08 to a(ij)=0.20 in increments of 0.01. Corresponding constraints for single nucleotide polymorphism-based kinship coefficients were derived from regression analysis. Applying the coefficient of 0.52 with an intercept of 0.14 estimated for the regression pedigree relationship on genomic relationship, the corresponding range to alter genomic relationships varied from f(ij) = 0.18 to f(ij) = 0.24. Despite differences for some bulls in genomic and pedigree relationships, the same trends were observed for constraints on pedigree and corresponding genomic relationships regarding results in genetic gain and achieved coefficients of relationships. Generally, allowing higher values for relationships resulted in an increase of genetic gain for Index-PROD and Index-SCS and in a reduction in the number of selected sires. Interestingly, more sires were selected for all scenarios when restricting genomic relationships compared with restricting

  18. Preservation of the wild European mouflon: the first example of genetic management using a complete program of reproductive biotechnologies.

    Science.gov (United States)

    Ptak, Grazyna; Clinton, Michael; Barboni, Barbara; Muzzeddu, Marco; Cappai, Pietro; Tischner, Marian; Loi, Pasqualino

    2002-03-01

    Although the potential use of reproductive biotechnologies for safeguarding endangered wildlife species is undoubted, practical efforts have met with limited success to date. In those instances in which modern technologies have been adapted to rescuing rare or endangered species, procedures have been applied piecemeal, and no consistent breeding program based on reproductive biotechnologies has been undertaken. Here we describe for the first time the rescue of an endangered species, the European mouflon (Ovis orientalis musimon), by the application of an integrated package of reproductive biotechnologies. This genetic management extended from the initial collection of gametes, through the in vitro production of embryos and interspecific transfer, to the birth of healthy mouflon offspring. In addition, a genetic resource bank for the European mouflon was established, with cryopreserved sperm, embryos, and somatic cells.

  19. The use of a genetic-counselling program by Dutch breeders for four hereditary health problems in boxer dogs.

    Science.gov (United States)

    van Hagen, Marjan A E; Janss, Luc L G; van den Broek, Jan; Knol, Bart W

    2004-04-30

    Our group developed a genetic-counselling program for boxer-dog breeders in The Netherlands, using data for cryptorchidism (uni- and/or bilateral), epilepsy, knee-problems (including ligament rupture, fractured or ruptured meniscus, severe osteo-arthrosis of the knee, or a combination of these disorders), and schisis (including cheiloschisis, palatoschisis, or cheilopalatoschisis). We transformed the estimated breeding values (EBVs) into odds ratios (ORs), to enable the breeder to compare the risk for each of the traits for a certain dam-sire combination with the average population risk (set at 1). The goal of the study was to evaluate the use of our genetic-counselling program by Dutch breeders of boxer dogs. We asked breeders of the Dutch Boxer Club to send in an application form for genetic-counselling from June 1 to December 1, 2000. Breeders indicated on this application form three desirable sires for their dam (sire 1, sire 2, sire 3) in random order. On the basis of this information, a counselling report was produced which included ORs for the four diseases in litters of the dam-sire combinations indicated on the application form. Together with the counselling report, the breeders received an evaluation form. We received 129 application forms from 70 breeders, and collected 125 evaluations. Of these evaluations, 96 were informative about the influence of the counselling report on sire choice. The most-important criteria used by breeders to select sires were: the exterior characteristics (60%) and known progeny (52%). Although it was the first time breeders could make use of genetic-counselling, 32% of the breeders indicated that the genetic-counselling played a major role in their sire selection. Breeders expressed little difference in importance for the four genetic traits, but there was a tendency to consider epilepsy more than the others. Breeders hesitated to put long-term population interest above short-term personal interest. Nevertheless, the general

  20. Application of the CUDA programming model in the simulation of genetic sequences evolution

    Directory of Open Access Journals (Sweden)

    Freddy Yasmany Chávez

    2017-03-01

    Full Text Available Simulation is a powerful approach in the study of the molecular evolution of genetic sequences and their divergence over time; there are different procedures for the simulation of molecular evolution, but all of them have high computational complexity, and in most cases the genetic sequences have large size, increasing the execution time of the implementations of those procedures. Based on this problem, this paper describes a proposal of parallelization model using CUDA technology and the results of this proposal are compared with its sequential equivalent.

  1. sup 2 sup 5 sup 2 Cf source-correlated transmission measurements and genetic programming for nuclear safeguards

    CERN Document Server

    Pozzi, S A

    2002-01-01

    One of the main targets of nuclear safeguards is to determine the mass and enrichment of fissile samples enclosed in special, non-accessible containers. In this paper, we present a method to estimate the mass of uranium oxide samples based on sup 2 sup 5 sup 2 Cf source-driven noise-analysis measurements. We show that the mass of the samples can be successfully predicted using a genetic programming algorithm. The input presented to the algorithm was in the form of features extracted from the physical properties of the measured correlation functions.

  2. Analysis of the Multi Strategy Goal Programming for Micro-Grid Based on Dynamic ant Genetic Algorithm

    Science.gov (United States)

    Qiu, J. P.; Niu, D. X.

    Micro-grid is one of the key technologies of the future energy supplies. Take economic planning. reliability, and environmental protection of micro grid as a basis for the analysis of multi-strategy objective programming problems for micro grid which contains wind power, solar power, and battery and micro gas turbine. Establish the mathematical model of each power generation characteristics and energy dissipation. and change micro grid planning multi-objective function under different operating strategies to a single objective model based on AHP method. Example analysis shows that in combination with dynamic ant mixed genetic algorithm can get the optimal power output of this model.

  3. Genetically Programming Interfaces between Active Materials, Conductive Pathway and Current Collector in Li Ion Batteries

    Science.gov (United States)

    2012-01-01

    assembled into coin cell with metallic lithium as counter electrode. Electrochemical characterization was conducted by galvanostatically cycling the half...encodes either A1, A2, S7, T7 or H7. These DNAs were then introduced into bacteria cells for amplification. Genetic sequencing performed on the

  4. DNA Commission of the International Society for Forensic Genetics: Recommendations on the validation of software programs performing biostatistical calculations for forensic genetics applications.

    Science.gov (United States)

    Coble, M D; Buckleton, J; Butler, J M; Egeland, T; Fimmers, R; Gill, P; Gusmão, L; Guttman, B; Krawczak, M; Morling, N; Parson, W; Pinto, N; Schneider, P M; Sherry, S T; Willuweit, S; Prinz, M

    2016-11-01

    The use of biostatistical software programs to assist in data interpretation and calculate likelihood ratios is essential to forensic geneticists and part of the daily case work flow for both kinship and DNA identification laboratories. Previous recommendations issued by the DNA Commission of the International Society for Forensic Genetics (ISFG) covered the application of bio-statistical evaluations for STR typing results in identification and kinship cases, and this is now being expanded to provide best practices regarding validation and verification of the software required for these calculations. With larger multiplexes, more complex mixtures, and increasing requests for extended family testing, laboratories are relying more than ever on specific software solutions and sufficient validation, training and extensive documentation are of upmost importance. Here, we present recommendations for the minimum requirements to validate bio-statistical software to be used in forensic genetics. We distinguish between developmental validation and the responsibilities of the software developer or provider, and the internal validation studies to be performed by the end user. Recommendations for the software provider address, for example, the documentation of the underlying models used by the software, validation data expectations, version control, implementation and training support, as well as continuity and user notifications. For the internal validations the recommendations include: creating a validation plan, requirements for the range of samples to be tested, Standard Operating Procedure development, and internal laboratory training and education. To ensure that all laboratories have access to a wide range of samples for validation and training purposes the ISFG DNA commission encourages collaborative studies and public repositories of STR typing results. Published by Elsevier Ireland Ltd.

  5. Search for Lambda+(c) ---> p K+ pi- and D+(s) ---> K+ K+ pi- using genetic programming event selection

    Energy Technology Data Exchange (ETDEWEB)

    Link, J.M.; Yager, P.M.; Anjos, J.C.; Bediaga, I.; Castromonte, C.; Machado, A.A.; Magnin, J.; Massafferri, A.; de Miranda, J.M.; Pepe, I.M.; Polycarpo, E.; dos Reis,; Carrillo, S.; Casimiro, E.; Cuautle, E.; Sanchez-Hernandez, A.; Uribe, C.; Vazquez, F.; Agostino, L.; Cinquini, L.; Cumalat, J.P.; /Wisconsin U., Madison

    2005-07-01

    The authors apply a genetic programming technique to search for the doubly Cabibbo suppressed decays {Lambda}{sub c}{sup +} {yields} pK{sup +} {pi}{sup -} and D{sub s}{sup +} {yields} K{sup +}K{sup +}{pi}{sup -}. They normalize these decays to their Cabibbo favored partners and find BR({Lambda}{sub c}{sup +} {yields} pK{sup +}{pi}{sup -})/BR({Lambda}{sub c}{sup +} {yields} pK{sup -}{pi}{sup +}) = (0.05 {+-} 0.26 {+-} 0.02)% and BR(D{sub s}{sup +} {yields} K{sup +}K{sup +}{pi}{sup -})/BR(D{sub s}{sup +} {yields} K{sup -}K{sup +}{pi}{sup +}) = (0.52 {+-} 0.17 {+-} 0.11)% where the first errors are statistical and the second are systematic. Expressed as 90% confidence levels (CL), they find < 0.46% and < 0.78% respectively. This is the first successful use of genetic programming in a high energy physics data analysis.

  6. Intra-Day Trading System Design Based on the Integrated Model of Wavelet De-Noise and Genetic Programming

    Directory of Open Access Journals (Sweden)

    Hongguang Liu

    2016-12-01

    Full Text Available Technical analysis has been proved to be capable of exploiting short-term fluctuations in financial markets. Recent results indicate that the market timing approach beats many traditional buy-and-hold approaches in most of the short-term trading periods. Genetic programming (GP was used to generate short-term trade rules on the stock markets during the last few decades. However, few of the related studies on the analysis of financial time series with genetic programming considered the non-stationary and noisy characteristics of the time series. In this paper, to de-noise the original financial time series and to search profitable trading rules, an integrated method is proposed based on the Wavelet Threshold (WT method and GP. Since relevant information that affects the movement of the time series is assumed to be fully digested during the market closed periods, to avoid the jumping points of the daily or monthly data, in this paper, intra-day high-frequency time series are used to fully exploit the short-term forecasting advantage of technical analysis. To validate the proposed integrated approach, an empirical study is conducted based on the China Securities Index (CSI 300 futures in the emerging China Financial Futures Exchange (CFFEX market. The analysis outcomes show that the wavelet de-noise approach outperforms many comparative models.

  7. Effectiveness of an integrated hatchery program: Can genetic-based performance differences between hatchery and wild Chinook salmon be avoided?

    Science.gov (United States)

    Hayes, Michael C.; Reisenbichler, Reginald R.; Rubin, Stephen P.; Drake, Deanne C.; Stenberg, Karl D.; Young, Sewall F.

    2013-01-01

    Performance of wild (W) and hatchery (H) spring Chinook salmon (Oncorhynchus tshawytscha) was evaluated for a sixth generation hatchery program. Management techniques to minimize genetic divergence from the wild stock included regular use of wild broodstock and volitional releases of juveniles. Performance of HH, WW, and HW (hatchery female spawned with wild male) crosses was compared in hatchery and stream environments. The WW juveniles emigrated from the hatchery at two to three times the rate of HH fish in the fall (HW intermediate) and 35% more HH than WW adults returned (27% more HW than WW adults). Performance in the stream did not differ statistically between HH and WW fish, but outmigrants (38% WW, 30% HW, and 32% HH fish) during the first 39 days of the 16-month sampling period composed 74% of total outmigrants. Differences among hatchery-reared crosses were partially due to additive genetic effects, were consistent with domestication (increased fitness for the hatchery population in the hatchery program), and suggested that selection against fall emigration from the hatchery was a possible mechanism of domestication.

  8. The retinoblastoma protein regulates hypoxia-inducible genetic programs, tumor cell invasiveness and neuroendocrine differentiation in prostate cancer cells

    Science.gov (United States)

    Labrecque, Mark P.; Takhar, Mandeep K.; Nason, Rebecca; Santacruz, Stephanie; Tam, Kevin J.; Massah, Shabnam; Haegert, Anne; Bell, Robert H.; Altamirano-Dimas, Manuel; Collins, Colin C.; Lee, Frank J.S.; Prefontaine, Gratien G.; Cox, Michael E.; Beischlag, Timothy V.

    2016-01-01

    Loss of tumor suppressor proteins, such as the retinoblastoma protein (Rb), results in tumor progression and metastasis. Metastasis is facilitated by low oxygen availability within the tumor that is detected by hypoxia inducible factors (HIFs). The HIF1 complex, HIF1α and dimerization partner the aryl hydrocarbon receptor nuclear translocator (ARNT), is the master regulator of the hypoxic response. Previously, we demonstrated that Rb represses the transcriptional response to hypoxia by virtue of its association with HIF1. In this report, we further characterized the role Rb plays in mediating hypoxia-regulated genetic programs by stably ablating Rb expression with retrovirally-introduced short hairpin RNA in LNCaP and 22Rv1 human prostate cancer cells. DNA microarray analysis revealed that loss of Rb in conjunction with hypoxia leads to aberrant expression of hypoxia-regulated genetic programs that increase cell invasion and promote neuroendocrine differentiation. For the first time, we have established a direct link between hypoxic tumor environments, Rb inactivation and progression to late stage metastatic neuroendocrine prostate cancer. Understanding the molecular pathways responsible for progression of benign prostate tumors to metastasized and lethal forms will aid in the development of more effective prostate cancer therapies. PMID:27015368

  9. Population prevalence of hereditary breast cancer phenotypes and implementation of a genetic cancer risk assessment program in southern Brazil

    Science.gov (United States)

    2009-01-01

    In 2004, a population-based cohort (the Núcleo Mama Porto Alegre - NMPOA Cohort) was started in Porto Alegre, southern Brazil and within that cohort, a hereditary breast cancer study was initiated, aiming to determine the prevalence of hereditary breast cancer phenotypes and evaluate acceptance of a genetic cancer risk assessment (GCRA) program. Women from that cohort who reported a positive family history of cancer were referred to GCRA. Of the 9218 women enrolled, 1286 (13.9%) reported a family history of cancer. Of the 902 women who attended GCRA, 55 (8%) had an estimated lifetime risk of breast cancer ≥ 20% and 214 (23.7%) had pedigrees suggestive of a breast cancer predisposition syndrome; an unexpectedly high number of these fulfilled criteria for Li-Fraumeni-like syndrome (122 families, 66.7%). The overall prevalence of a hereditary breast cancer phenotype was 6.2% (95%CI: 5.67-6.65). These findings identified a problem of significant magnitude in the region and indicate that genetic cancer risk evaluation should be undertaken in a considerable proportion of the women from this community. The large proportion of women who attended GCRA (72.3%) indicates that the program was well-accepted by the community, regardless of the potential cultural, economic and social barriers. PMID:21637504

  10. The retinoblastoma protein regulates hypoxia-inducible genetic programs, tumor cell invasiveness and neuroendocrine differentiation in prostate cancer cells.

    Science.gov (United States)

    Labrecque, Mark P; Takhar, Mandeep K; Nason, Rebecca; Santacruz, Stephanie; Tam, Kevin J; Massah, Shabnam; Haegert, Anne; Bell, Robert H; Altamirano-Dimas, Manuel; Collins, Colin C; Lee, Frank J S; Prefontaine, Gratien G; Cox, Michael E; Beischlag, Timothy V

    2016-04-26

    Loss of tumor suppressor proteins, such as the retinoblastoma protein (Rb), results in tumor progression and metastasis. Metastasis is facilitated by low oxygen availability within the tumor that is detected by hypoxia inducible factors (HIFs). The HIF1 complex, HIF1α and dimerization partner the aryl hydrocarbon receptor nuclear translocator (ARNT), is the master regulator of the hypoxic response. Previously, we demonstrated that Rb represses the transcriptional response to hypoxia by virtue of its association with HIF1. In this report, we further characterized the role Rb plays in mediating hypoxia-regulated genetic programs by stably ablating Rb expression with retrovirally-introduced short hairpin RNA in LNCaP and 22Rv1 human prostate cancer cells. DNA microarray analysis revealed that loss of Rb in conjunction with hypoxia leads to aberrant expression of hypoxia-regulated genetic programs that increase cell invasion and promote neuroendocrine differentiation. For the first time, we have established a direct link between hypoxic tumor environments, Rb inactivation and progression to late stage metastatic neuroendocrine prostate cancer. Understanding the molecular pathways responsible for progression of benign prostate tumors to metastasized and lethal forms will aid in the development of more effective prostate cancer therapies.

  11. Genetic and epigenetic catalysts in early-life programming of adult cardiometabolic disorders

    OpenAIRE

    Estampador AC; Franks PW

    2014-01-01

    Angela C Estampador,1,2 Paul W Franks1,3,4 1Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Skåne University Hospital Malmö, Malmö, Sweden; 2Department of Endocrinology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark; 3Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden; 4Department of Nutrition, Harvard School of Public Health, Boston, MA, USA Abstract...

  12. Genetic counseling and presymptomatic testing programs for Machado-Joseph disease: lessons from Brazil and Portugal

    Directory of Open Access Journals (Sweden)

    Lavínia Schuler-Faccini

    2014-01-01

    Full Text Available Machado-Joseph disease (MJD is an autosomal dominant, late-onset neurological disorder and the most common form of spinocerebellar ataxia (SCA worldwide. Diagnostic genetic testing is available to detect the disease-causing mutation by direct sizing of the CAG repeat tract in the ataxin 3 gene. Presymptomatic testing (PST can be used to identify persons at risk of developing the disease. Genetic counseling provides patients with information about the disease, genetic risks, PST, and the decision-making process. In this study, we present the protocol used in PST for MJD and the relevant observations from two centers: Brazil (Porto Alegre and Portugal (Porto. We provide a case report that illustrates the significant ethical and psychological issues related to PST in late-onset neurological disorders. In both centers, counseling and PST are performed by a multidisciplinary team, and genetic testing is conducted at the same institutions. From 1999 to 2012, 343 individuals sought PST in Porto Alegre; 263 (77% of these individuals were from families with MJD. In Porto, 1,530 individuals sought PST between 1996 and 2013, but only 66 (4% individuals were from families with MJD. In Brazil, approximately 50% of the people seeking PST eventually took the test and received their results, whereas 77% took the test in Portugal. In this case report, we highlight several issues that might be raised by the consultand and how the team can extract significant information. Literature about PST testing for MJD and other SCAs is scarce, and we hope this report will encourage similar studies and enable the implementation of PST protocols in other populations, mainly in Latin America.

  13. Genetic, nongenetic and epigenetic risk determinants in developmental programming of type 2 diabetes

    DEFF Research Database (Denmark)

    Vaag, Allan; Brøns, Charlotte; Gillberg, Linn

    2014-01-01

    the mother and her offspring. Epigenetic mechanisms may explain the link between factors operating in fetal life and later risk of developing T2D, but so far convincing evidence is lacking for epigenetic changes as a prime and direct cause of T2D. This review addresses recent literature on the early origins...... of adult disease hypothesis, with a special emphasis on the role of genetic compared with nongenetic and epigenetic risk determinants and disease mechanisms....

  14. Genetic control of programmed cell death in the nematode Caenorhabditis elegans

    National Research Council Canada - National Science Library

    Horvitz, H R

    1999-01-01

    Studies of the development of the nematode Caenorhabditis elegans established that programmed cell death involves specific genes and proteins and that those genes and proteins act within the cells that die...

  15. Genetically Programmed Clusters of Gold Nanoparticles for Cancer Cell-Targeted Photothermal Therapy.

    Science.gov (United States)

    Oh, Mi Hwa; Yu, Jeong Heon; Kim, Insu; Nam, Yoon Sung

    2015-10-14

    Interpretations of the interactions of nanocarriers with biological cells are often complicated by complex synthesis of materials, broad size distribution, and heterogeneous surface chemistry. Herein, the major capsid proteins of an icosahedral T7 phage (55 nm in diameter) are genetically engineered to display a gold-binding peptide and a prostate cancer cell-binding peptide in a tandem sequence. The genetically modified phage attracts gold nanoparticles (AuNPs) to form a cluster of gold nanoparticles (about 70 nanoparticles per phage). The cluster of AuNPs maintains cell-targeting functionality and exhibits excellent dispersion stability in serum. Under a very low light irradiation (60 mW cm(-2)), only targeted AuNP clusters kill the prostate cancer cells in minutes (not in other cell types), whereas neither nontargeted AuNP clusters nor citrate-stabilized AuNPs cause any significant cell death. The result suggests that the prostate cancer cell-targeted clusters of AuNPs are targeted to only prostate cancer cells and, when illuminated, generate local heating to more efficiently and selectively kill the targeted cancer cells. Our strategy can be generalized to target other types of cells and assemble other kinds of nanoparticles for a broad range of applications.

  16. Genetic shift in local rice populations during rice breeding programs in the northern limit of rice cultivation in the world.

    Science.gov (United States)

    Fujino, Kenji; Obara, Mari; Ikegaya, Tomohito; Tamura, Kenichi

    2015-09-01

    The rapid accumulation of pre-existing mutations may play major roles in the establishment and shaping of adaptability for local regions in current rice breeding programs. The cultivated rice, Oryza sativa L., which originated from tropical regions, is now grown worldwide due to the concerted efforts of breeding programs. However, the process of establishing local populations and their origins remain unclear. In the present study, we characterized DNA polymorphisms in the rice variety KITAAKE from Hokkaido, one of the northern limits of rice cultivation in the world. Indel polymorphisms were attributed to transposable element-like insertions, tandem duplications, and non-TE deletions as the original mutation events in the NIPPONBARE and KITAAKE genomes. The allele frequencies of the KITAAKE alleles markedly shifted to the current variety types among the local population from Hokkaido in the last two decades. The KITAAKE alleles widely distributed throughout wild rice and cultivated rice over the world. These have accumulated in the local population from Hokkaido via Japanese landraces as the ancestral population of Hokkaido. These results strongly suggested that combinations of pre-existing mutations played a role in the establishment of adaptability. This approach using the re-sequencing of local varieties in unique environmental conditions will be useful as a genetic resource in plant breeding programs in local regions.

  17. Genetic and environmental variation in a commercial breeding program of perennial ryegrass

    DEFF Research Database (Denmark)

    Fé, Dario; Pedersen, Morten Greve; Jensen, Christian S;

    2015-01-01

    for future GSbased breeding programs. Forage yield showed family heritabilities of up to 0.30 across locations and up to 0.60 within a location. Similar or moderately lower values were found for the other traits. In particular, the heritabilities of rust resistance and aftermath heading were very promising...

  18. Daily reference evapotranspiration modeling by using genetic programming approach in the Basque Country (Northern Spain)

    NARCIS (Netherlands)

    Shiri, J.; Kisi, O.; Landeras, G.; Lopez, J.J.; Nazemi, A.H.; Stuyt, L.C.P.M.

    2012-01-01

    Evapotranspiration, as a major component of the hydrological cycle, is of importance for water resources management and development, as well as for estimating the water budget of irrigation schemes. This study presents a Gene Expression Programming (GEP) approach, for estimating daily reference evap

  19. Daily reference evapotranspiration modeling by using genetic programming approach in the Basque Country (Northern Spain)

    NARCIS (Netherlands)

    Shiri, J.; Kisi, O.; Landeras, G.; Lopez, J.J.; Nazemi, A.H.; Stuyt, L.C.P.M.

    2012-01-01

    Evapotranspiration, as a major component of the hydrological cycle, is of importance for water resources management and development, as well as for estimating the water budget of irrigation schemes. This study presents a Gene Expression Programming (GEP) approach, for estimating daily reference

  20. Daily reference evapotranspiration modeling by using genetic programming approach in the Basque Country (Northern Spain)

    NARCIS (Netherlands)

    Shiri, J.; Kisi, O.; Landeras, G.; Lopez, J.J.; Nazemi, A.H.; Stuyt, L.C.P.M.

    2012-01-01

    Evapotranspiration, as a major component of the hydrological cycle, is of importance for water resources management and development, as well as for estimating the water budget of irrigation schemes. This study presents a Gene Expression Programming (GEP) approach, for estimating daily reference evap

  1. Software For Genetic Algorithms

    Science.gov (United States)

    Wang, Lui; Bayer, Steve E.

    1992-01-01

    SPLICER computer program is genetic-algorithm software tool used to solve search and optimization problems. Provides underlying framework and structure for building genetic-algorithm application program. Written in Think C.

  2. A genetic program theory of aging using an RNA population model.

    Science.gov (United States)

    Wang, Xiufang; Ma, Zhihong; Cheng, Jianjun; Lv, Zhanjun

    2014-01-01

    Aging is a common characteristic of multicellular eukaryotes. Copious hypotheses have been proposed to explain the mechanisms of aging, but no single theory is generally acceptable. In this article, we refine the RNA population gene activating model (Lv et al., 2003) based on existing reports as well as on our own latest findings. We propose the RNA population model as a genetic theory of aging. The new model can also be applied to differentiation and tumorigenesis and could explain the biological significance of non-coding DNA, RNA, and repetitive sequence DNA. We provide evidence from the literature as well as from our own findings for the roles of repetitive sequences in gene activation. In addition, we predict several phenomena related to aging and differentiation based on this model.

  3. A Genetic Programming Framework for Topic Discovery from Online Digital Library

    Directory of Open Access Journals (Sweden)

    Yinxing Li

    2010-11-01

    Full Text Available Various topic extraction techniques for digital libraries have been proposed over the past decade. Generally the topic extraction system requires a large number of features and complicated lexical analysis. While these features and analysis are effective to represent the statistical characteristics of the document, they didn't capture the high level semantics. In this paper, we present a new approach for topic extraction. Our approach combines user's click stream data with traditional lexical analysis. From our point of view, the user's click stream directly reflects human understanding of the high-level semantics in the document. Furthermore, a simple, yet effective, piece-wise linear model for topic evolution is proposed. We apply genetic algorithm to estimate the model and extract topics. Experiments on the set of US congress digital library documents demonstrate that our approach achieves better accuracy for the topic extraction than traditional methods.

  4. A genetic algorithm based stochastic programming model for air quality management

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    This paper presents a model that can aid planners in defining the total allowable pollutant discharge in the planning region,accounting for the dynamic and stochastic character of meteorological conditions.This is accomplished by integrating Monte Carlo simulation and using genetic algorithm to solve the model.The model is demonstrated by using a realistic air urban-scale SO2 control problem in the Yuxi City of China.To evaluate effectiveness of the model,results of the approach are shown to compare with those of the linear deterministic procedures.This paper also provides a valuable insight into how air quality targets should be made when the air pollutant will not threat the residents'health.Finally,a discussion of the areas for further research are briefly delineated.

  5. Potential for cell therapy in Parkinson's disease using genetically programmed human embryonic stem cell-derived neural progenitor cells.

    Science.gov (United States)

    Ambasudhan, Rajesh; Dolatabadi, Nima; Nutter, Anthony; Masliah, Eliezer; Mckercher, Scott R; Lipton, Stuart A

    2014-08-15

    Neural transplantation is a promising strategy for restoring dopaminergic dysfunction and modifying disease progression in Parkinson's disease (PD). Human embryonic stem cells (hESCs) are a potential resource in this regard because of their ability to provide a virtually limitless supply of homogenous dopaminergic progenitors and neurons of appropriate lineage. The recent advances in developing robust cell culture protocols for directed differentiation of hESCs to near pure populations of ventral mesencephalic (A9-type) dopaminergic neurons has heightened the prospects for PD cell therapy. Here, we focus our review on current state-of-the-art techniques for harnessing hESC-based strategies toward development of a stem cell therapeutic for PD. Importantly, we also briefly describe a novel genetic-programming approach that may address many of the key challenges that remain in the field and that may hasten clinical translation. © 2014 Wiley Periodicals, Inc.

  6. CAFFEINE: Template-Free Symbolic Model Generation of Analog Circuits via Canonical Form Functions and Genetic Programming

    CERN Document Server

    Mcconaghy, Trent; Gielen, Georges

    2011-01-01

    This paper presents a method to automatically generate compact symbolic performance models of analog circuits with no prior specification of an equation template. The approach takes SPICE simulation data as input, which enables modeling of any nonlinear circuits and circuit characteristics. Genetic programming is applied as a means of traversing the space of possible symbolic expressions. A grammar is specially designed to constrain the search to a canonical form for functions. Novel evolutionary search operators are designed to exploit the structure of the grammar. The approach generates a set of symbolic models which collectively provide a tradeoff between error and model complexity. Experimental results show that the symbolic models generated are compact and easy to understand, making this an effective method for aiding understanding in analog design. The models also demonstrate better prediction quality than posynomials.

  7. Energy management of a power-split plug-in hybrid electric vehicle based on genetic algorithm and quadratic programming

    Science.gov (United States)

    Chen, Zheng; Mi, Chris Chunting; Xiong, Rui; Xu, Jun; You, Chenwen

    2014-02-01

    This paper introduces an online and intelligent energy management controller to improve the fuel economy of a power-split plug-in hybrid electric vehicle (PHEV). Based on analytic analysis between fuel-rate and battery current at different driveline power and vehicle speed, quadratic equations are applied to simulate the relationship between battery current and vehicle fuel-rate. The power threshold at which engine is turned on is optimized by genetic algorithm (GA) based on vehicle fuel-rate, battery state of charge (SOC) and driveline power demand. The optimal battery current when the engine is on is calculated using quadratic programming (QP) method. The proposed algorithm can control the battery current effectively, which makes the engine work more efficiently and thus reduce the fuel-consumption. Moreover, the controller is still applicable when the battery is unhealthy. Numerical simulations validated the feasibility of the proposed controller.

  8. Landscape genetics of raccoons (Procyon lotor) associated with ridges and valleys of Pennsylvania: implications for oral rabies vaccination programs.

    Science.gov (United States)

    Root, J Jeffrey; Puskas, Robert B; Fischer, Justin W; Swope, Craig B; Neubaum, Melissa A; Reeder, Serena A; Piaggio, Antoinette J

    2009-12-01

    Raccoons are the reservoir for the raccoon rabies virus variant in the United States. To combat this threat, oral rabies vaccination (ORV) programs are conducted in many eastern states. To aid in these efforts, the genetic structure of raccoons (Procyon lotor) was assessed in southwestern Pennsylvania to determine if select geographic features (i.e., ridges and valleys) serve as corridors or hindrances to raccoon gene flow (e.g., movement) and, therefore, rabies virus trafficking in this physiographic region. Raccoon DNA samples (n = 185) were collected from one ridge site and two adjacent valleys in southwestern Pennsylvania (Westmoreland, Cambria, Fayette, and Somerset counties). Raccoon genetic structure within and among these study sites was characterized at nine microsatellite loci. Results indicated that there was little population subdivision among any sites sampled. Furthermore, analyses using a model-based clustering approach indicated one essentially panmictic population was present among all the raccoons sampled over a reasonably broad geographic area (e.g., sites up to 36 km apart). However, a signature of isolation by distance was detected, suggesting that widths of ORV zones are critical for success. Combined, these data indicate that geographic features within this landscape influence raccoon gene flow only to a limited extent, suggesting that ridges of this physiographic system will not provide substantial long-term natural barriers to rabies virus trafficking. These results may be of value for future ORV efforts in Pennsylvania and other eastern states with similar landscapes.

  9. Tree-based genetic programming approach to infer microphysical parameters of the DSDs from the polarization diversity measurements

    Science.gov (United States)

    Islam, Tanvir; Rico-Ramirez, Miguel A.; Han, Dawei

    2012-11-01

    The use of polarization diversity measurements to infer the microphysical parametrization has remained an active goal in the radar remote sensing community. In view of this, the tree-based genetic programming (GP) as a novel approach has been presented for retrieving the governing microphysical parameters of a normalized gamma drop size distribution model D0 (median drop diameter), Nw (concentration parameter), and μ (shape parameter) from the polarization diversity measurements. A large number of raindrop spectra acquired from a Joss-Waldvogel disdrometer has been utilized to develop the GP models, relating the microphysical parameters to the T-matrix scattering simulated polarization measurements. Several functional formulations retrieving the microphysical parameters-D0 [f(ZDR), f(ZH, ZDR)], log10Nw [f(ZH, D0), f(ZH, ZDR, D0), and μ[f(ZDR, D0), f(ZH, ZDR, D0)], where ZH represents reflectivity and ZDR represents differential reflectivity, have been investigated, and applied to a S-band polarimetric radar (CAMRA) for evaluation. It has been shown that the GP model retrieved microphysical parameters from the polarization measurements are in a reasonable agreement with disdrometer observations. The calculated root mean squared errors (RMSE) are noted as 0.23-0.25 mm for D0, 0.74-0.85 for log10Nw (Nw in mm-1 mm-3), and 3.30-3.36 for μ. The GP model based microphysical retrieval procedure is further compared with a physically based constrained gamma model for D0 and log10Nw estimates. The close agreement of the retrieval results between the GP and the constrained gamma models supports the suitability of the proposed genetic programming approach to infer microphysical parameterization.

  10. A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

    Directory of Open Access Journals (Sweden)

    Chandra Nagasuma R

    2009-02-01

    Full Text Available Abstract Background A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN from transcript profiling data. Results The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting problem and solved finally by formulating a Linear Program (LP. A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known

  11. Designing A Nonlinear Integer Programming Model For A Cross-Dock By A Genetic Algorithm

    OpenAIRE

    Bahareh Vaisi; Reza Tavakkoli-Moghaddam

    2015-01-01

    Abstract This paper presents a non-linear integer programming model for a cross-dock problem that considers the total transportation cost of inbound and outbound trucks from an origin to a destination and the total cost of assigning strip and stack doors to trucks based on their number of trips and the distance between doors in cross-dock. In previous studies these two cost-based problems are modeled separately however it is more realistic and practical to use both of them as an integrated cr...

  12. Modelling of the Elasticity Modulus for Rock Using Genetic Expression Programming

    Directory of Open Access Journals (Sweden)

    Umit Atici

    2016-01-01

    Full Text Available In rock engineering projects, statically determined parameters are more reflective of actual load conditions than dynamic parameters. This study reports a new and efficient approach to the formulation of the static modulus of elasticity Es applying gene expression programming (GEP with nondestructive testing (NDT methods. The results obtained using GEP are compared with the results of multivariable linear regression analysis (MRA, univariate nonlinear regression analysis (URA, and the dynamic elasticity modulus (Ed. The GEP model was found to produce the most accurate calculation of Es. The proposed approach is a simple, nondestructive, and practical way to determine Es for anisotropic and heterogeneous rocks.

  13. Consequences of Early Life Programing by Genetic and Environmental Influences: A Synthesis Regarding Pubertal Timing.

    Science.gov (United States)

    Roth, Christian L; DiVall, Sara

    2016-01-01

    Sexual maturation is closely tied to growth and body weight gain, suggesting that regulative metabolic pathways are shared between somatic and pubertal development. The pre- and postnatal environment affects both growth and pubertal development, indicating that common pathways are affected by the environment. Intrauterine and early infantile developmental phases are characterized by high plasticity and thereby susceptibility to factors that affect metabolic function as well as related reproductive function throughout life. In children born small for gestational age, poor nutritional conditions during gestation can modify metabolic systems to adapt to expectations of chronic undernutrition. These children are potentially poorly equipped to cope with energy-dense diets and are possibly programmed to store as much energy as possible, causing rapid weight gain with the risk for adult disease and premature onset of puberty. Environmental factors can cause modifications to the genome, so-called epigenetic changes, to affect gene expression and subsequently modify phenotypic expression of genomic information. Epigenetic modifications, which occur in children born small for gestational age, are thought to underlie part of the metabolic programming that subsequently effects both somatic and pubertal development. © 2016 S. Karger AG, Basel.

  14. Genetic programs of the developing tuberal hypothalamus and potential mechanisms of their disruption by environmental factors.

    Science.gov (United States)

    Nesan, Dinushan; Kurrasch, Deborah M

    2016-12-15

    The hypothalamus is a critical regulator of body homeostasis, influencing the autonomic nervous system and releasing trophic hormones to modulate the endocrine system. The developmental mechanisms that govern formation of the mature hypothalamus are becoming increasingly understood as research in this area grows, leading us to gain appreciation for how these developmental programs are susceptible to disruption by maternal exposure to endocrine disrupting chemicals or other environmental factors in utero. These vulnerabilities, combined with the prominent roles of the various hypothalamic nuclei in regulating appetite, reproductive behaviour, mood, and other physiologies, create a window whereby early developmental disruption can have potent long-term effects. Here we broadly outline our current understanding of hypothalamic development, with a particular focus on the tuberal hypothalamus, including what is know about nuclear coalescing and maturation. We finish by discussing how exposure to environmental or maternally-derived factors can perhaps disrupt these hypothalamic developmental programs, and potentially lead to neuroendocrine disease states. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  15. A Hybrid Genetic Programming Method in Optimization and Forecasting: A Case Study of the Broadband Penetration in OECD Countries

    Directory of Open Access Journals (Sweden)

    Konstantinos Salpasaranis

    2012-01-01

    Full Text Available The introduction of a hybrid genetic programming method (hGP in fitting and forecasting of the broadband penetration data is proposed. The hGP uses some well-known diffusion models, such as those of Gompertz, Logistic, and Bass, in the initial population of the solutions in order to accelerate the algorithm. The produced solutions models of the hGP are used in fitting and forecasting the adoption of broadband penetration. We investigate the fitting performance of the hGP, and we use the hGP to forecast the broadband penetration in OECD (Organisation for Economic Co-operation and Development countries. The results of the optimized diffusion models are compared to those of the hGP-generated models. The comparison indicates that the hGP manages to generate solutions with high-performance statistical indicators. The hGP cooperates with the existing diffusion models, thus allowing multiple approaches to forecasting. The modified algorithm is implemented in the Python programming language, which is fast in execution time, compact, and user friendly.

  16. ASCL1 and NEUROD1 Reveal Heterogeneity in Pulmonary Neuroendocrine Tumors and Regulate Distinct Genetic Programs

    Directory of Open Access Journals (Sweden)

    Mark D. Borromeo

    2016-08-01

    Full Text Available Small cell lung carcinoma (SCLC is a high-grade pulmonary neuroendocrine tumor. The transcription factors ASCL1 and NEUROD1 play crucial roles in promoting malignant behavior and survival of human SCLC cell lines. Here, we find that ASCL1 and NEUROD1 identify heterogeneity in SCLC, bind distinct genomic loci, and regulate mostly distinct genes. ASCL1, but not NEUROD1, is present in mouse pulmonary neuroendocrine cells, and only ASCL1 is required in vivo for tumor formation in mouse models of SCLC. ASCL1 targets oncogenic genes including MYCL1, RET, SOX2, and NFIB while NEUROD1 targets MYC. ASCL1 and NEUROD1 regulate different genes that commonly contribute to neuronal function. ASCL1 also regulates multiple genes in the NOTCH pathway including DLL3. Together, ASCL1 and NEUROD1 distinguish heterogeneity in SCLC with distinct genomic landscapes and distinct gene expression programs.

  17. Monthly reservoir inflow forecasting using a new hybrid SARIMA genetic programming approach

    Science.gov (United States)

    Moeeni, Hamid; Bonakdari, Hossein; Ebtehaj, Isa

    2017-03-01

    Forecasting reservoir inflow is one of the most important components of water resources and hydroelectric systems operation management. Seasonal autoregressive integrated moving average (SARIMA) models have been frequently used for predicting river flow. SARIMA models are linear and do not consider the random component of statistical data. To overcome this shortcoming, monthly inflow is predicted in this study based on a combination of seasonal autoregressive integrated moving average (SARIMA) and gene expression programming (GEP) models, which is a new hybrid method (SARIMA-GEP). To this end, a four-step process is employed. First, the monthly inflow datasets are pre-processed. Second, the datasets are modelled linearly with SARIMA and in the third stage, the non-linearity of residual series caused by linear modelling is evaluated. After confirming the non-linearity, the residuals are modelled in the fourth step using a gene expression programming (GEP) method. The proposed hybrid model is employed to predict the monthly inflow to the Jamishan Dam in west Iran. Thirty years' worth of site measurements of monthly reservoir dam inflow with extreme seasonal variations are used. The results of this hybrid model (SARIMA-GEP) are compared with SARIMA, GEP, artificial neural network (ANN) and SARIMA-ANN models. The results indicate that the SARIMA-GEP model ( R 2=78.8, VAF =78.8, RMSE =0.89, MAPE =43.4, CRM =0.053) outperforms SARIMA and GEP and SARIMA-ANN ( R 2=68.3, VAF =66.4, RMSE =1.12, MAPE =56.6, CRM =0.032) displays better performance than the SARIMA and ANN models. A comparison of the two hybrid models indicates the superiority of SARIMA-GEP over the SARIMA-ANN model.

  18. Monthly reservoir inflow forecasting using a new hybrid SARIMA genetic programming approach

    Indian Academy of Sciences (India)

    Hamid Moeeni; Hossein Bonakdari; Isa Ebtehaj

    2017-03-01

    Forecasting reservoir inflow is one of the most important components of water resources and hydroelectric systems operation management. Seasonal autoregressive integrated moving average (SARIMA) models have been frequently used for predicting river flow. SARIMA models are linear and do not consider the random component of statistical data. To overcome this shortcoming, monthly inflow is predicted in this study based on a combination of seasonal autoregressive integrated moving average (SARIMA) andgene expression programming (GEP) models, which is a new hybrid method (SARIMA–GEP). To this end, a four-step process is employed. First, the monthly inflow datasets are pre-processed. Second, the datasets are modelled linearly with SARIMA and in the third stage, the non-linearity of residual seriescaused by linear modelling is evaluated. After confirming the non-linearity, the residuals are modelled in the fourth step using a gene expression programming (GEP) method. The proposed hybrid model is employed to predict the monthly inflow to the Jamishan Dam in west Iran. Thirty years’ worth of site measurements of monthly reservoir dam inflow with extreme seasonal variations are used. The results of this hybrid model (SARIMA–GEP) are compared with SARIMA, GEP, artificial neural network (ANN) and SARIMA–ANN models. The results indicate that the SARIMA–GEP model (R2=78.8, VAF=78.8, RMSE=0.89, MAPE=43.4, CRM=0.053) outperforms SARIMA and GEP and SARIMA– ANN (R2=68.3, VAF=66.4, RMSE=1.12, MAPE=56.6, CRM=0.032) displays better performance than the SARIMA and ANN models. A comparison of the two hybrid models indicates the superiority of SARIMA–GEP over the SARIMA–ANN model.

  19. A case-based approach to the development of practice-based competencies for accreditation of and training in graduate programs in genetic counseling.

    Science.gov (United States)

    Fiddler, M B; Fine, B A; Baker, D L

    1996-09-01

    The American Board of Genetic Counseling (ABGC) sponsored a consensus development conference with participation from directors of graduate programs in genetic counseling, board members, and expert consultants. Using a collective, narrative, and case-based approach, 27 competencies were identified as embedded in the practice of genetic counseling. These competencies were organized into four domains of skills: Communication; Critical Thinking; Interpersonal, Counseling, and Psychosocial Assessment; and Professional Ethics and Values. The adoption of a competency framework for accreditation has a variety of implications for curriculum design and implementation. We report here the process by which a set of practice-based genetic counseling competencies have been derived; and in an accompanying article, the competencies themselves are provided. We also discuss the application of the competencies to graduate program accreditation as well as some of the implications competency-based standards may have for education and the genetic counseling profession. These guidelines may also serve as a basis for the continuing education of practicing genetic counselors and a performance evaluation tool in the workplace.

  20. Solving a multi-objective location routing problem for infectious waste disposal using hybrid goal programming and hybrid genetic algorithm

    Directory of Open Access Journals (Sweden)

    Narong Wichapa

    2018-01-01

    Full Text Available Infectious waste disposal remains one of the most serious problems in the medical, social and environmental domains of almost every country. Selection of new suitable locations and finding the optimal set of transport routes for a fleet of vehicles to transport infectious waste material, location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Determining locations for infectious waste disposal is a difficult and complex process, because it requires combining both intangible and tangible factors. Additionally, it depends on several criteria and various regulations. This facility location problem for infectious waste disposal is complicated, and it cannot be addressed using any stand-alone technique. Based on a case study, 107 hospitals and 6 candidate municipalities in Upper-Northeastern Thailand, we considered criteria such as infrastructure, geology and social & environmental criteria, evaluating global priority weights using the fuzzy analytical hierarchy process (Fuzzy AHP. After that, a new multi-objective facility location problem model which hybridizes fuzzy AHP and goal programming (GP, namely the HGP model, was tested. Finally, the vehicle routing problem (VRP for a case study was formulated, and it was tested using a hybrid genetic algorithm (HGA which hybridizes the push forward insertion heuristic (PFIH, genetic algorithm (GA and three local searches including 2-opt, insertion-move and interexchange-move. The results show that both the HGP and HGA can lead to select new suitable locations and to find the optimal set of transport routes for vehicles delivering infectious waste material. The novelty of the proposed methodologies, HGP, is the simultaneous combination of relevant factors that are difficult to interpret and cost factors in order to determine new suitable locations, and HGA can be applied to determine the transport routes which provide a minimum number of vehicles

  1. Partial discharge localization in power transformers based on the sequential quadratic programming-genetic algorithm adopting acoustic emission techniques

    Science.gov (United States)

    Liu, Hua-Long; Liu, Hua-Dong

    2014-10-01

    Partial discharge (PD) in power transformers is one of the prime reasons resulting in insulation degradation and power faults. Hence, it is of great importance to study the techniques of the detection and localization of PD in theory and practice. The detection and localization of PD employing acoustic emission (AE) techniques, as a kind of non-destructive testing, plus due to the advantages of powerful capability of locating and high precision, have been paid more and more attention. The localization algorithm is the key factor to decide the localization accuracy in AE localization of PD. Many kinds of localization algorithms exist for the PD source localization adopting AE techniques including intelligent and non-intelligent algorithms. However, the existed algorithms possess some defects such as the premature convergence phenomenon, poor local optimization ability and unsuitability for the field applications. To overcome the poor local optimization ability and easily caused premature convergence phenomenon of the fundamental genetic algorithm (GA), a new kind of improved GA is proposed, namely the sequence quadratic programming-genetic algorithm (SQP-GA). For the hybrid optimization algorithm, SQP-GA, the sequence quadratic programming (SQP) algorithm which is used as a basic operator is integrated into the fundamental GA, so the local searching ability of the fundamental GA is improved effectively and the premature convergence phenomenon is overcome. Experimental results of the numerical simulations of benchmark functions show that the hybrid optimization algorithm, SQP-GA, is better than the fundamental GA in the convergence speed and optimization precision, and the proposed algorithm in this paper has outstanding optimization effect. At the same time, the presented SQP-GA in the paper is applied to solve the ultrasonic localization problem of PD in transformers, then the ultrasonic localization method of PD in transformers based on the SQP-GA is proposed. And

  2. Long term culture of mesenchymal stem cells in hypoxia promotes a genetic program maintaining their undifferentiated and multipotent status

    Directory of Open Access Journals (Sweden)

    de Carvalho Marcelo

    2011-03-01

    Full Text Available Abstract Background In the bone marrow, hematopietic and mesenchymal stem cells form a unique niche in which the oxygen tension is low. Hypoxia may have a role in maintaining stem cell fate, self renewal and multipotency. However, whereas most studies addressed the effect of transient in vitro exposure of MSC to hypoxia, permanent culture under hypoxia should reflect the better physiological conditions. Results Morphologic studies, differentiation and transcriptional profiling experiments were performed on MSC cultured in normoxia (21% O2 versus hypoxia (5% O2 for up to passage 2. Cells at passage 0 and at passage 2 were compared, and those at passage 0 in hypoxia generated fewer and smaller colonies than in normoxia. In parallel, MSC displayed (>4 fold inhibition of genes involved in DNA metabolism, cell cycle progression and chromosome cohesion whereas transcripts involved in adhesion and metabolism (CD93, ESAM, VWF, PLVAP, ANGPT2, LEP, TCF1 were stimulated. Compared to normoxic cells, hypoxic cells were morphologically undifferentiated and contained less mitochondrias. After this lag phase, cells at passage 2 in hypoxia outgrew the cells cultured in normoxia and displayed an enhanced expression of genes (4-60 fold involved in extracellular matrix assembly (SMOC2, neural and muscle development (NOG, GPR56, SNTG2, LAMA and epithelial development (DMKN. This group described herein for the first time was assigned by the Gene Ontology program to "plasticity". Conclusion The duration of hypoxemia is a critical parameter in the differentiation capacity of MSC. Even in growth promoting conditions, hypoxia enhanced a genetic program that maintained the cells undifferentiated and multipotent. This condition may better reflect the in vivo gene signature of MSC, with potential implications in regenerative medicine.

  3. Determination of the genetic structure of remnant Morus boninensis Koidz. trees to establish a conservation program on the Bonin Islands, Japan.

    Science.gov (United States)

    Tani, Naoki; Yoshimaru, Hiroshi; Kawahara, Takayuki; Hoshi, Yoshio; Nobushima, Fuyuo; Yasui, Takaya

    2006-10-11

    Morus boninensis, is an endemic plant of the Bonin (Ogasawara) Islands of Japan and is categorized as "critically endangered" in the Japanese red data book. However, little information is available about its ecological, evolutionary and genetic status, despite the urgent need for guidelines for the conservation of the species. Therefore, we adopted Moritz's MU concept, based on the species' current genetic structure, to define management units and to select mother tree candidates for seed orchards. Nearly all individuals of the species were genotyped on the basis of seven microsatellite markers. Genetic diversity levels in putative natural populations were higher than in putative man-made populations with the exception of those on Otouto-jima Island. This is because a limited number of maternal trees are likely to have been used for seed collection to establish the man-made populations. A model-based clustering analysis clearly distinguished individuals into nine clusters, with a large difference in genetic composition between the population on Otouto-jima Island, the putative natural populations and the putative man-made populations. The Otouto-jima population appeared to be genetically differentiated from the others; a finding that was also supported by pairwise FST and RST analysis. Although multiple clusters were detected in the putative man-made populations, the pattern of genetic diversity was monotonous in comparison to the natural populations. The genotyping by microsatellite markers revealed strong genetic structures. Typically, artificial propagation of this species has ignored the genetic structure, relying only on seeds from Otouto-jima for replanting on other islands, because of a problem with inter-specific hybridization on Chichi-jima and Haha-jima Islands. However, this study demonstrates that we should be taking into consideration the genetic structure of the species when designing a propagation program for the conservation of this species.

  4. Determination of the genetic structure of remnant Morus boninensis Koidz. trees to establish a conservation program on the Bonin Islands, Japan

    Directory of Open Access Journals (Sweden)

    Nobushima Fuyuo

    2006-10-01

    Full Text Available Abstract Background Morus boninensis, is an endemic plant of the Bonin (Ogasawara Islands of Japan and is categorized as "critically endangered" in the Japanese red data book. However, little information is available about its ecological, evolutionary and genetic status, despite the urgent need for guidelines for the conservation of the species. Therefore, we adopted Moritz's MU concept, based on the species' current genetic structure, to define management units and to select mother tree candidates for seed orchards. Results Nearly all individuals of the species were genotyped on the basis of seven microsatellite markers. Genetic diversity levels in putative natural populations were higher than in putative man-made populations with the exception of those on Otouto-jima Island. This is because a limited number of maternal trees are likely to have been used for seed collection to establish the man-made populations. A model-based clustering analysis clearly distinguished individuals into nine clusters, with a large difference in genetic composition between the population on Otouto-jima Island, the putative natural populations and the putative man-made populations. The Otouto-jima population appeared to be genetically differentiated from the others; a finding that was also supported by pairwise FST and RST analysis. Although multiple clusters were detected in the putative man-made populations, the pattern of genetic diversity was monotonous in comparison to the natural populations. Conclusion The genotyping by microsatellite markers revealed strong genetic structures. Typically, artificial propagation of this species has ignored the genetic structure, relying only on seeds from Otouto-jima for replanting on other islands, because of a problem with inter-specific hybridization on Chichi-jima and Haha-jima Islands. However, this study demonstrates that we should be taking into consideration the genetic structure of the species when designing a

  5. Symbolic regression via genetic programming for data driven derivation of confinement scaling laws without any assumption on their mathematical form

    Science.gov (United States)

    Murari, A.; Peluso, E.; Gelfusa, M.; Lupelli, I.; Lungaroni, M.; Gaudio, P.

    2015-01-01

    Many measurements are required to control thermonuclear plasmas and to fully exploit them scientifically. In the last years JET has shown the potential to generate about 50 GB of data per shot. These amounts of data require more sophisticated data analysis methodologies to perform correct inference and various techniques have been recently developed in this respect. The present paper covers a new methodology to extract mathematical models directly from the data without any a priori assumption about their expression. The approach, based on symbolic regression via genetic programming, is exemplified using the data of the International Tokamak Physics Activity database for the energy confinement time. The best obtained scaling laws are not in power law form and suggest a revisiting of the extrapolation to ITER. Indeed the best non-power law scalings predict confinement times in ITER approximately between 2 and 3 s. On the other hand, more comprehensive and better databases are required to fully profit from the power of these new methods and to discriminate between the hundreds of thousands of models that they can generate.

  6. Evaluation of liquefaction potential of soil based on standard penetration test using multi-gene genetic programming model

    Science.gov (United States)

    Muduli, Pradyut; Das, Sarat

    2014-06-01

    This paper discusses the evaluation of liquefaction potential of soil based on standard penetration test (SPT) dataset using evolutionary artificial intelligence technique, multi-gene genetic programming (MGGP). The liquefaction classification accuracy (94.19%) of the developed liquefaction index (LI) model is found to be better than that of available artificial neural network (ANN) model (88.37%) and at par with the available support vector machine (SVM) model (94.19%) on the basis of the testing data. Further, an empirical equation is presented using MGGP to approximate the unknown limit state function representing the cyclic resistance ratio (CRR) of soil based on developed LI model. Using an independent database of 227 cases, the overall rates of successful prediction of occurrence of liquefaction and non-liquefaction are found to be 87, 86, and 84% by the developed MGGP based model, available ANN and the statistical models, respectively, on the basis of calculated factor of safety (F s) against the liquefaction occurrence.

  7. An integrated portfolio optimisation procedure based on data envelopment analysis, artificial bee colony algorithm and genetic programming

    Science.gov (United States)

    Hsu, Chih-Ming

    2014-12-01

    Portfolio optimisation is an important issue in the field of investment/financial decision-making and has received considerable attention from both researchers and practitioners. However, besides portfolio optimisation, a complete investment procedure should also include the selection of profitable investment targets and determine the optimal timing for buying/selling the investment targets. In this study, an integrated procedure using data envelopment analysis (DEA), artificial bee colony (ABC) and genetic programming (GP) is proposed to resolve a portfolio optimisation problem. The proposed procedure is evaluated through a case study on investing in stocks in the semiconductor sub-section of the Taiwan stock market for 4 years. The potential average 6-month return on investment of 9.31% from 1 November 2007 to 31 October 2011 indicates that the proposed procedure can be considered a feasible and effective tool for making outstanding investment plans, and thus making profits in the Taiwan stock market. Moreover, it is a strategy that can help investors to make profits even when the overall stock market suffers a loss.

  8. A type I IFN-dependent DNA damage response regulates the genetic program and inflammasome activation in macrophages

    Science.gov (United States)

    Morales, Abigail J; Carrero, Javier A; Hung, Putzer J; Tubbs, Anthony T; Andrews, Jared M; Edelson, Brian T; Calderon, Boris; Innes, Cynthia L; Paules, Richard S; Payton, Jacqueline E; Sleckman, Barry P

    2017-01-01

    Macrophages produce genotoxic agents, such as reactive oxygen and nitrogen species, that kill invading pathogens. Here we show that these agents activate the DNA damage response (DDR) kinases ATM and DNA-PKcs through the generation of double stranded breaks (DSBs) in murine macrophage genomic DNA. In contrast to other cell types, initiation of this DDR depends on signaling from the type I interferon receptor. Once activated, ATM and DNA-PKcs regulate a genetic program with diverse immune functions and promote inflammasome activation and the production of IL-1β and IL-18. Indeed, following infection with Listeria monocytogenes, DNA-PKcs-deficient murine macrophages produce reduced levels of IL-18 and are unable to optimally stimulate IFN-γ production by NK cells. Thus, genomic DNA DSBs act as signaling intermediates in murine macrophages, regulating innate immune responses through the initiation of a type I IFN-dependent DDR. DOI: http://dx.doi.org/10.7554/eLife.24655.001 PMID:28362262

  9. From Heuristic to Mathematical Modeling of Drugs Dissolution Profiles: Application of Artificial Neural Networks and Genetic Programming.

    Science.gov (United States)

    Mendyk, Aleksander; Güres, Sinan; Jachowicz, Renata; Szlęk, Jakub; Polak, Sebastian; Wiśniowska, Barbara; Kleinebudde, Peter

    2015-01-01

    The purpose of this work was to develop a mathematical model of the drug dissolution (Q) from the solid lipid extrudates based on the empirical approach. Artificial neural networks (ANNs) and genetic programming (GP) tools were used. Sensitivity analysis of ANNs provided reduction of the original input vector. GP allowed creation of the mathematical equation in two major approaches: (1) direct modeling of Q versus extrudate diameter (d) and the time variable (t) and (2) indirect modeling through Weibull equation. ANNs provided also information about minimum achievable generalization error and the way to enhance the original dataset used for adjustment of the equations' parameters. Two inputs were found important for the drug dissolution: d and t. The extrudates length (L) was found not important. Both GP modeling approaches allowed creation of relatively simple equations with their predictive performance comparable to the ANNs (root mean squared error (RMSE) from 2.19 to 2.33). The direct mode of GP modeling of Q versus d and t resulted in the most robust model. The idea of how to combine ANNs and GP in order to escape ANNs' black-box drawback without losing their superior predictive performance was demonstrated. Open Source software was used to deliver the state-of-the-art models and modeling strategies.

  10. Optimizing a multi-echelon supply chain network flow using nonlinear fuzzy multi-objective integer programming: Genetic algorithm approach

    Directory of Open Access Journals (Sweden)

    Mohammad Ali Afshari

    2012-10-01

    Full Text Available The aim of this paper is to present mathematical models optimizing all materials flows in supply chain. In this research a fuzzy multi-objective nonlinear mixed- integer programming model with piecewise linear membership function is applied to design a multi echelon supply chain network (SCN by considering total transportation costs and capacities of all echelons with fuzzy objectives. The model that is proposed in this study has 4 fuzzy functions. The first function is minimizing the total transportation costs between all echelons (suppliers, factories, distribution centers (DCs and customers. The second one is minimizing holding and ordering cost on DCs. The third objective is minimizing the unnecessary and unused capacity of factories and DCs via decreasing variance of transported amounts between echelons. The forth is minimizing the number of total vehicles that ship the materials and products along with SCN. For solving such a problem, as nodes increases in SCN, the traditional method does not have ability to solve large scale problem. So, we applied a Meta heuristic method called Genetic Algorithm. The numerical example is real world applied and compared the results with each other demonstrate the feasibility of applying the proposed model to given problem, and also its advantages are discussed.

  11. Modelling and prediction of complex non-linear processes by using Pareto multi-objective genetic programming

    Science.gov (United States)

    Jamali, A.; Khaleghi, E.; Gholaminezhad, I.; Nariman-zadeh, N.

    2016-05-01

    In this paper, a new multi-objective genetic programming (GP) with a diversity preserving mechanism and a real number alteration operator is presented and successfully used for Pareto optimal modelling of some complex non-linear systems using some input-output data. In this study, two different input-output data-sets of a non-linear mathematical model and of an explosive cutting process are considered separately in three-objective optimisation processes. The pertinent conflicting objective functions that have been considered for such Pareto optimisations are namely, training error (TE), prediction error (PE), and the length of tree (complexity of the network) (TL) of the GP models. Such three-objective optimisation implementations leads to some non-dominated choices of GP-type models for both cases representing the trade-offs among those objective functions. Therefore, optimal Pareto fronts of such GP models exhibit the trade-off among the corresponding conflicting objectives and, thus, provide different non-dominated optimal choices of GP-type models. Moreover, the results show that no significant optimality in TE and PE may occur when the TL of the corresponding GP model exceeds some values.

  12. Norrin, Frizzled4, and Lrp5 signaling in endothelial cells controls a genetic program for retinal vascularization

    Science.gov (United States)

    Ye, Xin; Wang, Yanshu; Cahill, Hugh; Yu, Minzhong; Badea, Tudor C.; Smallwood, Philip M.; Peachey, Neal S.; Nathans, Jeremy

    2009-01-01

    SUMMARY Disorders of vascular structure and function play a central role in a wide variety of CNS diseases. Mutations in the Frizzled4 (Fz4) receptor, Lrp5 co-receptor, or Norrin ligand cause retinal hypovascularization, but the role of Norrin/Fz4/Lrp signaling in vascular development has not been defined. Using mouse genetic and cell culture models, we show that loss of Fz4 signaling in endothelial cells causes defective vascular growth, which leads to chronic but reversible silencing of retinal neurons. Loss of Fz4 in all endothelial cells disrupts the blood brain barrier in the cerebellum, while excessive Fz4 signaling disrupts embryonic angiogenesis. Sox17, a transcription factor that is up-regulated by Norrin/Fz4/Lrp signaling, plays a central role in inducing the angiogenic program controlled by Norrin/Fz4/Lrp. These experiments establish a cellular basis for retinal hypovascularization diseases due to insufficient Frizzled signaling, and they suggest a broader role for Frizzled signaling in vascular growth, remodeling, maintenance, and disease. PMID:19837032

  13. Race, Ethnicity and Ancestry in Unrelated Transplant Matching for the National Marrow Donor Program: A Comparison of Multiple Forms of Self-Identification with Genetics.

    Science.gov (United States)

    Hollenbach, Jill A; Saperstein, Aliya; Albrecht, Mark; Vierra-Green, Cynthia; Parham, Peter; Norman, Paul J; Maiers, Martin

    2015-01-01

    We conducted a nationwide study comparing self-identification to genetic ancestry classifications in a large cohort (n = 1752) from the National Marrow Donor Program. We sought to determine how various measures of self-identification intersect with genetic ancestry, with the aim of improving matching algorithms for unrelated bone marrow transplant. Multiple dimensions of self-identification, including race/ethnicity and geographic ancestry were compared to classifications based on ancestry informative markers (AIMs), and the human leukocyte antigen (HLA) genes, which are required for transplant matching. Nearly 20% of responses were inconsistent between reporting race/ethnicity versus geographic ancestry. Despite strong concordance between AIMs and HLA, no measure of self-identification shows complete correspondence with genetic ancestry. In certain cases geographic ancestry reporting matches genetic ancestry not reflected in race/ethnicity identification, but in other cases geographic ancestries show little correspondence to genetic measures, with important differences by gender. However, when respondents assign ancestry to grandparents, we observe sub-groups of individuals with well- defined genetic ancestries, including important differences in HLA frequencies, with implications for transplant matching. While we advocate for tailored questioning to improve accuracy of ancestry ascertainment, collection of donor grandparents' information will improve the chances of finding matches for many patients, particularly for mixed-ancestry individuals.

  14. Genetic similarity of polyploids - A new version of the computer program POPDIST (ver. 1.2.0) considers intraspecific genetic differentiation

    DEFF Research Database (Denmark)

    Tomiuk, Jürgen; Guldbrandtsen, Bernt; Loeschcke, Volker

    2009-01-01

    For evolutionary studies of polyploid species estimates of the genetic identity between species with different degrees of ploidy are particularly required because gene counting in samples of polyploid individuals often cannot be done, e.g., in triploids the phenotype AB can be genotypically eithe...

  15. Testing of chemicals for genetic activity with Saccharomyces cerevisiae: a report of the U. S. Environmental Protection Agency Gene-Tox Program

    Energy Technology Data Exchange (ETDEWEB)

    Zimmermann, F.K.; von Borstel, R.C.; von Halle, E.S.; Parry, J.M.; Siebert, D.; Zetterberg, G.; Barale, R.; Loprieno, N.

    1984-01-01

    This review article with over 200 references summarizes the results of mutation screening tests with 492 chemicals using saccharomyces cerevisiae as the test organism. In addition, an extensive description of S. cerevisiae as a test organism is given. Yeast can be used to study genetic effects both in mitotic and in meiotic cells because it can be cultured as a stable haploid or a stable diploid. The most commonly used genetic endpoint has been mitotic recombination either as mitotic crossing-over or mitotic gene conversion. Data were available on tests with 492 chemicals, of which 249 were positive, as reported in 173 articles or reports. The genetic test/carcinogenicity accuracy was 0.74, based on the carcinogen listing established in the gene-tox program. The yeast tests supplement the bacterial tests for detecting agents that act via radical formation, antibacterial drugs, and other chemicals interfering with chromosome segregation and recombination processes.

  16. Comparison between genetic programming and an ensemble Kalman filter as data assimilation techniques for probabilistic flood forecasting

    Science.gov (United States)

    Mediero, L.; Garrote, L.; Requena, A.; Chávez, A.

    2012-04-01

    Flood events are among the natural disasters that cause most economic and social damages in Europe. Information and Communication Technology (ICT) developments in last years have enabled hydrometeorological observations available in real-time. High performance computing promises the improvement of real-time flood forecasting systems and makes the use of post processing techniques easier. This is the case of data assimilation techniques, which are used to develop an adaptive forecast model. In this paper, a real-time framework for probabilistic flood forecasting is presented and two data assimilation techniques are compared. The first data assimilation technique uses genetic programming to adapt the model to the observations as new information is available, updating the estimation of the probability distribution of the model parameters. The second data assimilation technique uses an ensemble Kalman filter to quantify errors in both hydrologic model and observations, updating estimates of system states. Both forecast models take the result of the hydrologic model calibration as a starting point and adapts the individuals of this first population to the new observations in each operation time step. Data assimilation techniques have great potential when are used in hydrological distributed models. The distributed RIBS (Real-time Interactive Basin Simulator) rainfall-runoff model was selected to simulate the hydrological process in the basin. The RIBS model is deterministic, but it is run in a probabilistic way through Monte Carlo simulations over the probability distribution functions that best characterise the most relevant model parameters, which were identified by a probabilistic multi-objective calibration developed in a previous work. The Manzanares River basin was selected as a case study. Data assimilation processes are computationally intensive. Therefore, they are well suited to test the applicability of the potential of the Grid technology to

  17. Generating information-rich high-throughput experimental materials genomes using functional clustering via multitree genetic programming and information theory.

    Science.gov (United States)

    Suram, Santosh K; Haber, Joel A; Jin, Jian; Gregoire, John M

    2015-04-13

    High-throughput experimental methodologies are capable of synthesizing, screening and characterizing vast arrays of combinatorial material libraries at a very rapid rate. These methodologies strategically employ tiered screening wherein the number of compositions screened decreases as the complexity, and very often the scientific information obtained from a screening experiment, increases. The algorithm used for down-selection of samples from higher throughput screening experiment to a lower throughput screening experiment is vital in achieving information-rich experimental materials genomes. The fundamental science of material discovery lies in the establishment of composition-structure-property relationships, motivating the development of advanced down-selection algorithms which consider the information value of the selected compositions, as opposed to simply selecting the best performing compositions from a high throughput experiment. Identification of property fields (composition regions with distinct composition-property relationships) in high throughput data enables down-selection algorithms to employ advanced selection strategies, such as the selection of representative compositions from each field or selection of compositions that span the composition space of the highest performing field. Such strategies would greatly enhance the generation of data-driven discoveries. We introduce an informatics-based clustering of composition-property functional relationships using a combination of information theory and multitree genetic programming concepts for identification of property fields in a composition library. We demonstrate our approach using a complex synthetic composition-property map for a 5 at. % step ternary library consisting of four distinct property fields and finally explore the application of this methodology for capturing relationships between composition and catalytic activity for the oxygen evolution reaction for 5429 catalyst compositions in a

  18. Slit/Robo-mediated axon guidance in Tribolium and Drosophila: divergent genetic programs build insect nervous systems.

    Science.gov (United States)

    Evans, Timothy A; Bashaw, Greg J

    2012-03-01

    As the complexity of animal nervous systems has increased during evolution, developmental control of neuronal connectivity has become increasingly refined. How has functional diversification within related axon guidance molecules contributed to the evolution of nervous systems? To address this question, we explore the evolution of functional diversity within the Roundabout (Robo) family of axon guidance receptors. In Drosophila, Robo and Robo2 promote midline repulsion, while Robo2 and Robo3 specify the position of longitudinal axon pathways. The Robo family has expanded by gene duplication in insects; robo2 and robo3 exist as distinct genes only within dipterans, while other insects, like the flour beetle Tribolium castaneum, retain an ancestral robo2/3 gene. Both Robos from Tribolium can mediate midline repulsion in Drosophila, but unlike the fly Robos cannot be down-regulated by Commissureless. The overall architecture and arrangement of longitudinal pathways are remarkably conserved in Tribolium, despite it having only two Robos. Loss of TcSlit causes midline collapse of axons in the beetle, a phenotype recapitulated by simultaneous knockdown of both Robos. Single gene knockdowns reveal that beetle Robos have specialized axon guidance functions: TcRobo is dedicated to midline repulsion, while TcRobo2/3 also regulates longitudinal pathway formation. TcRobo2/3 knockdown reproduces aspects of both Drosophila robo2 and robo3 mutants, suggesting that TcRobo2/3 has two functions that in Drosophila are divided between Robo2 and Robo3. The ability of Tribolium to organize longitudinal axons into three discrete medial-lateral zones with only two Robo receptors demonstrates that beetle and fly achieve equivalent developmental outcomes using divergent genetic programs.

  19. A method of evolving novel feature extraction algorithms for detecting buried objects in FLIR imagery using genetic programming

    Science.gov (United States)

    Paino, A.; Keller, J.; Popescu, M.; Stone, K.

    2014-06-01

    In this paper we present an approach that uses Genetic Programming (GP) to evolve novel feature extraction algorithms for greyscale images. Our motivation is to create an automated method of building new feature extraction algorithms for images that are competitive with commonly used human-engineered features, such as Local Binary Pattern (LBP) and Histogram of Oriented Gradients (HOG). The evolved feature extraction algorithms are functions defined over the image space, and each produces a real-valued feature vector of variable length. Each evolved feature extractor breaks up the given image into a set of cells centered on every pixel, performs evolved operations on each cell, and then combines the results of those operations for every cell using an evolved operator. Using this method, the algorithm is flexible enough to reproduce both LBP and HOG features. The dataset we use to train and test our approach consists of a large number of pre-segmented image "chips" taken from a Forward Looking Infrared Imagery (FLIR) camera mounted on the hood of a moving vehicle. The goal is to classify each image chip as either containing or not containing a buried object. To this end, we define the fitness of a candidate solution as the cross-fold validation accuracy of the features generated by said candidate solution when used in conjunction with a Support Vector Machine (SVM) classifier. In order to validate our approach, we compare the classification accuracy of an SVM trained using our evolved features with the accuracy of an SVM trained using mainstream feature extraction algorithms, including LBP and HOG.

  20. Seasonal change detection of riparian zones with remote sensing images and genetic programming in a semi-arid watershed.

    Science.gov (United States)

    Makkeasorn, Ammarin; Chang, Ni-Bin; Li, Jiahong

    2009-02-01

    Riparian zones are deemed significant due to their interception capability of non-point source impacts and the maintenance of ecosystem integrity region wide. To improve classification and change detection of riparian buffers, this paper developed an evolutionary computational, supervised classification method--the RIparian Classification Algorithm (RICAL)--to conduct the seasonal change detection of riparian zones in a vast semi-arid watershed, South Texas. RICAL uniquely demonstrates an integrative effort to incorporate both vegetation indices and soil moisture images derived from LANDSAT 5 TM and RADARSAT-1 satellite images, respectively. First, an estimation of soil moisture based on RADARSAT-1 Synthetic Aperture Radar (SAR) images was conducted via the first-stage genetic programming (GP) practice. Second, for the statistical analyses and image classification, eight vegetation indices were prepared based on reflectance factors that were calculated as the response of the instrument on LANDSAT. These spectral vegetation indices were then independently used for discriminate analysis along with soil moisture images to classify the riparian zones via the second-stage GP practice. The practical implementation was assessed by a case study in the Choke Canyon Reservoir Watershed (CCRW), South Texas, which is mostly agricultural and range land in a semi-arid coastal environment. To enhance the application potential, a combination of Iterative Self-Organizing Data Analysis Techniques (ISODATA) and maximum likelihood supervised classification was also performed for spectral discrimination and classification of riparian varieties comparatively. Research findings show that the RICAL algorithm may yield around 90% accuracy based on the unseen ground data. But using different vegetation indices would not significantly improve the final quality of the spectral discrimination and classification. Such practices may lead to the formulation of more effective management strategies

  1. Genetic expression programming-based DBA for enhancing peer-assisted music-on-demand service in EPON

    Science.gov (United States)

    Liem, Andrew Tanny; Hwang, I.-Shyan; Nikoukar, AliAkbar; Lee, Jhong-Yue

    2015-03-01

    Today, the popularity of peer-assisted music-on-demand (MoD) has increased significantly worldwide. This service allows users to access large music library tracks, listen to music, and share their playlist with other users. Unlike the conventional voice traffic, such an application maintains music quality that ranges from 160 kbps to 320 kbps, which most likely consumes more bandwidth than other traffics. In the access network, Ethernet passive optical network (EPON) is one of the best candidates for delivering such a service because of being cost-effective and with high bandwidth. To maintain music quality, a stutter needs to be prevented because of either network effects or when the due user was not receiving enough resources to play in a timely manner. Therefore, in this paper, we propose two genetic expression programming (GEP)-based dynamic bandwidth allocations (DBAs). The first DBA is a generic DBA that aims to find an optimum formula for voice, video, and data services. The second DBA aims to find optimum formulas so that Optical Line Terminal (OLT) can satisfy not only the voice and Peer-to-Peer (P2P) MoD traffics but also reduce the stutter. Optical Network Unit (ONU) traits such as REPORT and GATE messages, cycle time, and mean packet delay are set to be predictor variables. Simulation results show that our proposed DBAs can satisfy the voice and P2P MoD services packet delay and monitor other overall system performances such as expedited forwarding (EF) jitter, packet loss, bandwidth waste, and system throughputs.

  2. Six-year outcome of the national premarital screening and genetic counseling program for sickle cell disease and β-thalassemia in Saudi Arabia.

    Science.gov (United States)

    Memish, Ziad Ahmed; Saeedi, Mohammad Y

    2011-01-01

    Saudi Arabia has a high prevalence of hereditary hemoglobin disorders. Data has been collected by the Saudi Premarital Screening and Genetic Counseling Program on the prevalence of sickle cell disease and β-thalassemia but the outcomes were not quantified. We used six years of premarital screening data to estimate the burden of sickle disease and β-thalassemia over the program period and to assess the frequency of at-risk marriage detection and prevention. Retrospective review, premarital couples attending premarital and genetic counseling clinics with marriage proposals between 2004 and 2009. Blood samples obtained from all couples with marriage proposals between 2004 and 2009 were tested for sickle cell disease and β-thalassemia. Test results were shared with all examinees and genetic counseling was offered for all at-risk couples. Marriage certificates were issued irrespective of the results and compliance with medical advice was voluntary. Out of all men and women examined, 70,962 (4.5%) and 29,006 (1.8%) were carriers or cases of sickle cell disease and β-thalassemia, respectively. While the prevalence of sickle cell disease was constant between 2004 and 2009 (average 45.1 per 1000 examined persons, P=.803), the prevalence of β-thalassemia steadily decreased from 32.9 to 9.0 per 1000 examined persons (Ppremarital screening in Saudi Arabia markedly reduced the number of at-risk marriages, which may considerably reduce the genetic disease burden in Saudi Arabia in the next decades.

  3. The "Plant Drosophila": E.B. Babcock, the genus "Crepis," and the evolution of a genetics research program at Berkeley, 1915-1947.

    Science.gov (United States)

    Smocovitis, Vassiliki Betty

    2009-01-01

    This paper explores the research and administrative efforts of Ernest Brown Babcock, head of the Division of Genetics in the College of Agriculture at the University of California, Berkeley, the first academic unit so named in the United States. It explores the rationale for his choice of "model organism," the development--and transformation--of his ambitious genetics research program centering on the weedy plant genus named "Crepis" (commonly known as the hawkbeard), along with examining in detail the historical development of the understanding of genetic mechanisms of evolutionary change in plants leading to the period of the evolutionary synthesis. Chosen initially as the plant counterpart of Thomas Hunt Morgan's "Drosophila melanogaster," the genus "Crepis" instead came to serve as the counterpart of Theodosius Dobzhansky's "Drosophila pseudoobscura," leading the way in plant evolutionary genetics, and eventually providing the first comprehensive systematic treatise of any genus that was part of the movement known as biosystematics, or the "new" systematics. The paper also suggests a historical rethinking of the application of the terms model organism, research program, and experimental system in the history of biology.

  4. The Root Hair Assay Facilitates the Use of Genetic and Pharmacological Tools in Order to Dissect Multiple Signalling Pathways That Lead to Programmed Cell Death

    OpenAIRE

    Joanna Kacprzyk; Aoife Devine; McCabe, Paul F.

    2014-01-01

    The activation of programmed cell death (PCD) is often a result of complex signalling pathways whose relationship and intersection are not well understood. We recently described a PCD root hair assay and proposed that it could be used to rapidly screen genetic or pharmacological modulators of PCD. To further assess the applicability of the root hair assay for studying multiple signalling pathways leading to PCD activation we have investigated the crosstalk between salicylic acid, autophagy an...

  5. Within a smoking-cessation program, what impact does genetic information on lung cancer need to have to demonstrate cost-effectiveness?

    Science.gov (United States)

    Gordon, Louisa G; Hirst, Nicholas G; Young, Robert P; Brown, Paul M

    2010-09-16

    Many smoking-cessation programs and pharmaceutical aids demonstrate substantial health gains for a relatively low allocation of resources. Genetic information represents a type of individualized or personal feedback regarding the risk of developing lung cancer, and hence the potential benefits from stopping smoking, may motivate the person to remain smoke-free. The purpose of this study was to explore what the impact of a genetic test needs to have within a typical smoking-cessation program aimed at heavy smokers in order to be cost-effective. Two strategies were modelled for a hypothetical cohort of heavy smokers aged 50 years; individuals either received or did not receive a genetic test within the course of a usual smoking-cessation intervention comprising nicotine replacement therapy (NRT) and counselling. A Markov model was constructed using evidence from published randomized controlled trials and meta-analyses for estimates on 12-month quit rates and long-term relapse rates. Epidemiological data were used for estimates on lung cancer risk stratified by time since quitting and smoking patterns. Extensive sensitivity analyses were used to explore parameter uncertainty. The discounted incremental cost per QALY was AU$34,687 (95% CI $12,483, $87,734) over 35 years. At a willingness-to-pay of AU$20,000 per QALY gained, the genetic testing strategy needs to produce a 12-month quit rate of at least 12.4% or a relapse rate 12% lower than NRT and counselling alone for it to be equally cost-effective. The likelihood that adding a genetic test to the usual smoking-cessation intervention is cost-effective was 20.6% however cost-effectiveness ratios were favourable in certain situations (e.g., applied to men only, a 60 year old cohort). The findings were sensitive to small changes in critical variables such as the 12-month quit rates and relapse rates. As such, the cost-effectiveness of the genetic testing smoking cessation program is uncertain. Further clinical research

  6. An Ensemble Empirical Mode Decomposition, Self-Organizing Map, and Linear Genetic Programming Approach for Forecasting River Streamflow

    Directory of Open Access Journals (Sweden)

    Jonathan T. Barge

    2016-06-01

    Full Text Available This study focused on employing Linear Genetic Programming (LGP, Ensemble Empirical Mode Decomposition (EEMD, and the Self-Organizing Map (SOM in modeling the rainfall–runoff relationship in a mid-size catchment. Models were assessed with regard to their ability to capture daily discharge at Lock and Dam 10 along the Kentucky River as well as the hybrid design of EEM-SOM-LGP to make predictions multiple time-steps ahead. Different model designs were implemented to demonstrate the improvements of hybrid designs compared to LGP as a standalone application. Additionally, LGP was utilized to gain a better understanding of the catchment in question and to assess its ability to capture different aspects of the flow hydrograph. As a standalone application, LGP was able to outperform published Artificial Neural Network (ANN results over the same dataset, posting an average absolute relative error (AARE of 17.118 and Nash-Sutcliff (E of 0.937. Utilizing EEMD derived IMF runoff subcomponents for forecasting daily discharge resulted in an AARE of 14.232 and E of 0.981. Clustering the EEMD-derived input space through an SOM before LGP application returned the strongest results, posting an AARE of 10.122 and E of 0.987. Applying LGP to the distinctive low and high flow seasons demonstrated a loss in correlation for the low flow season with an under-predictive nature signified by a normalized mean biased error (NMBE of −2.353. Separating the rising and falling trends of the hydrograph showed that the falling trends were more easily captured with an AARE of 8.511 and E of 0.968 compared to the rising trends AARE of 38.744 and E of 0.948. Utilizing the EEMD-SOM-LGP design to make predictions multiple-time-steps ahead resulted in a AARE of 43.365 and E of 0.902 for predicting streamflow three days ahead. The results demonstrate the effectiveness of utilizing EEMD and an SOM in conjunction with LGP for streamflow forecasting.

  7. Estimation of nonadditive genetic impacts on lifetime performance through a grading-up breeding program with Holstein-Friesian

    Directory of Open Access Journals (Sweden)

    Zsolt Nemes

    2014-11-01

    Full Text Available The aim of this study was to estimate the total lifetime milk production and non additive genetic effects (recombination and heterosis of cows with different proportions of Holstein-Friesian genes, obtained from the Serbian Fleckvieh (SF and the Holstein-Friesian (HF crossbreeding program in Vojvodina. Upgrading of local breeds with the Holstein-Friesian breed in Vojvodina started in 1971 and continued 2008. Six genotypes of cows (F1, R1, R2, R3, R4, R5 were obtained with increasing percentage of Holstein genes, in order to attain purebred Holstein cows. Of all obtained genotypes, cows of genotype R4 with a proportion of Holstein genes from 96.87 % had the highest lifetime milk production (20000 kg, followed by cows R3 with 19950 kg (93.75 % HF genes and cows R5 with 19850 kg (98.44 % HF genes. Finally the process of upgrading resulted in pure Holsteins with 19780 kg of milk. The total lifetime production of milk fat did not show statistically significant difference (P>0.05 among the genotypes R1 - R5 which ranged from 675 to 690 kg. The pure Holstein obtained after sixth intermediate generations had the average lifetime milk fat production of 690 kg. With the increase in the proportion of Holstein-Friesian genes percentage of milk fat was decreased, so that the cows of genotypes R3, R4, R5 and pure Holsteins, had less than 3.5 % milk fat. In relation to the total milk yield, the highest realized heterosis effect was observed in the cows of F1 generation (hRF1=594 kg, while the lowest was observed in generation R2 (hRR2=72 kg, where negative effect of recombination was also found (hIR2=-77 kg. Positive values of the actual and relative of heterosis effect of the milk fat yield was observed in all genotypes, whereas the negative heterosis effect of the milk fat percentage was observed also in all genotypes, with the exception of R1 and R2 cows, in which the typical consequence of the positive recombination in the early crossed Holstein

  8. Comparison of deterministically predicted genetic gains with those realised in a South African Eucalyptus grandis breeding program

    CSIR Research Space (South Africa)

    Verryn, SD

    2009-06-01

    Full Text Available Tree breeders attempt to predict the genetic gains that are likely to be achieved through selection and breeding of new generations, using stochastic or deterministic modelling. There are many factors that may cause a discrepancy between...

  9. Linear Programming and Genetic Algorithm Based Optimization for the Weighting Scheme of a Value Focused Thinking Hierarchy

    Science.gov (United States)

    2007-11-02

    scarce resources ( Bazaraa vii). The modeling capabilities linear programming provides has made it a success in many fields of study. Since the...Planning and Programming of Facility Construction Projects. 12 May 1994. Bazaraa , Mokhtar S., John J Jarvis and Hanif D. Sherali. Linear Programming

  10. From the genetic to the computer program: the historicity of 'data' and 'computation' in the investigations on the nematode worm C. elegans (1963-1998).

    Science.gov (United States)

    García-Sancho, Miguel

    2012-03-01

    This paper argues that the history of the computer, of the practice of computation and of the notions of 'data' and 'programme' are essential for a critical account of the emergence and implications of data-driven research. In order to show this, I focus on the transition that the investigations on the worm C. elegans experienced in the Laboratory of Molecular Biology of Cambridge (UK). Throughout the 1980s, this research programme evolved from a study of the genetic basis of the worm's development and behaviour to a DNA mapping and sequencing initiative. By examining the changing computing technologies which were used at the Laboratory, I demonstrate that by the time of this transition researchers shifted from modelling the worm's genetic programme on a mainframe apparatus to writing minicomputer programs aimed at providing map and sequence data which was then circulated to other groups working on the genetics of C. elegans. The shift in the worm research should thus not be simply explained in the application of computers which transformed the project from hypothesis-driven to a data-intensive endeavour. The key factor was rather a historically specific technology-in-house and easy programmable minicomputers-which redefined the way of achieving the project's long-standing goal, leading the genetic programme to co-evolve with the practices of data production and distribution.

  11. Optimizing the creation of base populations for aquaculture breeding programs using phenotypic and genomic data and its consequences on genetic progress.

    Science.gov (United States)

    Fernández, Jesús; Toro, Miguel Á; Sonesson, Anna K; Villanueva, Beatriz

    2014-01-01

    The success of an aquaculture breeding program critically depends on the way in which the base population of breeders is constructed since all the genetic variability for the traits included originally in the breeding goal as well as those to be included in the future is contained in the initial founders. Traditionally, base populations were created from a number of wild strains by sampling equal numbers from each strain. However, for some aquaculture species improved strains are already available and, therefore, mean phenotypic values for economically important traits can be used as a criterion to optimize the sampling when creating base populations. Also, the increasing availability of genome-wide genotype information in aquaculture species could help to refine the estimation of relationships within and between candidate strains and, thus, to optimize the percentage of individuals to be sampled from each strain. This study explores the advantages of using phenotypic and genome-wide information when constructing base populations for aquaculture breeding programs in terms of initial and subsequent trait performance and genetic diversity level. Results show that a compromise solution between diversity and performance can be found when creating base populations. Up to 6% higher levels of phenotypic performance can be achieved at the same level of global diversity in the base population by optimizing the selection of breeders instead of sampling equal numbers from each strain. The higher performance observed in the base population persisted during 10 generations of phenotypic selection applied in the subsequent breeding program.

  12. Optimizing the creation of base populations for aquaculture breeding programs using phenotypic and genomic data and its consequences on genetic progress

    Directory of Open Access Journals (Sweden)

    Jesús eFernández

    2014-11-01

    Full Text Available The success of an aquaculture breeding program critically depends on the way in which the base population of breeders is constructed since all the genetic variability for the traits included originally in the breeding goal as well as those to be included in the future is contained in those initial founders. Traditionally base populations were created from a number of wild strains by sampling equal numbers from each strain. However, for some aquaculture species improved strains are already available and therefore, mean phenotypic values for economically important traits can be used as a criterion to optimize the sampling when creating base populations. Also, the increasing availability of genome-wide genotype information in aquaculture species could help to refine the estimation of relationships within and between candidate strains and, thus, to optimize the percentage of individuals to be sampled from each strain. This study explores the advantages of using phenotypic and genome-wide information when constructing base populations for aquaculture breeding programs in terms of initial and subsequent trait performance and genetic diversity level. Results show that a compromise solution between diversity and performance can be found when creating base populations. Up to 6% higher levels of phenotypic performance can be achieved at the same level of global diversity in the base population by optimizing the selection of breeders instead of sampling equal numbers from each strain. The higher performance observed in the base population persisted during ten generations of phenotypic selection applied in the subsequent breeding program.

  13. Infrastructure and Educational Needs of Newborn Screening Short-Term Follow-Up Programs within the Southeast Regional Newborn Screening & Genetics Collaborative: A Pilot Survey

    Directory of Open Access Journals (Sweden)

    Cecelia A. Bellcross

    2015-10-01

    Full Text Available Newborn screening (NBS follow-up protocols vary significantly by state, and there is a need to better understand the infrastructure and communication flow of NBS programs. In addition, assessment of the educational needs of families and providers with regard to the implications of NBS results is required to inform the development of appropriate informational resources and training opportunities. To begin to address these issues, we administered a web-based survey to state NBS coordinators within the Southeast Regional Newborn Screening & Genetics Collaborative (SERC. Fourteen coordinators responded to the survey, including at least one from each of the 10 SERC states/territories. Over one-third of respondents had never received formal training regarding the metabolic conditions identified on NBS. Most communicated results via telephone or fax, though two centers indicated use of a web-based platform. Only two programs were involved in directly reporting results to the family. Four programs reported a long-term follow-up protocol. Deficits were noted for primary care provider (PCP knowledge of metabolic disorders identified on NBS, and how to inform parents of abnormal results. Close to half indicated that the adequacy of the number of genetic counselors, dietitians, and medical/biochemical geneticists was minimal to insufficient. Respondents uniformly recognized the importance of providing additional educational and informational resources in multiple categories to NBS staff, PCPs, and families.

  14. Combining Diffusion Models and Macroeconomic Indicators with a Modified Genetic Programming Method: Implementation in Forecasting the Number of Mobile Telecommunications Subscribers in OECD Countries

    Directory of Open Access Journals (Sweden)

    Konstantinos Salpasaranis

    2014-01-01

    Full Text Available This paper proposes a modified Genetic Programming method for forecasting the mobile telecommunications subscribers’ population. The method constitutes an expansion of the hybrid Genetic Programming (hGP method improved by the introduction of diffusion models for technological forecasting purposes in the initial population, such as the Logistic, Gompertz, and Bass, as well as the Bi-Logistic and LogInLog. In addition, the aforementioned functions and models expand the function set of hGP. The application of the method in combination with macroeconomic indicators such as Gross Domestic Product per Capita (GDPpC and Consumer Prices Index (CPI leads to the creation of forecasting models and scenarios for medium- and long-term level of predictability. The forecasting module of the program has also been improved with the multi-levelled use of the statistical indices as fitness functions and model selection indices. The implementation of the modified-hGP in the datasets of mobile subscribers in the Organisation for Economic Cooperation and Development (OECD countries shows very satisfactory forecasting performance.

  15. Genetics as a modernization program: biological research at the Kaiser Wilhelm Institutes and the political economy of the Nazi State.

    Science.gov (United States)

    Gausemeier, Bernd

    2010-01-01

    During the Third Reich, the biological institutes of the Kaiser Wilhelm Society (KWG, Kaiser-Wilhelm-Gesellschaft) underwent a substantial reorganization and modernization. This paper discusses the development of projects in the fields of biochemical genetics, virus research, radiation genetics, and plant genetics that were initiated in those years. These cases exemplify, on the one hand, the political conditions for biological research in the Nazi state. They highlight how leading scientists advanced their projects by building close ties with politicians and science-funding organizations and companies. On the other hand, the study examines how the contents of research were shaped by, and how they contributed to, the aims and needs of the political economy of the Nazi system. This paper therefore aims not only to highlight basic aspects of scientific development under Nazism, but also to provide general insights into the structure of the Third Reich and the dynamics of its war economy.

  16. Overlaps in the Transcriptional Profiles of Medicago truncatula Roots Inoculated with Two Different Glomus Fungi Provide Insights into the Genetic Program Activated during Arbuscular Mycorrhiza1[w

    Science.gov (United States)

    Hohnjec, Natalija; Vieweg, Martin F.; Pühler, Alfred; Becker, Anke; Küster, Helge

    2005-01-01

    Arbuscular mycorrhiza (AM) is a widespread symbiotic association between plants and fungal microsymbionts that supports plant development under nutrient-limiting and various stress conditions. In this study, we focused on the overlapping genetic program activated by two commonly studied microsymbionts in addition to identifying AM-related genes. We thus applied 16,086 probe microarrays to profile the transcriptome of the model legume Medicago truncatula during interactions with Glomus mosseae and Glomus intraradices and specified a total of 201 plant genes as significantly coinduced at least 2-fold, with more than 160 being reported as AM induced for the first time. Several hundred genes were additionally up-regulated during a sole interaction, indicating that the plant genetic program activated in AM to some extent depends on the colonizing microsymbiont. Genes induced during both interactions specified AM-related nitrate, ion, and sugar transporters, enzymes involved in secondary metabolism, proteases, and Kunitz-type protease inhibitors. Furthermore, coinduced genes encoded receptor kinases and other components of signal transduction pathways as well as AM-induced transcriptional regulators, thus reflecting changes in signaling. By the use of reporter gene expression, we demonstrated that one member of the AM-induced gene family encoding blue copper binding proteins (MtBcp1) was both specifically and strongly up-regulated in arbuscule-containing regions of mycorrhizal roots. A comparison of the AM expression profiles to those of nitrogen-fixing root nodules suggested only a limited overlap between the genetic programs orchestrating root endosymbioses. PMID:15778460

  17. Genetic and Environmental Variance Among F2 Families in a Commercial Breeding Program for Perennial Ryegrass (Lolium perenne L.)

    DEFF Research Database (Denmark)

    Fé, Dario; Greve-Pedersen, Morten; Jensen, Christian Sig

    2013-01-01

    In the joint project “FORAGESELECT”, we aim to implement Genome Wide Selection (GWS) in breeding of perennial ryegrass (Lolium perenne L.), in order to increase genetic response in important agronomic traits such as yield, seed production, stress tolerance and disease resistance, while decreasing...... of this study was to estimate the genetic and environmental variance in the training set composed of F2 families selected from a ten year breeding period. Variance components were estimated on 1193 of those families, sown in 2001, 2003 and 2005 in five locations around Europe. Families were tested together...

  18. Lifestyle and Metformin Ameliorate Insulin Sensitivity Independently of the Genetic Burden of Established Insulin Resistance Variants in Diabetes Prevention Program Participants.

    Science.gov (United States)

    Hivert, Marie-France; Christophi, Costas A; Franks, Paul W; Jablonski, Kathleen A; Ehrmann, David A; Kahn, Steven E; Horton, Edward S; Pollin, Toni I; Mather, Kieren J; Perreault, Leigh; Barrett-Connor, Elizabeth; Knowler, William C; Florez, Jose C

    2016-02-01

    Large genome-wide association studies of glycemic traits have identified genetics variants that are associated with insulin resistance (IR) in the general population. It is unknown whether people with genetic enrichment for these IR variants respond differently to interventions that aim to improve insulin sensitivity. We built a genetic risk score (GRS) based on 17 established IR variants and effect sizes (weighted IR-GRS) in 2,713 participants of the Diabetes Prevention Program (DPP) with genetic consent. We tested associations between the weighted IR-GRS and insulin sensitivity index (ISI) at baseline in all participants, and with change in ISI over 1 year of follow-up in the DPP intervention (metformin and lifestyle) and control (placebo) arms. All models were adjusted for age, sex, ethnicity, and waist circumference at baseline (plus baseline ISI for 1-year ISI change models). A higher IR-GRS was associated with lower baseline ISI (β = -0.754 [SE = 0.229] log-ISI per unit, P = 0.001 in fully adjusted models). There was no differential effect of treatment for the association between the IR-GRS on the change in ISI; higher IR-GRS was associated with an attenuation in ISI improvement over 1 year (β = -0.520 [SE = 0.233], P = 0.03 in fully adjusted models; all treatment arms). Lifestyle intervention and metformin treatment improved the ISI, regardless of the genetic burden of IR variants. © 2016 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

  19. Genetic Differentiation in Native and Introduced Populations of Cryptolaemus montrouzieri (Coleoptera: Coccinellidae) and Its Implications for Biological Control Programs.

    Science.gov (United States)

    Li, Hao-Sen; Jin, Meng-Jie; Ślipiński, Adam; De Clercq, Patrick; Pang, Hong

    2015-10-01

    Cryptolaemus montrouzieri Mulsant (Coleoptera: Coccinellidae) is an effective biological control agent of Australian origin, which has been introduced worldwide to control mealybugs. Although successfully used for >100 yr, its introduction in a new area may cause environmental risks should the populations become invasive. In the present study, a population genetics method was used to make predictions of the invasive potential of C. montrouzieri. Our results showed a similar level of genetic diversity among all populations. No significant genetic differentiation between native and introduced populations was observed, while three populations from the native region were significantly divergent. The fact that genetic diversity was not reduced in introduced areas suggests that no bottleneck effect has occurred during introduction. To avoid rapid evolution of the introduced C. montrouzieri, the introduction records of each population should be clearly traced and introductions from multiple sources into the same area should be avoided. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  20. Session 6: Infant nutrition: future research developments in Europe EARNEST, the early nutrition programming project: EARly Nutrition programming - long-term Efficacy and Safety Trials and integrated epidemiological, genetic, animal, consumer and economic research.

    Science.gov (United States)

    Fewtrell, M S

    2007-08-01

    Increasing evidence from lifetime experimental studies in animals and observational and experimental studies in human subjects suggests that pre- and postnatal nutrition programme long-term health. However, key unanswered questions remain on the extent of early-life programming in contemporary European populations, relevant nutritional exposures, critical time periods, mechanisms and the effectiveness of interventions to prevent or reverse programming effects. The EARly Nutrition programming - long-term Efficacy and Safety Trials and integrated epidemiological, genetic, animal, consumer and economic research (EARNEST) consortium brings together a multi-disciplinary team of scientists from European research institutions in an integrated programme of work that includes experimental studies in human subjects, modern prospective observational studies and mechanistic animal work including physiological studies, cell-culture models and molecular techniques. Theme 1 tests early nutritional programming of disease in human subjects, measuring disease markers in childhood and early adulthood in nineteen randomised controlled trials of nutritional interventions in pregnancy and infancy. Theme 2 examines associations between early nutrition and later outcomes in large modern European population-based prospective studies, with detailed measures of diet in pregnancy and early life. Theme 3 uses animal, cellular and molecular techniques to study lifetime effects of early nutrition. Biomedical studies are complemented by studies of the social and economic importance of programming (themes 4 and 5), and themes encouraging integration, communication, training and wealth creation. The project aims to: help formulate policies on the composition and testing of infant foods; improve the nutritional value of infant formulas; identify interventions to prevent and reverse adverse early nutritional programming. In addition, it has the potential to develop new products through industrial

  1. Peking University Center of Medical Genetics (PUCMG): a comprehensive medical genetics program in China%中国医学遗传综合项目基地--北京大学医学遗传中心

    Institute of Scientific and Technical Information of China (English)

    Nanbert ZHONG

    2006-01-01

    @@ Medical genetics, as an important component in the advanced medical practice, has touched in variant aspects of clinical aspects. Globally, in both developed and developing countries, medical genetics is playing more and more important roles in dealing with the public healthcare. Being a medical specialty performing diagnosis and intervention for genetic disorders, the medical genetics has bridged the clinical practice and basic medical sciences. It is derived, but different, from human genetics. The difference of which is that the medical genetics provides clinical service for medical professionals and patients; however, the human genetics focuses on investigation of genetic principles.

  2. The Italian National External Quality Assessment Program in Molecular Genetic Testing: Results of the VII Round (2010-2011

    Directory of Open Access Journals (Sweden)

    F. Censi

    2013-01-01

    Full Text Available Since 2001 the Istituto Superiore di Sanità established a quality assurance programme for molecular genetic testing that covers four pathologies: Cystic Fibrosis (CF, Beta Thalassemia (BT, Fragile X Syndrome (FX, and Familial Adenomatous Polyposis Coli (APC. Since 2009 this activity is an institutional activity and participation is open to both public and private laboratories. Seven rounds have been performed until now and the eighth is in progress. Laboratories receive 4 DNA samples with mock clinical indications. They analyze the samples using their routine procedures. A panel of assessors review the raw data and the reports; all data are managed through a web utility. In 2010 the number of participants was 43, 17, 15, 5 for CF, BT, FX, APC schemes respectively. Genotyping results were correct in 96%, 98.5%, 100%, and 100% of CF, BT, FX, and APC samples, respectively. Interpretation was correct in 74%, 91%, 88%, and 60% of CF, BT, FX, and APC reports, respectively; however in most of them it was not complete but a referral to genetic counseling was given. Reports were satisfactory in more than 60% of samples in all schemes. This work presents the 2010 results in detail comparing our data with those from other European schemes.

  3. Genetic Discrimination

    Science.gov (United States)

    ... in Genetics Archive Regulation of Genetic Tests Genetic Discrimination Overview Many Americans fear that participating in research ... I) and employment (Title II). Read more Genetic Discrimination and Other Laws Genetic Discrimination and Other Laws ...

  4. Influence of Nitrogen-di-Oxide, Temperature and Relative Humidity on Surface Ozone Modeling Process Using Multigene Symbolic Regression Genetic Programming

    Directory of Open Access Journals (Sweden)

    Alaa F. Sheta

    2015-06-01

    Full Text Available Automatic monitoring, data collection, analysis and prediction of environmental changes is essential for all living things. Understanding future climate changes does not only helps in measuring the influence on people life, habits, agricultural and health but also helps in avoiding disasters. Giving the high emission of chemicals on air, scientist discovered the growing depletion in ozone layer. This causes a serious environmental problem. Modeling and observing changes in the Ozone layer have been studied in the past. Understanding the dynamics of the pollutants features that influence Ozone is ex-plored in this article. A short term prediction model for surface Ozone is offered using Multigene Symbolic Regression Genetic Programming (GP. The proposed model customs Nitrogen-di-Oxide, Temperature and Relative Humidity as the main features to predict the Ozone level. Moreover, a comparison between GP and Artificial Neural Network (ANN in modeling Ozone is presented. The developed results show that GP outperform the ANN.

  5. Predicting High or Low Transfer Efficiency of Photovoltaic Systems Using a Novel Hybrid Methodology Combining Rough Set Theory, Data Envelopment Analysis and Genetic Programming

    Directory of Open Access Journals (Sweden)

    Lee-Ing Tong

    2012-02-01

    Full Text Available Solar energy has become an important energy source in recent years as it generates less pollution than other energies. A photovoltaic (PV system, which typically has many components, converts solar energy into electrical energy. With the development of advanced engineering technologies, the transfer efficiency of a PV system has been increased from low to high. The combination of components in a PV system influences its transfer efficiency. Therefore, when predicting the transfer efficiency of a PV system, one must consider the relationship among system components. This work accurately predicts whether transfer efficiency of a PV system is high or low using a novel hybrid model that combines rough set theory (RST, data envelopment analysis (DEA, and genetic programming (GP. Finally, real data-set are utilized to demonstrate the accuracy of the proposed method.

  6. Genetic predictors of weight loss and weight regain after intensive lifestyle modification, metformin treatment, or standard care in the Diabetes Prevention Program.

    Science.gov (United States)

    Delahanty, Linda M; Pan, Qing; Jablonski, Kathleen A; Watson, Karol E; McCaffery, Jeanne M; Shuldiner, Alan; Kahn, Steven E; Knowler, William C; Florez, Jose C; Franks, Paul W

    2012-02-01

    We tested genetic associations with weight loss and weight regain in the Diabetes Prevention Program, a randomized controlled trial of weight loss-inducing interventions (lifestyle and metformin) versus placebo. Sixteen obesity-predisposing single nucleotide polymorphisms (SNPs) were tested for association with short-term (baseline to 6 months) and long-term (baseline to 2 years) weight loss and weight regain (6 months to study end). Irrespective of treatment, the Ala12 allele at PPARG associated with short- and long-term weight loss (-0.63 and -0.93 kg/allele, P ≤ 0.005, respectively). Gene-treatment interactions were observed for short-term (LYPLAL1 rs2605100, P(lifestyle*SNP) = 0.032; GNPDA2 rs10938397, P(lifestyle*SNP) = 0.016; MTCH2 rs10838738, P(lifestyle*SNP) = 0.022) and long-term (NEGR1 rs2815752, P(metformin*SNP) = 0.028; FTO rs9939609, P(lifestyle*SNP) = 0.044) weight loss. Three of 16 SNPs were associated with weight regain (NEGR1 rs2815752, BDNF rs6265, PPARG rs1801282), irrespective of treatment. TMEM18 rs6548238 and KTCD15 rs29941 showed treatment-specific effects (P(lifestyle*SNP) < 0.05). Genetic information may help identify people who require additional support to maintain reduced weight after clinical intervention.

  7. [Reliability of electron-transport membranes and the role of oxygen anion-radicals in aging: stochastic modulation of the genetic program].

    Science.gov (United States)

    Kol'tover, V K

    2010-01-01

    All biomolecular constructions and nanorecators are designed to perform preset functions. All of them operate with limited reliability, namely, for each and every device or bionanoreactor normal operation alternates with accidental malfunctions (failures). Timely preventive maintenance replacement (prophylaxis) of functional elements in cells and tissues, the so-called turnover, is the main line of assuring high system reliability of organism as a whole. There is a finite number of special groups of genes (reliability assuring structures, RAS) that perform supervisory functions over the preventive maintenance. In a hierarchic pluricellular organism, RAS are genetic regulatory networks of a special group of cells, like hypothalamic neurons in the suprachiasmatic nucleus of mammals. Of the primary importance is limited reliability of mitochondrial nanoreactors, since the random malfunctions of electron transport chains produce reactive anion-radicals of oxygen (superoxide radical, O2*(-)). With time, O2*(-) radicals initiate accumulation of irreparable damages in RAS. When these damages accumulate up to preset threshold level, a fatal decrease in reliability of RAS occurs. Thus, aging is the stochastic consequence of programmed deficiency in reliability of biomolecular constructions and nanoreactors including the genetically preset limit of the system reliability. This reliability approach provides the realistic explanation of the data on prolongation of life of experimental animals with antioxidants as well as the explanation of similar "hormetic" effects of ionizing radiation in low doses.

  8. Giant Galápagos tortoises; molecular genetic analyses identify a trans-island hybrid in a repatriation program of an endangered taxon

    Directory of Open Access Journals (Sweden)

    Caccone Adalgisa

    2007-02-01

    Full Text Available Abstract Background Giant Galápagos tortoises on the island of Española have been the focus of an intensive captive breeding-repatriation programme for over 35 years that saved the taxon from extinction. However, analysis of 118 samples from released individuals indicated that the bias sex ratio and large variance in reproductive success among the 15 breeders has severely reduced the effective population size (Ne. Results We report here that an analysis of an additional 473 captive-bred tortoises released back to the island reveals an individual (E1465 that exhibits nuclear microsatellite alleles not found in any of the 15 breeders. Statistical analyses incorporating genotypes of 304 field-sampled individuals from all populations on the major islands indicate that E1465 is most probably a hybrid between an Española female tortoise and a male from the island of Pinzón, likely present on Española due to human transport. Conclusion Removal of E1465 as well as its father and possible (half-siblings is warranted to prevent further contamination within this taxon of particular conservation significance. Despite this detected single contamination, it is highly noteworthy to emphasize the success of this repatriation program conducted over nearly 40 years and involving release of over 2000 captive-bred tortoises that now reproduce in situ. The incorporation of molecular genetic analysis of the program is providing guidance that will aid in monitoring the genetic integrity of this ambitious effort to restore a unique linage of a spectacular animal.

  9. Transcriptomic evidence for the evolution of shoot meristem function in sporophyte-dominant land plants through concerted selection of ancestral gametophytic and sporophytic genetic programs.

    Science.gov (United States)

    Frank, Margaret H; Scanlon, Michael J

    2015-02-01

    Alternation of generations, in which the haploid and diploid stages of the life cycle are each represented by multicellular forms that differ in their morphology, is a defining feature of the land plants (embryophytes). Anciently derived lineages of embryophytes grow predominately in the haploid gametophytic generation from apical cells that give rise to the photosynthetic body of the plant. More recently evolved plant lineages have multicellular shoot apical meristems (SAMs), and photosynthetic shoot development is restricted to the sporophyte generation. The molecular genetic basis for this evolutionary shift from gametophyte-dominant to sporophyte-dominant life cycles remains a major question in the study of land plant evolution. We used laser microdissection and next generation RNA sequencing to address whether angiosperm meristem patterning genes expressed in the sporophytic SAM of Zea mays are expressed in the gametophytic apical cells, or in the determinate sporophytes, of the model bryophytes Marchantia polymorpha and Physcomitrella patens. A wealth of upregulated genes involved in stem cell maintenance and organogenesis are identified in the maize SAM and in both the gametophytic apical cell and sporophyte of moss, but not in Marchantia. Significantly, meiosis-specific genetic programs are expressed in bryophyte sporophytes, long before the onset of sporogenesis. Our data suggest that this upregulated accumulation of meiotic gene transcripts suppresses indeterminate cell fate in the Physcomitrella sporophyte, and overrides the observed accumulation of meristem patterning genes. A model for the evolution of indeterminate growth in the sporophytic generation through the concerted selection of ancestral meristem gene programs from gametophyte-dominant lineages is proposed. © The Author 2014. 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.

  10. Allele-specific programming of Npy and epigenetic effects of physical activity in a genetic model of depression.

    Science.gov (United States)

    Melas, P A; Lennartsson, A; Vakifahmetoglu-Norberg, H; Wei, Y; Åberg, E; Werme, M; Rogdaki, M; Mannervik, M; Wegener, G; Brené, S; Mathé, A A; Lavebratt, C

    2013-05-07

    Neuropeptide Y (NPY) has been implicated in depression, emotional processing and stress response. Part of this evidence originates from human single-nucleotide polymorphism (SNP) studies. In the present study, we report that a SNP in the rat Npy promoter (C/T; rs105431668) affects in vitro transcription and DNA-protein interactions. Genotyping studies showed that the C-allele of rs105431668 is present in a genetic rat model of depression (Flinders sensitive line; FSL), while the SNP's T-allele is present in its controls (Flinders resistant line; FRL). In vivo experiments revealed binding of a transcription factor (CREB2) and a histone acetyltransferase (Ep300) only at the SNP locus of the FRL. Accordingly, the FRL had increased hippocampal levels of Npy mRNA and H3K18 acetylation; a gene-activating histone modification maintained by Ep300. Next, based on previous studies showing antidepressant-like effects of physical activity in the FSL, we hypothesized that physical activity may affect Npy's epigenetic status. In line with this assumption, physical activity was associated with increased levels of Npy mRNA and H3K18 acetylation. Physical activity was also associated with reduced mRNA levels of a histone deacetylase (Hdac5). Conclusively, the rat rs105431668 appears to be a functional Npy SNP that may underlie depression-like characteristics. In addition, the achieved epigenetic reprogramming of Npy provides molecular support for the putative effectiveness of physical activity as a non-pharmacological antidepressant.

  11. O Programa Brasileiro de genética evolucionária de populações, de Theodosius Dobzhansky Theodosius Dobzhansky's Brazilian program of evolutionary population genetics

    Directory of Open Access Journals (Sweden)

    Thomas F. Glick

    2008-01-01

    Full Text Available Nas décadas de 1940 e 1950, a Fundação Rockefeller estabeleceu um programa para o desenvolvimento da genética de populações na Universidade de São Paulo, sob a direção do geneticista norte-americano Theodosius Dobzhansky, nascido na Rússia. O grande sucesso desse programa foi atribuído ao tipo de organização da pesquisa, realizada em grupos, prática introduzida por Dobzhansky. O presente artigo analisa essa conclusão, com base nas reminiscências do geneticista suíço Hans Burla, membro estrangeiro do grupo original de Dobzhansky.In the 1940s and 50s the Rockefeller Foundation established a program for the development of population genetics at the Universidade de São Paulo under the direction of the Russian/North American geneticist Theodosius Dobzhansky. The great success of this program was said to have been the result of the kind of research organization, in teams, that Dobzhansky introduced. An evaluation of this conclusion is analyzed, based on the reminiscence of the Swiss geneticist, Hans Burla, a foreign member of the original Dobzhansky group.

  12. Blockade of the programmed death-1 (PD1 pathway undermines potent genetic protection from type 1 diabetes.

    Directory of Open Access Journals (Sweden)

    Nora M Kochupurakkal

    Full Text Available AIMS/HYPOTHESIS: Inhibition of PD1-PDL1 signaling in NOD mice accelerates onset of type 1 diabetes implicating this pathway in suppressing the emergence of pancreatic beta cell reactive T-cells. However, the molecular mechanism by which PD1 signaling protects from type 1 diabetes is not clear. We hypothesized that differential susceptibility of Idd mouse strains to type 1 diabetes when challenged with anti PDL1 will identify genomic loci that collaborate with PD1 signaling in suppressing type 1 diabetes. METHODS: Anti PDL1 was administered to NOD and various Idd mouse strains at 10 weeks of age and onset of disease was monitored by measuring blood glucose levels. Additionally, histological evaluation of the pancreas was performed to determine degree of insulitis. Statistical analysis of the data was performed using Log-Rank and Student's t-test. RESULTS: Blockade of PDL1 rapidly precipitated type 1 diabetes in nearly all NOD Idd congenic strains tested, despite the fact that all are moderately (Idd5, Idd3 and Idd10/18 or highly (Idd3/10/18 and Idd9 protected from spontaneous type 1 diabetes by virtue of their protective Idd genes. Only the Idd3/5 strain, which is nearly 100% protected from spontaneous disease, remained normoglycemic following PDL1 blockade. CONCLUSIONS: These results indicate that multiple Idd loci collaborate with PD1 signaling. Anti PDL1 treatment undermines a large portion of the genetic protection mediated by Idd genes in the NOD model of type 1 diabetes. Basal insulitis correlated with higher susceptibility to type 1 diabetes. These findings have important implications since the PD1 pathway is a target for immunotherapy.

  13. Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows.

    Science.gov (United States)

    Excoffier, Laurent; Lischer, Heidi E L

    2010-05-01

    We present here a new version of the Arlequin program available under three different forms: a Windows graphical version (Winarl35), a console version of Arlequin (arlecore), and a specific console version to compute summary statistics (arlsumstat). The command-line versions run under both Linux and Windows. The main innovations of the new version include enhanced outputs in XML format, the possibility to embed graphics displaying computation results directly into output files, and the implementation of a new method to detect loci under selection from genome scans. Command-line versions are designed to handle large series of files, and arlsumstat can be used to generate summary statistics from simulated data sets within an Approximate Bayesian Computation framework.

  14. Genetic Sample Inventory

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This database archives genetic tissue samples from marine mammals collected primarily from the U.S. east coast. The collection includes samples from field programs,...

  15. Synthetic biology and genetic causation.

    Science.gov (United States)

    Oftedal, Gry; Parkkinen, Veli-Pekka

    2013-06-01

    Synthetic biology research is often described in terms of programming cells through the introduction of synthetic genes. Genetic material is seemingly attributed with a high level of causal responsibility. We discuss genetic causation in synthetic biology and distinguish three gene concepts differing in their assumptions of genetic control. We argue that synthetic biology generally employs a difference-making approach to establishing genetic causes, and that this approach does not commit to a specific notion of genetic program or genetic control. Still, we suggest that a strong program concept of genetic material can be used as a successful heuristic in certain areas of synthetic biology. Its application requires control of causal context, and may stand in need of a modular decomposition of the target system. We relate different modularity concepts to the discussion of genetic causation and point to possible advantages of and important limitations to seeking modularity in synthetic biology systems. Copyright © 2013 Elsevier Ltd. All rights reserved.

  16. New Genetics

    Science.gov (United States)

    ... Home > Science Education > The New Genetics The New Genetics Living Laboratories Classroom Poster Order a Free Copy ... Piece to a Century-Old Evolutionary Puzzle Computing Genetics Model Organisms RNA Interference The New Genetics is ...

  17. From observational to dynamic genetics

    Directory of Open Access Journals (Sweden)

    Claire M. A. Haworth

    2014-01-01

    Full Text Available Twin and family studies have shown that most traits are at least moderately heritable. But what are the implications of finding genetic influence for the design of intervention and prevention programs? For complex traits, heritability does not mean immutability, and research has shown that genetic influences can change with age, context and in response to behavioural and drug interventions. The most significant implications for intervention will come when we move from observational genetics to investigating dynamic genetics, including genetically sensitive interventions. Future interventions should be designed to overcome genetic risk and draw upon genetic strengths by changing the environment.

  18. Improved model reduction and tuning of fractional-order PI(λ)D(μ) controllers for analytical rule extraction with genetic programming.

    Science.gov (United States)

    Das, Saptarshi; Pan, Indranil; Das, Shantanu; Gupta, Amitava

    2012-03-01

    Genetic algorithm (GA) has been used in this study for a new approach of suboptimal model reduction in the Nyquist plane and optimal time domain tuning of proportional-integral-derivative (PID) and fractional-order (FO) PI(λ)D(μ) controllers. Simulation studies show that the new Nyquist-based model reduction technique outperforms the conventional H(2)-norm-based reduced parameter modeling technique. With the tuned controller parameters and reduced-order model parameter dataset, optimum tuning rules have been developed with a test-bench of higher-order processes via genetic programming (GP). The GP performs a symbolic regression on the reduced process parameters to evolve a tuning rule which provides the best analytical expression to map the data. The tuning rules are developed for a minimum time domain integral performance index described by a weighted sum of error index and controller effort. From the reported Pareto optimal front of the GP-based optimal rule extraction technique, a trade-off can be made between the complexity of the tuning formulae and the control performance. The efficacy of the single-gene and multi-gene GP-based tuning rules has been compared with the original GA-based control performance for the PID and PI(λ)D(μ) controllers, handling four different classes of representative higher-order processes. These rules are very useful for process control engineers, as they inherit the power of the GA-based tuning methodology, but can be easily calculated without the requirement for running the computationally intensive GA every time. Three-dimensional plots of the required variation in PID/fractional-order PID (FOPID) controller parameters with reduced process parameters have been shown as a guideline for the operator. Parametric robustness of the reported GP-based tuning rules has also been shown with credible simulation examples.

  19. The root hair assay facilitates the use of genetic and pharmacological tools in order to dissect multiple signalling pathways that lead to programmed cell death.

    Directory of Open Access Journals (Sweden)

    Joanna Kacprzyk

    Full Text Available The activation of programmed cell death (PCD is often a result of complex signalling pathways whose relationship and intersection are not well understood. We recently described a PCD root hair assay and proposed that it could be used to rapidly screen genetic or pharmacological modulators of PCD. To further assess the applicability of the root hair assay for studying multiple signalling pathways leading to PCD activation we have investigated the crosstalk between salicylic acid, autophagy and apoptosis-like PCD (AL-PCD in Arabidopsis thaliana. The root hair assay was used to determine rates of AL-PCD induced by a panel of cell death inducing treatments in wild type plants treated with chemical modulators of salicylic acid synthesis or autophagy, and in genetic lines defective in autophagy or salicylic acid signalling. The assay demonstrated that PCD induced by exogenous salicylic acid or fumonisin B1 displayed a requirement for salicylic acid signalling and was partially dependent on the salicylic acid signal transducer NPR1. Autophagy deficiency resulted in an increase in the rates of AL-PCD induced by salicylic acid and fumonisin B1, but not by gibberellic acid or abiotic stress. The phenylalanine ammonia lyase-dependent salicylic acid synthesis pathway contributed only to death induced by salicylic acid and fumonisin B1. 3-Methyladenine, which is commonly used as an inhibitor of autophagy, appeared to influence PCD induction in all treatments suggesting a possible secondary, non-autophagic, effect on a core component of the plant PCD pathway. The results suggest that salicylic acid signalling is negatively regulated by autophagy during salicylic acid and mycotoxin-induced AL-PCD. However, this crosstalk does not appear to be directly involved in PCD induced by gibberellic acid or abiotic stress. This study demonstrates that the root hair assay is an effective tool for relatively rapid investigation of complex signalling pathways leading to

  20. MILK PRODUCTION GENETIC IMPROVEMENT PROGRAM OF THE TRANSYLVANIAN PINZGAU BREED IN THE BIHOR, HUNEDOARA AND SUCEAVA COUNTIES

    Directory of Open Access Journals (Sweden)

    F. PAVEL

    2013-12-01

    Full Text Available Starting from the average values of productive performances gained by the activecows in the Bihor, Hunedoara and Suceava counties, there has been established agenetic improvement program for the milk production of Transylvanian Pinzgaubreed in the three counties. The morpho-productive parameters followed in themaking of the projected type of Transylvanian Pinzgau breed were: body weight 600kg, height at withers 135 cm, milk production 4500 kg, 3.9% fat, fat yield 175.5 kg,3.5% protein, protein yield 157.5 kg, average daily gain 1000 g, live weight at 500days of age 500 kg, killing out percentage 58%. To realize a production of 4500 kgof milk, starting from the active actual production, in the Bihor County will berequired 3.42 generations, in the Hunedoara County 1.4 generations and in Suceava1.56 generations. For realizing the selection objective of 175.5 kg fat from milk, inBihor County will be required 2.03 generations, in Hunedoara 0.95 generations andin Suceava 0.89 generations. The projected type of Transylvanian Pinzgau breeddoesn’t have to impair the rustic element, the resistance, the longevity and the abilityof movement through which this breed gained a specific exploitation habitat in anarea in which it is irreplaceable. The projected type of Transylvanian Pinzgau breedcan adapt to the mountain habitat and can represent one of the essential factors forthe long term development of mountain agriculture and agro-tourism, in thecondition that it will be sustained financially, imperative for the whole Romanianmountain area.

  1. 基于遗传规划的疾病鉴别诊断研究%Research of disease differential diagnosis based on Genetic Programming

    Institute of Scientific and Technical Information of China (English)

    马桂峰; 张惠卿; 周梅; 代学之; 孙永红; 盛红旗; 陈景武; 孙肖伟

    2010-01-01

    目的 对难以诊断为Graves病或Hashimotos病的患者之各项临床检查指标进行定量分析,构建函数模型,以对2种疾病做出正确诊断.方法 收集、整理2所三级甲等医院患者基础数据,引入遗传规划(Genetic Programming)法,借助MATLAB的GPLAB工具箱建立函数模型,对这2种疾病进行准确的鉴别诊断.结果 建立了疾病诊断的非线性模型,在临床实践中应用效果良好,能够有效的降低误诊率.结论 遗传规划法建立的非线形函数模型可以用作Graves病或Hashimotos病的鉴别诊断,有一定的推广价值和临床实践意义.

  2. Variance estimation between different body measurements at the females population from Romanian Mioritic Shepherd Dog breed, to develop a genetic improvement program

    Directory of Open Access Journals (Sweden)

    Dorel Dronca

    2016-05-01

    Full Text Available Romanian Mioritic Shepherd Dog, was selected from a natural population breed in Carpathian Mountains. The aim of this paper was to estimate variance at 12 body measurements using 23 females from Romanian Mioritic Shepherd Dog breed. The animals were registered with the Romanian Mioritic Association Club from Romania. In order to develop a genetic improvement program at this effective of 23 females from Romanian Sheperd Dog breed, found in evidence of Romanian Mioritic Association Club from Romania, should be considered the following conclusions on variance those 12 characters studied in this paper, respectively, there is a large variance for the height at the middle back, the height at the croup, the height at the base of the tail, the width of the croup, the length of the tail, the depth of the thorax, the thorax perimeter, the height of the elbow and  for the height at the withers, the body length and the height at the hocks, the variance is middle.

  3. Genetic algorithms

    Science.gov (United States)

    Wang, Lui; Bayer, Steven E.

    1991-01-01

    Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solving methods) based loosely on the processes of natural genetics and Darwinian survival of the fittest. Basic genetic algorithms concepts are introduced, genetic algorithm applications are introduced, and results are presented from a project to develop a software tool that will enable the widespread use of genetic algorithm technology.

  4. Genetic Mapping

    Science.gov (United States)

    ... Fact Sheets Fact Sheets En Español: Mapeo Genético Genetic Mapping What is genetic mapping? How do researchers create ... genetic map? What are genetic markers? What is genetic mapping? Among the main goals of the Human Genome ...

  5. Genetic toxicology: web resources.

    Science.gov (United States)

    Young, Robert R

    2002-04-25

    Genetic toxicology is the scientific discipline dealing with the effects of chemical, physical and biological agents on the heredity of living organisms. The Internet offers a wide range of online digital resources for the field of Genetic Toxicology. The history of genetic toxicology and electronic data collections are reviewed. Web-based resources at US National Library of Medicine (NLM), including MEDLINE, PUBMED, Gateway, Entrez, and TOXNET, are discussed. Search strategies and Medical Subject Headings (MeSH) are reviewed in the context of genetic toxicology. The TOXNET group of databases are discussed with emphasis on those databases with genetic toxicology content including GENE-TOX, TOXLINE, Hazardous Substances Data Bank, Integrated Risk Information System, and Chemical Carcinogenesis Research Information System. Location of chemical information including chemical structure and linkage to health and regulatory information using CHEMIDPLUS at NLM and other databases is reviewed. Various government agencies have active genetic toxicology research programs or use genetic toxicology data to assist fulfilling the agency's mission. Online resources at the US Food and Drug Administration (FDA), the US Environmental Protection Agency (EPA), the National Institutes of Environmental Health Sciences, and the National Toxicology Program (NTP) are outlined. Much of the genetic toxicology for pharmaceuticals, industrial chemicals and pesticides that is performed in the world is regulatory-driven. Regulatory web resources are presented for the laws mandating testing, guidelines on study design, Good Laboratory Practice (GLP) regulations, and requirements for electronic data collection and reporting. The Internet provides a range of other supporting resources to the field of genetic toxicology. The web links for key professional societies and journals in genetic toxicology are listed. Distance education, educational media resources, and job placement services are also

  6. mPed : a computer program for converting pedigree data to a format used by the PMx-software for conservation genetic analysis

    OpenAIRE

    Jansson, Mija; Ståhl, Ingvar; Laikre, Linda

    2013-01-01

    There is a growing need for conservation genetic management of animal populations when individual relatedness data (pedigrees) are available. Such data can be used to monitor rates of inbreeding and loss of genetic diversity. Traditionally, pedigree analysis for conservationmanagement has focused on zoo populations of threatened wild animals; available software has been developed in that context. Population Management x (PMx) is a free software for estimating genetic parameters including inbr...

  7. Genetic Counseling

    Science.gov (United States)

    Genetic counseling provides information and support to people who have, or may be at risk for, genetic disorders. A ... meets with you to discuss genetic risks. The counseling may be for yourself or a family member. ...

  8. Scientific discovery using genetic programming

    DEFF Research Database (Denmark)

    Keijzer, Maarten

    2001-01-01

    that are numerically stable and correct. A case study using four real-world problems in the induction of dimensionally correct empirical equations on data using the two different methods is presented to illustrate to use and limitations of these methods in a framework of scientific discovery....

  9. Nutrition, genetic programming and immunometabolism

    Science.gov (United States)

    Diets with high saturated fat increase inflammation, insulin resistance, and obesity resulting in greater risk of as type 2 diabetes mellitus and other chronic diseases. However, it is not yet known whether the maternal diet influences offspring inflammatory responses to alter offspring metabolic di...

  10. Possibilities of using the German Federal States' permanent soil monitoring program for the monitoring of potential effects of genetically modified organisms (GMO).

    Science.gov (United States)

    Toschki, Andreas; Jänsch, Stephan; Roß-Nickoll, Martina; Römbke, Jörg; Züghart, Wiebke

    2015-01-01

    In the Directive 2001/18/EC on the deliberate release of genetically modified organisms (GMO) into the environment, a monitoring of potential risks is prescribed after their deliberate release or placing on the market. Experience and data of already existing monitoring networks should be included. The present paper summarizes the major findings of a project funded by the Federal Agency for Nature Conservation (Nutzungsmöglichkeiten der Boden-Dauerbeobachtung der Länder für das Monitoring der Umweltwirkungen gentechnisch veränderter Pflanzen. BfN Skripten, Bonn-Bad Godesberg 369, 2014). The full report in german language can be accessed on http://www.bfn.de and is available as Additional file 1. The aim of the project was to check if it is possible to use the German permanent soil monitoring program (PSM) for the monitoring of GMO. Soil organism communities are highly diverse and relevant with respect to the sustainability of soil functions. They are exposed to GMO material directly by feeding or indirectly through food chain interactions. Other impacts are possible due to their close association to soil particles. The PSM program can be considered as representative with regard to different soil types and ecoregions in Germany, but not for all habitat types relevant for soil organisms. Nevertheless, it is suitable as a basic grid for monitoring the potential effects of GMO on soil invertebrates. PSM sites should be used to derive reference values, i.e. range of abundance and presence of different relevant species of soil organisms. Based on these references, it is possible to derive threshold values to define the limit of acceptable change or impact. Therefore, a minimum set of sites and minimum set of standardized methods are needed, i.e. characterization of each site, sampling of selected soil organism groups, adequate adaptation of methods for the purpose of monitoring of potential effects of GMO. Finally, and probably most demanding, it is needed to develop

  11. Updated Genetic Score Based on 34 Confirmed Type 2 Diabetes Loci Is Associated With Diabetes Incidence and Regression to Normoglycemia in the Diabetes Prevention Program

    Science.gov (United States)

    Hivert, Marie-France; Jablonski, Kathleen A.; Perreault, Leigh; Saxena, Richa; McAteer, Jarred B.; Franks, Paul W.; Hamman, Richard F.; Kahn, Steven E.; Haffner, Steven; Meigs, James B.; Altshuler, David; Knowler, William C.; Florez, Jose C.

    2011-01-01

    OBJECTIVE Over 30 loci have been associated with risk of type 2 diabetes at genome-wide statistical significance. Genetic risk scores (GRSs) developed from these loci predict diabetes in the general population. We tested if a GRS based on an updated list of 34 type 2 diabetes–associated loci predicted progression to diabetes or regression toward normal glucose regulation (NGR) in the Diabetes Prevention Program (DPP). RESEARCH DESIGN AND METHODS We genotyped 34 type 2 diabetes–associated variants in 2,843 DPP participants at high risk of type 2 diabetes from five ethnic groups representative of the U.S. population, who had been randomized to placebo, metformin, or lifestyle intervention. We built a GRS by weighting each risk allele by its reported effect size on type 2 diabetes risk and summing these values. We tested its ability to predict diabetes incidence or regression to NGR in models adjusted for age, sex, ethnicity, waist circumference, and treatment assignment. RESULTS In multivariate-adjusted models, the GRS was significantly associated with increased risk of progression to diabetes (hazard ratio [HR] = 1.02 per risk allele [95% CI 1.00–1.05]; P = 0.03) and a lower probability of regression to NGR (HR = 0.95 per risk allele [95% CI 0.93–0.98]; P < 0.0001). At baseline, a higher GRS was associated with a lower insulinogenic index (P < 0.001), confirming an impairment in β-cell function. We detected no significant interaction between GRS and treatment, but the lifestyle intervention was effective in the highest quartile of GRS (P < 0.0001). CONCLUSIONS A high GRS is associated with increased risk of developing diabetes and lower probability of returning to NGR in high-risk individuals, but a lifestyle intervention attenuates this risk. PMID:21378175

  12. Genetic Predisposition to Weight Loss and Regain With Lifestyle Intervention: Analyses From the Diabetes Prevention Program and the Look AHEAD Randomized Controlled Trials.

    Science.gov (United States)

    Papandonatos, George D; Pan, Qing; Pajewski, Nicholas M; Delahanty, Linda M; Peter, Inga; Erar, Bahar; Ahmad, Shafqat; Harden, Maegan; Chen, Ling; Fontanillas, Pierre; Wagenknecht, Lynne E; Kahn, Steven E; Wing, Rena R; Jablonski, Kathleen A; Huggins, Gordon S; Knowler, William C; Florez, Jose C; McCaffery, Jeanne M; Franks, Paul W

    2015-12-01

    Clinically relevant weight loss is achievable through lifestyle modification, but unintentional weight regain is common. We investigated whether recently discovered genetic variants affect weight loss and/or weight regain during behavioral intervention. Participants at high-risk of type 2 diabetes (Diabetes Prevention Program [DPP]; N = 917/907 intervention/comparison) or with type 2 diabetes (Look AHEAD [Action for Health in Diabetes]; N = 2,014/1,892 intervention/comparison) were from two parallel arm (lifestyle vs. comparison) randomized controlled trials. The associations of 91 established obesity-predisposing loci with weight loss across 4 years and with weight regain across years 2-4 after a minimum of 3% weight loss were tested. Each copy of the minor G allele of MTIF3 rs1885988 was consistently associated with greater weight loss following lifestyle intervention over 4 years across the DPP and Look AHEAD. No such effect was observed across comparison arms, leading to a nominally significant single nucleotide polymorphism×treatment interaction (P = 4.3 × 10(-3)). However, this effect was not significant at a study-wise significance level (Bonferroni threshold P < 5.8 × 10(-4)). Most obesity-predisposing gene variants were not associated with weight loss or regain within the DPP and Look AHEAD trials, directly or via interactions with lifestyle. © 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

  13. 基于遗传算法的动力配煤规划模型研究%Genetic algorithm programming model for coal blending under uncertainty

    Institute of Scientific and Technical Information of China (English)

    郭树银; 许野

    2015-01-01

    文章建立了一个基于遗传算法的动力配煤规划模型。该模型可以通过引入污染控制措施来确保受影响区域的空气污染物浓度满足环境要求和维持人体健康的空气质量水平,同时确保动力配煤的总成本最小化。该模型应用于北京市某供暖公司和某热电公司的动力配煤规划,运算结果准确、可靠。结果表明,该模型可以有效地控制空气污染物的排放水平,为决策者提供可行的动力配煤方案,并最终实现系统成本的最小化。%A genetic algorithm programming model ( GAPM) for supporting the coal blending under uncertainty was developed .GAPM model could not only control air pollutants to satisfy the overall en-vironmental regulation and guarantee a healthy air quality level , but also tackle coal blending problems under uncertainty .The developed model was applied to handle the coal blending problem sourced from the heating company and power plant of city , Beijing.The obtained results demonstrated that GAPM was suitable in controlling air pollution , providing desired coal blending strategies for decision maker , as well as minimizing total system cost .

  14. [Genetic amniocentesis].

    Science.gov (United States)

    Violante Díaz, M; Carrillo Hinojosa, M; García Necoechea, M P; Escobedo Aguirre, F; Lowenberg Favela, E; Ahued Ahued, J R

    1989-04-01

    179 patients were studied by genetic amniocentesis (GA) in sessions of 3 punctures each. This was done in order to follow a prenatal diagnosis (PD) program and study amniotic fluid at the Hospital Regional 20 de Novembre (ISSSTE) between May 1983 and December 1987. The parameters taken were: age, indications, number of sessions, number punctures, echosonographic studies for gestational age, placental insertion, punction site, amniotic fluid volume, blood contamination, failures and handling of the patient. A low incidence of abortion is reported. We don't have cases of dripping of amniotic fluid or transvaginal haemorrhage. Multiple insertion of the needle and placental or vessel lesions of the cord, as causes of a fetal death are still argued if we have in mind avoiding chances; we didn't have those complications in our cases. The percent is low if there are not previous spontaneous abortions. 79% of the amniotic fluid samples were sent between the 15th and 17th weeks of pregnancy. For alpha fetus protein determination 12 and for biochemical studies 1, specially for beta-galactosidase level. This was done at the Biomedical Investigation Institute of the National Autonomous University of Mexico (in parents with generalized gangliosidosis GM1). Even though results were good, the technique has still risks and complications. An ultrasonic study of the procedures made by physicians with trustable experience is needed. Our country has the need to create more Prenatal Genetic Diagnosis Centers.

  15. Microsatellite data analysis for population genetics.

    Science.gov (United States)

    Kim, Kyung Seok; Sappington, Thomas W

    2013-01-01

    Theories and analytical tools of population genetics have been widely applied for addressing various questions in the fields of ecological genetics, conservation biology, and any context where the role of dispersal or gene flow is important. Underlying much of population genetics is the analysis of variation at selectively neutral marker loci, and microsatellites continue to be a popular choice of marker. In recent decades, software programs to estimate population genetics parameters have been developed at an increasing pace as computational science and theoretical knowledge advance. Numerous population genetics software programs are presently available to analyze microsatellite genotype data, but only a handful are commonly employed for calculating parameters such as genetic variation, genetic structure, patterns of spatial and temporal gene flow, population demography, individual population assignment, and genetic relationships within and between populations. In this chapter, we introduce statistical analyses and relevant population genetic software programs that are commonly employed in the field of population genetics and molecular ecology.

  16. Feline genetics: clinical applications and genetic testing.

    Science.gov (United States)

    Lyons, Leslie A

    2010-11-01

    DNA testing for domestic cat diseases and appearance traits is a rapidly growing asset for veterinary medicine. Approximately 33 genes contain 50 mutations that cause feline health problems or alterations in the cat's appearance. A variety of commercial laboratories can now perform cat genetic diagnostics, allowing both the veterinary clinician and the private owner to obtain DNA test results. DNA is easily obtained from a cat via a buccal swab with a standard cotton bud or cytological brush, allowing DNA samples to be easily sent to any laboratory in the world. The DNA test results identify carriers of the traits, predict the incidence of traits from breeding programs, and influence medical prognoses and treatments. An overall goal of identifying these genetic mutations is the correction of the defect via gene therapies and designer drug therapies. Thus, genetic testing is an effective preventative medicine and a potential ultimate cure. However, genetic diagnostic tests may still be novel for many veterinary practitioners and their application in the clinical setting needs to have the same scrutiny as any other diagnostic procedure. This article will review the genetic tests for the domestic cat, potential sources of error for genetic testing, and the pros and cons of DNA results in veterinary medicine. Highlighted are genetic tests specific to the individual cat, which are a part of the cat's internal genome.

  17. Primer on molecular genetics

    Energy Technology Data Exchange (ETDEWEB)

    1992-04-01

    This report is taken from the April 1992 draft of the DOE Human Genome 1991--1992 Program Report, which is expected to be published in May 1992. The primer is intended to be an introduction to basic principles of molecular genetics pertaining to the genome project. The material contained herein is not final and may be incomplete. Techniques of genetic mapping and DNA sequencing are described.

  18. Development of a modular streamflow model to quantify runoff contributions from different land uses in tropical urban environments using Genetic Programming

    Science.gov (United States)

    Meshgi, Ali; Schmitter, Petra; Chui, Ting Fong May; Babovic, Vladan

    2015-06-01

    The decrease of pervious areas during urbanization has severely altered the hydrological cycle, diminishing infiltration and therefore sub-surface flows during rainfall events, and further increasing peak discharges in urban drainage infrastructure. Designing appropriate waster sensitive infrastructure that reduces peak discharges requires a better understanding of land use specific contributions towards surface and sub-surface processes. However, to date, such understanding in tropical urban environments is still limited. On the other hand, the rainfall-runoff process in tropical urban systems experiences a high degree of non-linearity and heterogeneity. Therefore, this study used Genetic Programming to establish a physically interpretable modular model consisting of two sub-models: (i) a baseflow module and (ii) a quick flow module to simulate the two hydrograph flow components. The relationship between the input variables in the model (i.e. meteorological data and catchment initial conditions) and its overall structure can be explained in terms of catchment hydrological processes. Therefore, the model is a partial greying of what is often a black-box approach in catchment modelling. The model was further generalized to the sub-catchments of the main catchment, extending the potential for more widespread applications. Subsequently, this study used the modular model to predict both flow components of events as well as time series, and applied optimization techniques to estimate the contributions of various land uses (i.e. impervious, steep grassland, grassland on mild slope, mixed grasses and trees and relatively natural vegetation) towards baseflow and quickflow in tropical urban systems. The sub-catchment containing the highest portion of impervious surfaces (40% of the area) contributed the least towards the baseflow (6.3%) while the sub-catchment covered with 87% of relatively natural vegetation contributed the most (34.9%). The results from the quickflow

  19. Genetic Monitoring and Evaluation Program for Supplemented Populations of Salmon and Steelhead in the Snake River Basin, 1990-1991 Annual Report.

    Energy Technology Data Exchange (ETDEWEB)

    Waples, Robin S.; Teel, David J.; Aebersold, Paul B.

    1991-08-01

    This is the first report of research for an ongoing study to evaluate the genetic effects of using hatchery-reared fish to supplement natural populations of chinook salmon and steelhead in the Snake River Basin.

  20. Genetic Disorders

    Science.gov (United States)

    ... This can cause a medical condition called a genetic disorder. You can inherit a gene mutation from ... during your lifetime. There are three types of genetic disorders: Single-gene disorders, where a mutation affects ...

  1. Genetic modification and genetic determinism.

    Science.gov (United States)

    Resnik, David B; Vorhaus, Daniel B

    2006-06-26

    In this article we examine four objections to the genetic modification of human beings: the freedom argument, the giftedness argument, the authenticity argument, and the uniqueness argument. We then demonstrate that each of these arguments against genetic modification assumes a strong version of genetic determinism. Since these strong deterministic assumptions are false, the arguments against genetic modification, which assume and depend upon these assumptions, are therefore unsound. Serious discussion of the morality of genetic modification, and the development of sound science policy, should be driven by arguments that address the actual consequences of genetic modification for individuals and society, not by ones propped up by false or misleading biological assumptions.

  2. Imaging Genetics

    Science.gov (United States)

    Munoz, Karen E.; Hyde, Luke W.; Hariri, Ahmad R.

    2009-01-01

    Imaging genetics is an experimental strategy that integrates molecular genetics and neuroimaging technology to examine biological mechanisms that mediate differences in behavior and the risks for psychiatric disorder. The basic principles in imaging genetics and the development of the field are discussed.

  3. Genetic principles.

    Science.gov (United States)

    Abuelo, D

    1987-01-01

    The author discusses the basic principles of genetics, including the classification of genetic disorders and a consideration of the rules and mechanisms of inheritance. The most common pitfalls in clinical genetic diagnosis are described, with emphasis on the problem of the negative or misleading family history.

  4. Imaging Genetics

    Science.gov (United States)

    Munoz, Karen E.; Hyde, Luke W.; Hariri, Ahmad R.

    2009-01-01

    Imaging genetics is an experimental strategy that integrates molecular genetics and neuroimaging technology to examine biological mechanisms that mediate differences in behavior and the risks for psychiatric disorder. The basic principles in imaging genetics and the development of the field are discussed.

  5. A Genetic Monitoring and Evaluation Program for Supplemented Populations of Salmon and Steelhead in the Snake River Basin : 1992 Annual Report.

    Energy Technology Data Exchange (ETDEWEB)

    Waples, Robin S.

    1993-07-01

    This is the second report of research for an ongoing study to evaluate the genetic effects of using hatchery-reared fish to supplement natural populations of chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss) in the Snake River Basin. The study plan involves yearly monitoring of genetic and meristic characteristics in hatchery, natural (supplemented), and wild (unsupplemented) populations in four different drainages for each species. This report summarizes the first two years of electrophoretic data for chinook salmon and steelhead and the first two years of meristic data for chinook salmon. Results obtained to date include the following: (1) Genetic variation was detected at 35 gene loci in chinook salmon and 50 gene loci in steelhead, both considerable increases over the number of polymorphic loci reported previously for Snake River populations. No substantial differences in levels of genetic variability were observed between years or between hatchery and natural/wild populations in either species. (2) In both species, statistically significant differences in allele frequency were typically found between years within populations. However, the temporal changes within populations were generally smaller than differences between populations. (3) Differences between chinook salmon populations classified as spring-and summer-run accounted for little of the overall genetic diversity; in contrast, substantial genetic differences were observed between ''B'' run steelhead from Dworshak Hatchery and ''A'' run populations from other study sites. (4) Estimates of the effective number of breeders per year (N,) derived from genetic data suggest that N{sub b} in natural and wild Snake River spring/summer chinook salmon populations is generally about one-quarter to three-quarters of the estimated number of adult spawners. (5) Analysis of the effects on data quality of sampling juveniles indicates that the small size of some

  6. Genetic professionals' views on genetic counsellors: a French survey.

    Science.gov (United States)

    Cordier, Christophe; Taris, Nicolas; Moldovan, Ramona; Sobol, Hagay; Voelckel, Marie-Antoinette

    2016-01-01

    The genetic counselling profession was established in France in 2004. Eight years later, 122 genetic counsellors have graduated from the unique educational French program which awards the Professional Master Degree of Human Pathology, entitled "Master of Genetic Counselling and Predictive Medicine". As part of a global evaluation of this new profession by health genetic professionals, we undertook a national survey investigating various aspects such as employment, work responsibilities and integration. To our knowledge, this is the first study to investigate the views of genetic professionals on the genetic counsellors' role. Of 422 French professionals invited to take part in this study, 126 participated. The survey underlines that this profession is significantly recognized by physicians practicing within genetics departments. French genetic counsellors are allowed to manage consultations independently, without the necessary presence of a qualified medical geneticist but under his or her responsibility. Genetic counsellors participate in a wide range of consultations. They provide both information for relevant and for genetic testing and sometimes disclose the genetic test result to patient. Eventually, the role of genetic counsellors appears to be directly dependent from the relationship of trust between the two health professions.

  7. Genetic modification and genetic determinism

    OpenAIRE

    Vorhaus Daniel B; Resnik David B

    2006-01-01

    Abstract In this article we examine four objections to the genetic modification of human beings: the freedom argument, the giftedness argument, the authenticity argument, and the uniqueness argument. We then demonstrate that each of these arguments against genetic modification assumes a strong version of genetic determinism. Since these strong deterministic assumptions are false, the arguments against genetic modification, which assume and depend upon these assumptions, are therefore unsound....

  8. The Genetics Revolution: Programs and Issues for the Community College. A Monograph Highlighting the Winners of the Exxon Education Foundation Innovation Awards.

    Science.gov (United States)

    Mays, Marilyn Elaine, Ed.

    Presented at a 1996 conference on the implications of the Human Genome Project for community and technical colleges, the 30 papers included in this monograph describe methods for incorporating genetics studies into the two-year college curriculum. Among the papers provided are: (1) "Facing the Unknown: The Ethical Challenges of…

  9. DEVELOPMENT OF A MULTI-TIERED INSECT RESISTANCE MANAGEMENT PROGRAM FOR GENETICALLY MODIFIED CORN HYBRIDS EXPRESSING THE PLANT INCORPORATED PROTECTANT, BACILLUS THURINGIENSIS

    Science.gov (United States)

    A significant increase in genetically modified corn planting driven by biofuel demand is expected for the 2007 growing season with future planted acreages approaching 80% of total corn plantings anticipated by 2009. As demand increases, incidence of farmer non-compliance with ma...

  10. Genetic enetic characterization of curimba (“Prochilodus lineatus” stocks used in stock enhancement programs Caracterização genética de estoques de curimba ("Prochilodus lineatus" utilizados em programas de repovoamento

    Directory of Open Access Journals (Sweden)

    Patrícia Cristina Gomes

    2008-12-01

    Full Text Available The aim with this study was to determine the genetic diversity of P. lineatus stocks, destined to stocking programs, with the RAPD molecular marker (Random Amplified Polymorphic DNA. Fifty two broodstocks of two fish farmings located at Salto Grande - SP (A and Palotina - PR (B counties and 32 juvenile progenies of Palotina stock (C were analyzed. The six primers produced 63 fragments (96.83% polymorphism. The genetic variability values determined by the polymorphic fragments percentage (A: 80.95%; B: 85.71% and C: 79.37% showed decreasing genetic variability in C possibly due to the inadequate reproductive management. The genetic variability between A and B stocks showed moderate genetic differentiation among them, mainly due to the founder effect. This result was confirmed by the values of Gst (0.084, gene flow Nm (5.48, genetic identity (0.926 and distance (0.077 and genetic similarity (A: 0.603 and B: 0.658, that provided important informations for a safe ichthyofauna and ecosystem conservation.Objetivou-se com este estudo determinar a diversidade genética de estoques de P. lineatus, destinados a programas de repovoamento, com o marcador molecular RAPD (Random Amplified Polymorphic DNA. Foram analisados 52 reprodutores de duas pisciculturas localizadas nas cidades de Salto Grande - SP (A e Palotina – PR (B e 32 alevinos da progênie do estoque de Palotina (C. Os seis primers produziram 63 fragmentos (96,83% polimórficos. Os valores de variabilidade genética determinados pela porcentagem de fragmentos polimórficos (A: 80,95%; B: 85,71% e C: 79,37% mostraram que houve diminuição da variabilidade genética em C, devido possivelmente ao inadequado manejo reprodutivo. A variabilidade genética entre os estoques A e B mostrou moderada diferenciação genética entre eles, decorrente possivelmente do efeito fundador. Esse resultado foi corroborado pelos valores de Gst (0,084, fluxo gênico Nm (5,48, identidade (0,926 e distância gen

  11. Control of Angra 1' PZR by a fuzzy rule base build through genetic programming; Controle do PZR de Angra 1 por meio de uma base de regras nebulosas construidas atraves de programacao genetica

    Energy Technology Data Exchange (ETDEWEB)

    Caldas, Gustavo Henrique Flores; Schirru, Roberto [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia. Programa de Engenharia Nuclear

    2002-07-01

    There is an optimum pressure for the normal operation of nuclear power plant reactors and thresholds that must be respected during transients, what make the pressurizer an important control mechanism. Inside a pressurizer there are heaters and a shower. From their actuation levels, they control the vapor pressure inside the pressurizer and, consequently, inside the primary circuit. Therefore, the control of the pressurizer consists in controlling the actuation levels of the heaters and of the shower. In the present work this function is implemented through a fuzzy controller. Besides the efficient way of exerting control, this approach presents the possibility of extracting knowledge of how this control is been made. A fuzzy controller consists basically in an inference machine and a rule base, the later been constructed with specialized knowledge. In some circumstances, however, this knowledge is not accurate, and may lead to non-efficient results. With the development of artificial intelligence techniques, there wore found methods to substitute specialists, simulating its knowledge. Genetic programming is an evolutionary algorithm particularly efficient in manipulating rule base structures. In this work genetic programming was used as a substitute for the specialist. The goal is to test if an irrational object, a computer, is capable, by it self, to find out a rule base reproducing a pre-established actuation levels profile. The result is positive, with the discovery of a fuzzy rule base presenting an insignificant error. A remarkable result that proves the efficiency of the approach. (author)

  12. Research and Application of Union of Genetic Programming with Automatically Defined Function%遗传编程与自动定义函数结合的研究及应用

    Institute of Scientific and Technical Information of China (English)

    孙波; 孙冬

    2012-01-01

    本文根据在标准遗传编程中由于种群多样性对算法收敛特性的影响,引入了结合自动定义函数的方法,对标准遗传编程进行改进,从而得到更优的收敛性能和缩短运行时间。文中结合求路径最优化的旅行商问题来进行实际验证,结论得出改进的算法具有更好的收敛性能。%This paper,according to the standard Genetic Programming as a result of the population multiplicity to the algorithm convergence characteristic influence,has introduced the Automatically Defined Function(ADF) into the GP.It makes the improvement to the standard Genetic Programming,thus obtains the more superior convergence performance and the reduction of runtime.In the paper,used the example of traveling salesman problem to carry on the actual confirmation.The conclusion obtains the improvement for the algorithm to have the better convergence performance.

  13. Medical genetics in Paraguay.

    Science.gov (United States)

    Ascurra de Duarte, Marta

    2004-01-01

    Paraguay is a developing country with low levels of health coverage, with 81% of the population without health insurance, a proportion that reaches 98.1% among the poor, 93% among the rural population and 91.7% among the mainly Guarani-speaking population. The infant mortality rate is 19.4 per 1,000, although there is gross under-reporting. Maternal mortality rate is alarmingly high at 110.9 per 100,000 livebirths, reaching 420.5 in rural areas. There are only two clinical geneticists and four biochemists trained in human genetics, and virtually all genetic services in the country are concentrated in the 'Instituto de Investigaciones en Ciencias de la Salud' (IICS) from the National University. The teaching of medical genetics in medical schools is included in physiology and pathology courses, while at the postgraduate level, training in medical genetics is limited to pediatrics and gynecology. In 1999, a pilot newborn screening program was initiated to determine the frequency of congenital hypothyroidism and phenylketonuria and to provide early treatment for affected babies. Another pilot project recently launched by the Ministry of Health is the Program for the Prevention of Neural Tube Defects, mandating folic acid fortification of flour, but as of the end of 2003 it had not been implemented. Paraguay lacks adequate resources to provide accurate diagnoses and treatment of genetic conditions.

  14. VARIABILIDAD GENÉTICA DE LOTES DE Brycon orbignyanus UTILIZADOS EN PROGRAMAS DE REPOBLAMIENTO: MANEJO Y CONSERVACIÓN Genetic Variability in Brycon orbignyanus Stocks Used in Stocking Programs: Management and Conservation

    Directory of Open Access Journals (Sweden)

    NELSON M LOPERA-BARRERO

    Full Text Available Alteraciones ambientales causadas por el calentamiento global y principalmente causa-das por la acción del hombre, han reducido poblaciones naturales de peces. Como forma de conservación, programas de repoblamiento han sido utilizados; sin embargo, sin una debida orientación científica, estas medidas pueden generar disturbios genéticos sobre la diversidad genética de poblaciones de peces naturales y sobre el ecosistema. El objetivo de este estudio fue estimar y analizar la variabilidad genética de dos lotes y una progenie de Brycon orbignyanus utilizados en programas de repoblamiento, utilizando el marcador molecular RAPD (Random Amplified Polymorphic DNA. Cincuenta y ocho reproductores de dos lotes (A y C y 30 larvas de la progenie del lote A (B pertenecientes a la Estação de Aqüicultura e Hidrologia da Duke Energy Internacional (Geração Parana-panema; São Paulo, Brasil fueron analizados. Los resultados de variabilidad genética estimados por el índice de diversidad de Shannon (A: 0,3184; B: 0,3433 y C: 0,3687 y por el porcentaje de fragmentos polimórficos (A: 54,02%; B: 57,47% y C: 58,62% mostraron que la variabilidad genética fue mantenida en la progenie, debido posiblemente al adecuado manejo reproductivo y al efecto fundador. Por el contrario, la variabilidad encontrada entre los dos lotes de reproductores indica una similaridad genética, a pesar de ser originarios de diferentes pisciculturas. Este resultado es comprobado en el valor moderado de diferenciación genética encontrado (0,0968, en el alto Nm (4,67 y en el dendrograma, que sugieren que los lotes poseen un pool genético similar.Environmental alterations caused by the global heating and mainly caused by man's action, have reduced natural fish populations. As a conservation measure, stocking programs have been used; however, without scientific orientation these measures can generate genetic disturbances on the genetic diversity of natural fish populations and the

  15. Genetic evaluation of seeds of highly endangered Pinus uliginosa Neumann from Węgliniec reserve for ex-situ conservation program

    Directory of Open Access Journals (Sweden)

    Andrzej Lewandowski

    2011-01-01

    Full Text Available Peat-bog pine Pinus uliginosa Neumann has become extinct or rare in many parts of Europe. We have investigated the levels of genetic variation and inbreeding in seeds collected from a highly endangered reserve of this species in Poland, using allozymes as genetic markers. Generally, a high level of genetic variation was observed. The mean expected heterozygosity was 0.376, while average (Na and effective (Ne numbers of alleles per locus were 2.45 and 1.67, respectively. Nevertheless, we have detected relatively low levels of outcrossing, and potential biparental inbreeding. The population-wide multilocus outcrossing rate was estimated to be 0.706 (±0.091, while the minimum variance mean of single-locus estimates was distinctly lower (ts=0.611. The estimates of outcrossing calculated for individual trees ranged widely from 0.051 to 1.017, indicating the complexity of outcrossing patterns. The investigated population of P. uliginasa from Węgliniec is small and surrounded by extensive forest stands of P. sylvestris. Our three-year records of phenological observations demonstrated that flowering periods for P. uliginosa and P. sylvestris overlap, allowing for cross-pollination. The possibility of P. uliginosa pollination by P. sylvestris creates a potential danger of genetic erosion of the P. uliginosa gene pool. Nonetheless, based on a species specific cpDNA marker we have found that among 533 seedlings of P. uliginosa there were only six seedlings carrying cpDNA marker specific for P. sylvestris, indicating that such hybridization seems to be rare.

  16. Genetic barcodes

    Energy Technology Data Exchange (ETDEWEB)

    Weier, Heinz -Ulrich G

    2015-08-04

    Herein are described multicolor FISH probe sets termed "genetic barcodes" targeting several cancer or disease-related loci to assess gene rearrangements and copy number changes in tumor cells. Two, three or more different fluorophores are used to detect the genetic barcode sections thus permitting unique labeling and multilocus analysis in individual cell nuclei. Gene specific barcodes can be generated and combined to provide both numerical and structural genetic information for these and other pertinent disease associated genes.

  17. Diversidad genética de piracanjuba usada en programas de repoblación con marcadores microsatélites Genetic diversity of piracanjuba used in stock enhancement programs with microsatellite markers

    Directory of Open Access Journals (Sweden)

    Maria del Pilar Rodriguez-Rodriguez

    2010-01-01

    Full Text Available El objetivo de este trabajo fue estimar la diversidad genética de un lote de Brycon orbignyanus usado en programas de repoblación, a través de marcadores microsatélites. Se analizaron muestras de 44 reproductores, de 70 larvas y de 69 alevinos, con la amplificación de cinco loci descritos para Brycon opalinus. El número de alelos, la heterozigosidad observada (Ho y esperada (He, el índice de Shannon (IS, la diversidad genética de Nei (DGN, el coeficiente de endogamia (Fis, la distancia (DG e identidad genética (IG, el número efectivo de alelos, el test del equilibrio de Hardy-Weinberg (EHW y el desequilibrio de ligación fueron calculados. Reproductores y progenie tuvieron un número similar de alelos en los loci evaluados. La Ho media, IS, DGN, DG e IG mostraron que existe menor distancia genética entre parentales y larvas y una disminución de variabilidad genética en los alevinos. Fueron observados desvíos en EHW y desequilibrio de ligación en seis pares de loci. El Fis mostró exceso de heterocigotos en parentales y larvas y déficit de heterocigotos en los alevinos. El lote de reproductores está en proceso de pérdida de alelos y hubo disminución de la variabilidad genética entre la fase de larva y alevino.The objective of this work was to estimate the genetic diversity of a Brycon orbignyanus lot used in stock enhancement programs, using microsatellite markers. Samples of 44 broodstocks, 70 larvae and 69 fingerlings, were analyzed with amplification of five loci described for Brycon opalinus. The number of alleles, the observed (Ho and expected (He heterozygosity, Shannon index (IS, Nei's genetic diversity (DGN, the inbreeding coefficient (Fis, distance (DG and genetic identity (IG, the effective number of alleles, the test of Hardy-Weinberg equilibrium (EHW and the linkage disequilibrium were calculated. Broodstocks and offspring had a similar number of alleles at the tested loci. Ho average, IS, DGN, DG and IG showed

  18. Genetics and caries: prospects

    Directory of Open Access Journals (Sweden)

    Alexandre Rezende Vieira

    2012-01-01

    Full Text Available Caries remains the most prevalent non-contagious infectious disease in humans. It is clear that the current approaches to decrease the prevalence of caries in human populations, including water fluoridation and school-based programs, are not enough to protect everyone. The scientific community has suggested the need for innovative work in a number of areas in cariology, encompassing disease etiology, epidemiology, definition, prevention, and treatment. We have pioneered the work on genetic studies to identify genes and genetic markers of diagnostic, prognostic, and therapeutic value. This paper summarizes a presentation that elaborated on these initial findings.

  19. Genetic modification and genetic determinism

    Directory of Open Access Journals (Sweden)

    Vorhaus Daniel B

    2006-06-01

    Full Text Available Abstract In this article we examine four objections to the genetic modification of human beings: the freedom argument, the giftedness argument, the authenticity argument, and the uniqueness argument. We then demonstrate that each of these arguments against genetic modification assumes a strong version of genetic determinism. Since these strong deterministic assumptions are false, the arguments against genetic modification, which assume and depend upon these assumptions, are therefore unsound. Serious discussion of the morality of genetic modification, and the development of sound science policy, should be driven by arguments that address the actual consequences of genetic modification for individuals and society, not by ones propped up by false or misleading biological assumptions.

  20. Genetic Engineering

    Science.gov (United States)

    Phillips, John

    1973-01-01

    Presents a review of genetic engineering, in which the genotypes of plants and animals (including human genotypes) may be manipulated for the benefit of the human species. Discusses associated problems and solutions and provides an extensive bibliography of literature relating to genetic engineering. (JR)

  1. Genetic Counseling

    Science.gov (United States)

    ... for certain types of genetic conditions (such as Down syndrome) in the baby if mother-to-be is 35 years of age or more, or is concerned at any age about her chances of having a child with a genetic condition To learn about the ...

  2. Genetic Romanticism

    DEFF Research Database (Denmark)

    Tupasela, Aaro

    2016-01-01

    . This article compares and contrasts the work of two doctors in Finland, Elias Lönnrot and Reijo Norio, working over a century and a half apart, to examine the ways in which they have contributed to the formation of national identity and unity. The notion of genetic romanticism is introduced as a term...... to complement the notion of national romanticism that has been used to describe the ways in which nineteenth-century scholars sought to create and deploy common traditions for national-romantic purposes. Unlike national romanticism, however, strategies of genetic romanticism rely on the study of genetic...... inheritance as a way to unify populations within politically and geographically bounded areas. Thus, new genetics have contributed to the development of genetic romanticisms, whereby populations (human, plant, and animal) can be delineated and mobilized through scientific and medical practices to represent...

  3. Certification Programs for Citrus

    Science.gov (United States)

    Citrus certification programs designed to ensure that healthy plants of the highest genetic potential are being planted in the field are the basic building block of an integrated pest management program. Certification programs began for citrus began with the discovery that the diseases were graft t...

  4. Programmed Nanomaterial Assemblies in Large Scales: Applications of Synthetic and Genetically- Engineered Peptides to Bridge Nano-Assemblies and Macro-Assemblies

    Energy Technology Data Exchange (ETDEWEB)

    Matsui, Hiroshi

    2014-09-09

    Work is reported in these areas: Large-scale & reconfigurable 3D structures of precise nanoparticle assemblies in self-assembled collagen peptide grids; Binary QD-Au NP 3D superlattices assembled with collagen-like peptides and energy transfer between QD and Au NP in 3D peptide frameworks; Catalytic peptides discovered by new hydrogel-based combinatorial phage display approach and their enzyme-mimicking 2D assembly; New autonomous motors of metal-organic frameworks (MOFs) powered by reorganization of self-assembled peptides at interfaces; Biomimetic assembly of proteins into microcapsules on oil-in-water droplets with structural reinforcement via biomolecular recognition-based cross-linking of surface peptides; and Biomimetic fabrication of strong freestanding genetically-engineered collagen peptide films reinforced by quantum dot joints. We gained the broad knowledge about biomimetic material assembly from nanoscale to microscale ranges by coassembling peptides and NPs via biomolecular recognition. We discovered: Genetically-engineered collagen-like peptides can be self-assembled with Au NPs to generate 3D superlattices in large volumes (> μm{sup 3}); The assembly of the 3D peptide-Au NP superstructures is dynamic and the interparticle distance changes with assembly time as the reconfiguration of structure is triggered by pH change; QDs/NPs can be assembled with the peptide frameworks to generate 3D superlattices and these QDs/NPs can be electronically coupled for the efficient energy transfer; The controlled assembly of catalytic peptides mimicking the catalytic pocket of enzymes can catalyze chemical reactions with high selectivity; and, For the bacteria-mimicking swimmer fabrication, peptide-MOF superlattices can power translational and propellant motions by the reconfiguration of peptide assembly at the MOF-liquid interface.

  5. 一种基于遗传规划的多特征图像排序算法%A GENETIC PROGRAMMING-BASED MULTI-FEATURE IMAGES RANKING ALGORITHM

    Institute of Scientific and Technical Information of China (English)

    林龄; 潘峰

    2013-01-01

    In this paper we propose a multi-feature images ranking algorithm, and model the multi-feature images ranking problem by using genetic programming algorithm.We utilise the ranking trees to represent the candidate ranking functions as the individuals in genetic programming populations, and the individual in genetic programming algorithm of this paper is made up of a triple which contains the image features , constants, and arithmetic operators.A group of initial ranking functions are randomly selected as the individuals in genetic programming algorithm, and then to be organised as ranking trees.In every iteration process, the fitness of each ranking tree is calculated, and then the ranking trees with high fitness value are recorded.Next, new individuals are generated by the mutation, crossover and reproduction operations.Particularly, diversity images ranking can be implemented by the crossover operation which can obviously promote the population diversity .Afterwards, the ranking tree which can rank the images in training dataset with highest accuracy is chosen as the image ranking function.Experimental results show that the proposed algorithm can effectively fuse the multi-features of images, and can significantly improve the accuracy of image ranking results with high diversity.%提出一种多特征图像的排序算法,通过遗传规划算法对多特征图像排序问题进行建模。利用排序树将候选排序函数表示为遗传规划种群中的个体,把遗传规划算法中的个体由图像特征、常数以及算数运算符组成的三元组构成。随机选择一组初始排序函数作为遗传规划算法的个体,并将其表示成排序树。在每次迭代过程中,计算每棵排序树的适应度,并记录适应度高的排序树,通过变异、交叉以及繁殖操作生成新的个体。交叉操作可以提高种群的多样性,从而实现图像的多样化排序。接下来,从记录过的排序树中,选择对图

  6. Genetic Breakthrough

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    A new calf breeding technique shows promise for treating malignant tumors Chinese scientists have successfully bred a genetically altered cow capable of producing cancer-curing proteins for human beings.

  7. Chaos genetic programming method for job-shop scheduling problem%一种求解车间调度问题的混沌遗传规划方法

    Institute of Scientific and Technical Information of China (English)

    周强; 崔逊学

    2011-01-01

    作业车间调度问题是制造业的一个经典 NP-hard 组合优化难题.提出一种基于混沌遗传规划的调度算法,利用遗传规划进行染色体的结构设计,采用混沌序列改善初始种群质量,利用混沌扰动来维持进化群体的多样性,并自适应调整个体权重,使算法具有优良的综合求解性能.实验表明,算法对典型的标准调度测试问题具有较强的全局搜索能力,甘特图表明其获得的最优解优于当前已知的最优解历史记录,对比结果表明了该方法的有效性.%The job-shop scheduling problem is an NP-hard combinational optimization problem in the manufacturing field. The paper proposes a job-shop scheduling algorithm based on chaos genetic programming. Genetic programming is adopted to design a chromosome structure,the chaos sequence method is used to improve the quality of initial population,chaos disturbances are taken to maintain the diversity of evolutionary population, and the self-adaptive adjusting method of individual weight is applied.Accordingly the proposed algorithm has a comprehensive solving capacity for a scheduling problem. Simulation experiments show that it has better ability to find the global optimum for several typical scheduling testing benchmarks. The results of Gantt charts point out that the optimum solutions obtained by this novel algorithm are better than the historic ones. The comparison of the results reveals the feasibility and efficiency of the method.

  8. Mitochondrial genetics

    OpenAIRE

    Chinnery, Patrick Francis; Hudson, Gavin

    2013-01-01

    Introduction In the last 10 years the field of mitochondrial genetics has widened, shifting the focus from rare sporadic, metabolic disease to the effects of mitochondrial DNA (mtDNA) variation in a growing spectrum of human disease. The aim of this review is to guide the reader through some key concepts regarding mitochondria before introducing both classic and emerging mitochondrial disorders. Sources of data In this article, a review of the current mitochondrial genetics literature was con...

  9. 用EXCEL中的VBA编写“质量性状遗传分析”相关程序及其在农业上的应用%Coding Programs in Genetic Analysis of Quality Traits by VBA of EXCEL Applied in Agriculture

    Institute of Scientific and Technical Information of China (English)

    杨振宇; 杨海智; 杨信东

    2012-01-01

    Excel是常用的电子表格处理软件,笔者采用基于Excel的VBA编程方法,编写了“质量性状遗传分析”有关程序,经教学和农业科研工作中使用,获得了理想的效果.%The Excel is a commonly used sheet-processing software. Using Excel-based VBA programming methods, we coded programs for genetic analysis of quality traits. The programs have been used successfully in our teaching and agricultural research work. This article discussed the source code and application methods of the programs.

  10. Genetic algorithms and fuzzy multiobjective optimization

    CERN Document Server

    Sakawa, Masatoshi

    2002-01-01

    Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together with several significant monographs and books have been published on this methodology. As a result, genetic algorithms have made a major contribution to optimization, adaptation, and learning in a wide variety of unexpected fields. Over the years, many excellent books in genetic algorithm optimization have been published; however, they focus mainly on single-objective discrete or other hard optimization problems under certainty. There appears to be no book that is designed to present genetic algorithms for solving not only single-objective but also fuzzy and multiobjective optimization problems in a unified way. Genetic Algorithms And Fuzzy Multiobjective Optimization introduces the latest advances in the field of genetic algorithm optimization for 0-1 programming, integer programming, nonconvex programming, and job-shop scheduling problems under multiobjectiveness and fuzziness. In addition, the book treats a w...

  11. Integrating genetics and social science: genetic risk scores.

    Science.gov (United States)

    Belsky, Daniel W; Israel, Salomon

    2014-01-01

    The sequencing of the human genome and the advent of low-cost genome-wide assays that generate millions of observations of individual genomes in a matter of hours constitute a disruptive innovation for social science. Many public use social science datasets have or will soon add genome-wide genetic data. With these new data come technical challenges, but also new possibilities. Among these, the lowest-hanging fruit and the most potentially disruptive to existing research programs is the ability to measure previously invisible contours of health and disease risk within populations. In this article, we outline why now is the time for social scientists to bring genetics into their research programs. We discuss how to select genetic variants to study. We explain how the polygenic architecture of complex traits and the low penetrance of individual genetic loci pose challenges to research integrating genetics and social science. We introduce genetic risk scores as a method of addressing these challenges and provide guidance on how genetic risk scores can be constructed. We conclude by outlining research questions that are ripe for social science inquiry.

  12. Engaging nurses in genetics: the strategic approach of the NHS National Genetics Education and Development Centre.

    Science.gov (United States)

    Kirk, Maggie; Tonkin, Emma; Burke, Sarah

    2008-04-01

    The UK government announced the establishment of an NHS National Genetics Education and Development Centre in its Genetics White Paper. The Centre aims to lead and coordinate developments to enhance genetics literacy of health professionals. The nursing program takes a strategic approach based on Ajzen's Theory of Planned Behavior, using the UK nursing genetics competences as the platform for development. The program team uses innovative approaches to raise awareness of the relevance of genetics, working collaboratively with policy stakeholders, as key agents of change in promoting competence. Providing practical help in preparing learning and teaching resources lends further encouragement. Evaluation of the program is dependent on gathering baseline data, and the program has been informed by an education needs analysis. The challenges faced are substantial and necessitate international collaboration where expertise and resources can be shared to produce a global system of influence to facilitate the engagement of non-genetic nurses.

  13. Genetic GIScience

    DEFF Research Database (Denmark)

    Jacquez, Geoffrey; Sabel, Clive E; Shi, Chen

    2015-01-01

    The exposome, defined as the totality of an individual's exposures over the life course, is a seminal concept in the environmental health sciences. Although inherently geographic, the exposome as yet is unfamiliar to many geographers. This article proposes a place-based synthesis, genetic...... geographic information science (genetic GIScience), that is founded on the exposome, genome+, and behavome. It provides an improved understanding of human health in relation to biology (the genome+), environmental exposures (the exposome), and their social, societal, and behavioral determinants (the behavome......). Genetic GIScience poses three key needs: first, a mathematical foundation for emergent theory; second, process-based models that bridge biological and geographic scales; third, biologically plausible estimates of space?time disease lags. Compartmental models are a possible solution; this article develops...

  14. The behavior-genetics debate in the United States

    Energy Technology Data Exchange (ETDEWEB)

    Yesley, M.S.

    1993-12-31

    This paper, submitted to the Third Bioethics Seminar in Fukai, Japan, presents information on program activities and discusses primary topics concerning genetic factors in behavior. Proponents and critics views on genetic explanations of antisocial behavior are discussed.

  15. Genetic Variation Among Open-Pollinated Progeny of Eastern Cottonwood

    Science.gov (United States)

    R. E. Farmer

    1970-01-01

    Improvement programs in eastern cottonwood (Populus deltoides Bartr.) are most frequently designed to produce genetically superior clones for direct commercial use. This paper describes a progeny test to assess genetic variability on which selection might be based.

  16. Use of Computer Simulations in Microbial and Molecular Genetics.

    Science.gov (United States)

    Wood, Peter

    1984-01-01

    Describes five computer programs: four simulations of genetic and physical mapping experiments and one interactive learning program on the genetic coding mechanism. The programs were originally written in BASIC for the VAX-11/750 V.3. mainframe computer and have been translated into Applesoft BASIC for Apple IIe microcomputers. (JN)

  17. Genetically Engineering Entomopathogenic Fungi.

    Science.gov (United States)

    Zhao, H; Lovett, B; Fang, W

    2016-01-01

    Entomopathogenic fungi have been developed as environmentally friendly alternatives to chemical insecticides in biocontrol programs for agricultural pests and vectors of disease. However, mycoinsecticides currently have a small market share due to low virulence and inconsistencies in their performance. Genetic engineering has made it possible to significantly improve the virulence of fungi and their tolerance to adverse conditions. Virulence enhancement has been achieved by engineering fungi to express insect proteins and insecticidal proteins/peptides from insect predators and other insect pathogens, or by overexpressing the pathogen's own genes. Importantly, protein engineering can be used to mix and match functional domains from diverse genes sourced from entomopathogenic fungi and other organisms, producing insecticidal proteins with novel characteristics. Fungal tolerance to abiotic stresses, especially UV radiation, has been greatly improved by introducing into entomopathogens a photoreactivation system from an archaean and pigment synthesis pathways from nonentomopathogenic fungi. Conversely, gene knockout strategies have produced strains with reduced ecological fitness as recipients for genetic engineering to improve virulence; the resulting strains are hypervirulent, but will not persist in the environment. Coupled with their natural insect specificity, safety concerns can also be mitigated by using safe effector proteins with selection marker genes removed after transformation. With the increasing public concern over the continued use of synthetic chemical insecticides and growing public acceptance of genetically modified organisms, new types of biological insecticides produced by genetic engineering offer a range of environmentally friendly options for cost-effective control of insect pests. Copyright © 2016 Elsevier Inc. All rights reserved.

  18. RNA genetics

    Energy Technology Data Exchange (ETDEWEB)

    Domingo, E. (Instituto de Biologia Molecular, Facultad de Ciencias, Universidad Autonoma de Madrid, Canto Blanco, Madrid (ES)); Holland, J.J. (California Univ., San Diego, La Jolla, CA (USA). Dept. of Biology); Ahlquist, P. (Wisconsin Univ., Madison, WI (USA). Dept. of Plant Pathology)

    1988-01-01

    This book contains the proceedings on RNA genetics: RNA-directed virus replication Volume 1. Topics covered include: Replication of the poliovirus genome; Influenza viral RNA transcription and replication; and Relication of the reoviridal: Information derived from gene cloning and expression.

  19. Genetic counseling

    Science.gov (United States)

    ... MF, eds. Creasy and Resnik's Maternal-Fetal Medicine: Principles and Practice . 7th ed. Philadelphia, PA: Elsevier Saunders; 2014:chap 30. Review Date 1/25/2016 Updated by: Chad Haldeman-Englert, MD, FACMG, Fullerton Genetics Center, Asheville, NC. Review provided by VeriMed Healthcare ...

  20. Genetic Transformation in Citrus

    Directory of Open Access Journals (Sweden)

    Dicle Donmez

    2013-01-01

    Full Text Available Citrus is one of the world’s important fruit crops. Recently, citrus molecular genetics and biotechnology work have been accelerated in the world. Genetic transformation, a biotechnological tool, allows the release of improved cultivars with desirable characteristics in a shorter period of time and therefore may be useful in citrus breeding programs. Citrus transformation has now been achieved in a number of laboratories by various methods. Agrobacterium tumefaciens is used mainly in citrus transformation studies. Particle bombardment, electroporation, A. rhizogenes, and a new method called RNA interference are used in citrus transformation studies in addition to A. tumefaciens. In this review, we illustrate how different gene transformation methods can be employed in different citrus species.

  1. LIN28A facilitates the transformation of human neural stem cells and promotes glioblastoma tumorigenesis through a pro-invasive genetic program.

    Science.gov (United States)

    Mao, Xing-gang; Hütt-Cabezas, Marianne; Orr, Brent A; Weingart, Melanie; Taylor, Isabella; Rajan, Anand K D; Odia, Yazmin; Kahlert, Ulf; Maciaczyk, Jarek; Nikkhah, Guido; Eberhart, Charles G; Raabe, Eric H

    2013-07-01

    The cellular reprogramming factor LIN28A promotes tumorigenicity in cancers arising outside the central nervous system, but its role in brain tumors is unknown. We detected LIN28A protein in a subset of human gliomas observed higher expression in glioblastoma (GBM) than in lower grade tumors. Knockdown of LIN28A using lentiviral shRNA in GBM cell lines inhibited their invasion, growth and clonogenicity. Expression of LIN28A in GBM cell lines increased the number and size of orthotopic xenograft tumors. LIN28A expression also enhanced the invasiveness of GBM cells in vitro and in vivo. Increasing LIN28A was associated with down-regulation of tumor suppressing microRNAs let-7b and let-7g and up-regulation of the chromatin modifying protein HMGA2. The increase in tumor cell aggressiveness in vivo and in vitro was accompanied by an upregulation of pro-invasive gene expression, including SNAI1. To further investigate the oncogenic potential of LIN28A, we infected hNSC with lentiviruses encoding LIN28A together with dominant negative R248W-TP53, constitutively active KRAS and hTERT. Resulting subclones proliferated at an increased rate and formed invasive GBM-like tumors in orthotopic xenografts in immunodeficient mice. Similar to LIN28A-transduced GBM neurosphere lines, hNSC-derived tumor cells showed increased expression of HMGA2. Taken together, these data suggest a role for LIN28A in high grade gliomas and illustrate an HMGA2-associated, pro-invasive program that can be activated in GBM by LIN28A-mediated suppression of let-7 microRNAs.

  2. Marked regional variations in the prevalence of sickle cell disease and β-thalassemia in Saudi Arabia: findings from the premarital screening and genetic counseling program.

    Science.gov (United States)

    Memish, Ziad A; Owaidah, Tariq M; Saeedi, Mohamad Y

    2011-12-01

    Hemoglobinopathies represent a major public health problem in Saudi Arabia (SA). Reports suggest that their higher prevalence is not evenly distributed in SA. Regional differences were studied in sickle cell disease and β-thalassemia and their at-risk marriages using national data. The carrier and case status of sickle cell disease and β-thalassemia were determined in couples approaching marriage between 2004 and 2009 using standard blood tests. Prevalence of both diseases and at-risk marriages in different SA administrative and geographical regions were calculated and compared. A total of 15,72,140 men and women were examined over 6 years. This represented 0.06% of the entire population of Saudi Arabia. The prevalence of couples who tested positive for sickle cell was 45.1 (42.4 for carriers and 2.7 for cases) per 1000 persons examined. The prevalence was highest in the Eastern region (134.1 per 1000), followed by Southern and Western regions (55.6 and 28.5 per 1000, respectively) and lowest in Central and Northern regions (13.7 and 13.5 per 1000, respectively). The prevalence of couples testing positive for β-thalassemia was 18.5 (18.0 for carriers and 0.5 for cases) per 1000 persons examined. The prevalence was highest in the Eastern region (59.0), moderate in the Southern, Western and Central regions (14.2, 10.2, and 10.1 per 1000, respectively) and lowest in the Northern region (3.9). Vast regional differences in hemoglobinopathies among adult Saudis are being reported that may help policy makers better allocate resources of available preventive programs. Copyright © 2011 Ministry of Health, Saudi Arabia. Published by Elsevier Ltd. All rights reserved.

  3. Nurses' knowledge and educational needs regarding genetics.

    Science.gov (United States)

    Seven, Memnun; Akyüz, Aygül; Elbüken, Burcu; Skirton, Heather; Öztürk, Hatice

    2015-03-01

    Nurses now require a basic knowledge of genetics to provide patient care in a range of settings. To determine Turkish registered nurses' current knowledge and educational needs in relation to genetics. A descriptive, cross-sectional study. Turkish registered nurses working in a university hospital in Turkey were recruited. All registered nurses were invited to participate and 175 completed the study. The survey instrument, basic knowledge of health genetics, confidence in knowledge and the nurses' need for genetics education were used to collect data. The majority (81.1%, n=142) of participants indicated that genetics was not taught during their degree program, although 53.1% to 96% of respondents felt confident in defining different genetic concepts. The average genetics knowledge score was 6.89±1.99 of a possible 11 (range 0-11). The majority (70.3%) expressed a strong wish to attend a continuing nursing education program in genetics. The study shows that although Turkish nurses are not sufficiently knowledgeable to apply genetics in practice, they are willing to have more education to support their care of patients. Nurses need to have more education related to genetics in accordance with advances in human genetics to optimize health care. Copyright © 2014 Elsevier Ltd. All rights reserved.

  4. 多产品间歇过程的分层次在线调度--一种数学规划与遗传算法的混合算法%Hierarchical On-line Scheduling of Multiproduct Batch Plants with a Combined Approach of Mathematical Programming and Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    陈理; 王克峰; 徐霄羽; 姚平经

    2004-01-01

    In this contribution we present an online scheduling algorithm for a real world multiproduct batch plant.The overall mixed integer nonlinear programming (MINLP) problem is hierarchically structured into a mixed integer linear programming (MILP) problem first and then a reduced dimensional MINLP problem, which are optimized by mathematical programming (MP) and genetic algorithm (GA) respectively. The basis idea relies on combining MP with GA to exploit their complementary capacity. The key features of the hierarchical model are explained and illustrated with some real world cases from the multiproduct batch plants.

  5. Long-term effects of an inpatient weight-loss program in obese children and the role of genetic predisposition-rationale and design of the LOGIC-trial

    Directory of Open Access Journals (Sweden)

    Rank Melanie

    2012-03-01

    measured. Discussion Apart from illustrating the short, middle and long-term effects of an inpatient weight-loss program, this study will contribute to a better understanding of inter-individual differences in the regulation of body weight, taking into account the role of genetic predisposition and lifestyle factors. Trial Registration NCT01067157.

  6. Predicting Protein Structure Using Parallel Genetic Algorithms.

    Science.gov (United States)

    1994-12-01

    34 IEEE Transactions on Systems, Man and Cybernetics, 10(9) (September 1980). 16. De Jong, Kenneth A. "On Using Genetic Algoriths to Search Program...By " Predicting rotein Structure D istribticfiar.. ................ Using Parallel Genetic Algorithms ,Avaiu " ’ •"... Dist THESIS I IGeorge H...iiLite-d Approved for public release; distribution unlimited AFIT/ GCS /ENG/94D-03 Predicting Protein Structure Using Parallel Genetic Algorithms

  7. Melanoma genetics

    DEFF Research Database (Denmark)

    Read, Jazlyn; Wadt, Karin A W; Hayward, Nicholas K

    2016-01-01

    Approximately 10% of melanoma cases report a relative affected with melanoma, and a positive family history is associated with an increased risk of developing melanoma. Although the majority of genetic alterations associated with melanoma development are somatic, the underlying presence...... of heritable melanoma risk genes is an important component of disease occurrence. Susceptibility for some families is due to mutation in one of the known high penetrance melanoma predisposition genes: CDKN2A, CDK4, BAP1, POT1, ACD, TERF2IP and TERT. However, despite such mutations being implicated...... in a combined total of approximately 50% of familial melanoma cases, the underlying genetic basis is unexplained for the remainder of high-density melanoma families. Aside from the possibility of extremely rare mutations in a few additional high penetrance genes yet to be discovered, this suggests a likely...

  8. Measuring Financial Gains from Genetically Superior Trees

    Science.gov (United States)

    George Dutrow; Clark Row

    1976-01-01

    Planting genetically superior loblolly pines will probably yield high profits.Forest economists have made computer simulations that predict financial gains expected from a tree improvement program under actual field conditions.

  9. Genetic testing and your cancer risk

    Science.gov (United States)

    ... patientinstructions/000842.htm Genetic testing and your cancer risk To use the sharing features on this page, ... urac.org). URAC's accreditation program is an independent audit to verify that A.D.A.M. follows ...

  10. Genetic Algorithms and Genetic Programming Modern Concepts and Practical Applications

    CERN Document Server

    Affenzeller, Michael

    2009-01-01

    Describes several generic algorithmic concepts that can be used in various kinds of GA or with evolutionary optimization techniques. This title provides a better understanding of the basic workflow of GAs and GP, encouraging readers to establish new bionic, problem-independent theoretical concepts.

  11. Optimal screening for genetic diseases.

    Science.gov (United States)

    Nævdal, Eric

    2014-12-01

    Screening for genetic diseases is performed in many regions and/or ethnic groups where there is a high prevalence of possibly malign genes. The propagation of such genes can be considered a dynamic externality. Given that many of these diseases are untreatable and give rise to truly tragic outcomes, they are a source of societal concern, and the screening process should perhaps be regulated. This paper incorporates a standard model of genetic propagation into an economic model of dynamic management to derive cost benefit rules for optimal screening. The highly non-linear nature of genetic dynamics gives rise to perhaps surprising results that include discontinuous controls and threshold effects. One insight is that any screening program that is in place for any amount of time should screen all individuals in a target population. The incorporation of genetic models may prove to be useful to several emerging fields in economics such as genoeconomics, neuroeconomics and paleoeconomics.

  12. An overview of genetic counseling in Cuba.

    Science.gov (United States)

    Cruz, Araceli Lantigua

    2013-12-01

    This brief report provides an overview of the history and current status of genetic services in Cuba. In 1971, the University of Medical Sciences of Havana began to train doctors in medical genetics according to the medicine development plan in Cuba. With the aim of introducing genetic services to the population, two main issues were identified: the impact of neural tube defects as a cause of infantile mortality, and a founder effect resulting in a high frequency of sickle cell anemia, which increased the mortality rate and impacted the quality of peoples' lives. The impact of consanguinity is variable; it depends on the isolation of the population, with rates of 1 to 11% in different regions for first and second cousin marriages. From 1981, the services of medical genetics began to expand to the entire country, according to a government directive, and the need to design a program for the specialty became evident. From 1995 to 2000, two Masters-level programs were designed by professors of the Department of Medical Genetics, University of Medical Sciences of Havana, and authorized by the Ministry of Higher Education. One program in medical genetics was designed for physicians with other specialties, and the second program was designed to train professionals to become genetic counselors. The majority of graduates from the latter program are working at the primary level of healthcare.

  13. Genetic Testing for ALS

    Science.gov (United States)

    ... Involved Donate Familial Amyotrophic Lateral Sclerosis (FALS) and Genetic Testing By Deborah Hartzfeld, MS, CGC, Certified Genetic Counselor ... in your area, please visit www.nsgc.org . Genetic Testing Genetic testing can help determine the cause of ...

  14. Genetic Science Learning Center

    Science.gov (United States)

    ... Mouse Party on Learn.Genetics.utah.edu Students doing the Tree of Genetic Traits activity Learn.Genetics is one of the most widely used science education websites in the world The Community Genetics ...

  15. Genetic counseling training in the Philippines.

    Science.gov (United States)

    Laurino, Mercy Ygona; Padilla, Carmencita David

    2013-12-01

    The recently established Master of Science in Genetic Counseling (MSGC) program serves a vital role in implementing and expanding genetic counseling services in the Philippines. Currently, only eight clinical geneticists practice in the Philippines, a country of approximately 94 million people, which yields a clinical-geneticist-to-population-density ratio of 1:11,750,000. The MSGC program was created to train health care providers to become crucial members of medical genetics teams being formed to meet increasing patient and healthcare provider demands. In 2011, the Board of Regents approved our proposed curriculum at the Department of Pediatrics College of Medicine, University of the Philippines Manila. As we relate how the Philippines began its efforts to implement the program and attempted to overcome the challenges the program faced, we hope we can provide an example to those interested in creating a similar MSGC program in other low-income and middle-income countries.

  16. Genetic privacy in sports: clearing the hurdles.

    Science.gov (United States)

    Callier, Shawneequa

    2012-12-01

    As genomic medicine continues to advance and inform clinical care, knowledge gained is likely to influence sports medicine and training practices. Susceptibility to injury, sudden cardiac failure, and other serious conditions may one day be tackled on a subclinical level through genetic testing programs. In addition, athletes may increasingly consider using genetic testing services to maximize their performance potential. This paper assesses the role of privacy and genetic discrimination laws that would apply to athletes who engage in genetic testing and the limits of these protections.

  17. Transcription factories: genetic programming in three dimensions.

    Science.gov (United States)

    Edelman, Lucas Brandon; Fraser, Peter

    2012-04-01

    Among the most intensively studied systems in molecular biology is the eukaryotic transcriptional apparatus, which expresses genes in a regulated manner across hundreds of different cell types. Several studies over the past few years have added weight to the concept that transcription takes place within discrete 'transcription factories' assembled inside the cell nucleus. These studies apply innovative technical approaches to gain insights into the molecular constituents, dynamical behaviour and organizational regulators of transcription factories, providing exciting insights into the spatial dimension of transcriptional control.

  18. Genetic divergence of tomato subsamples

    Directory of Open Access Journals (Sweden)

    André Pugnal Mattedi

    2014-02-01

    Full Text Available Understanding the genetic variability of a species is crucial for the progress of a genetic breeding program and requires characterization and evaluation of germplasm. This study aimed to characterize and evaluate 101 tomato subsamples of the Salad group (fresh market and two commercial controls, one of the Salad group (cv. Fanny and another of the Santa Cruz group (cv. Santa Clara. Four experiments were conducted in a randomized block design with three replications and five plants per plot. The joint analysis of variance was performed and characteristics with significant complex interaction between control and experiment were excluded. Subsequently, the multicollinearity diagnostic test was carried out and characteristics that contributed to severe multicollinearity were excluded. The relative importance of each characteristics for genetic divergence was calculated by the Singh's method (Singh, 1981, and the less important ones were excluded according to Garcia (1998. Results showed large genetic divergence among the subsamples for morphological, agronomic and organoleptic characteristics, indicating potential for genetic improvement. The characteristics total soluble solids, mean number of good fruits per plant, endocarp thickness, mean mass of marketable fruit per plant, total acidity, mean number of unmarketable fruit per plant, internode diameter, internode length, main stem thickness and leaf width contributed little to the genetic divergence between the subsamples and may be excluded in future studies.

  19. Análisis de las malformaciones congénitas detectadas por el programa alfafetoproteína-ultrasonido genético Analysis of the congenital malformations detected by the alpha-fetoprotein-genetic ultrasound program

    Directory of Open Access Journals (Sweden)

    Aicha Julia Llamos Paneque

    2007-03-01

    Full Text Available La alfafetoproteína es una glicoproteína específica del plasma fetal, cuya determinación en suero materno se realiza entre las 15 y 19 semanas de gestación. Para conocer el comportamiento del programa alfafetoproteína-ultrasonido genético en el municipio 10 de Octubre se realizó esta investigación. En ella se encontró que 862 gestantes presentaron alfafetoproteína elevada en suero materno en el período analizado, y las principales causas encontradas dependientes de la madre fueron: el error en la fecha de última menstruación, seguida de la amenaza de aborto; y las malformaciones congénitas más frecuentemente encontradas fueron los defectos de cierre del tubo neural, seguidos de las malformaciones cardiovasculares.The alpha-fetoprotein is a specific glycoprotein of the fetal plasma, whose determination in maternal serum is performed from the 15th to the 19th week of gestation. This research was conducted to know the behavior of the alpha-fetoprotein-genetic ultrasound program in “10 de Octubre” municipality. It was found that 108 pregnant women presented elevated alpha-fetoprotein in maternal serum during the analyzed period. The main causes depending on the mother were: error in the date of the last menstruation and threatened abortion. The most frequent congenital malformations were the defects of the neural tube closure, and the cardiovascular malformations.

  20. Milestones in beef cattle genetic evaluation.

    Science.gov (United States)

    Golden, B L; Garrick, D J; Benyshek, L L

    2009-04-01

    National beef cattle genetic evaluation programs have evolved in the United States over the last 35 yr to create important tools that are part of sustainable breeding programs. The history of national beef cattle genetic evaluation programs has lessons to offer the next generation of researchers as new approaches in molecular genetics and decision support are developed. Through a series of complex and intricate pressures from technology and organizational challenges, national cattle evaluation programs continue to grow in importance and impact. Development of enabling technologies and the interface of the disciplines of computer science, numerical methods, statistics, and quantitative genetics have created an example of how academics, government, and industry can work together to create more effective solutions to technical problems. The advent of mixed model procedures was complemented by a series of breakthrough discoveries that made what was previously considered intractable a reality. The creation of modern genetic evaluation procedures has followed a path characterized by a steady and constant approach to identification and solution for each technical problem encountered. At its core, the driving force for the evolution has been the need to constantly improve the accuracy of the predictions of genetic merit for breeding stock, especially young animals. Sensible approaches, such as the principle of economically relevant traits, were developed that created the rules to be followed as the programs grew. However, the current systems are far from complete or perfect. Modern genetic evaluation programs have a long way to go, and a great deal of improvement in the accuracy of prediction is still possible. But the greatest challenge remains: the need to understand that genetic predictions are only parameters for decision support procedures and not an end in themselves.

  1. Newborn genetic screening: blessing or curse?

    Science.gov (United States)

    Kenner, C; Amlung, S

    1999-10-01

    Newly discovered genes and advances in genetic screening programs prompt many questions reflecting the kinds of ethical dilemmas that go hand in hand with life-changing discoveries. Neonatal genetic screening has been a standard of care for some time, but as our knowledge in the field of genetics expands, should we continue with the same approach? What newborn genetic screening tests should be mandatory, and what are the long-range consequences associated with testing? This article reviews genetic modes of inheritance, outlines and explains the most common newborn screening tests, and enumerates the ethical issues associated with these screening procedures. The role of the neonatal nurse in the newborn genetic screening process is discussed.

  2. A genetic engineering approach to genetic algorithms.

    Science.gov (United States)

    Gero, J S; Kazakov, V

    2001-01-01

    We present an extension to the standard genetic algorithm (GA), which is based on concepts of genetic engineering. The motivation is to discover useful and harmful genetic materials and then execute an evolutionary process in such a way that the population becomes increasingly composed of useful genetic material and increasingly free of the harmful genetic material. Compared to the standard GA, it provides some computational advantages as well as a tool for automatic generation of hierarchical genetic representations specifically tailored to suit certain classes of problems.

  3. Genetics and Rheumatic Disease

    Science.gov (United States)

    ... Well with Rheumatic Disease Genetics and Rheumatic Disease Genetics and Rheumatic Disease Fast Facts Studying twins has ... 70%, and for non-identical pairs, even lower. Genetics and ankylosing spondylitis Each rheumatic disease has its ...

  4. Applying the New Genetics

    Science.gov (United States)

    Sorenson, James

    1976-01-01

    New developments in the prediction and treatment of genetic diseases are presented. Genetic counseling and the role of the counselor, and rights of individuals to reproduce versus societal impact of genetic disorders, are discussed. (RW)

  5. Genetics and Rheumatic Disease

    Science.gov (United States)

    ... Well with Rheumatic Disease Genetics and Rheumatic Disease Genetics and Rheumatic Disease Fast Facts Studying twins has ... 70%, and for non-identical pairs, even lower. Genetics and ankylosing spondylitis Each rheumatic disease has its ...

  6. Current genetic counseling in China%中国目前的遗传咨询

    Institute of Scientific and Technical Information of China (English)

    章远志; Nanbert ZHONG

    2006-01-01

    @@ In 1975, the American Society of Human Genetics adopted the following definition of genetic counseling: genetic counseling is a communication process which deals with the human problems associated with the occurrence or risk of occurrence of a genetic disorder in a family. This definition indicates that genetic counseling is the delivery of information about genetic diseases, including genetic risks, natural history of the disease, and clinical management of the disease, to patients and their families. Although genetic counseling is not a new word for both western countries and China, the development of which is quite different. Many excellent genetic counseling programs have been developed since then in developed countries, whereas there is no formal one in China. In the United States, professionals who carry out genetic counseling must have taken a professional training and have had the certificate of American Board of Genetic Counseling (ABGC) (www.abgc.net). The ABGC prepares and administers examinations to certify individuals who provide services in the medical genetics specialty of genetic counseling, and accredits training programs in the field of genetic counseling. There are more than two dozen master degree programs of genetic counseling accredited by the ABGC with either full, interim, or recognized new programs (www.abgc.net). There are twenty-one full credential programs in the United States, three in Australia, three in Canada and two in United Kingdom (www.abgc.net). Looking through all over the China, there is no any official genetic counseling program, so neither any professional genetic counselor. Genetic counseling in China now is not offered by professionally trained genetic counselors, but clinicians such as pediatricians or obstetricians[1]. These clinicians who performing genetic counseling in China have not been trained professionally on genetic counseling. Further more, there is no any board to certificate counselors.

  7. Genetics Home Reference: vitiligo

    Science.gov (United States)

    ... physical functioning. However, concerns about appearance and ethnic identity are significant issues for many affected ... What information about a genetic condition can statistics provide? Why are some genetic ...

  8. Community Genetic Services in Iran

    Directory of Open Access Journals (Sweden)

    Shirin Atri Barzanjeh

    2012-01-01

    Full Text Available The aim of the study was to report a description of the primary, secondary, and tertiary level services available for genetic disorders in Iran. For the purpose of this study, essential data were collected from every facility providing community genetic services in Tabriz city of Iran using a prestructured checklist. Technical information was filled in the predesigned forms using diagnostic records of each client/patient. Information was also gathered from community genetic services clients through a face-to-face interview at these facilities to assess the quality of services provided. Primary prevention measures were available in 80 percent of centres in the study population. Diagnostic techniques were fully available in the study area both in public and private sectors. Screening of congenital hypothyroidism and thalassemia has been successfully performed across the country by the Ministry of Health. Other screening programs have also been initiated by the country health authorities for neural tube defects, Down syndrome, and phenylketonuria. The high cost of genetic services at secondary and tertiary levels does not allow many people to get access to these services despite their needs. Governments will therefore need to allocate necessary resources to make the essential genetic services available for everyone needing these in the community.

  9. SOLUTION OF NONLINEAR PROBLEMS IN WATER RESOURCES SYSTEMS BY GENETIC ALGORITHM

    Directory of Open Access Journals (Sweden)

    Ahmet BAYLAR

    1998-03-01

    Full Text Available Genetic Algorithm methodology is a genetic process treated on computer which is considering evolution process in the nature. The genetic operations takes place within the chromosomes stored in computer memory. By means of various operators, the genetic knowledge in chromosomes change continuously and success of the community progressively increases as a result of these operations. The primary purpose of this study is calculation of nonlinear programming problems in water resources systems by Genetic Algorithm. For this purpose a Genetic Algoritm based optimization program were developed. It can be concluded that the results obtained from the genetic search based method give the precise results.

  10. Genetic aspects and genetic epidemiology of parasomnias.

    Science.gov (United States)

    Hublin, Christer; Kaprio, Jaakko

    2003-10-01

    Parasomnias are undesirable phenomena associated with sleep. Many of them run in families, and genetic factors have been long suggested to be involved in their occurrence. This article reviews the present knowledge of the genetics of the major classical behavioral parasomnias as well as present results from genetic epidemiological studies. The level and type of evidence for genetic effects varies much from parasomnia to parasomnia. The genetic factors are best established in enuresis, with several linkages to chromosomal loci, but their functions are not so far known. Environmental causes and gene-environment interactions are most probably also of great importance in the origin of complex traits or disorders such as parasomnias.

  11. Conservation genetics of managed ungulate populations

    Science.gov (United States)

    Scribner, Kim T.

    1993-01-01

    Natural populations of many species are increasingly impacted by human activities. Perturbations are particularly pronunced for large ungulates due in part to sport and commercial harvest, to reductions and fragmentation of native habitat, and as the result of reintroductions. These perturbations affect population size, sex and age composition, and population breeding structure, and as a consequence affect the levels and partitioning of genetic variation. Three case histories highlighting long-term ecological genetic research on mule deer Odocoileus hemionus (Rafinesque, 1817), white-tailed deer O. virginianus (Zimmermann, 1780), and Alpine ibex Capra i. ibex Linnaeus, 1758 are presented. Joint examinations of population ecological and genetic data from several populations of each species reveal: (1) that populations are not in genetic equilibrium, but that allele frequencies and heterozygosity change dramatically over time and among cohorts produced in successive years, (2) populations are genetically structured over short and large geographic distances reflecting local breeding structure and patterns of gene flow, respectively; however, this structure is quite dynamic over time, due in part to population exploitation, and (3) restocking programs are often undertaken with small numbers of founding individuals resulting in dramatic declines in levels of genetic variability and increasing levels of genetic differentiation among populations due to genetic drift. Genetic characteristics have and will continue to provide valuable indirect sources of information relating enviromental and human perturbations to changes in population processes.

  12. The genetics of immunity.

    Science.gov (United States)

    Lazzaro, Brian P; Schneider, David S

    2014-06-17

    In this commentary, Brian P. Lazzaro and David S. Schneider examine the topic of the Genetics of Immunity as explored in this month's issues of GENETICS and G3: Genes|Genomes|Genetics. These inaugural articles are part of a joint Genetics of Immunity collection (ongoing) in the GSA journals. Copyright © 2014 Lazzaro and Schneider.

  13. GENETIC AND NON-GENETIC PARAMETER ESTIMATES OF DAIRY CATTLE IN ETHIOPIA: A REVIEW

    Directory of Open Access Journals (Sweden)

    A. TESFA

    2014-07-01

    Full Text Available Ethiopia is endowed with diverse ecosystems inhabited by an abundant diversity of animal, plant and microbial genetic resources due to the availability of diverse agro-ecology. The productivity of any species depends largely on their reproductive performance. Reproduction is an indicator of reproductive efficiency and the rate of genetic progress in both selection and crossbreeding programs. Reproductive performance does not usually refer to a single trait, but to a combination of many traits and is an indicator of reproductive efficiency and the rate of genetic progress. The main indicators of reproductive performance those are reported by many authors are age at first service, age at first calving, calving interval, days open and number of services per conception. The non-genetic factors like sex of calf, season, year, and parity had significant effect on reproductive performance traits. Knowledge on these factors and their influence on cattle performance are important in management and selection decisions. Development of breeding objectives and effective genetic improvement programs require knowledge of the genetic variation among economically important traits and accurate estimates of heritability, repeatability and genetic correlations of these traits. The estimates of genetic parameters are helpful in determining the method of selection to predict direct and correlated response to selection, choosing a breeding system to be adopted for future improvement as well as genetic gains. The reproductive performance of Ethiopian indigenous and exotic breeds producing in the country is low due to various environmental factors and absence of integrated record on the sector that leads a biased result and recommendations of the genetic parameter estimates. Selection and designing of breeding programs for improving the production and productivity of indigenous breed through keeping their native potentials should be based on the results obtained from

  14. Genetic Algorithms for multiple objective vehicle routing

    CERN Document Server

    Geiger, Martin Josef

    2008-01-01

    The talk describes a general approach of a genetic algorithm for multiple objective optimization problems. A particular dominance relation between the individuals of the population is used to define a fitness operator, enabling the genetic algorithm to adress even problems with efficient, but convex-dominated alternatives. The algorithm is implemented in a multilingual computer program, solving vehicle routing problems with time windows under multiple objectives. The graphical user interface of the program shows the progress of the genetic algorithm and the main parameters of the approach can be easily modified. In addition to that, the program provides powerful decision support to the decision maker. The software has proved it's excellence at the finals of the European Academic Software Award EASA, held at the Keble college/ University of Oxford/ Great Britain.

  15. Genetic screening services provided in Turkey.

    Science.gov (United States)

    Erdem, Yurdagül; Tekşen, Fulya

    2013-12-01

    In Turkey, the rate of consanguineous marriage is quite high (22-24 %) and as a result, the incidence of autosomal recessive diseases and congenital anomalies is also very high and gives rise to a serious public health problem. In the last three decades, great effort has been made to avoid increases in the prevalence of these hereditary diseases. For this purpose, population-based premarital, prenatal, neonatal and adult genetic screening programs are performed in various centers such as Community Health Centers, Early Diagnosis of Cancer and Education Centers (KETEM), Prenatal and Neonatal Departments of Universities and State Hospitals and Thalessemia Screening Centers. Such centers are staffed by health professionals including physicians, family physicians, nurses, midwives, biologists and medical geneticists. Genetic counseling is also provided to patients attending these centers after screening tests are performed. Since there are no specialized training programs for genetic counselors, genetic counseling is generally provided by doctors or medical geneticists. The aim of this paper is to give an overview of the genetic screening services provided in Turkey, the prevalence of genetic diseases and the design of intensive educational programs for health professionals.

  16. Genetic Engineering Workshop Report, 2010

    Energy Technology Data Exchange (ETDEWEB)

    Allen, J; Slezak, T

    2010-11-03

    The Lawrence Livermore National Laboratory (LLNL) Bioinformatics group has recently taken on a role in DTRA's Transformation Medical Technologies (TMT) program. The high-level goal of TMT is to accelerate the development of broad-spectrum countermeasures. To achieve this goal, there is a need to assess the genetic engineering (GE) approaches, potential application as well as detection and mitigation strategies. LLNL was tasked to coordinate a workshop to determine the scope of investments that DTRA should make to stay current with the rapid advances in genetic engineering technologies, so that accidental or malicious uses of GE technologies could be adequately detected and characterized. Attachment A is an earlier report produced by LLNL for TMT that provides some relevant background on Genetic Engineering detection. A workshop was held on September 23-24, 2010 in Springfield, Virginia. It was attended by a total of 55 people (see Attachment B). Twenty four (44%) of the attendees were academic researchers involved in GE or bioinformatics technology, 6 (11%) were from DTRA or the TMT program management, 7 (13%) were current TMT performers (including Jonathan Allen and Tom Slezak of LLNL who hosted the workshop), 11 (20%) were from other Federal agencies, and 7 (13%) were from industries that are involved in genetic engineering. Several attendees could be placed in multiple categories. There were 26 attendees (47%) who were from out of the DC area and received travel assistance through Invitational Travel Orders (ITOs). We note that this workshop could not have been as successful without the ability to invite experts from outside of the Beltway region. This workshop was an unclassified discussion of the science behind current genetic engineering capabilities. US citizenship was not required for attendance. While this may have limited some discussions concerning risk, we felt that it was more important for this first workshop to focus on the scientific state of

  17. Applying new genetic approaches to improve quality of population assessment of green and loggerhead turtles

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — As the NOAA-Fisheries? National Sea Turtle Genetics Lab, the SWFSC Marine Turtle Genetics Program has the lead responsibility for generating, analyzing and...

  18. Genetic engineering, medicine and medical genetics.

    Science.gov (United States)

    Motulsky, A G

    1984-01-01

    The impact of DNA technology in the near future will be on the manufacture of biologic agents and reagents that will lead to improved therapy and diagnosis. The use of DNA technology for prenatal and preclinical diagnosis in genetic diseases is likely to affect management of genetic diseases considerably. New and old questions regarding selective abortion and the psychosocial impact of early diagnosis of late appearing diseases and of genetic susceptibilities are being raised. Somatic therapy with isolated genes to treat disease has not been achieved. True germinal genetic engineering is far off for humans but may find applications in animal agriculture.

  19. Marine biosurfaces research program

    Science.gov (United States)

    The Office of Naval Research (ONR) of the U.S. Navy is starting a basic research program to address the initial events that control colonization of surfaces by organisms in marine environments. The program “arises from the Navy's need to understand and ultimately control biofouling and biocorrosion in marine environments,” according to a Navy announcement.The program, “Biological Processes Controlling Surface Modification in the Marine Environment,” will emphasize the application of in situ techniques and modern molecular biological, biochemical, and biophysical approaches; it will also encourage the development of interdisciplinary projects. Specific areas of interest include sensing and response to environmental surface (physiology/physical chemistry), factors controlling movement to and retention at surfaces (behavior/hydrodynamics), genetic regulation of attachment (molecular genetics), and mechanisms of attachment (biochemistry/surface chemistry).

  20. Theory and practice in quantitative genetics.

    Science.gov (United States)

    Posthuma, Daniëlle; Beem, A Leo; de Geus, Eco J C; van Baal, G Caroline M; von Hjelmborg, Jacob B; Iachine, Ivan; Boomsma, Dorret I

    2003-10-01

    With the rapid advances in molecular biology, the near completion of the human genome, the development of appropriate statistical genetic methods and the availability of the necessary computing power, the identification of quantitative trait loci has now become a realistic prospect for quantitative geneticists. We briefly describe the theoretical biometrical foundations underlying quantitative genetics. These theoretical underpinnings are translated into mathematical equations that allow the assessment of the contribution of observed (using DNA samples) and unobserved (using known genetic relationships) genetic variation to population variance in quantitative traits. Several statistical models for quantitative genetic analyses are described, such as models for the classical twin design, multivariate and longitudinal genetic analyses, extended twin analyses, and linkage and association analyses. For each, we show how the theoretical biometrical model can be translated into algebraic equations that may be used to generate scripts for statistical genetic software packages, such as Mx, Lisrel, SOLAR, or MERLIN. For using the former program a web-library (available from http://www.psy.vu.nl/mxbib) has been developed of freely available scripts that can be used to conduct all genetic analyses described in this paper.

  1. Genetics of pediatric obesity.

    Science.gov (United States)

    Manco, Melania; Dallapiccola, Bruno

    2012-07-01

    Onset of obesity has been anticipated at earlier ages, and prevalence has dramatically increased worldwide over the past decades. Epidemic obesity is mainly attributable to modern lifestyle, but family studies prove the significant role of genes in the individual's predisposition to obesity. Advances in genotyping technologies have raised great hope and expectations that genetic testing will pave the way to personalized medicine and that complex traits such as obesity will be prevented even before birth. In the presence of the pressing offer of direct-to-consumer genetic testing services from private companies to estimate the individual's risk for complex phenotypes including obesity, the present review offers pediatricians an update of the state of the art on genomics obesity in childhood. Discrepancies with respect to genomics of adult obesity are discussed. After an appraisal of findings from genome-wide association studies in pediatric populations, the rare variant-common disease hypothesis, the theoretical soil for next-generation sequencing techniques, is discussed as opposite to the common disease-common variant hypothesis. Next-generation sequencing techniques are expected to fill the gap of "missing heritability" of obesity, identifying rare variants associated with the trait and clarifying the role of epigenetics in its heritability. Pediatric obesity emerges as a complex phenotype, modulated by unique gene-environment interactions that occur in periods of life and are "permissive" for the programming of adult obesity. With the advent of next-generation sequencing techniques and advances in the field of exposomics, sensitive and specific tools to predict the obesity risk as early as possible are the challenge for the next decade.

  2. Basic genetics for dermatologists

    Directory of Open Access Journals (Sweden)

    Muthu Sendhil Kumaran

    2013-01-01

    Full Text Available During the past few decades, advances in the field of molecular genetics have enriched us in understanding the pathogenesis of diseases, their identification, and appropriate therapeutic interventions. In the last 20 years, genetic basis of more than 350 monogenic skin diseases have been elucidated and is counting. The widespread use of molecular genetics as a tool in diagnosis is not practiced routinely due to genetic heterogenicity, limited access and low sensitivity. In this review, we have presented the very basics of genetics so as to enable dermatologists to have working understanding of medical genetics.

  3. UPDATE ON US NATIONAL PRRS PROJECT PLANS: THE USDA FUNDED PRRS CAP PROGRAM, THE NPB FUNDED PRRS HOST GENETIC CONSORTIUM, AND US NATIONAL SWINE RESPIRATORY DISEASE NC229 PROJECT

    Science.gov (United States)

    There are several major US efforts to address swine respiratory diseases. These include the US Department of Agriculture (USDA) funded PRRS coordinated agricultural project (PRRS CAP), the US National Pork Board (NPB) funded PRRS Host Genetic Consortium (PHGC), and the US national Swine Respiratory ...

  4. Clinical applications of schizophrenia genetics: genetic diagnosis, risk, and counseling in the molecular era

    Directory of Open Access Journals (Sweden)

    Costain G

    2012-02-01

    Full Text Available Gregory Costain1,2, Anne S Bassett1–41Clinical Genetics Research Program, Centre for Addiction and Mental Health, 2Institute of Medical Science, University of Toronto, 3Division of Cardiology, Department of Medicine and Department of Psychiatry, University Health Network, 4Department of Psychiatry, University of Toronto, Toronto, Ontario, CanadaAbstract: Schizophrenia is a complex neuropsychiatric disease with documented clinical and genetic heterogeneity, and evidence for neurodevelopmental origins. Driven by new genetic technologies and advances in molecular medicine, there has recently been concrete progress in understanding some of the specific genetic causes of this serious psychiatric illness. In particular, several large rare structural variants have been convincingly associated with schizophrenia, in targeted studies over two decades with respect to 22q11.2 microdeletions, and more recently in large-scale, genome-wide case-control studies. These advances promise to help many families afflicted with this disease. In this review, we critically appraise recent developments in the field of schizophrenia genetics through the lens of immediate clinical applicability. Much work remains in translating the recent surge of genetic research discoveries into the clinic. The epidemiology and basic genetic parameters (such as penetrance and expression of most genomic disorders associated with schizophrenia are not yet well characterized. To date, 22q11.2 deletion syndrome is the only established genetic subtype of schizophrenia of proven clinical relevance. We use this well-established association as a model to chart the pathway for translating emerging genetic discoveries into clinical practice. We also propose new directions for research involving general genetic risk prediction and counseling in schizophrenia.Keywords: schizophrenia, genetics, 22q11 deletion syndrome, copy number variation, genetic counseling, genetic predisposition to disease

  5. Inconsistencies in pedigree symbols in human genetics publications: A need for standardization

    Energy Technology Data Exchange (ETDEWEB)

    Steinhaus, K.A.; Bennett, R.L.; Resta, R.G. [Univ. of California at Irvine, Orange, CA (United States)] [and others

    1995-04-10

    To determine consistency in usage of pedigree symbols by genetics professionals, we reviewed pedigrees printed in 10 human genetic and medical journals and 24 medical genetics textbooks. We found no consistent symbolization for common situations such as pregnancy, spontaneous abortion, death, or test results. Inconsistency in pedigree design can create difficulties in the interpretation of family studies and detract from the pedigree`s basic strength of simple and accurate communication of medical information. We recommend the development of standard pedigree symbols, and their incorporation into genetic publications, professional genetics training programs, pedigree software programs, and genetic board examinations. 5 refs., 11 figs., 2 tabs.

  6. Genetics Home Reference

    Science.gov (United States)

    Skip Navigation Bar Home Current Issue Past Issues Genetics Home Reference Past Issues / Spring 2007 Table of ... of this page please turn Javascript on. The Genetics Home Reference (GHR) Web site — ghr.nlm.nih. ...

  7. Genetics of Hearing Loss

    Science.gov (United States)

    ... in Latin America Information For... Media Policy Makers Genetics of Hearing Loss Language: English Español (Spanish) Recommend ... of hearing loss in babies is due to genetic causes. There are also a number of things ...

  8. Frontotemporal Dementia: Genetics

    Science.gov (United States)

    ... Calendar of Events Fundraising Events Conferences Press Releases Genetics of FTD After receiving a diagnosis of FTD ... that recent advances in science have brought the genetics of FTD into much better focus. In 2012, ...

  9. Genetic Disease Foundation

    Science.gov (United States)

    ... mission to help prevent, manage and treat inherited genetic diseases. View our latest News Brief here . You can ... contributions to the diagnosis, prevention and treatment of genetic diseases. Learn how advances at Mount Sinai have impacted ...

  10. Genetic Brain Disorders

    Science.gov (United States)

    A genetic brain disorder is caused by a variation or a mutation in a gene. A variation is a different form ... mutation is a change in a gene. Genetic brain disorders affect the development and function of the ...

  11. Genetics Home Reference

    Science.gov (United States)

    ... changes Browse A–Z Chromosomes & mtDNA Autosomes, sex chromosomes, and mitochondrial DNA (mtDNA) Browse Help Me Understand Genetics Learn about the basics of human genetics Browse New & Updated Pages New Pages Omenn ...

  12. Genetically engineered foods

    Science.gov (United States)

    Bioengineered foods; GMOs; Genetically modified foods ... helps speed up the process of creating new foods with desired traits. The possible benefits of genetic engineering include: More nutritious food Tastier food Disease- and ...

  13. Genetics of Parkinson's disease

    National Research Council Canada - National Science Library

    Klein, Christine; Westenberger, Ana

    2012-01-01

    Fifteen years of genetic research in Parkinson's disease (PD) have led to the identification of several monogenic forms of the disorder and of numerous genetic risk factors increasing the risk to develop PD...

  14. Prenatal screening and genetics

    DEFF Research Database (Denmark)

    Alderson, P; Aro, A R; Dragonas, T

    2001-01-01

    Although the term 'genetic screening' has been used for decades, this paper discusses how, in its most precise meaning, genetic screening has not yet been widely introduced. 'Prenatal screening' is often confused with 'genetic screening'. As we show, these terms have different meanings, and we...... examine definitions of the relevant concepts in order to illustrate this point. The concepts are i) prenatal, ii) genetic screening, iii) screening, scanning and testing, iv) maternal and foetal tests, v) test techniques and vi) genetic conditions. So far, prenatal screening has little connection...... with precisely defined genetics. There are benefits but also disadvantages in overstating current links between them in the term genetic screening. Policy making and professional and public understandings about screening could be clarified if the distinct meanings of prenatal screening and genetic screening were...

  15. Genetics Home Reference: hyperprolinemia

    Science.gov (United States)

    ... can also occur with other conditions, such as malnutrition or liver disease. In particular, individuals with conditions ... Topic: Amino Acid Metabolism Disorders Health Topic: Genetic Brain Disorders Health Topic: Newborn Screening Genetic and Rare ...

  16. Genetics Home Reference: hypermethioninemia

    Science.gov (United States)

    ... C. Mutations in human glycine N-methyltransferase give insights into its role in methionine metabolism. Hum Genet. ... healthcare professional . About Genetics Home Reference Site Map Customer Support Selection Criteria for Links USA.gov Copyright ...

  17. Genetics in psychiatry.

    Science.gov (United States)

    Umesh, Shreekantiah; Nizamie, Shamshul Haque

    2014-04-01

    Today, psychiatrists are focusing on genetics aspects of various psychiatric disorders not only for a future classification of psychiatric disorders but also a notion that genetics would aid in the development of new medications to treat these disabling illnesses. This review therefore emphasizes on the basics of genetics in psychiatry as well as focuses on the emerging picture of genetics in psychiatry and their future implications.

  18. Behavioral genetics and taste

    Directory of Open Access Journals (Sweden)

    Bachmanov Alexander A

    2007-09-01

    Full Text Available Abstract This review focuses on behavioral genetic studies of sweet, umami, bitter and salt taste responses in mammals. Studies involving mouse inbred strain comparisons and genetic analyses, and their impact on elucidation of taste receptors and transduction mechanisms are discussed. Finally, the effect of genetic variation in taste responsiveness on complex traits such as drug intake is considered. Recent advances in development of genomic resources make behavioral genetics a powerful approach for understanding mechanisms of taste.

  19. Statistics for Learning Genetics

    Science.gov (United States)

    Charles, Abigail Sheena

    2012-01-01

    This study investigated the knowledge and skills that biology students may need to help them understand statistics/mathematics as it applies to genetics. The data are based on analyses of current representative genetics texts, practicing genetics professors' perspectives, and more directly, students' perceptions of, and performance in, doing…

  20. Report: Human cancer genetics

    Institute of Scientific and Technical Information of China (English)

    LI Marilyn; ALBERTSON Donna

    2006-01-01

    The short report will be focused on the genetic basis and possible mechanisms of tumorigenesis, common types of cancer, the importance of genetic diagnosis of cancer, and the methodology of cancer genetic diagnosis. They will also review presymptomatic testing of hereditary cancers, and the application of expression profiling to identify patients likely to benefit from particular therapeutic approaches.

  1. Prenatal screening and genetics

    NARCIS (Netherlands)

    Alderson, P.; Aro, A.R.; Dragonas, T.; Ettorre, E.; Hemminki, E.; Jalinoja, P.; Santalahti, P.; Tijmstra, T.

    Although the term 'genetic screening' has been used for decades, this paper discusses how, in its most precise meaning, genetic screening has not yet been widely introduced. 'Prenatal screening' is often confused with 'genetic screening'. As we show, these terms have different meanings, and we

  2. Human cancer genetics*

    OpenAIRE

    2006-01-01

    The short report will be focused on the genetic basis and possible mechanisms of tumorigenesis, common types of cancer, the importance of genetic diagnosis of cancer, and the methodology of cancer genetic diagnosis. They will also review presymptomatic testing of hereditary cancers, and the application of expression profiling to identify patients likely to benefit from particular therapeutic approaches.

  3. Statistics for Learning Genetics

    Science.gov (United States)

    Charles, Abigail Sheena

    2012-01-01

    This study investigated the knowledge and skills that biology students may need to help them understand statistics/mathematics as it applies to genetics. The data are based on analyses of current representative genetics texts, practicing genetics professors' perspectives, and more directly, students' perceptions of, and performance in, doing…

  4. Prenatal screening and genetics

    NARCIS (Netherlands)

    Alderson, P.; Aro, A.R.; Dragonas, T.; Ettorre, E.; Hemminki, E.; Jalinoja, P.; Santalahti, P.; Tijmstra, T.

    2001-01-01

    Although the term 'genetic screening' has been used for decades, this paper discusses how, in its most precise meaning, genetic screening has not yet been widely introduced. 'Prenatal screening' is often confused with 'genetic screening'. As we show, these terms have different meanings, and we exami

  5. Prenatal screening and genetics

    DEFF Research Database (Denmark)

    Alderson, P; Aro, A R; Dragonas, T

    2001-01-01

    Although the term 'genetic screening' has been used for decades, this paper discusses how, in its most precise meaning, genetic screening has not yet been widely introduced. 'Prenatal screening' is often confused with 'genetic screening'. As we show, these terms have different meanings, and we ex...

  6. GENETICS AND GENOMICS OF PLANT GENETIC RESOURCES

    Directory of Open Access Journals (Sweden)

    Börner A.

    2012-08-01

    Full Text Available Plant genetic resources play a major role for global food security. The most significant and widespread mean of conserving plant genetic resources is ex situ conservation. Most conserved accessions are kept in specialized facilities known as genebanks maintained by public or private institutions. World-wide 7.4 million accessions are stored in about 1,500 ex situ genebanks.In addition, series of genetic stocks including chromosome substitution lines, alloplasmic lines, single chromosome recombinant lines, introgression lines, etc. have been created. Analysing these genetic stocks many qualitative and quantitative inherited traits were associated to certain chromosomes, chromosome arms or introgressed segments. Today, genetic stocks are supplemented by a huge number of genotyped mapping populations. Beside progenies of bi-parental crosses (doubled haploid lines, recombinant inbred lines, etc. panels for association mapping were created recently.In our presentation we give examples for the successful utilisation of genebank accessions and genetic stocks for genetic and genomic studies. Using both segregation and association mapping approaches, data on mapping of loci/marker trait associations for a range of different traits are presented.

  7. GENMAP--A Microbial Genetics Computer Simulation.

    Science.gov (United States)

    Day, M. J.; And Others

    1985-01-01

    An interactive computer program in microbial genetics is described. The simulation allows students to work at their own pace and develop understanding of microbial techniques as they choose donor bacterial strains, specify selective media, and interact with demonstration experiments. Sample questions and outputs are included. (DH)

  8. Factors affecting student performance in an undergraduate genetics course.

    Science.gov (United States)

    Bormann, J Minick; Moser, D W; Bates, K E

    2013-05-01

    The objective of this study was to determine some of the factors that affect student success in a genetics course. Genetics for the Kansas State University College of Agriculture is taught in the Department of Animal Sciences and Industry and covers Mendelian inheritance, molecular genetics, and quantitative/population genetics. Data collected from 1,516 students over 7 yr included year and semester of the course; age; gender; state of residence; population of hometown; Kansas City metro resident or not; instructor of course; American College Testing Program (ACT) scores; number of transfer credits; major; college; preveterinary student or not; freshman, sophomore, junior, and senior grade point average (GPA); semester credits when taking genetics; class standing when enrolled in genetics; cumulative GPA before and after taking genetics; semester GPA in semester taking genetics, number of semesters between the biology prerequisite and genetics; grade in biology; location of biology course; and final percentage in genetics. Final percentage in genetics did not differ due to instructor, gender, state of residence, major, or college (P > 0.16). Transfer students tended to perform better than nontransfer students (P = 0.09), and students from the Kansas City metro outscored students from other areas (P = 0.03). Preveterinary option students scored higher in genetics than non-preveterinary students (P genetics (P = 0.06). Students who took biology at Kansas State University performed better in genetics than students who transferred the credit (P genetics (P genetics, students should take biology from Kansas State, perform well in biology, and wait until at least sophomore standing to enroll in genetics.

  9. Practical strategies of black walnut genetic improvement—an update

    Science.gov (United States)

    George Rink; J.W. Van Sambeek; Phil O' Connor; Mark. Coggeshall

    2017-01-01

    The ultimate goal of any tree improvement program is the large-scale production and distribution of genetically improved seedlings. In black walnut, projections based on earlier research indicate that genetically improved seedlings could provide growth improvement of between 15 to 25 percent by using seed or seedlings of the proper geographic origin (Bey 1980; Clausen...

  10. Genetic architecture of gene expression in ovine skeletal muscle

    DEFF Research Database (Denmark)

    Kogelman, Lisette Johanna Antonia; Byrne, Keren; Vuocolo, Tony

    2011-01-01

    -based gene expression data we directly tested the hypothesis that there is genetic structure in the gene expression program in ovine skeletal muscle.Results: The genetic performance of six sires for a well defined muscling trait, longissimus lumborum muscle depth, was measured using extensive progeny testing...

  11. Private and public eugenics: genetic and screening in India

    NARCIS (Netherlands)

    Gupta, J.A.

    2007-01-01

    Epidemiologists and geneticists claim that genetics has an increasing role to play in public health policies and programs in the future. Within this perspective, genetic testing and screening are instrumental in avoiding the birth of children with serious, costly or untreatable disorders. This paper

  12. Genetic Potential of Winter Wheat Grain Quality in Central Asia

    Science.gov (United States)

    Abugaliyeva, Aigul I.; Morgounov, Alexey I.

    2016-01-01

    The grain quality of winter wheat varies significantly by cultivars and growing region, not previously differentiated by end-use (baking, confectionery, etc.) in the national breeding programs. In these conditions it is advisable to determine the genetic potential and analyze the actual grain quality. Determining the genetic potential requires the…

  13. Computer program for allocation of generators in isolated systems of direct current using genetic algorithm; Programa computacional para alocacao de geradores em sistemas isolados de corrente continua utilizando algoritmo genetico

    Energy Technology Data Exchange (ETDEWEB)

    Gewehr, Diego N.; Vargas, Ricardo B.; Melo, Eduardo D. de; Paschoareli Junior, Dionizio [Universidade Estadual Paulista (DEE/UNESP), Ilha Solteira, SP (Brazil). Dept. de Engenharia Eletrica. Grupo de Pesquisa em Fontes Alternativas e Aproveitamento de Energia

    2008-07-01

    This paper presents a methodology for electric power sources location in isolated direct current micro grids, using genetic algorithm. In this work, photovoltaic panels are considered, although the methodology can be extended for any kind of DC sources. A computational tool is developed using the Matlab simulator, to obtain the best dc system configuration for reduction of panels quantity and costs, and to improve the system performance. (author)

  14. Massively Parallel Genetics.

    Science.gov (United States)

    Shendure, Jay; Fields, Stanley

    2016-06-01

    Human genetics has historically depended on the identification of individuals whose natural genetic variation underlies an observable trait or disease risk. Here we argue that new technologies now augment this historical approach by allowing the use of massively parallel assays in model systems to measure the functional effects of genetic variation in many human genes. These studies will help establish the disease risk of both observed and potential genetic variants and to overcome the problem of "variants of uncertain significance." Copyright © 2016 by the Genetics Society of America.

  15. Primer on genetic counseling.

    Science.gov (United States)

    Hahn, Susan Estabrooks

    2011-04-01

    Once limited to rare mendelian disorders, genetic counseling is playing an ever-increasing role in the multidisciplinary approach to predicting, diagnosing, and managing neurologic disease. However, genetic counseling services may not be optimized because of lack of availability and lack of knowledge regarding when it is appropriate to refer, what occurs in genetic counseling, and how genetic counseling can affect care. These issues are addressed in this article, along with corresponding clinical scenarios. Websites to find genetic counseling services and resources are also provided.

  16. How Is Genetic Testing Done?

    Science.gov (United States)

    ... Testing How is genetic testing done? How is genetic testing done? Once a person decides to proceed with ... is called informed consent . For more information about genetic testing procedures: The National Society of Genetic Counselors offers ...

  17. BPA genetic monitoring - BPA Genetic Monitoring Project

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Initiated in 1989, this study monitors genetic changes associated with hatchery propagation in multiple Snake River sub-basins for Chinook salmon and steelhead. We...

  18. Molecular genetics made simple

    Directory of Open Access Journals (Sweden)

    Heba Sh. Kassem

    2012-07-01

    Full Text Available Genetics have undoubtedly become an integral part of biomedical science and clinical practice, with important implications in deciphering disease pathogenesis and progression, identifying diagnostic and prognostic markers, as well as designing better targeted treatments. The exponential growth of our understanding of different genetic concepts is paralleled by a growing list of genetic terminology that can easily intimidate the unfamiliar reader. Rendering genetics incomprehensible to the clinician however, defeats the very essence of genetic research: its utilization for combating disease and improving quality of life. Herein we attempt to correct this notion by presenting the basic genetic concepts along with their usefulness in the cardiology clinic. Bringing genetics closer to the clinician will enable its harmonious incorporation into clinical care, thus not only restoring our perception of its simple and elegant nature, but importantly ensuring the maximal benefit for our patients.

  19. Genetic interest assessment

    Science.gov (United States)

    Doughney, Erin

    Genetics is becoming increasingly integrated into peoples' lives. Different measures have been taken to try and better genetics education. This thesis examined undergraduate students at the University of North Texas not majoring in the life sciences interest in genetic concepts through the means of a Likert style survey. ANOVA analysis showed there was variation amongst the interest level in different genetic concepts. In addition age and lecture were also analyzed as contributing factors to students' interest. Both age and lecture were evaluated to see if they contributed to the interest of students in genetic concepts and neither showed statistical significance. The Genetic Interest Assessment (GIA) serves to help mediate the gap between genetic curriculum and students' interest.

  20. Rewriting the Genetic Code.

    Science.gov (United States)

    Mukai, Takahito; Lajoie, Marc J; Englert, Markus; Söll, Dieter

    2017-09-08

    The genetic code-the language used by cells to translate their genomes into proteins that perform many cellular functions-is highly conserved throughout natural life. Rewriting the genetic code could lead to new biological functions such as expanding protein chemistries with noncanonical amino acids (ncAAs) and genetically isolating synthetic organisms from natural organisms and viruses. It has long been possible to transiently produce proteins bearing ncAAs, but stabilizing an expanded genetic code for sustained function in vivo requires an integrated approach: creating recoded genomes and introducing new translation machinery that function together without compromising viability or clashing with endogenous pathways. In this review, we discuss design considerations and technologies for expanding the genetic code. The knowledge obtained by rewriting the genetic code will deepen our understanding of how genomes are designed and how the canonical genetic code evolved.

  1. Outcomes of genetics services: creating an inclusive definition and outcomes menu for public health and clinical genetics services.

    Science.gov (United States)

    Silvey, Kerry; Stock, Jacquie; Hasegawa, Lianne E; Au, Sylvia Mann

    2009-08-15

    Third party payers, funding agencies, and lawmakers often require clinicians and public health agencies to justify programs and services by documenting results. This article describes two assessment tools--"Defining Genetics Services Framework" and "Genetics Services Outcomes Menu," created to assist public health professionals, clinicians, family advocates, and researchers to plan, evaluate, and demonstrate the effectiveness of genetics services. The tools were developed by a work group of the Western States Genetics Services Collaborative (WSGSC) consisting of public health genetics and newborn screening professionals, family representatives, a medical geneticist, and genetic counselors from Alaska, California, Hawaii, Idaho, Oregon, and Washington. The work group created both tools by an iterative process of combining their ideas with findings from a literature and World Wide Web review. The Defining Genetics Services Framework reflects the diversity of work group members. Three over-lapping areas of genetics services from public health core functions to population screening to clinical genetics services are depicted. The Genetics Services Outcomes Menu lists sample long-term outcomes of genetics services. Menu outcomes are classified under impact areas of Knowledge and Information; Financing; Screening and Identification; Diagnosis, Treatment, and Management; and Population Health. The WSGSC incorporated aspects of both tools into their Regional Genetics Plan. 2009 Wiley-Liss, Inc.

  2. Molecular Population Genetics

    Science.gov (United States)

    Casillas, Sònia; Barbadilla, Antonio

    2017-01-01

    Molecular population genetics aims to explain genetic variation and molecular evolution from population genetics principles. The field was born 50 years ago with the first measures of genetic variation in allozyme loci, continued with the nucleotide sequencing era, and is currently in the era of population genomics. During this period, molecular population genetics has been revolutionized by progress in data acquisition and theoretical developments. The conceptual elegance of the neutral theory of molecular evolution or the footprint carved by natural selection on the patterns of genetic variation are two examples of the vast number of inspiring findings of population genetics research. Since the inception of the field, Drosophila has been the prominent model species: molecular variation in populations was first described in Drosophila and most of the population genetics hypotheses were tested in Drosophila species. In this review, we describe the main concepts, methods, and landmarks of molecular population genetics, using the Drosophila model as a reference. We describe the different genetic data sets made available by advances in molecular technologies, and the theoretical developments fostered by these data. Finally, we review the results and new insights provided by the population genomics approach, and conclude by enumerating challenges and new lines of inquiry posed by increasingly large population scale sequence data. PMID:28270526

  3. Molecular Population Genetics.

    Science.gov (United States)

    Casillas, Sònia; Barbadilla, Antonio

    2017-03-01

    Molecular population genetics aims to explain genetic variation and molecular evolution from population genetics principles. The field was born 50 years ago with the first measures of genetic variation in allozyme loci, continued with the nucleotide sequencing era, and is currently in the era of population genomics. During this period, molecular population genetics has been revolutionized by progress in data acquisition and theoretical developments. The conceptual elegance of the neutral theory of molecular evolution or the footprint carved by natural selection on the patterns of genetic variation are two examples of the vast number of inspiring findings of population genetics research. Since the inception of the field, Drosophila has been the prominent model species: molecular variation in populations was first described in Drosophila and most of the population genetics hypotheses were tested in Drosophila species. In this review, we describe the main concepts, methods, and landmarks of molecular population genetics, using the Drosophila model as a reference. We describe the different genetic data sets made available by advances in molecular technologies, and the theoretical developments fostered by these data. Finally, we review the results and new insights provided by the population genomics approach, and conclude by enumerating challenges and new lines of inquiry posed by increasingly large population scale sequence data. Copyright © 2017 Casillas and Barbadilla.

  4. Genetic Susceptibility to Atherosclerosis

    Directory of Open Access Journals (Sweden)

    Sanja Kovacic

    2012-01-01

    Full Text Available Atherosclerosis is a complex multifocal arterial disease involving interactions of multiple genetic and environmental factors. Advances in techniques of molecular genetics have revealed that genetic ground significantly influences susceptibility to atherosclerotic vascular diseases. Besides further investigations of monogenetic diseases, candidate genes, genetic polymorphisms, and susceptibility loci associated with atherosclerotic diseases have been identified in recent years, and their number is rapidly increasing. This paper discusses main genetic investigations fields associated with human atherosclerotic vascular diseases. The paper concludes with a discussion of the directions and implications of future genetic research in arteriosclerosis with an emphasis on prospective prediction from an early age of individuals who are predisposed to develop premature atherosclerosis as well as to facilitate the discovery of novel drug targets.

  5. Genetic Pathways to Insomnia

    Directory of Open Access Journals (Sweden)

    Mackenzie J. Lind

    2016-12-01

    Full Text Available This review summarizes current research on the genetics of insomnia, as genetic contributions are thought to be important for insomnia etiology. We begin by providing an overview of genetic methods (both quantitative and measured gene, followed by a discussion of the insomnia genetics literature with regard to each of the following common methodologies: twin and family studies, candidate gene studies, and genome-wide association studies (GWAS. Next, we summarize the most recent gene identification efforts (primarily GWAS results and propose several potential mechanisms through which identified genes may contribute to the disorder. Finally, we discuss new genetic approaches and how these may prove useful for insomnia, proposing an agenda for future insomnia genetics research.

  6. Genetic diversity in soybean genotypes with resistance to Heterodera glycines

    Directory of Open Access Journals (Sweden)

    Ana Paula Oliveira Nogueira

    2011-01-01

    Full Text Available The purpose of this study was to analyze the genetic diversity among soybean genotypes inoculated with Heteroderaglycines race 3. The experiments were conducted in a greenhouse. In two performance tests of morphological characteristics andresistance to the pathogen, 27 soybean genotypes were assessed. The coefficient of genotypic determination was estimated by themethod of analysis of variance and the genetic diversity analyzed based on dendrograms and optimization method. The estimatedcoefficients of determination indicated a predominantly genetic origin of the genotypic differences in the traits. The genetic variabilitywas maintained in the superior genotypes, which can be used in breeding programs for resistance to soybean cyst nematode

  7. PCR in forensic genetics

    DEFF Research Database (Denmark)

    Morling, Niels

    2009-01-01

    Since the introduction in the mid-1980s of analyses of minisatellites for DNA analyses, a revolution has taken place in forensic genetics. The subsequent invention of the PCR made it possible to develop forensic genetics tools that allow both very informative routine investigations and still more...... and more advanced, special investigations in cases concerning crime, paternity, relationship, disaster victim identification etc. The present review gives an update on the use of DNA investigations in forensic genetics....

  8. Genetics of stroke

    OpenAIRE

    Guo, Jin-Min; Liu, Ai-Jun; Su, Ding-Feng

    2010-01-01

    Stroke is the second most common cause of death and the most common cause of disability in developed countries. Stroke is a multi-factorial disease caused by a combination of environmental and genetic factors. Numerous epidemiologic studies have documented a significant genetic component in the occurrence of strokes. Genes encoding products involved in lipid metabolism, thrombosis, and inflammation are believed to be potential genetic factors for stroke. Although a large group of candidate ge...

  9. Genetics of mental retardation

    OpenAIRE

    Ahuja A; Thapar Anita; Owen M

    2005-01-01

    Mental retardation can follow any of the biological, environmental and psychological events that are capable of producing deficits in cognitive functions. Recent advances in molecular genetic techniques have enabled us to understand more about the molecular basis of several genetic syndromes associated with mental retardation. In contrast, where there is no discrete cause, the interplay of genetic and environmental influences remains poorly understood. This article presents a critical review ...

  10. Genetic engineering possibilities for CELSS: A bibliography and summary of techniques

    Science.gov (United States)

    Johnson, E. J.

    1982-01-01

    A bibliography of the most useful techniques employed in genetic engineering of higher plants, bacteria associated with plants, and plant cell cultures is provided. A resume of state-of-the-art genetic engineering of plants and bacteria is presented. The potential application of plant bacterial genetic engineering to CELSS (Controlled Ecological Life Support System) program and future research needs are discussed.

  11. Genetics of complex diseases

    DEFF Research Database (Denmark)

    Mellerup, Erling; Møller, Gert Lykke; Koefoed, Pernille

    2012-01-01

    A complex disease with an inheritable component is polygenic, meaning that several different changes in DNA are the genetic basis for the disease. Such a disease may also be genetically heterogeneous, meaning that independent changes in DNA, i.e. various genotypes, can be the genetic basis...... for the disease. Each of these genotypes may be characterized by specific combinations of key genetic changes. It is suggested that even if all key changes are found in genes related to the biology of a certain disease, the number of combinations may be so large that the number of different genotypes may be close...

  12. Genetics of nonsyndromic obesity.

    Science.gov (United States)

    Lee, Yung Seng

    2013-12-01

    Common obesity is widely regarded as a complex, multifactorial trait influenced by the 'obesogenic' environment, sedentary behavior, and genetic susceptibility contributed by common and rare genetic variants. This review describes the recent advances in understanding the role of genetics in obesity. New susceptibility loci and genetic variants are being uncovered, but the collective effect is relatively small and could not explain most of the BMI heritability. Yet-to-be identified common and rare variants, epistasis, and heritable epigenetic changes may account for part of the 'missing heritability'. Evidence is emerging about the role of epigenetics in determining obesity susceptibility, mediating developmental plasticity, which confers obesity risk from early life experiences. Genetic prediction scores derived from selected genetic variants, and also differential DNA methylation levels and methylation scores, have been shown to correlate with measures of obesity and response to weight loss intervention. Genetic variants, which confer susceptibility to obesity-related morbidities like nonalcoholic fatty liver disease, were also discovered recently. We can expect discovery of more rare genetic variants with the advent of whole exome and genome sequencing, and also greater understanding of epigenetic mechanisms by which environment influences genetic expression and which mediate the gene-environment interaction.

  13. Genetics Home Reference: abetalipoproteinemia

    Science.gov (United States)

    ... Betalipoprotein Deficiency Disease Congenital betalipoprotein deficiency syndrome Microsomal Triglyceride Transfer Protein Deficiency Disease Related Information How are genetic conditions and genes ...

  14. [From genetics to law, the viewpoint of the physician].

    Science.gov (United States)

    Kahn, Axel

    2002-05-25

    OF ALL SCIENCES: Genetics, science of the transmission of hereditary characteristics, is probably that which interferes most with the Law. However, it was not genetics that provoked the ideological, social and political upheaval at the end of the 19th and during the 20th century; it was the theory of evolution, which preceded the discovery of genetics that was to provide the substratum of evolution mechanisms. Most of the lethal ideologies of the 20th century were based on this. As was the case of eugenics, with the participation of scientists, legislators and judges. GENETIC ENGINEERING: The logical application of the theory of evolution and universality of the genetic code, led to the development of the genome program. Today, sequencing of the human genome is almost finished, but many years will be needed before details of the physiological genetic manifestations will be known. Genes themselves would not generally be concerned by patenting rules. However, there is an international tendency towards envisaging the patenting of genes. DEVELOPMENT OF GENETIC TESTS AND THEIR INCREASING USE FOR MEDICAL PURPOSES: Are among the ethical problems raised by genetics. Genetic diagnosis, conducted before embryo transfer is called "pre-implantation". This raises the problem of an eventual pre-implantation eugenic selection and therefore requires strict control. Reinforcement of the right to knowledge of genetic origins is also one of the socio-legal problems raised by the progress in genetics.

  15. DNA microsatellite analysis for tomato genetic differentiation

    Directory of Open Access Journals (Sweden)

    Miskoska-Milevska Elizabeta

    2015-01-01

    Full Text Available Commonly used method for determination of the genetic diversity among the populations is the test for genetic differentiation. DNA microsatellite markers are usually used to investigate the genetic structure of natural populations. The aim of this study was to evaluate the applicability of eight DNA microsatellite loci (LECH13, LE21085, LEMDDNa, LEEF1Aa, LELEUZIP, LE20592, TMS9 and LE2A11 in genetic differentiation of six morphologically different tomato varieties (var. grandifolium from subsp. cultum; var. cerasiforme - red and yellow, var. pruniforme and var. pyriforme from subsp. subspontaneum; and var. racemigerum from subsp. spontaneum. The fragment analyses was performed using Applied Biosystems DNA analyzer (ABI 3130 and GeneMapper® Software program. The data were analysed using the specific program Power Marker Software. The average number of detected alleles was 3,625. Also, the average PIC value for all 8 DNA microsatellites loci was 0,3571. The genetic differentiation test in the researched tomato subspecies showed minor differentiation for locus LELEUZIP (- 0,0009, modest differentiation for locus LECH13 (0,0896, locus LEMDDNa (0,0896 and locus LE21085 (0,0551 and major differentiation for locus LE2A11 (0,7633, locus LEEF1Aa (0,6167, locus TMS9 (0.4967 and locus LE20592 (0,4263. On the other hand, in the estimated tomato varieties, locus LE21085 (0,0297, locus LECH13 (0,0256 and locus LELEUZIP (0,0005 showed minor differentiation, locus LEMDDNa (0,1333 showed modest differentiation, while locus TMS9 (0,5929, locus LEEF1Aa (0,5006, locus LE2A11 (0,4013 and locus LE20592 (0,2606 showed major differentiation. The eight DNA microsatellite loci can be applicable solution for tomato genetic differentiation. The overall results suggest that these microsatellite loci could be used in further population genetic studies of tomatoes.

  16. [Advances in the genetics of exercise performance].

    Science.gov (United States)

    Zhou, Wenting

    2014-04-01

    Differences among individuals in exercise performance are determined by a range of environmental and genetic factors. Since 2008, numerous studies in the genetics of exercise performance have been published and a set of significant results have been obtained. In this review, we analyze the research results in physical activity, muscular strength and endurance from reputable papers selected based on these following aspects: sample size, quality of phenotype measurements, quality of the exercise program or physical activity exposure, study design, adjustment for experimental testing and quality of genotyping. We also review the progress of these three research fields and suggest new directions to future research.

  17. Genetic algorithm for neural networks optimization

    Science.gov (United States)

    Setyawati, Bina R.; Creese, Robert C.; Sahirman, Sidharta

    2004-11-01

    This paper examines the forecasting performance of multi-layer feed forward neural networks in modeling a particular foreign exchange rates, i.e. Japanese Yen/US Dollar. The effects of two learning methods, Back Propagation and Genetic Algorithm, in which the neural network topology and other parameters fixed, were investigated. The early results indicate that the application of this hybrid system seems to be well suited for the forecasting of foreign exchange rates. The Neural Networks and Genetic Algorithm were programmed using MATLAB«.

  18. TIP: protein backtranslation aided by genetic algorithms.

    Science.gov (United States)

    Moreira, Andrés; Maass, Alejandro

    2004-09-01

    Several applications require the backtranslation of a protein sequence into a nucleic acid sequence. The degeneracy of the genetic code makes this process ambiguous; moreover, not every translation is equally viable. The usual answer is to mimic the codon usage of the target species; however, this does not capture all the relevant features of the 'genomic styles' from different taxa. The program TIP ' Traducción Inversa de Proteínas') applies genetic algorithms to improve the backtranslation, by minimizing the difference of some coding statistics with respect to their average value in the target. http://www.cmm.uchile.cl/genoma/tip/

  19. Role for Genetic Anticipation in Lynch Syndrome

    DEFF Research Database (Denmark)

    Nilbert, Mef; Timshel, Susanne; Bernstein, Inge

    2009-01-01

    parent-child pairs in which age at the first cancer diagnosis was assessed. A paired t-test and a specifically developed bivariate model were used to assess a possible role of anticipation. RESULTS: Both methods revealed anticipation with children developing cancer mean 9.8 years (P ... parents using the paired t-test and 5.5 years (P ... to initiate surveillance programs at young age. It should also stimulate research into the genetic mechanisms that determine age at onset and whether the genetic instability that characterizes Lynch syndrome can be linked to anticipation....

  20. Judaism, genetic screening and genetic therapy.

    Science.gov (United States)

    Rosner, F

    1998-01-01

    Genetic screening, gene therapy and other applications of genetic engineering are permissible in Judaism when used for the treatment, cure, or prevention of disease. Such genetic manipulation is not considered to be a violation of God's natural law, but a legitimate implementation of the biblical mandate to heal. If Tay-Sachs disease, diabetes, hemophilia, cystic fibrosis, Huntington's disease or other genetic diseases can be cured or prevented by "gene surgery," then it is certainly permitted in Jewish law. Genetic premarital screening is encouraged in Judaism for the purpose of discouraging at-risk marriages for a fatal illness such as Tay-Sachs disease. Neonatal screening for treatable conditions such as phenylketonuria is certainly desirable and perhaps required in Jewish law. Preimplantation screening and the implantation of only "healthy" zygotes into the mother's womb to prevent the birth of an affected child are probably sanctioned in Jewish law. Whether or not these assisted reproduction techniques may be used to choose the sex of one's offspring, to prevent the birth of a child with a sex-linked disease such as hemophilia, has not yet been ruled on by modern rabbinic decisions. Prenatal screening with the specific intent of aborting an affected fetus is not allowed according to most rabbinic authorities, although a minority view permits it "for great need." Not to have children if both parents are carriers of genetic diseases such as Tay-Sachs is not a Jewish option. Preimplantation screening is preferable. All screening test results must remain confidential. Judaism does not permit the alteration or manipulation of physical traits and characteristics such as height, eye and hair color, facial features and the like, when such change provides no useful benefit to mankind. On the other hand, it is permissible to clone organisms and microorganisms to facilitate the production of insulin, growth hormone, and other agents intended to benefit mankind and to