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Sample records for san-specific genetic program

  1. Genetic programming in microorganisms

    Energy Technology Data Exchange (ETDEWEB)

    Hopwood, D A

    1981-11-01

    Formerly, when microbiologists had only existing organisms at their disposal whose characteristics could only be changed randomly by genetic experiments, they used to dream of programmed genetic changes. This dream has come true with modern genetic engineering.

  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. Linear genetic programming

    CERN Document Server

    Brameier, Markus

    2007-01-01

    Presents a variant of Genetic Programming that evolves imperative computer programs as linear sequences of instructions, in contrast to the more traditional functional expressions or syntax trees. This book serves as a reference for researchers, but also contains sufficient introduction for students and those who are new to the field

  4. 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......Genetic Programming is capable of automatically inducing symbolic computer programs on the basis of a set of examples or their performance in a simulation. Mathematical expressions are a well-defined subset of symbolic computer programs and are also suitable for optimization using the genetic...... 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...

  5. 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...

  6. 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

  7. Hybrid of Genetic Programming with PBIL

    International Nuclear Information System (INIS)

    Caldas, Gustavo Henrique Flores; Schirru, Roberto

    2005-01-01

    Genetic programming and PBIL (Population-Based Incremental Learning) are evolutionary algorithms that have found applications in several fields of application. The Genetic Programming searches a solution allowing that the individuals of a population modify, mainly, its structures. The PBIL, on the other hand, works with individuals of fixed structure and is particularly successful in finding numerical solutions. There are problems where the simultaneous adjustment of the structure and numerical constants in a solution is essential. The Symbolic Regression is an example where both the form and the constants of a mathematical expression must be found. Although the traditional Genetic Programming is capable to solve this problem by itself, it is interesting to explore a cooperation with the PBIL, allowing each algorithm to do only that they do best: the Genetic Programming tries to find a structure while the PBIL adjust the constants that will be enclosed in the structure. In this work, the benchmark 'the sextic polynomial regression problem' is used to compare some traditional techniques of Genetic Programming with the proposed Hybrid of Genetic Programming with PBIL. The results are presented and discussed. (author)

  8. Genetically programmed chiral organoborane synthesis

    Science.gov (United States)

    Kan, S. B. Jennifer; Huang, Xiongyi; Gumulya, Yosephine; Chen, Kai; Arnold, Frances H.

    2017-12-01

    Recent advances in enzyme engineering and design have expanded nature’s catalytic repertoire to functions that are new to biology. However, only a subset of these engineered enzymes can function in living systems. Finding enzymatic pathways that form chemical bonds that are not found in biology is particularly difficult in the cellular environment, as this depends on the discovery not only of new enzyme activities, but also of reagents that are both sufficiently reactive for the desired transformation and stable in vivo. Here we report the discovery, evolution and generalization of a fully genetically encoded platform for producing chiral organoboranes in bacteria. Escherichia coli cells harbouring wild-type cytochrome c from Rhodothermus marinus (Rma cyt c) were found to form carbon-boron bonds in the presence of borane-Lewis base complexes, through carbene insertion into boron-hydrogen bonds. Directed evolution of Rma cyt c in the bacterial catalyst provided access to 16 novel chiral organoboranes. The catalyst is suitable for gram-scale biosynthesis, providing up to 15,300 turnovers, a turnover frequency of 6,100 h-1, a 99:1 enantiomeric ratio and 100% chemoselectivity. The enantiopreference of the biocatalyst could also be tuned to provide either enantiomer of the organoborane products. Evolved in the context of whole-cell catalysts, the proteins were more active in the whole-cell system than in purified forms. This study establishes a DNA-encoded and readily engineered bacterial platform for borylation; engineering can be accomplished at a pace that rivals the development of chemical synthetic methods, with the ability to achieve turnovers that are two orders of magnitude (over 400-fold) greater than those of known chiral catalysts for the same class of transformation. This tunable method for manipulating boron in cells could expand the scope of boron chemistry in living systems.

  9. Using genetic programming to find Lyapunov functions

    NARCIS (Netherlands)

    Soute, I.A.C.; Molengraft, van de M.J.G.; Angelis, G.Z.; Ryan, C; Spector, L.

    2001-01-01

    In this paper Genetic Programming is used to find Lyapunov functions for (non)linear dif ferential equations of autonomous systems. As Lyapunov functions can be difficult to find, we use OP to make the decisions concerning the form of the Lyapunov function. As an e5cample two systems are taken to

  10. Genetic Network Programming with Reconstructed Individuals

    Science.gov (United States)

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

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

  11. Applications of genetic programming in cancer research.

    Science.gov (United States)

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

    2009-02-01

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

  12. 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

  13. A NEW MUTATION OPERATOR IN GENETIC PROGRAMMING

    Directory of Open Access Journals (Sweden)

    Anuradha Purohit

    2013-01-01

    Full Text Available This paper proposes a new type of mutation operator, FEDS (Fitness, Elitism, Depth, and Size mutation in genetic programming. The concept behind the new mutation operator is inspired from already introduced FEDS crossover operator to handle the problem of code bloating. FEDS mutation operates by using local elitism replacement in combination with depth limit and size of the trees to reduce bloat with a subsequent improvement in the performance of trees (program structures. We have designed a multiclass classifier for some benchmark datasets to test the performance of proposed mutation. The results show that when the initial run uses FEDS crossover and the concluding run uses FEDS mutation, then not only is the final result significantly improved but there is reduction in bloat also.

  14. Testing the structure of a hydrological model using Genetic Programming

    Science.gov (United States)

    Selle, Benny; Muttil, Nitin

    2011-01-01

    SummaryGenetic Programming is able to systematically explore many alternative model structures of different complexity from available input and response data. We hypothesised that Genetic Programming can be used to test the structure of hydrological models and to identify dominant processes in hydrological systems. To test this, Genetic Programming was used to analyse a data set from a lysimeter experiment in southeastern Australia. The lysimeter experiment was conducted to quantify the deep percolation response under surface irrigated pasture to different soil types, watertable depths and water ponding times during surface irrigation. Using Genetic Programming, a simple model of deep percolation was recurrently evolved in multiple Genetic Programming runs. This simple and interpretable model supported the dominant process contributing to deep percolation represented in a conceptual model that was published earlier. Thus, this study shows that Genetic Programming can be used to evaluate the structure of hydrological models and to gain insight about the dominant processes in hydrological systems.

  15. Guidelines on the use of molecular genetics in reintroduction programs

    Science.gov (United States)

    Michael K. Schwartz

    2005-01-01

    The use of molecular genetics can play a key role in reintroduction efforts. Prior to the introduction of any individuals, molecular genetics can be used to identify the most appropriate source population for the reintroduction, ensure that no relic populations exist in the reintroduction area, and guide captive breeding programs. The use of molecular genetics post-...

  16. Testing the Structure of Hydrological Models using Genetic Programming

    Science.gov (United States)

    Selle, B.; Muttil, N.

    2009-04-01

    Genetic Programming is able to systematically explore many alternative model structures of different complexity from available input and response data. We hypothesised that genetic programming can be used to test the structure hydrological models and to identify dominant processes in hydrological systems. To test this, genetic programming was used to analyse a data set from a lysimeter experiment in southeastern Australia. The lysimeter experiment was conducted to quantify the deep percolation response under surface irrigated pasture to different soil types, water table depths and water ponding times during surface irrigation. Using genetic programming, a simple model of deep percolation was consistently evolved in multiple model runs. This simple and interpretable model confirmed the dominant process contributing to deep percolation represented in a conceptual model that was published earlier. Thus, this study shows that genetic programming can be used to evaluate the structure of hydrological models and to gain insight about the dominant processes in hydrological systems.

  17. Developing robotic behavior using a genetic programming model

    International Nuclear Information System (INIS)

    Pryor, R.J.

    1998-01-01

    This report describes the methodology for using a genetic programming model to develop tracking behaviors for autonomous, microscale robotic vehicles. The use of such vehicles for surveillance and detection operations has become increasingly important in defense and humanitarian applications. Through an evolutionary process similar to that found in nature, the genetic programming model generates a computer program that when downloaded onto a robotic vehicle's on-board computer will guide the robot to successfully accomplish its task. Simulations of multiple robots engaged in problem-solving tasks have demonstrated cooperative behaviors. This report also discusses the behavior model produced by genetic programming and presents some results achieved during the study

  18. Genetics Education in Nurse Residency Programs: A Natural Fit.

    Science.gov (United States)

    Hamilton, Nalo M; Stenman, Christina W; Sang, Elaine; Palmer, Christina

    2017-08-01

    Scientific advances are shedding light on the genetic underpinning of common diseases. With such insight, the entire health care team is faced with the need to address patient questions regarding genetic risk, testing, and the psychosocial aspects of genetics information. Nurses are in a prime position to help with patient education about genetic conditions, yet they often lack adequate genetics education within their nursing curriculum to address patient questions and provide resources. One mechanism to address this knowledge deficit is the incorporation of a genetics-based curriculum into nurse residency programs. This article describes a novel genetics-based curriculum designed and implemented in the UCLA Health System Nurse Residency Program. J Contin Educ Nurs. 2017;48(8):379-384. Copyright 2017, SLACK Incorporated.

  19. 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

  20. 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.

  1. 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.

  2. 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…

  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. Algorithmic Trading with Developmental and Linear Genetic Programming

    Science.gov (United States)

    Wilson, Garnett; Banzhaf, Wolfgang

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

  5. Non-linear nuclear engineering models as genetic programming application

    International Nuclear Information System (INIS)

    Domingos, Roberto P.; Schirru, Roberto; Martinez, Aquilino S.

    1997-01-01

    This work presents a Genetic Programming paradigm and a nuclear application. A field of Artificial Intelligence, based on the concepts of Species Evolution and Natural Selection, can be understood as a self-programming process where the computer is the main agent responsible for the discovery of a program able to solve a given problem. In the present case, the problem was to find a mathematical expression in symbolic form, able to express the existent relation between equivalent ratio of a fuel cell, the enrichment of fuel elements and the multiplication factor. Such expression would avoid repeatedly reactor physics codes execution for core optimization. The results were compared with those obtained by different techniques such as Neural Networks and Linear Multiple Regression. Genetic Programming has shown to present a performance as good as, and under some features superior to Neural Network and Linear Multiple Regression. (author). 10 refs., 8 figs., 1 tabs

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. Genetic Programming for Sea Level Predictions in an Island Environment

    Directory of Open Access Journals (Sweden)

    M.A. Ghorbani

    2010-03-01

    Full Text Available Accurate predictions of sea-level are important for geodetic applications, navigation, coastal, industrial and tourist activities. In the current work, the Genetic Programming (GP and artificial neural networks (ANNs were applied to forecast half-daily and daily sea-level variations from 12 hours to 5 days ahead. The measurements at the Cocos (Keeling Islands in the Indian Ocean were used for training and testing of the employed artificial intelligence techniques. A comparison was performed of the predictions from the GP model and the ANN simulations. Based on the comparison outcomes, it was found that the Genetic Programming approach can be successfully employed in forecasting of sea level variations.

  12. 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.

  13. Geometric Semantic Genetic Programming Algorithm and Slump Prediction

    OpenAIRE

    Xu, Juncai; Shen, Zhenzhong; Ren, Qingwen; Xie, Xin; Yang, Zhengyu

    2017-01-01

    Research on the performance of recycled concrete as building material in the current world is an important subject. Given the complex composition of recycled concrete, conventional methods for forecasting slump scarcely obtain satisfactory results. Based on theory of nonlinear prediction method, we propose a recycled concrete slump prediction model based on geometric semantic genetic programming (GSGP) and combined it with recycled concrete features. Tests show that the model can accurately p...

  14. Genetic diversity of tambaqui broodstocks in stock enhancement programs

    Directory of Open Access Journals (Sweden)

    Americo Moraes Neto

    2017-06-01

    Full Text Available Natural populations of tambaqui (Colossoma macropomum have significantly decreased in recent decades especially due to human extraction activities. So that the environmental impact may be reduced, the restocking of fish and increase in fish production are enhanced. Genetic evaluations using molecular markers are essential for this purpose. Current study evaluates the genetic variability of two tambaqui broodstocks used in restocking programs. Sixty-five samples (33 samples from broodstock A and 32 samples from broodstock B were collected. DNA was extracted from caudal fin samples, with the amplification of four microsatellite loci: Cm1A11 (EU685307 Cm1C8 (EU685308 Cm1F4 (EU685311 and Cm1H8 (EU685315. Fourteen alleles in the stock of broodstock A were produced, five alleles for Cm1A11 locus (230, 255, 260, 270 and 276 bp, three alleles Cm1C8 (239, 260, and 273 bp, two alleles Cm1F4 (211 and 245 bp, four alleles for Cm1H8 (275, 290, 320 and 331 bp and two unique alleles were found for Cm1A11 loci (alleles 270 and 276 bp and Cm1H8 (alleles 275 and 331 bp. In broodstock B, ten alleles were produced, the same alleles of the first stock except for alleles 270 and 276 bp in Cm1A11 locus and 275 and 331 bp in Cm1H8 locus. Broodstock A revealed low frequency alleles in Cm1A11 loci, Cm1C8, Cm1F4 and Cm1H8, whereas broodstock B had no locus with low allelic frequency. Loci Cm1A11, Cm1C8 and Cm1H8 exhibited significant deficit of heterozygotes in both broodstocks, revealing changes in Hardy-Weinberg equilibrium. Genetic diversity between stocks was 0.1120, whilst genetic similarity was 0.894, with FST rate = 0.05, and Nm = 3.93, indicating gene flow between the two broodstocks. Results show that broodstocks are genetically closely related, with no great genetic variability. Strategies such as a previous genetic analysis of breeding with its marking, use of a large Ne crossing between the most genetically divergent specimens, and the introduction of new

  15. The sheep blowfly genetic control program in Australia

    International Nuclear Information System (INIS)

    Foster, Geoffrey G.

    1989-01-01

    The blowfly Lucilia cuprina is the most important myiasis pet of sheep in Australia. Other species are associated with sheep myiasis, but L. cuprina is probably responsible for initiating more than 90% of infestations. Annual costs of production losses, prevention and treatment have been estimated at $149 millions in 1985. Prevention and treatment encompass both insecticidal applications to sheep and non-chemical management practices. In the absence of effective preventive measures, the sheep industry would be non-viable over much of Australia. Insecticide usage against L. cuprina has been marked by the appearance of widespread resistance to cyclodienes in 1956, the organophosphates in 1965, and carbamates in 1966. Resistance has not yet been reported against the triazine compounds introduced for blowfly control in 1981. The most effective non-chemical control measures are surgical (removal of skin from the breech in certain breeds of sheep, and tail-docking). They protect sheep by reducing favourable oviposition sites (dung and urine-stained wool). The spectre of insecticide resistance and the early success of the sterile insect technique (SIT) against screwworm fly in the U.S.A., led this Division to consider SIT and other autocidal methods in the 1960s. The L. cuprina genetics research program was established in 1966 and subsequently expanded in 1971. More recently, lobbying by animal welfare groups against surgical blowfly control practices, as well as increasing consumer awareness of insecticide residues in animal products, have accelerated the search for alternatives to chemical control. When SIT was first considered for L. cuprina control in 1960, little was known about the population dynamics of L. cuprina. There were insufficient ecological data to evaluate the prospects of alternative strategies such as suppression or containment. The number of flies which would have to be released in a SIT program was unknown, as were the costs. Assuming that the cost of

  16. 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.

  17. Programming peptidomimetic syntheses by translating genetic codes designed de novo.

    Science.gov (United States)

    Forster, Anthony C; Tan, Zhongping; Nalam, Madhavi N L; Lin, Hening; Qu, Hui; Cornish, Virginia W; Blacklow, Stephen C

    2003-05-27

    Although the universal genetic code exhibits only minor variations in nature, Francis Crick proposed in 1955 that "the adaptor hypothesis allows one to construct, in theory, codes of bewildering variety." The existing code has been expanded to enable incorporation of a variety of unnatural amino acids at one or two nonadjacent sites within a protein by using nonsense or frameshift suppressor aminoacyl-tRNAs (aa-tRNAs) as adaptors. However, the suppressor strategy is inherently limited by compatibility with only a small subset of codons, by the ways such codons can be combined, and by variation in the efficiency of incorporation. Here, by preventing competing reactions with aa-tRNA synthetases, aa-tRNAs, and release factors during translation and by using nonsuppressor aa-tRNA substrates, we realize a potentially generalizable approach for template-encoded polymer synthesis that unmasks the substantially broader versatility of the core translation apparatus as a catalyst. We show that several adjacent, arbitrarily chosen sense codons can be completely reassigned to various unnatural amino acids according to de novo genetic codes by translating mRNAs into specific peptide analog polymers (peptidomimetics). Unnatural aa-tRNA substrates do not uniformly function as well as natural substrates, revealing important recognition elements for the translation apparatus. Genetic programming of peptidomimetic synthesis should facilitate mechanistic studies of translation and may ultimately enable the directed evolution of small molecules with desirable catalytic or pharmacological properties.

  18. Experimental control of a fluidic pinball using genetic programming

    Science.gov (United States)

    Raibaudo, Cedric; Zhong, Peng; Noack, Bernd R.; Martinuzzi, Robert J.

    2017-11-01

    The wake stabilization of a triangular cluster of three rotating cylinders was investigated in the present study. Experiments were performed at Reynolds number Re 6000, and compared with URANS-2D simulations at same flow conditions. 2D2C PIV measurements and constant temperature anemometry were used to characterize the flow without and with actuation. Open-loop actuation was first considered for the identification of particular control strategies. Machine learning control was also implemented for the experimental study. Linear genetic programming has been used for the optimization of open-loop parameters and closed-loop controllers. Considering a cost function J based on the fluctuations of the velocity measured by the hot-wire sensor, significant performances were achieved using the machine learning approach. The present work is supported by the senior author's (R. J. Martinuzzi) NSERC discovery Grant. C. Raibaudo acknowledges the financial support of the University of Calgary Eyes-High PDF program.

  19. Towards Merging Binary Integer Programming Techniques with Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    Reza Zamani

    2017-01-01

    Full Text Available This paper presents a framework based on merging a binary integer programming technique with a genetic algorithm. The framework uses both lower and upper bounds to make the employed mathematical formulation of a problem as tight as possible. For problems whose optimal solutions cannot be obtained, precision is traded with speed through substituting the integrality constrains in a binary integer program with a penalty. In this way, instead of constraining a variable u with binary restriction, u is considered as real number between 0 and 1, with the penalty of Mu(1-u, in which M is a large number. Values not near to the boundary extremes of 0 and 1 make the component of Mu(1-u large and are expected to be avoided implicitly. The nonbinary values are then converted to priorities, and a genetic algorithm can use these priorities to fill its initial pool for producing feasible solutions. The presented framework can be applied to many combinatorial optimization problems. Here, a procedure based on this framework has been applied to a scheduling problem, and the results of computational experiments have been discussed, emphasizing the knowledge generated and inefficiencies to be circumvented with this framework in future.

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

    International Nuclear Information System (INIS)

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

    1999-01-01

    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

  1. 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.

  2. 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.

  3. Genetic Programming and Standardization in Water Temperature Modelling

    Directory of Open Access Journals (Sweden)

    Maritza Arganis

    2009-01-01

    Full Text Available An application of Genetic Programming (an evolutionary computational tool without and with standardization data is presented with the aim of modeling the behavior of the water temperature in a river in terms of meteorological variables that are easily measured, to explore their explanatory power and to emphasize the utility of the standardization of variables in order to reduce the effect of those with large variance. Recorded data corresponding to the water temperature behavior at the Ebro River, Spain, are used as analysis case, showing a performance improvement on the developed model when data are standardized. This improvement is reflected in a reduction of the mean square error. Finally, the models obtained in this document were applied to estimate the water temperature in 2004, in order to provide evidence about their applicability to forecasting purposes.

  4. Structural health monitoring feature design by genetic programming

    International Nuclear Information System (INIS)

    Harvey, Dustin Y; Todd, Michael D

    2014-01-01

    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. (paper)

  5. 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. © 2011 American Institute of Physics

  6. 76 FR 72424 - Submission for OMB Review; Comment Request Information Program on the Genetic Testing Registry

    Science.gov (United States)

    2011-11-23

    ... particular tests; and (3) facilitating genetic and genomic data-sharing for research and new scientific...; Comment Request Information Program on the Genetic Testing Registry AGENCY: National Institutes of Health... currently valid OMB control number. Proposed Collection: Title: The Genetic Testing Registry; Type of...

  7. Genetic programming over context-free languages with linear constraints for the knapsack problem: first results.

    Science.gov (United States)

    Bruhn, Peter; Geyer-Schulz, Andreas

    2002-01-01

    In this paper, we introduce genetic programming over context-free languages with linear constraints for combinatorial optimization, apply this method to several variants of the multidimensional knapsack problem, and discuss its performance relative to Michalewicz's genetic algorithm with penalty functions. With respect to Michalewicz's approach, we demonstrate that genetic programming over context-free languages with linear constraints improves convergence. A final result is that genetic programming over context-free languages with linear constraints is ideally suited to modeling complementarities between items in a knapsack problem: The more complementarities in the problem, the stronger the performance in comparison to its competitors.

  8. Swarm, genetic and evolutionary programming algorithms applied to multiuser detection

    Directory of Open Access Journals (Sweden)

    Paul Jean Etienne Jeszensky

    2005-02-01

    Full Text Available In this paper, the particles swarm optimization technique, recently published in the literature, and applied to Direct Sequence/Code Division Multiple Access systems (DS/CDMA with multiuser detection (MuD is analyzed, evaluated and compared. The Swarm algorithm efficiency when applied to the DS-CDMA multiuser detection (Swarm-MuD is compared through the tradeoff performance versus computational complexity, being the complexity expressed in terms of the number of necessary operations in order to reach the performance obtained through the optimum detector or the Maximum Likelihood detector (ML. The comparison is accomplished among the genetic algorithm, evolutionary programming with cloning and Swarm algorithm under the same simulation basis. Additionally, it is proposed an heuristics-MuD complexity analysis through the number of computational operations. Finally, an analysis is carried out for the input parameters of the Swarm algorithm in the attempt to find the optimum parameters (or almost-optimum for the algorithm applied to the MuD problem.

  9. Flow discharge prediction in compound channels using linear genetic programming

    Science.gov (United States)

    Azamathulla, H. Md.; Zahiri, A.

    2012-08-01

    SummaryFlow discharge determination in rivers is one of the key elements in mathematical modelling in the design of river engineering projects. Because of the inundation of floodplains and sudden changes in river geometry, flow resistance equations are not applicable for compound channels. Therefore, many approaches have been developed for modification of flow discharge computations. Most of these methods have satisfactory results only in laboratory flumes. Due to the ability to model complex phenomena, the artificial intelligence methods have recently been employed for wide applications in various fields of water engineering. Linear genetic programming (LGP), a branch of artificial intelligence methods, is able to optimise the model structure and its components and to derive an explicit equation based on the variables of the phenomena. In this paper, a precise dimensionless equation has been derived for prediction of flood discharge using LGP. The proposed model was developed using published data compiled for stage-discharge data sets for 394 laboratories, and field of 30 compound channels. The results indicate that the LGP model has a better performance than the existing models.

  10. 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....

  11. Stigmatization of carrier status: social implications of heterozygote genetic screening programs.

    Science.gov (United States)

    Kenen, R H; Schmidt, R M

    1978-01-01

    Possible latent psychological and social consequences ensuing from genetic screening programs need to be investigated during the planning phase of national genetic screening programs. The relatively few studies which have been performed to determine psychological, social, and economic consequences resulting from a genetic screening program are reviewed. Stigmatization of carrier-status, having major psychosocial implications in heterozygote genetic screening programs, is discussed and related to Erving Goffman's work in the area of stigmatization. Questions are raised regarding the relationship between such variables as religiosity and sex of the individual and acceptance of the status of newly identified carrier of a mutant gene. Severity of the deleterious gene and visibility of the carrier status are two important factors to consider in an estimation of potential stigma. Specific implications are discussed for four genetic diseases: Tay-Sachs, Sickle-Cell Anemia, Huntington's disease and Hemophilia. PMID:152585

  12. 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.

  13. A genetic programming approach to oral cancer prognosis.

    Science.gov (United States)

    Tan, Mei Sze; Tan, Jing Wei; Chang, Siow-Wee; Yap, Hwa Jen; Abdul Kareem, Sameem; Zain, Rosnah Binti

    2016-01-01

    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. 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. 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. 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.

  14. A genetic programming approach for Burkholderia Pseudomallei diagnostic pattern discovery

    Science.gov (United States)

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

    2009-01-01

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

  15. 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...

  16. Amount of Genetics Education is Low Among Didactic Programs in Dietetics.

    Science.gov (United States)

    Beretich, Kaitlan; Pope, Janet; Erickson, Dawn; Kennedy, Angela

    2017-01-01

    Nutritional genomics is a growing area of research. Research has shown registered dietitian nutritionists (RDNs) have limited knowledge of genetics. Limited research is available regarding how didactic programs in dietetics (DPDs) meet the genetics knowledge requirement of the Accreditation Council for Education in Nutrition and Dietetics (ACEND®). The purpose of this study was to determine the extent to which the study of nutritional genomics is incorporated into undergraduate DPDs in response to the Academy of Nutrition and Dietetics position statement on nutritional genomics. The sample included 62 DPD directors in the U.S. Most programs (63.9%) reported the ACEND genetics knowledge requirement was being met by integrating genetic information into the current curriculum. However, 88.7% of programs reported devoting only 1-10 clock hours to genetics education. While 60.3% of directors surveyed reported they were confident in their program's ability to teach information related to genetics, only 6 directors reported having specialized training in genetics. The overall amount of clock hours devoted to genetics education is low. DPD directors, faculty, and instructors are not adequately trained to provide this education to students enrolled in DPDs. Therefore, the primary recommendation of this study is the development of a standardized curriculum for genetics education in DPDs.

  17. Portfolio optimization by using linear programing models based on genetic algorithm

    Science.gov (United States)

    Sukono; Hidayat, Y.; Lesmana, E.; Putra, A. S.; Napitupulu, H.; Supian, S.

    2018-01-01

    In this paper, we discussed the investment portfolio optimization using linear programming model based on genetic algorithms. It is assumed that the portfolio risk is measured by absolute standard deviation, and each investor has a risk tolerance on the investment portfolio. To complete the investment portfolio optimization problem, the issue is arranged into a linear programming model. Furthermore, determination of the optimum solution for linear programming is done by using a genetic algorithm. As a numerical illustration, we analyze some of the stocks traded on the capital market in Indonesia. Based on the analysis, it is shown that the portfolio optimization performed by genetic algorithm approach produces more optimal efficient portfolio, compared to the portfolio optimization performed by a linear programming algorithm approach. Therefore, genetic algorithms can be considered as an alternative on determining the investment portfolio optimization, particularly using linear programming models.

  18. 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.

  19. 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.

  20. Applying genetic algorithms for programming manufactoring cell tasks

    Directory of Open Access Journals (Sweden)

    Efredy Delgado

    2005-05-01

    Full Text Available This work was aimed for developing computational intelligence for scheduling a manufacturing cell's tasks, based manily on genetic algorithms. The manufacturing cell was modelled as beign a production-line; the makespan was calculated by using heuristics adapted from several libraries for genetic algorithms computed in C++ builder. Several problems dealing with small, medium and large list of jobs and machinery were resolved. The results were compared with other heuristics. The approach developed here would seem to be promising for future research concerning scheduling manufacturing cell tasks involving mixed batches.

  1. 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.

  2. Genetic programs can be compressed and autonomously decompressed in live cells

    Science.gov (United States)

    Lapique, Nicolas; Benenson, Yaakov

    2018-04-01

    Fundamental computer science concepts have inspired novel information-processing molecular systems in test tubes1-13 and genetically encoded circuits in live cells14-21. Recent research has shown that digital information storage in DNA, implemented using deep sequencing and conventional software, can approach the maximum Shannon information capacity22 of two bits per nucleotide23. In nature, DNA is used to store genetic programs, but the information content of the encoding rarely approaches this maximum24. We hypothesize that the biological function of a genetic program can be preserved while reducing the length of its DNA encoding and increasing the information content per nucleotide. Here we support this hypothesis by describing an experimental procedure for compressing a genetic program and its subsequent autonomous decompression and execution in human cells. As a test-bed we choose an RNAi cell classifier circuit25 that comprises redundant DNA sequences and is therefore amenable for compression, as are many other complex gene circuits15,18,26-28. In one example, we implement a compressed encoding of a ten-gene four-input AND gate circuit using only four genetic constructs. The compression principles applied to gene circuits can enable fitting complex genetic programs into DNA delivery vehicles with limited cargo capacity, and storing compressed and biologically inert programs in vivo for on-demand activation.

  3. Genetic counseling for schizophrenia: a review of referrals to a provincial medical genetics program from 1968–2007

    Science.gov (United States)

    Hunter, MJ; Hippman, Catriona; Honer, William G; Austin, Jehannine C.

    2014-01-01

    Purpose Recent studies have shown that individuals with schizophrenia and their family members are interested in genetic counseling, but few have received this service. We conducted an exploratory, retrospective study to describe (a) the population of individuals who were referred to the provincial program for genetic counseling for a primary indication of schizophrenia, and (b) trends in number of referrals between 1968 and 2007. Methods Referrals for a primary indication of schizophrenia were identified through the provincial program database. Charts were reviewed and the following information was recorded: discipline of referring physician, demographics, psychiatric diagnosis, referred individual’s and partner’s (if applicable) family history, and any current pregnancy history. Data were characterized using descriptive statistics. Results Between 1968 and 2007, 288 referrals were made for a primary indication of schizophrenia. Most referrals were made: (a) for individuals who had a first-degree family member with schizophrenia, rather than for affected individuals, (b) for preconception counseling, and (c) by family physicians (69%), with only 2% by psychiatrists. Conclusions In British Columbia, individuals affected with schizophrenia and their family members are rarely referred for psychiatric genetic counseling. There is a need to identify barriers to psychiatric genetic counseling and develop strategies to improve access. PMID:20034078

  4. 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.

  5. Routine human-competitive machine intelligence by means of genetic programming

    Science.gov (United States)

    Koza, John R.; Streeter, Matthew J.; Keane, Martin

    2004-01-01

    Genetic programming is a systematic method for getting computers to automatically solve a problem. Genetic programming starts from a high-level statement of what needs to be done and automatically creates a computer program to solve the problem. The paper demonstrates that genetic programming (1) now routinely delivers high-return human-competitive machine intelligence; (2) is an automated invention machine; (3) can automatically create a general solution to a problem in the form of a parameterized topology; and (4) has delivered a progression of qualitatively more substantial results in synchrony with five approximately order-of-magnitude increases in the expenditure of computer time. Recent results involving the automatic synthesis of the topology and sizing of analog electrical circuits and controllers demonstrate these points.

  6. 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

  7. Evolving rule-based systems in two medical domains using genetic programming.

    Science.gov (United States)

    Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan; Axer, Hubertus; Bjerregaard, Beth; von Keyserlingk, Diedrich Graf

    2004-11-01

    To demonstrate and compare the application of different genetic programming (GP) based intelligent methodologies for the construction of rule-based systems in two medical domains: the diagnosis of aphasia's subtypes and the classification of pap-smear examinations. Past data representing (a) successful diagnosis of aphasia's subtypes from collaborating medical experts through a free interview per patient, and (b) correctly classified smears (images of cells) by cyto-technologists, previously stained using the Papanicolaou method. Initially a hybrid approach is proposed, which combines standard genetic programming and heuristic hierarchical crisp rule-base construction. Then, genetic programming for the production of crisp rule based systems is attempted. Finally, another hybrid intelligent model is composed by a grammar driven genetic programming system for the generation of fuzzy rule-based systems. Results denote the effectiveness of the proposed systems, while they are also compared for their efficiency, accuracy and comprehensibility, to those of an inductive machine learning approach as well as to those of a standard genetic programming symbolic expression approach. The proposed GP-based intelligent methodologies are able to produce accurate and comprehensible results for medical experts performing competitive to other intelligent approaches. The aim of the authors was the production of accurate but also sensible decision rules that could potentially help medical doctors to extract conclusions, even at the expense of a higher classification score achievement.

  8. Towards programming languages for genetic engineering of living cells.

    Science.gov (United States)

    Pedersen, Michael; Phillips, Andrew

    2009-08-06

    Synthetic biology aims at producing novel biological systems to carry out some desired and well-defined functions. An ultimate dream is to design these systems at a high level of abstraction using engineering-based tools and programming languages, press a button, and have the design translated to DNA sequences that can be synthesized and put to work in living cells. We introduce such a programming language, which allows logical interactions between potentially undetermined proteins and genes to be expressed in a modular manner. Programs can be translated by a compiler into sequences of standard biological parts, a process that relies on logic programming and prototype databases that contain known biological parts and protein interactions. Programs can also be translated to reactions, allowing simulations to be carried out. While current limitations on available data prevent full use of the language in practical applications, the language can be used to develop formal models of synthetic systems, which are otherwise often presented by informal notations. The language can also serve as a concrete proposal on which future language designs can be discussed, and can help to guide the emerging standard of biological parts which so far has focused on biological, rather than logical, properties of parts.

  9. A Hybrid Genetic Programming Algorithm for Automated Design of Dispatching Rules.

    Science.gov (United States)

    Nguyen, Su; Mei, Yi; Xue, Bing; Zhang, Mengjie

    2018-06-04

    Designing effective dispatching rules for production systems is a difficult and timeconsuming task if it is done manually. In the last decade, the growth of computing power, advanced machine learning, and optimisation techniques has made the automated design of dispatching rules possible and automatically discovered rules are competitive or outperform existing rules developed by researchers. Genetic programming is one of the most popular approaches to discovering dispatching rules in the literature, especially for complex production systems. However, the large heuristic search space may restrict genetic programming from finding near optimal dispatching rules. This paper develops a new hybrid genetic programming algorithm for dynamic job shop scheduling based on a new representation, a new local search heuristic, and efficient fitness evaluators. Experiments show that the new method is effective regarding the quality of evolved rules. Moreover, evolved rules are also significantly smaller and contain more relevant attributes.

  10. 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.

  11. 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 ...

  12. 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.

  13. 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

  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. 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...

  16. 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

  17. Evaluation of two-year Jewish genetic disease screening program in Atlanta: insight into community genetic screening approaches.

    Science.gov (United States)

    Shao, Yunru; Liu, Shuling; Grinzaid, Karen

    2015-04-01

    Improvements in genetic testing technologies have led to the development of expanded carrier screening panels for the Ashkenazi Jewish population; however, there are major inconsistencies in current screening practices. A 2-year pilot program was launched in Atlanta in 2010 to promote and facilitate screening for 19 Jewish genetic diseases. We analyzed data from this program, including participant demographics and outreach efforts. This retrospective analysis is based on a de-identified dataset of 724 screenees. Data were obtained through medical chart review and questionnaires and included demographic information, screening results, response to outreach efforts, and follow-up behavior and preferences. We applied descriptive analysis, chi-square tests, and logistic regression to analyze the data and compare findings with published literature. The majority of participants indicated that they were not pregnant or did not have a partner who was pregnant were affiliated with Jewish organizations and reported 100 % AJ ancestry. Overall, carrier frequency was 1 in 3.9. Friends, rabbis, and family members were the most common influencers of the decision to receive screening. People who were older, had a history of pregnancy, and had been previously screened were more likely to educate others (all p influencers who then encouraged screening in the target population. Educating influencers and increasing overall awareness were the most effective outreach strategies.

  18. Report on an Investigation into an Entry Level Clinical Doctorate for the Genetic Counseling Profession and a Survey of the Association of Genetic Counseling Program Directors.

    Science.gov (United States)

    Reiser, Catherine; LeRoy, Bonnie; Grubs, Robin; Walton, Carol

    2015-10-01

    The master's degree is the required entry-level degree for the genetic counseling profession in the US and Canada. In 2012 the Association of Genetic Counseling Program Directors (AGCPD) passed resolutions supporting retention of the master's as the entry-level and terminal degree and opposing introduction of an entry-level clinical doctorate (CD) degree. An AGCPD workgroup surveyed directors of all 34 accredited training programs with the objective of providing the Genetic Counseling Advanced Degrees Task Force (GCADTF) with information regarding potential challenges if master's programs were required to transition to an entry-level CD. Program demographics, projected ability to transition to an entry-level CD, factors influencing ability to transition, and potential effects of transition on programs, students and the genetic counseling workforce were characterized. Two programs would definitely be able to transition, four programs would close, thirteen programs would be at risk to close and fourteen programs would probably be able to transition with varying degrees of difficulty. The most frequently cited limiting factors were economic, stress on clinical sites, and administrative approval of a new degree/program. Student enrollment under an entry-level CD model was projected to decrease by 26.2 %, negatively impacting the workforce pipeline. The results further illuminate and justify AGCPD's position to maintain the master's as the entry-level degree.

  19. The genetic algorithm for the nonlinear programming of water pollution control system

    Energy Technology Data Exchange (ETDEWEB)

    Wei, J.; Zhang, J. [China University of Geosciences (China)

    1999-08-01

    In the programming of water pollution control system the combined method of optimization with simulation is used generally. It is not only laborious in calculation, but also the global optimum of the obtained solution is guaranteed difficult. In this paper, the genetic algorithm (GA) used in the nonlinear programming of water pollution control system is given, by which the preferred conception for the programming of waste water system is found in once-through operation. It is more succinct than the conventional method and the global optimum of the obtained solution could be ensured. 6 refs., 4 figs., 3 tabs.

  20. 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. Copyright © 2014 Elsevier Ltd. All rights reserved.

  1. 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 either...... ABB or AAB. We recently suggested a genetic distance measure that is based on phenotype counting and made available the computer program POPDIST. The program provides maximum-likelihood estimates of the genetic identities and distances between polyploid populations, but this approach...

  2. Implementation of genetic conservation practices in a muskellunge propagation and stocking program

    Science.gov (United States)

    Jennings, Martin J.; Sloss, Brian L.; Hatzenbeler, Gene R.; Kampa, Jeffrey M.; Simonson, Timothy D.; Avelallemant, Steven P.; Lindenberger, Gary A.; Underwood, Bruce D.

    2010-01-01

    Conservation of genetic resources is a challenging issue for agencies managing popular sport fishes. To address the ongoing potential for genetic risks, we developed a comprehensive set of recommendations to conserve genetic diversity of muskellunge (Esox masquinongy) in Wisconsin, and evaluated the extent to which the recommendations can be implemented. Although some details are specific to Wisconsin's muskellunge propagation program, many of the practical issues affecting implementation are applicable to other species and production systems. We developed guidelines to restrict future broodstock collection operations to lakes with natural reproduction and to develop a set of brood lakes to use on a rotational basis within regional stock boundaries, but implementation will require considering lakes with variable stocking histories. Maintaining an effective population size sufficient to minimize the risk of losing alleles requires limiting broodstock collection to large lakes. Recommendations to better approximate the temporal distribution of spawning in hatchery operations and randomize selection of brood fish are feasible. Guidelines to modify rearing and distribution procedures face some logistic constraints. An evaluation of genetic diversity of hatchery-produced fish during 2008 demonstrated variable success representing genetic variation of the source population. Continued evaluation of hatchery operations will optimize operational efficiency while moving toward genetic conservation goals.

  3. Mathematical programming models for solving in equal-sized facilities layout problems. A genetic search method

    International Nuclear Information System (INIS)

    Tavakkoli-Moghaddam, R.

    1999-01-01

    This paper present unequal-sized facilities layout solutions generated by a genetic search program. named Layout Design using a Genetic Algorithm) 9. The generalized quadratic assignment problem requiring pre-determined distance and material flow matrices as the input data and the continuous plane model employing a dynamic distance measure and a material flow matrix are discussed. Computational results on test problems are reported as compared with layout solutions generated by the branch - and bound algorithm a hybrid method merging simulated annealing and local search techniques, and an optimization process of an enveloped block

  4. Research on non-uniform strain profile reconstruction along fiber Bragg grating via genetic programming algorithm and interrelated experimental verification

    Science.gov (United States)

    Zheng, Shijie; Zhang, Nan; Xia, Yanjun; Wang, Hongtao

    2014-03-01

    A new heuristic strategy for the non-uniform strain profile reconstruction along Fiber Bragg Gratings is proposed in this paper, which is based on the modified transfer matrix and Genetic Programming(GP) algorithm. The present method uses Genetic Programming to determine the applied strain field as a function of position along the fiber length. The structures that undergo adaptation in genetic programming are hierarchical structures which are different from that of conventional genetic algorithm operating on strings. GP regress the strain profile function which matches the 'measured' spectrum best and makes space resolution of strain reconstruction arbitrarily high, or even infinite. This paper also presents an experimental verification of the reconstruction of non-homogeneous strain fields using GP. The results are compared with numerical calculations of finite element method. Both the simulation examples and experimental results demonstrate that Genetic Programming can effectively reconstruct continuous profile expression along the whole FBG, and greatly improves its computational efficiency and accuracy.

  5. 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.

  6. Mitigation of inbreeding while preserving genetic gain in genomic breeding programs for outbred plants.

    Science.gov (United States)

    Lin, Zibei; Shi, Fan; Hayes, Ben J; Daetwyler, Hans D

    2017-05-01

    Heuristic genomic inbreeding controls reduce inbreeding in genomic breeding schemes without reducing genetic gain. Genomic selection is increasingly being implemented in plant breeding programs to accelerate genetic gain of economically important traits. However, it may cause significant loss of genetic diversity when compared with traditional schemes using phenotypic selection. We propose heuristic strategies to control the rate of inbreeding in outbred plants, which can be categorised into three types: controls during mate allocation, during selection, and simultaneous selection and mate allocation. The proposed mate allocation measure GminF allocates two or more parents for mating in mating groups that minimise coancestry using a genomic relationship matrix. Two types of relationship-adjusted genomic breeding values for parent selection candidates ([Formula: see text]) and potential offspring ([Formula: see text]) are devised to control inbreeding during selection and even enabling simultaneous selection and mate allocation. These strategies were tested in a case study using a simulated perennial ryegrass breeding scheme. As compared to the genomic selection scheme without controls, all proposed strategies could significantly decrease inbreeding while achieving comparable genetic gain. In particular, the scenario using [Formula: see text] in simultaneous selection and mate allocation reduced inbreeding to one-third of the original genomic selection scheme. The proposed strategies are readily applicable in any outbred plant breeding program.

  7. Epileptic MEG Spike Detection Using Statistical Features and Genetic Programming with KNN

    Directory of Open Access Journals (Sweden)

    Turky N. Alotaiby

    2017-01-01

    Full Text Available Epilepsy is a neurological disorder that affects millions of people worldwide. Monitoring the brain activities and identifying the seizure source which starts with spike detection are important steps for epilepsy treatment. Magnetoencephalography (MEG is an emerging epileptic diagnostic tool with high-density sensors; this makes manual analysis a challenging task due to the vast amount of MEG data. This paper explores the use of eight statistical features and genetic programing (GP with the K-nearest neighbor (KNN for interictal spike detection. The proposed method is comprised of three stages: preprocessing, genetic programming-based feature generation, and classification. The effectiveness of the proposed approach has been evaluated using real MEG data obtained from 28 epileptic patients. It has achieved a 91.75% average sensitivity and 92.99% average specificity.

  8. 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.

  9. The use of genetic programming to develop a predictor of swash excursion on sandy beaches

    OpenAIRE

    M. Passarella; E. B. Goldstein; S. De Muro; G. Coco

    2018-01-01

    We use genetic programming (GP), a type of machine learning (ML) approach, to predict the total and infragravity swash excursion using previously published data sets that have been used extensively in swash prediction studies. Three previously published works with a range of new conditions are added to this data set to extend the range of measured swash conditions. Using this newly compiled data set we demonstrate that a ML approach can reduce the prediction errors compared ...

  10. Performance comparison of genetic algorithms and particle swarm optimization for model integer programming bus timetabling problem

    Science.gov (United States)

    Wihartiko, F. D.; Wijayanti, H.; Virgantari, F.

    2018-03-01

    Genetic Algorithm (GA) is a common algorithm used to solve optimization problems with artificial intelligence approach. Similarly, the Particle Swarm Optimization (PSO) algorithm. Both algorithms have different advantages and disadvantages when applied to the case of optimization of the Model Integer Programming for Bus Timetabling Problem (MIPBTP), where in the case of MIPBTP will be found the optimal number of trips confronted with various constraints. The comparison results show that the PSO algorithm is superior in terms of complexity, accuracy, iteration and program simplicity in finding the optimal solution.

  11. Empirical study of self-configuring genetic programming algorithm performance and behaviour

    International Nuclear Information System (INIS)

    KrasnoyarskiyRabochiy prospect, Krasnoyarsk, 660014 (Russian Federation))" data-affiliation=" (Siberian State Aerospace University named after Academician M.F. Reshetnev 31 KrasnoyarskiyRabochiy prospect, Krasnoyarsk, 660014 (Russian Federation))" >Semenkin, E; KrasnoyarskiyRabochiy prospect, Krasnoyarsk, 660014 (Russian Federation))" data-affiliation=" (Siberian State Aerospace University named after Academician M.F. Reshetnev 31 KrasnoyarskiyRabochiy prospect, Krasnoyarsk, 660014 (Russian Federation))" >Semenkina, M

    2015-01-01

    The behaviour of the self-configuring genetic programming algorithm with a modified uniform crossover operator that implements a selective pressure on the recombination stage, is studied over symbolic programming problems. The operator's probabilistic rates interplay is studied and the role of operator variants on algorithm performance is investigated. Algorithm modifications based on the results of investigations are suggested. The performance improvement of the algorithm is demonstrated by the comparative analysis of suggested algorithms on the benchmark and real world problems

  12. 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.

  13. 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.

  14. Including nonadditive genetic effects in mating programs to maximize dairy farm profitability.

    Science.gov (United States)

    Aliloo, H; Pryce, J E; González-Recio, O; Cocks, B G; Goddard, M E; Hayes, B J

    2017-02-01

    We compared the outcome of mating programs based on different evaluation models that included nonadditive genetic effects (dominance and heterozygosity) in addition to additive effects. The additive and dominance marker effects and the values of regression on average heterozygosity were estimated using 632,003 single nucleotide polymorphisms from 7,902 and 7,510 Holstein cows with calving interval and production (milk, fat, and protein yields) records, respectively. Expected progeny values were computed based on the estimated genetic effects and genotype probabilities of hypothetical progeny from matings between the available genotyped cows and the top 50 young genomic bulls. An index combining the traits based on their economic values was developed and used to evaluate the performance of different mating scenarios in terms of dollar profit. We observed that mating programs with nonadditive genetic effects performed better than a model with only additive effects. Mating programs with dominance and heterozygosity effects increased milk, fat, and protein yields by up to 38, 1.57, and 1.21 kg, respectively. The inclusion of dominance and heterozygosity effects decreased calving interval by up to 0.70 d compared with random mating. The average reduction in progeny inbreeding by the inclusion of nonadditive genetic effects in matings compared with random mating was between 0.25 to 1.57 and 0.64 to 1.57 percentage points for calving interval and production traits, respectively. The reduction in inbreeding was accompanied by an average of A$8.42 (Australian dollars) more profit per mating for a model with additive, dominance, and heterozygosity effects compared with random mating. Mate allocations that benefit from nonadditive genetic effects can improve progeny performance only in the generation where it is being implemented, and the gain from specific combining abilities cannot be accumulated over generations. Continuous updating of genomic predictions and mate

  15. Genetics

    International Nuclear Information System (INIS)

    Hubitschek, H.E.

    1975-01-01

    Progress is reported on the following research projects: genetic effects of high LET radiations; genetic regulation, alteration, and repair; chromosome replication and the division cycle of Escherichia coli; effects of radioisotope decay in the DNA of microorganisms; initiation and termination of DNA replication in Bacillus subtilis; mutagenesis in mouse myeloma cells; lethal and mutagenic effects of near-uv radiation; effect of 8-methoxypsoralen on photodynamic lethality and mutagenicity in Escherichia coli; DNA repair of the lethal effects of far-uv; and near uv irradiation of bacterial cells

  16. 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

  17. The Mouse House: a brief history of the ORNL mouse-genetics program, 1947-2009.

    Science.gov (United States)

    Russell, Liane B

    2013-01-01

    The large mouse genetics program at the Oak Ridge National Laboratory (ORNL) is often remembered 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

  18. 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...

  19. Implementation of the program for conservation and sustainable utilization of forest genetic resources in Republic of Serbia

    Directory of Open Access Journals (Sweden)

    Šijačić-Nikolić Mirjana

    2017-01-01

    Full Text Available Program for conservation and sustainable utilization of forest genetic resources has been defined for 2016-2025 period and it is a base for concrete activities in this field. This Program could be divided into several parts that deal with: the legal framework for the conservation and sustainable utilization of forest genetic resources; status of forest genetic resources in Serbia; previous activities on the conservation of forest genetic resources; and objectives, priorities and measures of conservation. The Program should have an impact on the development of the forestry sector through the following activities: conservation and sustainable utilization of the available gene pool; improving forest management in accordance with conservation principles; improving the production of reproductive material of forest trees; make the public awareness of the need for conservation and sustainable utilization of forest genetic resources; fulfillment of international obligations related to this field and the possibility of joining FAO activities related to forest genetic resources - development of the national report as a part of the publication The State of the World's Forest Genetic Resources. Implementation of the Program will depend upon raising the awareness on the importance, conservation and sustainable utilization of forest genetic resources, as a precondition for the forests survival; it will depend of funds that will be allocated for this purpose and enthusiasm of people who deal with these issues.

  20. 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...

  1. Genetic evaluation of reproductive potential in the Zatorska goose under a conservation program.

    Science.gov (United States)

    Graczyk, Magdalena; Andres, Krzysztof; Kapkowska, Ewa; Szwaczkowski, Tomasz

    2018-05-01

    The aim of this study was to estimate the genetic parameters and inbreeding effect on the fertility, embryo mortality and hatchability traits in the Zatorska goose covered by the animal genetic resources conservation program. The material for this study contains information about results of hatching of 18 863 eggs from 721 dams and 168 sires, laid between 1998-2015. Genetic parameters were estimated based on the threshold animal model by the use of Restricted Maximum Likelihood and Gibbs sampling. The percentage of fertilized eggs ranged yearly between 37-80%. The percentage of embryo mortality was very low, ranging between 4.63-23.73%. The percentage of the hatched goslings from the total number of analyzed eggs was on average 33.18%, and 53.72% from fertilized eggs. On average based on both methods, the heritability estimates of the fertility, embryo mortality and hatchability reached 0.36, 0.07, 0.24 for males and 0.44, 0.11, 0.32 for females. The genetic trend had increasing tendency for fertility and hatchability and was stable for embryo mortality for both sexes. The obtained result shows that the Zatorska goose can be still maintained in the reserves of the local gene pool according to current rules and use in the local market as a breed with good reproductive potential. © 2018 Japanese Society of Animal Science.

  2. Efficient experimental design of high-fidelity three-qubit quantum gates via genetic programming

    Science.gov (United States)

    Devra, Amit; Prabhu, Prithviraj; Singh, Harpreet; Arvind; Dorai, Kavita

    2018-03-01

    We have designed efficient quantum circuits for the three-qubit Toffoli (controlled-controlled-NOT) and the Fredkin (controlled-SWAP) gate, optimized via genetic programming methods. The gates thus obtained were experimentally implemented on a three-qubit NMR quantum information processor, with a high fidelity. Toffoli and Fredkin gates in conjunction with the single-qubit Hadamard gates form a universal gate set for quantum computing and are an essential component of several quantum algorithms. Genetic algorithms are stochastic search algorithms based on the logic of natural selection and biological genetics and have been widely used for quantum information processing applications. We devised a new selection mechanism within the genetic algorithm framework to select individuals from a population. We call this mechanism the "Luck-Choose" mechanism and were able to achieve faster convergence to a solution using this mechanism, as compared to existing selection mechanisms. The optimization was performed under the constraint that the experimentally implemented pulses are of short duration and can be implemented with high fidelity. We demonstrate the advantage of our pulse sequences by comparing our results with existing experimental schemes and other numerical optimization methods.

  3. 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.

  4. PhyloGeoViz: a web-based program that visualizes genetic data on maps.

    Science.gov (United States)

    Tsai, Yi-Hsin E

    2011-05-01

    The first step of many population genetic studies is the simple visualization of allele frequencies on a landscape. This basic data exploration can be challenging without proprietary software, and the manual plotting of data is cumbersome and unfeasible at large sample sizes. I present an open source, web-based program that plots any kind of frequency or count data as pie charts in Google Maps (Google Inc., Mountain View, CA). Pie polygons are then exportable to Google Earth (Google Inc.), a free Geographic Information Systems platform. Import of genetic data into Google Earth allows phylogeographers access to a wealth of spatial information layers integral to forming hypotheses and understanding patterns in the data. © 2010 Blackwell Publishing Ltd.

  5. 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.

  6. 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

  7. 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.

  8. Multi-objective genetic algorithm for solving N-version program design problem

    International Nuclear Information System (INIS)

    Yamachi, Hidemi; Tsujimura, Yasuhiro; Kambayashi, Yasushi; Yamamoto, Hisashi

    2006-01-01

    N-version programming (NVP) is a programming approach for constructing fault tolerant software systems. Generally, an optimization model utilized in NVP selects the optimal set of versions for each module to maximize the system reliability and to constrain the total cost to remain within a given budget. In such a model, while the number of versions included in the obtained solution is generally reduced, the budget restriction may be so rigid that it may fail to find the optimal solution. In order to ameliorate this problem, this paper proposes a novel bi-objective optimization model that maximizes the system reliability and minimizes the system total cost for designing N-version software systems. When solving multi-objective optimization problem, it is crucial to find Pareto solutions. It is, however, not easy to obtain them. In this paper, we propose a novel bi-objective optimization model that obtains many Pareto solutions efficiently. We formulate the optimal design problem of NVP as a bi-objective 0-1 nonlinear integer programming problem. In order to overcome this problem, we propose a Multi-objective genetic algorithm (MOGA), which is a powerful, though time-consuming, method to solve multi-objective optimization problems. When implementing genetic algorithm (GA), the use of an appropriate genetic representation scheme is one of the most important issues to obtain good performance. We employ random-key representation in our MOGA to find many Pareto solutions spaced as evenly as possible along the Pareto frontier. To pursue improve further performance, we introduce elitism, the Pareto-insertion and the Pareto-deletion operations based on distance between Pareto solutions in the selection process. The proposed MOGA obtains many Pareto solutions along the Pareto frontier evenly. The user of the MOGA can select the best compromise solution among the candidates by controlling the balance between the system reliability and the total cost

  9. Multi-objective genetic algorithm for solving N-version program design problem

    Energy Technology Data Exchange (ETDEWEB)

    Yamachi, Hidemi [Department of Computer and Information Engineering, Nippon Institute of Technology, Miyashiro, Saitama 345-8501 (Japan) and Department of Production and Information Systems Engineering, Tokyo Metropolitan Institute of Technology, Hino, Tokyo 191-0065 (Japan)]. E-mail: yamachi@nit.ac.jp; Tsujimura, Yasuhiro [Department of Computer and Information Engineering, Nippon Institute of Technology, Miyashiro, Saitama 345-8501 (Japan)]. E-mail: tujimr@nit.ac.jp; Kambayashi, Yasushi [Department of Computer and Information Engineering, Nippon Institute of Technology, Miyashiro, Saitama 345-8501 (Japan)]. E-mail: yasushi@nit.ac.jp; Yamamoto, Hisashi [Department of Production and Information Systems Engineering, Tokyo Metropolitan Institute of Technology, Hino, Tokyo 191-0065 (Japan)]. E-mail: yamamoto@cc.tmit.ac.jp

    2006-09-15

    N-version programming (NVP) is a programming approach for constructing fault tolerant software systems. Generally, an optimization model utilized in NVP selects the optimal set of versions for each module to maximize the system reliability and to constrain the total cost to remain within a given budget. In such a model, while the number of versions included in the obtained solution is generally reduced, the budget restriction may be so rigid that it may fail to find the optimal solution. In order to ameliorate this problem, this paper proposes a novel bi-objective optimization model that maximizes the system reliability and minimizes the system total cost for designing N-version software systems. When solving multi-objective optimization problem, it is crucial to find Pareto solutions. It is, however, not easy to obtain them. In this paper, we propose a novel bi-objective optimization model that obtains many Pareto solutions efficiently. We formulate the optimal design problem of NVP as a bi-objective 0-1 nonlinear integer programming problem. In order to overcome this problem, we propose a Multi-objective genetic algorithm (MOGA), which is a powerful, though time-consuming, method to solve multi-objective optimization problems. When implementing genetic algorithm (GA), the use of an appropriate genetic representation scheme is one of the most important issues to obtain good performance. We employ random-key representation in our MOGA to find many Pareto solutions spaced as evenly as possible along the Pareto frontier. To pursue improve further performance, we introduce elitism, the Pareto-insertion and the Pareto-deletion operations based on distance between Pareto solutions in the selection process. The proposed MOGA obtains many Pareto solutions along the Pareto frontier evenly. The user of the MOGA can select the best compromise solution among the candidates by controlling the balance between the system reliability and the total cost.

  10. Genetic Gain and Inbreeding from Genomic Selection in a Simulated Commercial Breeding Program for Perennial Ryegrass

    Directory of Open Access Journals (Sweden)

    Zibei Lin

    2016-03-01

    Full Text Available Genomic selection (GS provides an attractive option for accelerating genetic gain in perennial ryegrass ( improvement given the long cycle times of most current breeding programs. The present study used simulation to investigate the level of genetic gain and inbreeding obtained from GS breeding strategies compared with traditional breeding strategies for key traits (persistency, yield, and flowering time. Base population genomes were simulated through random mating for 60,000 generations at an effective population size of 10,000. The degree of linkage disequilibrium (LD in the resulting population was compared with that obtained from empirical studies. Initial parental varieties were simulated to match diversity of current commercial cultivars. Genomic selection was designed to fit into a company breeding program at two selection points in the breeding cycle (spaced plants and miniplot. Genomic estimated breeding values (GEBVs for productivity traits were trained with phenotypes and genotypes from plots. Accuracy of GEBVs was 0.24 for persistency and 0.36 for yield for single plants, while for plots it was lower (0.17 and 0.19, respectively. Higher accuracy of GEBVs was obtained for flowering time (up to 0.7, partially as a result of the larger reference population size that was available from the clonal row stage. The availability of GEBVs permit a 4-yr reduction in cycle time, which led to at least a doubling and trebling genetic gain for persistency and yield, respectively, than the traditional program. However, a higher rate of inbreeding per cycle among varieties was also observed for the GS strategy.

  11. Genetic Gain and Inbreeding from Genomic Selection in a Simulated Commercial Breeding Program for Perennial Ryegrass.

    Science.gov (United States)

    Lin, Zibei; Cogan, Noel O I; Pembleton, Luke W; Spangenberg, German C; Forster, John W; Hayes, Ben J; Daetwyler, Hans D

    2016-03-01

    Genomic selection (GS) provides an attractive option for accelerating genetic gain in perennial ryegrass () improvement given the long cycle times of most current breeding programs. The present study used simulation to investigate the level of genetic gain and inbreeding obtained from GS breeding strategies compared with traditional breeding strategies for key traits (persistency, yield, and flowering time). Base population genomes were simulated through random mating for 60,000 generations at an effective population size of 10,000. The degree of linkage disequilibrium (LD) in the resulting population was compared with that obtained from empirical studies. Initial parental varieties were simulated to match diversity of current commercial cultivars. Genomic selection was designed to fit into a company breeding program at two selection points in the breeding cycle (spaced plants and miniplot). Genomic estimated breeding values (GEBVs) for productivity traits were trained with phenotypes and genotypes from plots. Accuracy of GEBVs was 0.24 for persistency and 0.36 for yield for single plants, while for plots it was lower (0.17 and 0.19, respectively). Higher accuracy of GEBVs was obtained for flowering time (up to 0.7), partially as a result of the larger reference population size that was available from the clonal row stage. The availability of GEBVs permit a 4-yr reduction in cycle time, which led to at least a doubling and trebling genetic gain for persistency and yield, respectively, than the traditional program. However, a higher rate of inbreeding per cycle among varieties was also observed for the GS strategy. Copyright © 2016 Crop Science Society of America.

  12. Reactor Network Synthesis Using Coupled Genetic Algorithm with the Quasi-linear Programming Method

    OpenAIRE

    Soltani, H.; Shafiei, S.; Edraki, J.

    2016-01-01

    This research is an attempt to develop a new procedure for the synthesis of reactor networks (RNs) using a genetic algorithm (GA) coupled with the quasi-linear programming (LP) method. The GA is used to produce structural configuration, whereas continuous variables are handled using a quasi-LP formulation for finding the best objective function. Quasi-LP consists of LP together with a search loop to find the best reactor conversions (xi), as well as split and recycle ratios (yi). Quasi-LP rep...

  13. Genetic programming for evolving due-date assignment models in job shop environments.

    Science.gov (United States)

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

    2014-01-01

    Due-date assignment plays an important role in scheduling systems and strongly influences the delivery performance of job shops. Because of the stochastic and dynamic nature of job shops, the development of general due-date assignment models (DDAMs) is complicated. In this study, two genetic programming (GP) methods are proposed to evolve DDAMs for job shop environments. The experimental results show that the evolved DDAMs can make more accurate estimates than other existing dynamic DDAMs with promising reusability. In addition, the evolved operation-based DDAMs show better performance than the evolved DDAMs employing aggregate information of jobs and machines.

  14. Automatic Creation of Machine Learning Workflows with Strongly Typed Genetic Programming

    Czech Academy of Sciences Publication Activity Database

    Křen, T.; Pilát, M.; Neruda, Roman

    2017-01-01

    Roč. 26, č. 5 (2017), č. článku 1760020. ISSN 0218-2130 R&D Projects: GA ČR GA15-19877S Grant - others:GA MŠk(CZ) LM2015042 Institutional support: RVO:67985807 Keywords : genetic programming * machine learning workflows * asynchronous evolutionary algorithm Subject RIV: IN - Informatics, Computer Science OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 0.778, year: 2016

  15. Adaptive Test Selection for Factorization-based Surrogate Fitness in Genetic Programming

    Directory of Open Access Journals (Sweden)

    Krawiec Krzysztof

    2017-12-01

    Full Text Available Genetic programming (GP is a variant of evolutionary algorithm where the entities undergoing simulated evolution are computer programs. A fitness function in GP is usually based on a set of tests, each of which defines the desired output a correct program should return for an exemplary input. The outcomes of interactions between programs and tests in GP can be represented as an interaction matrix, with rows corresponding to programs in the current population and columns corresponding to tests. In previous work, we proposed SFIMX, a method that performs only a fraction of interactions and employs non-negative matrix factorization to estimate the outcomes of remaining ones, shortening GP’s runtime. In this paper, we build upon that work and propose three extensions of SFIMX, in which the subset of tests drawn to perform interactions is selected with respect to test difficulty. The conducted experiment indicates that the proposed extensions surpass the original SFIMX on a suite of discrete GP benchmarks.

  16. Internal combustion engine control for series hybrid electric vehicles by parallel and distributed genetic programming/multiobjective genetic algorithms

    Science.gov (United States)

    Gladwin, D.; Stewart, P.; Stewart, J.

    2011-02-01

    This article addresses the problem of maintaining a stable rectified DC output from the three-phase AC generator in a series-hybrid vehicle powertrain. The series-hybrid prime power source generally comprises an internal combustion (IC) engine driving a three-phase permanent magnet generator whose output is rectified to DC. A recent development has been to control the engine/generator combination by an electronically actuated throttle. This system can be represented as a nonlinear system with significant time delay. Previously, voltage control of the generator output has been achieved by model predictive methods such as the Smith Predictor. These methods rely on the incorporation of an accurate system model and time delay into the control algorithm, with a consequent increase in computational complexity in the real-time controller, and as a necessity relies to some extent on the accuracy of the models. Two complementary performance objectives exist for the control system. Firstly, to maintain the IC engine at its optimal operating point, and secondly, to supply a stable DC supply to the traction drive inverters. Achievement of these goals minimises the transient energy storage requirements at the DC link, with a consequent reduction in both weight and cost. These objectives imply constant velocity operation of the IC engine under external load disturbances and changes in both operating conditions and vehicle speed set-points. In order to achieve these objectives, and reduce the complexity of implementation, in this article a controller is designed by the use of Genetic Programming methods in the Simulink modelling environment, with the aim of obtaining a relatively simple controller for the time-delay system which does not rely on the implementation of real time system models or time delay approximations in the controller. A methodology is presented to utilise the miriad of existing control blocks in the Simulink libraries to automatically evolve optimal control

  17. Genetic diversity of Prochilodus lineatus stocks using in the stocking program of Tietê River, Brazil

    Directory of Open Access Journals (Sweden)

    Ricardo Ribeiro

    2013-11-01

    Full Text Available Objective. Assess the genetic diversity in four brood stocks and one juvenile stock of curimba Prochilodus lineatus in a Hydropower plant in São Paulo - Brazil, using the Tietê River stocking program. Materials and methods. Five RAPD primers were used to amplify the extracted DNA from 150 fin-clip samples. Results. Fifty-nine fragments were polymorphic, 52 had frequencies with significant differences (p<0.05, 45 had low frequencies, 54 were excluded, and two were fixed fragments. High values for polymorphic fragments (71.19% to 91.53% and Shannon index (0.327 to 0.428 were observed. The genetic divergence values within each stock were greater than 50%. Most of the genetic variation was found within the groups through the AMOVA analysis, which was confirmed by the results of the identity and genetic distance. High ancestry levels (FST among the groups value indicated high and moderate genetic differentiation. The estimates of number of migrants by generation (Nm indicated low levels of gene flow. High and moderate genetic divergence between groups (0.58 to 0.83 was observed. Conclusions. The results indicate high variability within the stocks, and genetic differentiation among them. The fish stocks analyzed represent a large genetic base that will allow the fish technicians to release juveniles without genetic risks to wild populations present in the river. These genetic procedures may be used as models for other migratory species, including those threatened by extinction.

  18. Control of Angra 1' PZR by a fuzzy rule base build through genetic programming

    International Nuclear Information System (INIS)

    Caldas, Gustavo Henrique Flores; Schirru, Roberto

    2002-01-01

    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)

  19. 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.

  20. 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.

  1. Prediksi Nilai Tukar Rupiah Terhadap US Dollar Menggunakan Metode Genetic Programming

    Directory of Open Access Journals (Sweden)

    Daneswara Jauhari

    2016-12-01

    Exchange currency rate has a wide influence in the economy of a country, both domestically or internationally. The importance of knowing the pattern of exchange rate against the IDR to USD could help the economic growth due to foreign trade involves the use of currencies of different countries. Therefore, we need an application that can predict the value of IDR against the USD in the future. In this research, the authors use genetic programming (GP method which produces solutions (chromosome that obtained from the evaluation of exchange rate and then this solution used as an approximation or prediction of currency exchange rate in the future. These solutions formed from the combination of the set terminal and the set of function that generated randomly. After testing by the number popsize and different iterations, it was found that the GP algorithm can predict the value of the rupiah against the US Dollar with a very good, judging from the value of Mean Absolute Percentage Error (MAPE generated by 0.08%. This research can be developed even better by adding terminal parameters and operating parameters so they can add variation calculation results. Keywords:  prediction, exchange currency rate, genetic programming, MAPE.

  2. 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.

  3. When Darwin meets Lorenz: Evolving new chaotic attractors through genetic programming

    International Nuclear Information System (INIS)

    Pan, Indranil; Das, Saptarshi

    2015-01-01

    Highlights: •New 3D continuous time chaotic systems with analytical expressions are obtained. •The multi-gene genetic programming (MGGP) paradigm is employed to achieve this. •Extends earlier works for evolving generalised family of Lorenz attractors. •Over one hundred of new chaotic attractors along with their parameters are reported. •The MGGP method have the potential for finding other similar chaotic attractors. -- Abstract: In this paper, we propose a novel methodology for automatically finding new chaotic attractors through a computational intelligence technique known as multi-gene genetic programming (MGGP). We apply this technique to the case of the Lorenz attractor and evolve several new chaotic attractors based on the basic Lorenz template. The MGGP algorithm automatically finds new nonlinear expressions for the different state variables starting from the original Lorenz system. The Lyapunov exponents of each of the attractors are calculated numerically based on the time series of the state variables using time delay embedding techniques. The MGGP algorithm tries to search the functional space of the attractors by aiming to maximise the largest Lyapunov exponent (LLE) of the evolved attractors. To demonstrate the potential of the proposed methodology, we report over one hundred new chaotic attractor structures along with their parameters, which are evolved from just the Lorenz system alone

  4. Extraction of Static and Dynamic Reservoir Operation Rules by Genetic Programming

    Directory of Open Access Journals (Sweden)

    Habib Akbari Alashti

    2014-11-01

    Full Text Available Considering the necessity of desirable operation of limited water resources and assuming the significant role of dams in controlling and consuming the surface waters, highlights the advantageous of suitable operation rules for optimal and sustainable operation of dams. This study investigates the hydroelectric supply of a one-reservoir system of Karoon3 using nonlinear programming (NLP, genetic algorithm (GA, genetic programming (GP and fixed length gen GP (FLGGP in real-time operation of dam considering two approaches of static and dynamic operation rules. In static operation rule, only one rule curve is extracted for all months in a year whereas in dynamic operation rule, monthly rule curves (12 rules are extracted for each month of a year. In addition, nonlinear decision rule (NLDR curves are considered, and the total deficiency function as the target (objective function have been used for evaluating the performance of each method and approach. Results show appropriate efficiency of GP and FLGGP methods in extracting operation rules in both approaches. Superiority of these methods to operation methods yielded by GA and NLP is 5%. Moreover, according to the results, it can be remarked that, FLGGP method is an alternative for GP method, whereas the GP method cannot be used due to its limitations. Comparison of two approaches of static and dynamic operation rules demonstrated the superiority of dynamic operation rule to static operation rule (about 10% and therefore this method has more capabilities in real-time operation of the reservoirs systems.

  5. 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.

  6. 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.

  7. A comparison of fitness-case sampling methods for genetic programming

    Science.gov (United States)

    Martínez, Yuliana; Naredo, Enrique; Trujillo, Leonardo; Legrand, Pierrick; López, Uriel

    2017-11-01

    Genetic programming (GP) is an evolutionary computation paradigm for automatic program induction. GP has produced impressive results but it still needs to overcome some practical limitations, particularly its high computational cost, overfitting and excessive code growth. Recently, many researchers have proposed fitness-case sampling methods to overcome some of these problems, with mixed results in several limited tests. This paper presents an extensive comparative study of four fitness-case sampling methods, namely: Interleaved Sampling, Random Interleaved Sampling, Lexicase Selection and Keep-Worst Interleaved Sampling. The algorithms are compared on 11 symbolic regression problems and 11 supervised classification problems, using 10 synthetic benchmarks and 12 real-world data-sets. They are evaluated based on test performance, overfitting and average program size, comparing them with a standard GP search. Comparisons are carried out using non-parametric multigroup tests and post hoc pairwise statistical tests. The experimental results suggest that fitness-case sampling methods are particularly useful for difficult real-world symbolic regression problems, improving performance, reducing overfitting and limiting code growth. On the other hand, it seems that fitness-case sampling cannot improve upon GP performance when considering supervised binary classification.

  8. Improving feature ranking for biomarker discovery in proteomics mass spectrometry data using genetic programming

    Science.gov (United States)

    Ahmed, Soha; Zhang, Mengjie; Peng, Lifeng

    2014-07-01

    Feature selection on mass spectrometry (MS) data is essential for improving classification performance and biomarker discovery. The number of MS samples is typically very small compared with the high dimensionality of the samples, which makes the problem of biomarker discovery very hard. In this paper, we propose the use of genetic programming for biomarker detection and classification of MS data. The proposed approach is composed of two phases: in the first phase, feature selection and ranking are performed. In the second phase, classification is performed. The results show that the proposed method can achieve better classification performance and biomarker detection rate than the information gain- (IG) based and the RELIEF feature selection methods. Meanwhile, four classifiers, Naive Bayes, J48 decision tree, random forest and support vector machines, are also used to further test the performance of the top ranked features. The results show that the four classifiers using the top ranked features from the proposed method achieve better performance than the IG and the RELIEF methods. Furthermore, GP also outperforms a genetic algorithm approach on most of the used data sets.

  9. On the Reliability of Nonlinear Modeling using Enhanced Genetic Programming Techniques

    Science.gov (United States)

    Winkler, S. M.; Affenzeller, M.; Wagner, S.

    The use of genetic programming (GP) in nonlinear system identification enables the automated search for mathematical models that are evolved by an evolutionary process using the principles of selection, crossover and mutation. Due to the stochastic element that is intrinsic to any evolutionary process, GP cannot guarantee the generation of similar or even equal models in each GP process execution; still, if there is a physical model underlying to the data that are analyzed, then GP is expected to find these structures and produce somehow similar results. In this paper we define a function for measuring the syntactic similarity of mathematical models represented as structure trees; using this similarity function we compare the results produced by GP techniques for a data set representing measurement data of a BMW Diesel engine.

  10. 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.

  11. The use of genetic programming to develop a predictor of swash excursion on sandy beaches

    Directory of Open Access Journals (Sweden)

    M. Passarella

    2018-02-01

    Full Text Available We use genetic programming (GP, a type of machine learning (ML approach, to predict the total and infragravity swash excursion using previously published data sets that have been used extensively in swash prediction studies. Three previously published works with a range of new conditions are added to this data set to extend the range of measured swash conditions. Using this newly compiled data set we demonstrate that a ML approach can reduce the prediction errors compared to well-established parameterizations and therefore it may improve coastal hazards assessment (e.g. coastal inundation. Predictors obtained using GP can also be physically sound and replicate the functionality and dependencies of previous published formulas. Overall, we show that ML techniques are capable of both improving predictability (compared to classical regression approaches and providing physical insight into coastal processes.

  12. The use of genetic programming to develop a predictor of swash excursion on sandy beaches

    Science.gov (United States)

    Passarella, Marinella; Goldstein, Evan B.; De Muro, Sandro; Coco, Giovanni

    2018-02-01

    We use genetic programming (GP), a type of machine learning (ML) approach, to predict the total and infragravity swash excursion using previously published data sets that have been used extensively in swash prediction studies. Three previously published works with a range of new conditions are added to this data set to extend the range of measured swash conditions. Using this newly compiled data set we demonstrate that a ML approach can reduce the prediction errors compared to well-established parameterizations and therefore it may improve coastal hazards assessment (e.g. coastal inundation). Predictors obtained using GP can also be physically sound and replicate the functionality and dependencies of previous published formulas. Overall, we show that ML techniques are capable of both improving predictability (compared to classical regression approaches) and providing physical insight into coastal processes.

  13. Improved Genetic and Simulating Annealing Algorithms to Solve the Traveling Salesman Problem Using Constraint Programming

    Directory of Open Access Journals (Sweden)

    M. Abdul-Niby

    2016-04-01

    Full Text Available The Traveling Salesman Problem (TSP is an integer programming problem that falls into the category of NP-Hard problems. As the problem become larger, there is no guarantee that optimal tours will be found within reasonable computation time. Heuristics techniques, like genetic algorithm and simulating annealing, can solve TSP instances with different levels of accuracy. Choosing which algorithm to use in order to get a best solution is still considered as a hard choice. This paper suggests domain reduction as a tool to be combined with any meta-heuristic so that the obtained results will be almost the same. The hybrid approach of combining domain reduction with any meta-heuristic encountered the challenge of choosing an algorithm that matches the TSP instance in order to get the best results.

  14. LPmerge: an R package for merging genetic maps by linear programming.

    Science.gov (United States)

    Endelman, Jeffrey B; Plomion, Christophe

    2014-06-01

    Consensus genetic maps constructed from multiple populations are an important resource for both basic and applied research, including genome-wide association analysis, genome sequence assembly and studies of evolution. The LPmerge software uses linear programming to efficiently minimize the mean absolute error between the consensus map and the linkage maps from each population. This minimization is performed subject to linear inequality constraints that ensure the ordering of the markers in the linkage maps is preserved. When marker order is inconsistent between linkage maps, a minimum set of ordinal constraints is deleted to resolve the conflicts. LPmerge is on CRAN at http://cran.r-project.org/web/packages/LPmerge. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

    Science.gov (United States)

    Taylan, Fatih

    2011-04-01

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

  16. Modelling the effect of structural QSAR parameters on skin penetration using genetic programming

    International Nuclear Information System (INIS)

    Chung, K K; Do, D Q

    2010-01-01

    In order to model relationships between chemical structures and biological effects in quantitative structure–activity relationship (QSAR) data, an alternative technique of artificial intelligence computing—genetic programming (GP)—was investigated and compared to the traditional method—statistical. GP, with the primary advantage of generating mathematical equations, was employed to model QSAR data and to define the most important molecular descriptions in QSAR data. The models predicted by GP agreed with the statistical results, and the most predictive models of GP were significantly improved when compared to the statistical models using ANOVA. Recently, artificial intelligence techniques have been applied widely to analyse QSAR data. With the capability of generating mathematical equations, GP can be considered as an effective and efficient method for modelling QSAR data

  17. Surrogate-Assisted Genetic Programming With Simplified Models for Automated Design of Dispatching Rules.

    Science.gov (United States)

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

    2017-09-01

    Automated design of dispatching rules for production systems has been an interesting research topic over the last several years. Machine learning, especially genetic programming (GP), has been a powerful approach to dealing with this design problem. However, intensive computational requirements, accuracy and interpretability are still its limitations. This paper aims at developing a new surrogate assisted GP to help improving the quality of the evolved rules without significant computational costs. The experiments have verified the effectiveness and efficiency of the proposed algorithms as compared to those in the literature. Furthermore, new simplification and visualisation approaches have also been developed to improve the interpretability of the evolved rules. These approaches have shown great potentials and proved to be a critical part of the automated design system.

  18. 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

  19. 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.

  20. Searching for globally optimal functional forms for interatomic potentials using genetic programming with parallel tempering.

    Science.gov (United States)

    Slepoy, A; Peters, M D; Thompson, A P

    2007-11-30

    Molecular dynamics and other molecular simulation methods rely on a potential energy function, based only on the relative coordinates of the atomic nuclei. Such a function, called a force field, approximately represents the electronic structure interactions of a condensed matter system. Developing such approximate functions and fitting their parameters remains an arduous, time-consuming process, relying on expert physical intuition. To address this problem, a functional programming methodology was developed that may enable automated discovery of entirely new force-field functional forms, while simultaneously fitting parameter values. The method uses a combination of genetic programming, Metropolis Monte Carlo importance sampling and parallel tempering, to efficiently search a large space of candidate functional forms and parameters. The methodology was tested using a nontrivial problem with a well-defined globally optimal solution: a small set of atomic configurations was generated and the energy of each configuration was calculated using the Lennard-Jones pair potential. Starting with a population of random functions, our fully automated, massively parallel implementation of the method reproducibly discovered the original Lennard-Jones pair potential by searching for several hours on 100 processors, sampling only a minuscule portion of the total search space. This result indicates that, with further improvement, the method may be suitable for unsupervised development of more accurate force fields with completely new functional forms. Copyright (c) 2007 Wiley Periodicals, Inc.

  1. 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

    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. 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 (~ 50%) and latency of the optimized engineered gene networks. 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.

  2. Estimating Typhoon Rainfall over Sea from SSM/I Satellite Data Using an Improved Genetic Programming

    Science.gov (United States)

    Yeh, K.; Wei, H.; Chen, L.; Liu, G.

    2010-12-01

    Estimating Typhoon Rainfall over Sea from SSM/I Satellite Data Using an Improved Genetic Programming Keh-Chia Yeha, Hsiao-Ping Weia,d, Li Chenb, and Gin-Rong Liuc a Department of Civil Engineering, National Chiao Tung University, Hsinchu, Taiwan, 300, R.O.C. b Department of Civil Engineering and Engineering Informatics, Chung Hua University, Hsinchu, Taiwan, 300, R.O.C. c Center for Space and Remote Sensing Research, National Central University, Tao-Yuan, Taiwan, 320, R.O.C. d National Science and Technology Center for Disaster Reduction, Taipei County, Taiwan, 231, R.O.C. Abstract This paper proposes an improved multi-run genetic programming (GP) and applies it to predict the rainfall using meteorological satellite data. GP is a well-known evolutionary programming and data mining method, used to automatically discover the complex relationships among nonlinear systems. The main advantage of GP is to optimize appropriate types of function and their associated coefficients simultaneously. This study makes an improvement to enhance escape ability from local optimums during the optimization procedure. The GP continuously runs several times by replacing the terminal nodes at the next run with the best solution at the current run. The current novel model improves GP, obtaining a highly nonlinear mathematical equation to estimate the rainfall. In the case study, this improved GP described above combining with SSM/I satellite data is employed to establish a suitable method for estimating rainfall at sea surface during typhoon periods. These estimated rainfalls are then verified with the data from four rainfall stations located at Peng-Jia-Yu, Don-Gji-Dao, Lan-Yu, and Green Island, which are four small islands around Taiwan. From the results, the improved GP can generate sophisticated and accurate nonlinear mathematical equation through two-run learning procedures which outperforms the traditional multiple linear regression, empirical equations and back-propagated network

  3. 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.

  4. Water Curtain System Pre-design for Crude Oil Storage URCs : A Numerical Modeling and Genetic Programming Approach

    NARCIS (Netherlands)

    Ghotbi Ravandi, Ebrahim; Rahmannejad, Reza; Karimi-Nasab, Saeed; Sarrafi, Amir; Raoof, Amir

    In this paper the main criteria of the water curtain system for unlined rock caverns (URCs) is described. By the application of numerical modeling and genetic programming (GP), a method for water curtain system pre-design for Iranian crude oil storage URCs (common dimension worldwide) is presented.

  5. 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.

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

    International Nuclear Information System (INIS)

    Sadegheih, A.; Drake, P.R.

    2008-01-01

    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

  7. Detecting high-order interactions of single nucleotide polymorphisms using genetic programming.

    Science.gov (United States)

    Nunkesser, Robin; Bernholt, Thorsten; Schwender, Holger; Ickstadt, Katja; Wegener, Ingo

    2007-12-15

    Not individual single nucleotide polymorphisms (SNPs), but high-order interactions of SNPs are assumed to be responsible for complex diseases such as cancer. Therefore, one of the major goals of genetic association studies concerned with such genotype data is the identification of these high-order interactions. This search is additionally impeded by the fact that these interactions often are only explanatory for a relatively small subgroup of patients. Most of the feature selection methods proposed in the literature, unfortunately, fail at this task, since they can either only identify individual variables or interactions of a low order, or try to find rules that are explanatory for a high percentage of the observations. In this article, we present a procedure based on genetic programming and multi-valued logic that enables the identification of high-order interactions of categorical variables such as SNPs. This method called GPAS cannot only be used for feature selection, but can also be employed for discrimination. In an application to the genotype data from the GENICA study, an association study concerned with sporadic breast cancer, GPAS is able to identify high-order interactions of SNPs leading to a considerably increased breast cancer risk for different subsets of patients that are not found by other feature selection methods. As an application to a subset of the HapMap data shows, GPAS is not restricted to association studies comprising several 10 SNPs, but can also be employed to analyze whole-genome data. Software can be downloaded from http://ls2-www.cs.uni-dortmund.de/~nunkesser/#Software

  8. Intelligent and robust prediction of short term wind power using genetic programming based ensemble of neural networks

    International Nuclear Information System (INIS)

    Zameer, Aneela; Arshad, Junaid; Khan, Asifullah; Raja, Muhammad Asif Zahoor

    2017-01-01

    Highlights: • Genetic programming based ensemble of neural networks is employed for short term wind power prediction. • Proposed predictor shows resilience against abrupt changes in weather. • Genetic programming evolves nonlinear mapping between meteorological measures and wind-power. • Proposed approach gives mathematical expressions of wind power to its independent variables. • Proposed model shows relatively accurate and steady wind-power prediction performance. - Abstract: The inherent instability of wind power production leads to critical problems for smooth power generation from wind turbines, which then requires an accurate forecast of wind power. In this study, an effective short term wind power prediction methodology is presented, which uses an intelligent ensemble regressor that comprises Artificial Neural Networks and Genetic Programming. In contrast to existing series based combination of wind power predictors, whereby the error or variation in the leading predictor is propagated down the stream to the next predictors, the proposed intelligent ensemble predictor avoids this shortcoming by introducing Genetical Programming based semi-stochastic combination of neural networks. It is observed that the decision of the individual base regressors may vary due to the frequent and inherent fluctuations in the atmospheric conditions and thus meteorological properties. The novelty of the reported work lies in creating ensemble to generate an intelligent, collective and robust decision space and thereby avoiding large errors due to the sensitivity of the individual wind predictors. The proposed ensemble based regressor, Genetic Programming based ensemble of Artificial Neural Networks, has been implemented and tested on data taken from five different wind farms located in Europe. Obtained numerical results of the proposed model in terms of various error measures are compared with the recent artificial intelligence based strategies to demonstrate the

  9. Estimation of genetic parameters for growth traits in a breeding program for rainbow trout (Oncorhynchus mykiss) in China.

    Science.gov (United States)

    Hu, G; Gu, W; Bai, Q L; Wang, B Q

    2013-04-26

    Genetic parameters and breeding values for growth traits were estimated in the first and, currently, the only family selective breeding program for rainbow trout (Oncorhynchus mykiss) in China. Genetic and phenotypic data were collected for growth traits from 75 full-sibling families with a 2-generation pedigree. Genetic parameters and breeding values for growth traits of rainbow trout were estimated using the derivative-free restricted maximum likelihood method. The goodness-of-fit of the models was tested using Akaike and Bayesian information criteria. Genetic parameters and breeding values were estimated using the best-fit model for each trait. The values for heritability estimating body weight and length ranged from 0.20 to 0.45 and from 0.27 to 0.60, respectively, and the heritability of condition factor was 0.34. Our results showed a moderate degree of heritability for growth traits in this breeding program and suggested that the genetic and phenotypic tendency of body length, body weight, and condition factor were similar. Therefore, the selection of phenotypic values based on pedigree information was also suitable in this research population.

  10. Review: fetal programming of polycystic ovary syndrome by androgen excess: evidence from experimental, clinical, and genetic association studies.

    Science.gov (United States)

    Xita, Nectaria; Tsatsoulis, Agathocles

    2006-05-01

    Polycystic ovary syndrome (PCOS) is a common endocrine disorder of premenopausal women, characterized by hyperandrogenism, polycystic ovaries, and chronic anovulation along with insulin resistance and abdominal obesity as frequent metabolic traits. Although PCOS manifests clinically during adolescence, emerging data suggest that the natural history of PCOS may originate in intrauterine life. Evidence from experimental, clinical, and genetic research supporting the hypothesis for the fetal origins of PCOS has been analyzed. Female primates, exposed in utero to androgen excess, exhibit the phenotypic features of PCOS during adult life. Clinical observations also support a potential fetal origin of PCOS. Women with fetal androgen excess disorders, including congenital 21-hydroxylase deficiency and congenital adrenal virilizing tumors, develop features characteristic of PCOS during adulthood despite the normalization of androgen excess after birth. The potential mechanisms of fetal androgen excess leading to a PCOS phenotype in humans are not clearly understood. However, maternal and/or fetal hyperandrogenism can provide a plausible mechanism for fetal programing of PCOS, and this, in part, may be genetically determined. Thus, genetic association studies have indicated that common polymorphic variants of genes determining androgen activity or genes that influence the availability of androgens to target tissues are associated with PCOS and increased androgen levels. These genomic variants may provide the genetic link to prenatal androgenization in human PCOS. Prenatal androgenization of the female fetus induced by genetic and environmental factors, or the interaction of both, may program differentiating target tissues toward the development of PCOS phenotype in adult life.

  11. Mining Context-Aware Association Rules Using Grammar-Based Genetic Programming.

    Science.gov (United States)

    Luna, Jose Maria; Pechenizkiy, Mykola; Del Jesus, Maria Jose; Ventura, Sebastian

    2017-09-25

    Real-world data usually comprise features whose interpretation depends on some contextual information. Such contextual-sensitive features and patterns are of high interest to be discovered and analyzed in order to obtain the right meaning. This paper formulates the problem of mining context-aware association rules, which refers to the search for associations between itemsets such that the strength of their implication depends on a contextual feature. For the discovery of this type of associations, a model that restricts the search space and includes syntax constraints by means of a grammar-based genetic programming methodology is proposed. Grammars can be considered as a useful way of introducing subjective knowledge to the pattern mining process as they are highly related to the background knowledge of the user. The performance and usefulness of the proposed approach is examined by considering synthetically generated datasets. A posteriori analysis on different domains is also carried out to demonstrate the utility of this kind of associations. For example, in educational domains, it is essential to identify and understand contextual and context-sensitive factors that affect overall and individual student behavior and performance. The results of the experiments suggest that the approach is feasible and it automatically identifies interesting context-aware associations from real-world datasets.

  12. 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.

  13. 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.

  14. Linear genetic programming application for successive-station monthly streamflow prediction

    Science.gov (United States)

    Danandeh Mehr, Ali; Kahya, Ercan; Yerdelen, Cahit

    2014-09-01

    In recent decades, artificial intelligence (AI) techniques have been pronounced as a branch of computer science to model wide range of hydrological phenomena. A number of researches have been still comparing these techniques in order to find more effective approaches in terms of accuracy and applicability. In this study, we examined the ability of linear genetic programming (LGP) technique to model successive-station monthly streamflow process, as an applied alternative for streamflow prediction. A comparative efficiency study between LGP and three different artificial neural network algorithms, namely feed forward back propagation (FFBP), generalized regression neural networks (GRNN), and radial basis function (RBF), has also been presented in this study. For this aim, firstly, we put forward six different successive-station monthly streamflow prediction scenarios subjected to training by LGP and FFBP using the field data recorded at two gauging stations on Çoruh River, Turkey. Based on Nash-Sutcliffe and root mean squared error measures, we then compared the efficiency of these techniques and selected the best prediction scenario. Eventually, GRNN and RBF algorithms were utilized to restructure the selected scenario and to compare with corresponding FFBP and LGP. Our results indicated the promising role of LGP for successive-station monthly streamflow prediction providing more accurate results than those of all the ANN algorithms. We found an explicit LGP-based expression evolved by only the basic arithmetic functions as the best prediction model for the river, which uses the records of the both target and upstream stations.

  15. 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.

  16. 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.

  17. 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.

  18. Comparison between Decision Tree and Genetic Programming to distinguish healthy from stroke postural sway patterns.

    Science.gov (United States)

    Marrega, Luiz H G; Silva, Simone M; Manffra, Elisangela F; Nievola, Julio C

    2015-01-01

    Maintaining balance is a motor task of crucial importance for humans to perform their daily activities safely and independently. Studies in the field of Artificial Intelligence have considered different classification methods in order to distinguish healthy subjects from patients with certain motor disorders based on their postural strategies during the balance control. The main purpose of this paper is to compare the performance between Decision Tree (DT) and Genetic Programming (GP) - both classification methods of easy interpretation by health professionals - to distinguish postural sway patterns produced by healthy and stroke individuals based on 16 widely used posturographic variables. For this purpose, we used a posturographic dataset of time-series of center-of-pressure displacements derived from 19 stroke patients and 19 healthy matched subjects in three quiet standing tasks of balance control. Then, DT and GP models were trained and tested under two different experiments where accuracy, sensitivity and specificity were adopted as performance metrics. The DT method has performed statistically significant (P < 0.05) better in both cases, showing for example an accuracy of 72.8% against 69.2% from GP in the second experiment of this paper.

  19. Online Learning of Genetic Network Programming and its Application to Prisoner’s Dilemma Game

    Science.gov (United States)

    Mabu, Shingo; Hirasawa, Kotaro; Hu, Jinglu; Murata, Junichi

    A new evolutionary model with the network structure named Genetic Network Programming (GNP) has been proposed recently. GNP, that is, an expansion of GA and GP, represents solutions as a network structure and evolves it by using “offline learning (selection, mutation, crossover)”. GNP can memorize the past action sequences in the network flow, so it can deal with Partially Observable Markov Decision Process (POMDP) well. In this paper, in order to improve the ability of GNP, Q learning (an off-policy TD control algorithm) that is one of the famous online methods is introduced for online learning of GNP. Q learning is suitable for GNP because (1) in reinforcement learning, the rewards an agent will get in the future can be estimated, (2) TD control doesn’t need much memory and can learn quickly, and (3) off-policy is suitable in order to search for an optimal solution independently of the policy. Finally, in the simulations, online learning of GNP is applied to a player for “Prisoner’s dilemma game” and its ability for online adaptation is confirmed.

  20. Comparison between dynamic programming and genetic algorithm for hydro unit economic load dispatch

    Directory of Open Access Journals (Sweden)

    Bin Xu

    2014-10-01

    Full Text Available The hydro unit economic load dispatch (ELD is of great importance in energy conservation and emission reduction. Dynamic programming (DP and genetic algorithm (GA are two representative algorithms for solving ELD problems. The goal of this study was to examine the performance of DP and GA while they were applied to ELD. We established numerical experiments to conduct performance comparisons between DP and GA with two given schemes. The schemes included comparing the CPU time of the algorithms when they had the same solution quality, and comparing the solution quality when they had the same CPU time. The numerical experiments were applied to the Three Gorges Reservoir in China, which is equipped with 26 hydro generation units. We found the relation between the performance of algorithms and the number of units through experiments. Results show that GA is adept at searching for optimal solutions in low-dimensional cases. In some cases, such as with a number of units of less than 10, GA's performance is superior to that of a coarse-grid DP. However, GA loses its superiority in high-dimensional cases. DP is powerful in obtaining stable and high-quality solutions. Its performance can be maintained even while searching over a large solution space. Nevertheless, due to its exhaustive enumerating nature, it costs excess time in low-dimensional cases.

  1. Generating and repairing genetically programmed DNA breaks during immunoglobulin class switch recombination

    Science.gov (United States)

    Nicolas, Laura; Cols, Montserrat; Choi, Jee Eun; Chaudhuri, Jayanta; Vuong, Bao

    2018-01-01

    Adaptive immune responses require the generation of a diverse repertoire of immunoglobulins (Igs) that can recognize and neutralize a seemingly infinite number of antigens. V(D)J recombination creates the primary Ig repertoire, which subsequently is modified by somatic hypermutation (SHM) and class switch recombination (CSR). SHM promotes Ig affinity maturation whereas CSR alters the effector function of the Ig. Both SHM and CSR require activation-induced cytidine deaminase (AID) to produce dU:dG mismatches in the Ig locus that are transformed into untemplated mutations in variable coding segments during SHM or DNA double-strand breaks (DSBs) in switch regions during CSR. Within the Ig locus, DNA repair pathways are diverted from their canonical role in maintaining genomic integrity to permit AID-directed mutation and deletion of gene coding segments. Recently identified proteins, genes, and regulatory networks have provided new insights into the temporally and spatially coordinated molecular interactions that control the formation and repair of DSBs within the Ig locus. Unravelling the genetic program that allows B cells to selectively alter the Ig coding regions while protecting non-Ig genes from DNA damage advances our understanding of the molecular processes that maintain genomic integrity as well as humoral immunity. PMID:29744038

  2. A Generic multi-dimensional feature extraction method using multiobjective genetic programming.

    Science.gov (United States)

    Zhang, Yang; Rockett, Peter I

    2009-01-01

    In this paper, we present a generic feature extraction method for pattern classification using multiobjective genetic programming. This not only evolves the (near-)optimal set of mappings from a pattern space to a multi-dimensional decision space, but also simultaneously optimizes the dimensionality of that decision space. The presented framework evolves vector-to-vector feature extractors that maximize class separability. We demonstrate the efficacy of our approach by making statistically-founded comparisons with a wide variety of established classifier paradigms over a range of datasets and find that for most of the pairwise comparisons, our evolutionary method delivers statistically smaller misclassification errors. At very worst, our method displays no statistical difference in a few pairwise comparisons with established classifier/dataset combinations; crucially, none of the misclassification results produced by our method is worse than any comparator classifier. Although principally focused on feature extraction, feature selection is also performed as an implicit side effect; we show that both feature extraction and selection are important to the success of our technique. The presented method has the practical consequence of obviating the need to exhaustively evaluate a large family of conventional classifiers when faced with a new pattern recognition problem in order to attain a good classification accuracy.

  3. Predicting temperature drop rate of mass concrete during an initial cooling period using genetic programming

    Science.gov (United States)

    Bhattarai, Santosh; Zhou, Yihong; Zhao, Chunju; Zhou, Huawei

    2018-02-01

    Thermal cracking on concrete dams depends upon the rate at which the concrete is cooled (temperature drop rate per day) within an initial cooling period during the construction phase. Thus, in order to control the thermal cracking of such structure, temperature development due to heat of hydration of cement should be dropped at suitable rate. In this study, an attempt have been made to formulate the relation between cooling rate of mass concrete with passage of time (age of concrete) and water cooling parameters: flow rate and inlet temperature of cooling water. Data measured at summer season (April-August from 2009 to 2012) from recently constructed high concrete dam were used to derive a prediction model with the help of Genetic Programming (GP) software “Eureqa”. Coefficient of Determination (R) and Mean Square Error (MSE) were used to evaluate the performance of the model. The value of R and MSE is 0.8855 and 0.002961 respectively. Sensitivity analysis was performed to evaluate the relative impact on the target parameter due to input parameters. Further, testing the proposed model with an independent dataset those not included during analysis, results obtained from the proposed GP model are close enough to the real field data.

  4. Genetic Algorithm for Mixed Integer Nonlinear Bilevel Programming and Applications in Product Family Design

    Directory of Open Access Journals (Sweden)

    Chenlu Miao

    2016-01-01

    Full Text Available Many leader-follower relationships exist in product family design engineering problems. We use bilevel programming (BLP to reflect the leader-follower relationship and describe such problems. Product family design problems have unique characteristics; thus, mixed integer nonlinear BLP (MINLBLP, which has both continuous and discrete variables and multiple independent lower-level problems, is widely used in product family optimization. However, BLP is difficult in theory and is an NP-hard problem. Consequently, using traditional methods to solve such problems is difficult. Genetic algorithms (GAs have great value in solving BLP problems, and many studies have designed GAs to solve BLP problems; however, such GAs are typically designed for special cases that do not involve MINLBLP with one or multiple followers. Therefore, we propose a bilevel GA to solve these particular MINLBLP problems, which are widely used in product family problems. We give numerical examples to demonstrate the effectiveness of the proposed algorithm. In addition, a reducer family case study is examined to demonstrate practical applications of the proposed BLGA.

  5. Loss of genetic diversity in Culex quinquefasciatus targeted by a lymphatic filariasis vector control program in Recife, Brazil.

    Science.gov (United States)

    Cartaxo, Marina F S; Ayres, Constância F J; Weetman, David

    2011-09-01

    Recife is one of the largest cities in north-eastern Brazil and is endemic for lymphatic filariasis transmitted by Culex quinquefasciatus. Since 2003 a control program has targeted mosquito larvae by elimination of breeding sites and bimonthly application of Bacillus sphaericus. To assess the impact of this program on the local vector population we monitored the genetic diversity and differentiation of Cx. quinquefasciatus using microsatellites and a B. sphaericus-resistance associated mutation (cqm1(REC)) over a 3-year period. We detected a significant but gradual decline in allelic diversity, which, coupled with subtle temporal genetic structure, suggests a major impact of the control program on the vector population. Selection on cqm1(REC) does not appear to be involved with loss of neutral diversity from the population, with no temporal trend in resistant allele frequency and no correlation with microsatellite differentiation. The evidence for short-term genetic drift we detected suggests a low ratio of effective population size: census population size for Cx. quinquefasciatus, perhaps coupled with strong geographically-restricted population structure. Spatial definition of populations will be an important step for success of an expanded vector control program. Copyright © 2011 Royal Society of Tropical Medicine and Hygiene. Published by Elsevier Ltd. All rights reserved.

  6. Genetic Parameters and the Impact of Off-Types for Theobroma cacao L. in a Breeding Program in Brazil

    Science.gov (United States)

    DuVal, Ashley; Gezan, Salvador A.; Mustiga, Guiliana; Stack, Conrad; Marelli, Jean-Philippe; Chaparro, José; Livingstone, Donald; Royaert, Stefan; Motamayor, Juan C.

    2017-01-01

    Breeding programs of cacao (Theobroma cacao L.) trees share the many challenges of breeding long-living perennial crops, and genetic progress is further constrained by both the limited understanding of the inheritance of complex traits and the prevalence of technical issues, such as mislabeled individuals (off-types). To better understand the genetic architecture of cacao, in this study, 13 years of phenotypic data collected from four progeny trials in Bahia, Brazil were analyzed jointly in a multisite analysis. Three separate analyses (multisite, single site with and without off-types) were performed to estimate genetic parameters from statistical models fitted on nine important agronomic traits (yield, seed index, pod index, % healthy pods, % pods infected with witches broom, % of pods other loss, vegetative brooms, diameter, and tree height). Genetic parameters were estimated along with variance components and heritabilities from the multisite analysis, and a trial was fingerprinted with low-density SNP markers to determine the impact of off-types on estimations. Heritabilities ranged from 0.37 to 0.64 for yield and its components and from 0.03 to 0.16 for disease resistance traits. A weighted index was used to make selections for clonal evaluation, and breeding values estimated for the parental selection and estimation of genetic gain. The impact of off-types to breeding progress in cacao was assessed for the first time. Even when present at <5% of the total population, off-types altered selections by 48%, and impacted heritability estimations for all nine of the traits analyzed, including a 41% difference in estimated heritability for yield. These results show that in a mixed model analysis, even a low level of pedigree error can significantly alter estimations of genetic parameters and selections in a breeding program. PMID:29250097

  7. Genetic diversity analysis in Malaysian giant prawns using expressed sequence tag microsatellite markers for stock improvement program.

    Science.gov (United States)

    Atin, K H; Christianus, A; Fatin, N; Lutas, A C; Shabanimofrad, M; Subha, B

    2017-08-17

    The Malaysian giant prawn is among the most commonly cultured species of the genus Macrobrachium. Stocks of giant prawns from four rivers in Peninsular Malaysia have been used for aquaculture over the past 25 years, which has led to repeated harvesting, restocking, and transplantation between rivers. Consequently, a stock improvement program is now important to avoid the depletion of wild stocks and the loss of genetic diversity. However, the success of such an improvement program depends on our knowledge of the genetic variation of these base populations. The aim of the current study was to estimate genetic variation and differentiation of these riverine sources using novel expressed sequence tag-microsatellite (EST-SSR) markers, which not only are informative on genetic diversity but also provide information on immune and metabolic traits. Our findings indicated that the tested stocks have inbreeding depression due to a significant deficiency in heterozygotes, and F IS was estimated as 0.15538 to 0.31938. An F-statistics analysis suggested that the stocks are composed of one large panmictic population. Among the four locations, stocks from Johor, in the southern region of the peninsular, showed higher allelic and genetic diversity than the other stocks. To overcome inbreeding problems, the Johor population could be used as a base population in a stock improvement program by crossing to the other populations. The study demonstrated that EST-SSR markers can be incorporated in future marker assisted breeding to aid the proper management of the stocks by breeders and stakeholders in Malaysia.

  8. 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.

  9. How Am I Driving? Using Genetic Programming to Generate Scoring Functions for Urban Driving Behavior

    Directory of Open Access Journals (Sweden)

    Roberto López

    2018-04-01

    Full Text Available Road traffic injuries are a serious concern in emerging economies. Their death toll and economic impact are shocking, with 9 out of 10 deaths occurring in low or middle-income countries; and road traffic crashes representing 3% of their gross domestic product. One way to mitigate these issues is to develop technology to effectively assist the driver, perhaps making him more aware about how her (his decisions influence safety. Following this idea, in this paper we evaluate computational models that can score the behavior of a driver based on a risky-safety scale. Potential applications of these models include car rental agencies, insurance companies or transportation service providers. In a previous work, we showed that Genetic Programming (GP was a successful methodology to evolve mathematical functions with the ability to learn how people subjectively score a road trip. The input to this model was a vector of frequencies of risky maneuvers, which were supposed to be detected in a sensor layer. Moreover, GP was shown, even with statistical significance, to be better than six other Machine Learning strategies, including Neural Networks, Support Vector Regression and a Fuzzy Inference system, among others. A pending task, since then, was to evaluate if a more detailed comparison of different strategies based on GP could improve upon the best GP model. In this work, we evaluate, side by side, scoring functions evolved by three different variants of GP. In the end, the results suggest that two of these strategies are very competitive in terms of accuracy and simplicity, both generating models that could be implemented in current technology that seeks to assist the driver in real-world scenarios.

  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. Monthly streamflow forecasting using continuous wavelet and multi-gene genetic programming combination

    Science.gov (United States)

    Hadi, Sinan Jasim; Tombul, Mustafa

    2018-06-01

    Streamflow is an essential component of the hydrologic cycle in the regional and global scale and the main source of fresh water supply. It is highly associated with natural disasters, such as droughts and floods. Therefore, accurate streamflow forecasting is essential. Forecasting streamflow in general and monthly streamflow in particular is a complex process that cannot be handled by data-driven models (DDMs) only and requires pre-processing. Wavelet transformation is a pre-processing technique; however, application of continuous wavelet transformation (CWT) produces many scales that cause deterioration in the performance of any DDM because of the high number of redundant variables. This study proposes multigene genetic programming (MGGP) as a selection tool. After the CWT analysis, it selects important scales to be imposed into the artificial neural network (ANN). A basin located in the southeast of Turkey is selected as case study to prove the forecasting ability of the proposed model. One month ahead downstream flow is used as output, and downstream flow, upstream, rainfall, temperature, and potential evapotranspiration with associated lags are used as inputs. Before modeling, wavelet coherence transformation (WCT) analysis was conducted to analyze the relationship between variables in the time-frequency domain. Several combinations were developed to investigate the effect of the variables on streamflow forecasting. The results indicated a high localized correlation between the streamflow and other variables, especially the upstream. In the models of the standalone layout where the data were entered to ANN and MGGP without CWT, the performance is found poor. In the best-scale layout, where the best scale of the CWT identified as the highest correlated scale is chosen and enters to ANN and MGGP, the performance increased slightly. Using the proposed model, the performance improved dramatically particularly in forecasting the peak values because of the inclusion

  12. Genetic diversity of pacu and piapara broodstocks in restocking programs in the rivers Paraná and Paranapanema (Brazil

    Directory of Open Access Journals (Sweden)

    Nelson Mauricio Lopera-Barrero

    2016-09-01

    Full Text Available The genetic diversity of Piaractus mesopotamicus (pacu and Leporinus elongatus (piapara broodstocks used in restocking programs in the rivers Paraná and Paranapanema is analyzed. One hundred and twenty specimens (two broodstocks of each species from fish ponds in Palotina PR Brazil and in Salto Grande SP Brazil were assessed. Ten primers produced 96 fragments, comprising 68 (70.83% and 94 (97.92% polymorphic fragments for P. mesopotamicus and L. elongatus broodstocks, respectively. Differences (p < 0.05 in the frequency of 15 and 27 fragments were detected for each species, without exclusive fragments. Shannon Index (0.347 - 0.572 and the percentage of polymorphic fragments (57.3% - 94.8% revealed high intra-population genetic variability for all broodstocks. Results of molecular variance analyses (AMOVA showed that most variations do not lie between the broodstocks but within each broodstock (89%. Genetic (0.088 and 0.142 and identity (0.916 and 0.868 distance rates demonstrated similarity between the broodstocks of each species, corroborated by Fst (0.1023 and 010.27 and Nm (4.18 and 4.33 rates, with a slight genetic difference due to genic flux. High intrapopulation genetic variability and similarity between the broodstocks of each species was also detected, proving a common ancestry.

  13. Using actual and ultrasound carcass information in beef genetic evaluation programs

    OpenAIRE

    Bertrand,Joseph Keith

    2009-01-01

    Increased movement toward alliances and grid pricing in the U.S. has led to an increase interest in genetic values for carcass traits. The literature suggests that carcass genetic values are an effective tool to enhance selection for carcass traits, and that it is possible to select sires within a breed that can increase marbling score without adversely affecting external fat thickness or percent retail product relative to the breed mean. Ultrasound has been investigated as a cheaper means of...

  14. 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

    Low birthweight (LBW) individuals and offspring of women with gestational diabetes mellitus (GDM) exhibit increased risk of developing type 2 diabetes (T2D) and associated cardiometabolic traits in adulthood, which for both groups may be mediated by adverse events and developmental changes in fetal...... factors. Indeed, it has been shown that genetic changes influencing risk of diabetes may also be associated with reduced fetal growth as a result of reduced insulin secretion and/or action. Similarly, increased risk of T2D among offspring could be explained by T2D susceptibility genes shared between...... life. T2D is a multifactorial disease occurring as a result of complicated interplay between genetic and both prenatal and postnatal nongenetic factors, and it remains unknown to what extent the increased risk of T2D associated with LBW or GDM in the mother may be due to, or confounded by, genetic...

  15. 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.

  16. 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.

  17. Area program in population genetics. Final report, November 1, 1975-August 31, 1982

    International Nuclear Information System (INIS)

    Chu, E.H.Y.; Gershowitz, H.; Meisler, M.H.; Mohrenweiser, H.W.; Neel, J.V.; Rothman, E.D.; Sing, C.S.

    1982-01-01

    Research results are summarized for the following task areas: (1) Amerindian mutation rates; (2) pilot study of monitoring populations for the frequency of mutation; (3) interdigitation with the biochemical genetics study of the Radiation Effects Research Foundation (Hiroshima, Japan); (4) intraindividual variation in erythrocyte blood group antigens as indicators of somatic mutation; (5) in vitro studies of somatic cell mutation rates; (6) development of approaches to the study of mutation rates; and (7) statistical problems associated with the study of mutation and selection

  18. 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.

  19. 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

  20. 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

  1. Development of a New Aprepitant Liquisolid Formulation with the Aid of Artificial Neural Networks and Genetic Programming.

    Science.gov (United States)

    Barmpalexis, Panagiotis; Grypioti, Agni; Eleftheriadis, Georgios K; Fatouros, Dimitris G

    2018-02-01

    In the present study, liquisolid formulations were developed for improving dissolution profile of aprepitant (APT) in a solid dosage form. Experimental studies were complemented with artificial neural networks and genetic programming. Specifically, the type and concentration of liquid vehicle was evaluated through saturation-solubility studies, while the effect of the amount of viscosity increasing agent (HPMC), the type of wetting (Soluplus® vs. PVP) and solubilizing (Poloxamer®407 vs. Kolliphor®ELP) agents, and the ratio of solid coating (microcrystalline cellulose) to carrier (colloidal silicon dioxide) were evaluated based on in vitro drug release studies. The optimum liquisolid formulation exhibited improved dissolution characteristics compared to the marketed product Emend®. X-ray diffraction (XRD), scanning electron microscopy (SEM) and a novel method combining particle size analysis by dynamic light scattering (DLS) and HPLC, revealed that the increase in dissolution rate of APT in the optimum liquisolid formulation was due to the formation of stable APT nanocrystals. Differential scanning calorimetry (DSC) and attenuated total reflection FTIR spectroscopy (ATR-FTIR) revealed the presence of intermolecular interactions between APT and liquisolid formulation excipients. Multilinear regression analysis (MLR), artificial neural networks (ANNs), and genetic programming (GP) were used to correlate several formulation variables with dissolution profile parameters (Y 15min and Y 30min ) using a full factorial experimental design. Results showed increased correlation efficacy for ANNs and GP (RMSE of 0.151 and 0.273, respectively) compared to MLR (RMSE = 0.413).

  2. Ethical dilemmas in genetic testing: examples from the Cuban program for predictive diagnosis of hereditary ataxias.

    Science.gov (United States)

    Mariño, Tania Cruz; Armiñán, Rubén Reynaldo; Cedeño, Humberto Jorge; Mesa, José Miguel Laffita; Zaldivar, Yanetza González; Rodríguez, Raúl Aguilera; Santos, Miguel Velázquez; Mederos, Luis Enrique Almaguer; Herrera, Milena Paneque; Pérez, Luis Velázquez

    2011-06-01

    Predictive testing protocols are intended to help patients affected with hereditary conditions understand their condition and make informed reproductive choices. However, predictive protocols may expose clinicians and patients to ethical dilemmas that interfere with genetic counseling and the decision making process. This paper describes ethical dilemmas in a series of five cases involving predictive testing for hereditary ataxias in Cuba. The examples herein present evidence of the deeply controversial situations faced by both individuals at risk and professionals in charge of these predictive studies, suggesting a need for expanded guidelines to address such complexities.

  3. THE USE THE GENETICALLY DIFFICULTLY INHERITED TRAIT OF PURPLE ROOT COLOR IN BREEDING PROGRAM FOR THE COMPLICATED TRAIT IN RADISH

    Directory of Open Access Journals (Sweden)

    S. V. Ugarova

    2017-01-01

    Full Text Available The understanding the nature of trait inheritance in any crops is that determines the quality of results in breeding program. According to reference on previous publication, it is known that phenotypic manifestation of purple root color in radish was caused by regulatory interrelationship mechanisms of genetic control that is difficult to be used directly in breeding program. From literature sources and on the basis of their own research work the authors have proven the practice to maintain the trait in generations, and implementations of development of purple radish breeding accessions have been presented. At first stage of breeding program the selection of initial breeding accessions was carried out, where 14 varieties (red x white were regarded on the basis of top-crosses to obtain F1 and F2 progenies to be analyzed. Thus, four best combinations from crossing were chosen with 100% of hybridity. Through analysis of hybrids for individual progenies the hybrid population F1 of radish ‘Konfeti’ with different root colors was developed. As result of the individual inbreeding selection on seed plants with pigmented stems and the colored flower rim, the stable breeding accession with purple root was obtained. Thus, in breeding practice in radish it was succeeded to obtain the stably inheriting purple root color in radish accessions, variety ‘Siniiy Iniey’. 

  4. 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

  5. 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.

  6. Designing a Web Spam Classifier Based on Feature Fusion in the Layered Multi-Population Genetic Programming Framework

    Directory of Open Access Journals (Sweden)

    Amir Hosein KEYHANIPOUR

    2013-11-01

    Full Text Available Nowadays, Web spam pages are a critical challenge for Web retrieval systems which have drastic influence on the performance of such systems. Although these systems try to combat the impact of spam pages on their final results list, spammers increasingly use more sophisticated techniques to increase the number of views for their intended pages in order to have more commercial success. This paper employs the recently proposed Layered Multi-population Genetic Programming model for Web spam detection task as well application of correlation coefficient analysis for feature space reduction. Based on our tentative results, the designed classifier, which is based on a combination of easy to compute features, has a very reasonable performance in comparison with similar methods.

  7. Genetic programming-based mathematical modeling of influence of weather parameters in BOD5 removal by Lemna minor.

    Science.gov (United States)

    Chandrasekaran, Sivapragasam; Sankararajan, Vanitha; Neelakandhan, Nampoothiri; Ram Kumar, Mahalakshmi

    2017-11-04

    This study, through extensive experiments and mathematical modeling, reveals that other than retention time and wastewater temperature (T w ), atmospheric parameters also play important role in the effective functioning of aquatic macrophyte-based treatment system. Duckweed species Lemna minor is considered in this study. It is observed that the combined effect of atmospheric temperature (T atm ), wind speed (U w ), and relative humidity (RH) can be reflected through one parameter, namely the "apparent temperature" (T a ). A total of eight different models are considered based on the combination of input parameters and the best mathematical model is arrived at which is validated through a new experimental set-up outside the modeling period. The validation results are highly encouraging. Genetic programming (GP)-based models are found to reveal deeper understandings of the wetland process.

  8. New horizontal global solar radiation estimation models for Turkey based on robust coplot supported genetic programming technique

    International Nuclear Information System (INIS)

    Demirhan, Haydar; Kayhan Atilgan, Yasemin

    2015-01-01

    Highlights: • Precise horizontal global solar radiation estimation models are proposed for Turkey. • Genetic programming technique is used to construct the models. • Robust coplot analysis is applied to reduce the impact of outlier observations. • Better estimation and prediction properties are observed for the models. - Abstract: Renewable energy sources have been attracting more and more attention of researchers due to the diminishing and harmful nature of fossil energy sources. Because of the importance of solar energy as a renewable energy source, an accurate determination of significant covariates and their relationships with the amount of global solar radiation reaching the Earth is a critical research problem. There are numerous meteorological and terrestrial covariates that can be used in the analysis of horizontal global solar radiation. Some of these covariates are highly correlated with each other. It is possible to find a large variety of linear or non-linear models to explain the amount of horizontal global solar radiation. However, models that explain the amount of global solar radiation with the smallest set of covariates should be obtained. In this study, use of the robust coplot technique to reduce the number of covariates before going forward with advanced modelling techniques is considered. After reducing the dimensionality of model space, yearly and monthly mean daily horizontal global solar radiation estimation models for Turkey are built by using the genetic programming technique. It is observed that application of robust coplot analysis is helpful for building precise models that explain the amount of global solar radiation with the minimum number of covariates without suffering from outlier observations and the multicollinearity problem. Consequently, over a dataset of Turkey, precise yearly and monthly mean daily global solar radiation estimation models are introduced using the model spaces obtained by robust coplot technique and

  9. Prediction of monthly rainfall on homogeneous monsoon regions of India based on large scale circulation patterns using Genetic Programming

    Science.gov (United States)

    Kashid, Satishkumar S.; Maity, Rajib

    2012-08-01

    SummaryPrediction of Indian Summer Monsoon Rainfall (ISMR) is of vital importance for Indian economy, and it has been remained a great challenge for hydro-meteorologists due to inherent complexities in the climatic systems. The Large-scale atmospheric circulation patterns from tropical Pacific Ocean (ENSO) and those from tropical Indian Ocean (EQUINOO) are established to influence the Indian Summer Monsoon Rainfall. The information of these two large scale atmospheric circulation patterns in terms of their indices is used to model the complex relationship between Indian Summer Monsoon Rainfall and the ENSO as well as EQUINOO indices. However, extracting the signal from such large-scale indices for modeling such complex systems is significantly difficult. Rainfall predictions have been done for 'All India' as one unit, as well as for five 'homogeneous monsoon regions of India', defined by Indian Institute of Tropical Meteorology. Recent 'Artificial Intelligence' tool 'Genetic Programming' (GP) has been employed for modeling such problem. The Genetic Programming approach is found to capture the complex relationship between the monthly Indian Summer Monsoon Rainfall and large scale atmospheric circulation pattern indices - ENSO and EQUINOO. Research findings of this study indicate that GP-derived monthly rainfall forecasting models, that use large-scale atmospheric circulation information are successful in prediction of All India Summer Monsoon Rainfall with correlation coefficient as good as 0.866, which may appears attractive for such a complex system. A separate analysis is carried out for All India Summer Monsoon rainfall for India as one unit, and five homogeneous monsoon regions, based on ENSO and EQUINOO indices of months of March, April and May only, performed at end of month of May. In this case, All India Summer Monsoon Rainfall could be predicted with 0.70 as correlation coefficient with somewhat lesser Correlation Coefficient (C.C.) values for different

  10. Genetic Algorithm for Mixed Integer Nonlinear Bilevel Programming and Applications in Product Family Design

    OpenAIRE

    Chenlu Miao; Gang Du; Yi Xia; Danping Wang

    2016-01-01

    Many leader-follower relationships exist in product family design engineering problems. We use bilevel programming (BLP) to reflect the leader-follower relationship and describe such problems. Product family design problems have unique characteristics; thus, mixed integer nonlinear BLP (MINLBLP), which has both continuous and discrete variables and multiple independent lower-level problems, is widely used in product family optimization. However, BLP is difficult in theory and is an NP-hard pr...

  11. Genetic screening: programs, principles, and research--thirty years later. Reviewing the recommendations of the Committee for the Study of Inborn Errors of Metabolism (SIEM).

    Science.gov (United States)

    Simopoulos, A P

    2009-01-01

    Screening programs for genetic diseases and characteristics have multiplied in the last 50 years. 'Genetic Screening: Programs, Principles, and Research' is the report of the Committee for the Study of Inborn Errors of Metabolism (SIEM Committee) commissioned by the Division of Medical Sciences of the National Research Council at the National Academy of Sciences in Washington, DC, published in 1975. The report is considered a classic in the field worldwide, therefore it was thought appropriate 30 years later to present the Committee's modus operandi and bring the Committee's recommendations to the attention of those involved in genetics, including organizational, educational, legal, and research aspects of genetic screening. The Committee's report anticipated many of the legal, ethical, economic, social, medical, and policy aspects of genetic screening. The recommendations are current, and future committees should be familiar with them. In 1975 the Committee stated: 'As new screening tests are devised, they should be carefully reviewed. If the experimental rate of discovery of new genetic characteristics means an accelerating rate of appearance of new screening tests, now is the time to develop the medical and social apparatus to accommodate what later on may otherwise turn out to be unmanageable growth.' What a prophetic statement that was. If the Committee's recommendations had been implemented on time, there would be today a federal agency in existence, responsive and responsible to carry out the programs and support research on various aspects of genetic screening, including implementation of a federal law that protects consumers from discrimination by their employers and the insurance industry on the basis of genetic information. Copyright 2008 S. Karger AG, Basel.

  12. A multinational Andean genetic and health program: growth and development in an hypoxic environment.

    Science.gov (United States)

    Mueller, W H; Schull, V N; Schull, W J; Soto, P; Rothhammer, F

    1978-07-01

    In 1972 a multidisciplinary study sought to assess the health status of the indigenous peoples of the Department of Arica in northern Chile, the Aymara, and to relate disease, morphological, physiological and biochemical variation, to the wide changes in altitude of the region. Presented here are the morphological changes which accompany age, altitude and ethnicity amoung 1047 children and adults, permanent residents of the coast, sierra and altiplano. At comparable ages, high-altitude residents were shorter, lighter and leaner but with more expansive and rounder chests than sea-level controls. None of these effects was systematically related to ethnicity (Spanish-Aymara surname), although when stature was held constant, children with greater Aymara ancestry had largest chest circumferences and longer bones. These results suggest that (1) altitude confers allometric growth changes (expensive growth of the chest and diminished growth of the structures less related to oxygen transport); and (2) size changes associated with altitude are acquired during development while shape changes may be under genetic control. Altitude appears to account for less of the variation in growth in this relatively homogeneous Chilean sample than has been reported for other Andean samples, suggesting other concomitants confounding the effects of hypoxia in Andean South America.

  13. Invesitgation of Drilling Parameters on Thrust Force on AZ91 Magnesium Alloy by Genetic Expression Programming

    Directory of Open Access Journals (Sweden)

    Kemal ALDAŞ

    2014-09-01

    Full Text Available Bu çalışmada AZ91 magnezyum alaşımının farklı parametreler altında işlenmesi ile oluşan kesme kuvvetlerinin deneysel tabanlı teorik bir model ile tahmin edilmesi sunulmuştur. Modelleme için gerekli deneyler kuru işleme ortamında ve işleme devri ilerleme hızı ve 4 farklı matkap ucunun tam faktöriyel deney tasarımı kullanarak gerçekleştirilmiştir. Deneyler sonucunca elde edilen veriler Genetic Expression yazılımı ile modellenerek kesme kuvveti tahmini için formulasyon oluşturulmuştur. Bu formulasyon kullanılarak deneyde kullanılan parametrelerin kesme kuvveti üzerindeki etkileri detaylı olarak analiz edilmiştir

  14. Genetic programming based models in plant tissue culture: An addendum to traditional statistical approach.

    Science.gov (United States)

    Mridula, Meenu R; Nair, Ashalatha S; Kumar, K Satheesh

    2018-02-01

    In this paper, we compared the efficacy of observation based modeling approach using a genetic algorithm with the regular statistical analysis as an alternative methodology in plant research. Preliminary experimental data on in vitro rooting was taken for this study with an aim to understand the effect of charcoal and naphthalene acetic acid (NAA) on successful rooting and also to optimize the two variables for maximum result. Observation-based modelling, as well as traditional approach, could identify NAA as a critical factor in rooting of the plantlets under the experimental conditions employed. Symbolic regression analysis using the software deployed here optimised the treatments studied and was successful in identifying the complex non-linear interaction among the variables, with minimalistic preliminary data. The presence of charcoal in the culture medium has a significant impact on root generation by reducing basal callus mass formation. Such an approach is advantageous for establishing in vitro culture protocols as these models will have significant potential for saving time and expenditure in plant tissue culture laboratories, and it further reduces the need for specialised background.

  15. 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

    on forage yield (green and dry matter) and six traits scored by visual inspection (i.e., rust resistance, aftermath heading, spring growth, density, winter hardiness, and heading date). Data were analyzed with linear mixed models, including fixed effects (trial and control varieties, within year...... 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...

  16. 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 computer program Geneland designed to infer population structure has been adapted to deal with dominant markers; and (ii) we use Geneland for numerical comparison of dominant and codominant markers to perform clustering. AFLP markers lead to less accurate results than bi-allelic codominant markers...... 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...

  17. 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.

  18. Non-linear nuclear engineering models as genetic programming application; Modelos nao-lineares de engenharia nuclear como aplicacao de programacao genetica

    Energy Technology Data Exchange (ETDEWEB)

    Domingos, Roberto P.; Schirru, Roberto; Martinez, Aquilino S. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia

    1997-12-01

    This work presents a Genetic Programming paradigm and a nuclear application. A field of Artificial Intelligence, based on the concepts of Species Evolution and Natural Selection, can be understood as a self-programming process where the computer is the main agent responsible for the discovery of a program able to solve a given problem. In the present case, the problem was to find a mathematical expression in symbolic form, able to express the existent relation between equivalent ratio of a fuel cell, the enrichment of fuel elements and the multiplication factor. Such expression would avoid repeatedly reactor physics codes execution for core optimization. The results were compared with those obtained by different techniques such as Neural Networks and Linear Multiple Regression. Genetic Programming has shown to present a performance as good as, and under some features superior to Neural Network and Linear Multiple Regression. (author). 10 refs., 8 figs., 1 tabs.

  19. 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.

  20. Profitability of a dairy sheep genetic improvement program using artificial insemination.

    Science.gov (United States)

    Valergakis, G E; Gelasakis, A I; Oikonomou, G; Arsenos, G; Fortomaris, P; Banos, G

    2010-10-01

    This simulation study investigated the farm-level economic benefits of a genetic improvement scheme using artificial insemination (AI) with fresh ram semen in dairy sheep of the Chios breed in Greece. Data were collected from 67 farms associated with the Chios Sheep Breeders' Cooperative 'Macedonia', describing the percentage of ewes that would be artificially inseminated in the flock, pregnancy rate, annual ram costs that could be saved using AI rather than natural mating, expected improvement in milk production, annual costs of semen and feed, milk price and number of years of AI usage. The study considered 77 760 possible scenarios in a 3 × 4 × 4 × 3 × 3 × 3 × 4 × 15 factorial arrangement. Analysis of variance was used to investigate the effect of each factor on farm profitability. All factors considered were statistically significant (P profitability and farmers should become aware that using AI is a long-term investment. Semen price, pregnancy rate and improvement in milk production also had substantial effects. The price of milk and feed had a considerably lower effect on profitability, as did the annual cost of maintaining rams that would be replaced by AI. A positive annual and cumulative return was achieved in the model within the first 6 years. The cost of semen was estimated at 8€ to 10€ per dose for the first 5 years. Where the annual improvement in milk production was 1% of annual phenotypic mean (e.g. 3.0 kg) profitability of the scheme was improved greatly.

  1. 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.

  2. Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposaL

    Energy Technology Data Exchange (ETDEWEB)

    Wichapa, Narong; Khokhajaikiat, Porntep

    2017-07-01

    Disposal of infectious waste remains one of the most serious problems in the social and environmental domains of almost every nation. Selection of new suitable locations and finding the optimal set of transport routes to transport infectious waste, namely location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Design/methodology/approach: Due to the complexity of this problem, location routing problem for a case study, forty hospitals and three candidate municipalities in sub-Northeastern Thailand, was divided into two phases. The first phase is to choose suitable municipalities using hybrid fuzzy goal programming model which hybridizes the fuzzy analytic hierarchy process and fuzzy goal programming. The second phase is to find the optimal routes for each selected municipality using hybrid genetic algorithm which hybridizes the genetic algorithm and local searches including 2-Opt-move, Insertion-move and ?-interchange-move. Findings: The results indicate that the hybrid fuzzy goal programming model can guide the selection of new suitable municipalities, and the hybrid genetic algorithm can provide the optimal routes for a fleet of vehicles effectively. Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.

  3. Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposaL

    International Nuclear Information System (INIS)

    Wichapa, Narong; Khokhajaikiat, Porntep

    2017-01-01

    Disposal of infectious waste remains one of the most serious problems in the social and environmental domains of almost every nation. Selection of new suitable locations and finding the optimal set of transport routes to transport infectious waste, namely location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Design/methodology/approach: Due to the complexity of this problem, location routing problem for a case study, forty hospitals and three candidate municipalities in sub-Northeastern Thailand, was divided into two phases. The first phase is to choose suitable municipalities using hybrid fuzzy goal programming model which hybridizes the fuzzy analytic hierarchy process and fuzzy goal programming. The second phase is to find the optimal routes for each selected municipality using hybrid genetic algorithm which hybridizes the genetic algorithm and local searches including 2-Opt-move, Insertion-move and ?-interchange-move. Findings: The results indicate that the hybrid fuzzy goal programming model can guide the selection of new suitable municipalities, and the hybrid genetic algorithm can provide the optimal routes for a fleet of vehicles effectively. Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.

  4. Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposal

    Directory of Open Access Journals (Sweden)

    Narong Wichapa

    2017-11-01

    Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.

  5. 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

  6. Genetics and ecology of colonization and mass rearing of Hawaiian fruit flies (Diptera: Tephritidae) for use in sterile insect control programs

    International Nuclear Information System (INIS)

    Saul, S.H.; McCombs, S.D.

    1995-01-01

    It is critical to maintain the genetic, physiological and behavioral competence of colonized populations of insect species, such as fruit flies, which are reared for release in sterile insect and other genetic control programs. Selective pressures associated with the mass rearing process affect this competence, but the underlying mechanisms of genetic change arc largely unknown. However, competence is often an operational goal achieved by manipulating environmental factors without possessing precise genetic knowledge of alleles and their marginal effects on the desired traits. One goal of this paper is to show that the precise genetic and statistical analysis of components that determine competence in a broad sense or fitness in the narrower ecological sense, is extremely difficult. We can gel contradictory results from the different methods for estimating genetic variation in tephritid populations. We observe low levels of allozyme variation, but high levels of recessive mutants in inbred populations. We propose that genetic variability may be maintained in colonized and mass reared laboratory populations by balanced lethal systems and that the introduction of fresh genetic material may reduce, not increase, fitness. We require rigorous and precise models of directional selection in the laboratory and selective forces in the natural environment to aid our understanding of dynamic changes in courtship and mating behavior under artificial conditions. We have chosen to examine the lek model as an example of an idea whose usefulness has yet to be determined by test ing and validation. The inclusion of lek forming ability in genetic models will be depen dent on rigorously establishing the validity of the lek model for each tephritid species

  7. 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

  8. 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.

  9. 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

  10. 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. PMID:26287376

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

    Directory of Open Access Journals (Sweden)

    Jill A Hollenbach

    Full Text Available 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.

  12. A binary genetic programing model for teleconnection identification between global sea surface temperature and local maximum monthly rainfall events

    Science.gov (United States)

    Danandeh Mehr, Ali; Nourani, Vahid; Hrnjica, Bahrudin; Molajou, Amir

    2017-12-01

    The effectiveness of genetic programming (GP) for solving regression problems in hydrology has been recognized in recent studies. However, its capability to solve classification problems has not been sufficiently explored so far. This study develops and applies a novel classification-forecasting model, namely Binary GP (BGP), for teleconnection studies between sea surface temperature (SST) variations and maximum monthly rainfall (MMR) events. The BGP integrates certain types of data pre-processing and post-processing methods with conventional GP engine to enhance its ability to solve both regression and classification problems simultaneously. The model was trained and tested using SST series of Black Sea, Mediterranean Sea, and Red Sea as potential predictors as well as classified MMR events at two locations in Iran as predictand. Skill of the model was measured in regard to different rainfall thresholds and SST lags and compared to that of the hybrid decision tree-association rule (DTAR) model available in the literature. The results indicated that the proposed model can identify potential teleconnection signals of surrounding seas beneficial to long-term forecasting of the occurrence of the classified MMR events.

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

    International Nuclear Information System (INIS)

    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. (paper)

  14. 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.

  15. 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.

  16. A Double-Deck Elevator Group Supervisory Control System with Destination Floor Guidance System Using Genetic Network Programming

    Science.gov (United States)

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

    The Elevator Group Supervisory Control Systems (EGSCS) are the control systems that systematically manage three or more elevators in order to efficiently transport the passengers in buildings. Double-deck elevators, where two elevators are connected with each other, serve passengers at two consecutive floors simultaneously. Double-deck Elevator systems (DDES) become more complex in their behavior than conventional single-deck elevator systems (SDES). Recently, Artificial Intelligence (AI) technology has been used in such complex systems. Genetic Network Programming (GNP), a graph-based evolutionary method, has been applied to EGSCS and its advantages are shown in some papers. GNP can obtain the strategy of a new hall call assignment to the optimal elevator when it performs crossover and mutation operations to judgment nodes and processing nodes. Meanwhile, Destination Floor Guidance System (DFGS) is installed in DDES, so that passengers can also input their destinations at elevator halls. In this paper, we have applied GNP to DDES and compared DFGS with normal systems. The waiting time and traveling time of DFGS are all improved because of getting more information from DFGS. The simulations showed the effectiveness of the double-deck elevators with DFGS in different building traffics.

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

    Directory of Open Access Journals (Sweden)

    Aleksander Mendyk

    2015-01-01

    Full Text Available 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.

  18. 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.

  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. Short-term streamflow forecasting with global climate change implications A comparative study between genetic programming and neural network models

    Science.gov (United States)

    Makkeasorn, A.; Chang, N. B.; Zhou, X.

    2008-05-01

    SummarySustainable water resources management is a critically important priority across the globe. While water scarcity limits the uses of water in many ways, floods may also result in property damages and the loss of life. To more efficiently use the limited amount of water under the changing world or to resourcefully provide adequate time for flood warning, the issues have led us to seek advanced techniques for improving streamflow forecasting on a short-term basis. This study emphasizes the inclusion of sea surface temperature (SST) in addition to the spatio-temporal rainfall distribution via the Next Generation Radar (NEXRAD), meteorological data via local weather stations, and historical stream data via USGS gage stations to collectively forecast discharges in a semi-arid watershed in south Texas. Two types of artificial intelligence models, including genetic programming (GP) and neural network (NN) models, were employed comparatively. Four numerical evaluators were used to evaluate the validity of a suite of forecasting models. Research findings indicate that GP-derived streamflow forecasting models were generally favored in the assessment in which both SST and meteorological data significantly improve the accuracy of forecasting. Among several scenarios, NEXRAD rainfall data were proven its most effectiveness for a 3-day forecast, and SST Gulf-to-Atlantic index shows larger impacts than the SST Gulf-to-Pacific index on the streamflow forecasts. The most forward looking GP-derived models can even perform a 30-day streamflow forecast ahead of time with an r-square of 0.84 and RMS error 5.4 in our study.

  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. Application of Genetic Programing to Develop a Modular Model for the Simulation of Stream Flow Time Series

    Science.gov (United States)

    Meshgi, A.; Babovic, V.; Chui, T. F. M.; Schmitter, P.

    2014-12-01

    Developing reliable methods to estimate stream flow has been a subject of interest due to its importance in planning, design and management of water resources within a basin. Machine learning tools such as Artificial Neural Network (ANN) and Genetic Programming (GP) have been widely applied for rainfall-runoff modeling as they require less computational time as compared to physically-based models. As GP is able to generate a function with understandable structure, it may offer advantages over other data driven techniques and therefore has been used in different studies to generate rainfall-runoff functions. However, to date, proposed formulations only contain rainfall and/or streamflow data and consequently are local and cannot be generalized and adopted in other catchments which have different physical characteristics. This study investigated the capability of GP in developing a physically interpretable model with understandable structure to simulate stream flow based on hydrological parameters (e.g. precipitation) and catchment conditions (e.g., initial groundwater table elevation and area of the catchment) by following a modular approach. The modular model resulted in two sub-models where the baseflow was first predicted and the direct runoff was then estimated for a semi-urban catchment in Singapore. The simulated results matched very well with observed data in both the training and the testing of data sets, giving NSEs of 0.97 and 0.96 respectively demonstrated the successful estimation of stream flow using the modular model derived in this study. The results of this study indicate that GP is an effective tool in developing a physically interpretable model with understandable structure to simulate stream flow that can be transferred to other catchments.

  3. 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

  4. Development of a genetically programed vanillin-sensing bacterium for high-throughput screening of lignin-degrading enzyme libraries.

    Science.gov (United States)

    Sana, Barindra; Chia, Kuan Hui Burton; Raghavan, Sarada S; Ramalingam, Balamurugan; Nagarajan, Niranjan; Seayad, Jayasree; Ghadessy, Farid J

    2017-01-01

    Lignin is a potential biorefinery feedstock for the production of value-added chemicals including vanillin. A huge amount of lignin is produced as a by-product of the paper industry, while cellulosic components of plant biomass are utilized for the production of paper pulp. In spite of vast potential, lignin remains the least exploited component of plant biomass due to its extremely complex and heterogenous structure. Several enzymes have been reported to have lignin-degrading properties and could be potentially used in lignin biorefining if their catalytic properties could be improved by enzyme engineering. The much needed improvement of lignin-degrading enzymes by high-throughput selection techniques such as directed evolution is currently limited, as robust methods for detecting the conversion of lignin to desired small molecules are not available. We identified a vanillin-inducible promoter by RNAseq analysis of Escherichia coli cells treated with a sublethal dose of vanillin and developed a genetically programmed vanillin-sensing cell by placing the 'very green fluorescent protein' gene under the control of this promoter. Fluorescence of the biosensing cell is enhanced significantly when grown in the presence of vanillin and is readily visualized by fluorescence microscopy. The use of fluorescence-activated cell sorting analysis further enhances the sensitivity, enabling dose-dependent detection of as low as 200 µM vanillin. The biosensor is highly specific to vanillin and no major response is elicited by the presence of lignin, lignin model compound, DMSO, vanillin analogues or non-specific toxic chemicals. We developed an engineered E. coli cell that can detect vanillin at a concentration as low as 200 µM. The vanillin-sensing cell did not show cross-reactivity towards lignin or major lignin degradation products including vanillin analogues. This engineered E. coli cell could potentially be used as a host cell for screening lignin-degrading enzymes that

  5. 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

  6. Developmental status of bioassays in genetic toxicology: a report of Phase II of the US Environmental Protection Agency Gene-Tox program

    Energy Technology Data Exchange (ETDEWEB)

    Brusick, D; Auletta, A

    1985-01-01

    The Gene-Tox Program was structured around two phases of genetic test data evaluation. The first phase consisted of 36 Work Group reports, each evaluating the results and performance of a specific bioassay. The second phase consisted of a plan to summarize the information provided by the Work Groups. The Gene-Tox Coordinating Committee was to be responsible for Phase II, and several subgroups were assigned specific goals in implementing this analysis. This report deals with Goal I which is to identify the developmental status of the individual bioassays reviewed by the Gene-Tox Work Groups in the first phase of the Program. 5 references, 6 tables.

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

    Directory of Open Access Journals (Sweden)

    Gordon Louisa G

    2010-09-01

    Full Text Available Abstract Background 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. Methods 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. Results 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. Conclusions 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

  8. Which Individuals To Choose To Update the Reference Population? Minimizing the Loss of Genetic Diversity in Animal Genomic Selection Programs

    Directory of Open Access Journals (Sweden)

    Sonia E. Eynard

    2018-01-01

    Full Text Available Genomic selection (GS is commonly used in livestock and increasingly in plant breeding. Relying on phenotypes and genotypes of a reference population, GS allows performance prediction for young individuals having only genotypes. This is expected to achieve fast high genetic gain but with a potential loss of genetic diversity. Existing methods to conserve genetic diversity depend mostly on the choice of the breeding individuals. In this study, we propose a modification of the reference population composition to mitigate diversity loss. Since the high cost of phenotyping is the limiting factor for GS, our findings are of major economic interest. This study aims to answer the following questions: how would decisions on the reference population affect the breeding population, and how to best select individuals to update the reference population and balance maximizing genetic gain and minimizing loss of genetic diversity? We investigated three updating strategies for the reference population: random, truncation, and optimal contribution (OC strategies. OC maximizes genetic merit for a fixed loss of genetic diversity. A French Montbéliarde dairy cattle population with 50K SNP chip genotypes and simulations over 10 generations were used to compare these different strategies using milk production as the trait of interest. Candidates were selected to update the reference population. Prediction bias and both genetic merit and diversity were measured. Changes in the reference population composition slightly affected the breeding population. Optimal contribution strategy appeared to be an acceptable compromise to maintain both genetic gain and diversity in the reference and the breeding populations.

  9. Which Individuals To Choose To Update the Reference Population? Minimizing the Loss of Genetic Diversity in Animal Genomic Selection Programs.

    Science.gov (United States)

    Eynard, Sonia E; Croiseau, Pascal; Laloë, Denis; Fritz, Sebastien; Calus, Mario P L; Restoux, Gwendal

    2018-01-04

    Genomic selection (GS) is commonly used in livestock and increasingly in plant breeding. Relying on phenotypes and genotypes of a reference population, GS allows performance prediction for young individuals having only genotypes. This is expected to achieve fast high genetic gain but with a potential loss of genetic diversity. Existing methods to conserve genetic diversity depend mostly on the choice of the breeding individuals. In this study, we propose a modification of the reference population composition to mitigate diversity loss. Since the high cost of phenotyping is the limiting factor for GS, our findings are of major economic interest. This study aims to answer the following questions: how would decisions on the reference population affect the breeding population, and how to best select individuals to update the reference population and balance maximizing genetic gain and minimizing loss of genetic diversity? We investigated three updating strategies for the reference population: random, truncation, and optimal contribution (OC) strategies. OC maximizes genetic merit for a fixed loss of genetic diversity. A French Montbéliarde dairy cattle population with 50K SNP chip genotypes and simulations over 10 generations were used to compare these different strategies using milk production as the trait of interest. Candidates were selected to update the reference population. Prediction bias and both genetic merit and diversity were measured. Changes in the reference population composition slightly affected the breeding population. Optimal contribution strategy appeared to be an acceptable compromise to maintain both genetic gain and diversity in the reference and the breeding populations. Copyright © 2018 Eynard et al.

  10. Facilitating Breast Cancer Genetic Counseling Through Information, Preparation and Referral: A Pilot Program Using the Cancer Information Service

    National Research Council Canada - National Science Library

    Miller, Suzanne

    2001-01-01

    Previous research has shown that women often lack knowledge regarding the kinds of information that are required to determine inherited risk as well as on the process and content of risk assessment/genetic testing...

  11. Facilitating Breast Cancer Genetic Couseling through Information, Preparation and Referral: A Pilot Program Using the Cancer Information Service

    National Research Council Canada - National Science Library

    Miller, Suzanne

    2000-01-01

    Previous research has shown that women often lack knowledge regarding the kinds of information that are required to determine inherited risk as well as on the process and content of risk assessment/genetic testing...

  12. Multimedia messages in genetics: design, development, and evaluation of a computer-based instructional resource for secondary school students in a Tay Sachs disease carrier screening program.

    Science.gov (United States)

    Gason, Alexandra A; Aitken, MaryAnne; Delatycki, Martin B; Sheffield, Edith; Metcalfe, Sylvia A

    2004-01-01

    Tay Sachs disease is a recessively inherited neurodegenerative disorder, for which carrier screening programs exist worldwide. Education for those offered a screening test is essential in facilitating informed decision-making. In Melbourne, Australia, we have designed, developed, and evaluated a computer-based instructional resource for use in the Tay Sachs disease carrier screening program for secondary school students attending Jewish schools. The resource entitled "Genetics in the Community: Tay Sachs disease" was designed on a platform of educational learning theory. The development of the resource included formative evaluation using qualitative data analysis supported by descriptive quantitative data. The final resource was evaluated within the screening program and compared with the standard oral presentation using a questionnaire. Knowledge outcomes were measured both before and after either of the educational formats. Data from the formative evaluation were used to refine the content and functionality of the final resource. The questionnaire evaluation of 302 students over two years showed the multimedia resource to be equally effective as an oral educational presentation in facilitating participants' knowledge construction. The resource offers a large number of potential benefits, which are not limited to the Tay Sachs disease carrier screening program setting, such as delivery of a consistent educational message, short delivery time, and minimum financial and resource commitment. This article outlines the value of considering educational theory and describes the process of multimedia development providing a framework that may be of value when designing genetics multimedia resources in general.

  13. Microchip capillary gel electrophoresis using programmed field strength gradients for the ultra-fast analysis of genetically modified organisms in soybeans.

    Science.gov (United States)

    Kim, Yun-Jeong; Chae, Joon-Seok; Chang, Jun Keun; Kang, Seong Ho

    2005-08-12

    We have developed a novel method for the ultra-fast analysis of genetically modified organisms (GMOs) in soybeans by microchip capillary gel electrophoresis (MCGE) using programmed field strength gradients (PFSG) in a conventional glass double-T microchip. Under the programmed electric field strength and 0.3% poly(ethylene oxide) sieving matrix, the GMO in soybeans was analyzed within only 11 s of the microchip. The MCGE-PFSG method was a program that changes the electric field strength during GMO analysis, and was also applied to the ultra-fast analysis of PCR products. Compared to MCGE using a conventional and constantly applied electric field, the MCGE-PFSG analysis generated faster results without the loss of resolving power and reproducibility for specific DNA fragments (100- and 250-bp DNA) of GM-soybeans. The MCGE-PFSG technique may prove to be a new tool in the GMO analysis due to its speed, simplicity, and high efficiency.

  14. 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.

  15. 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...

  16. High genetic diversity and demographic history of captive Siamese and Saltwater crocodiles suggest the first step toward the establishment of a breeding and reintroduction program in Thailand.

    Directory of Open Access Journals (Sweden)

    Sorravis Lapbenjakul

    Full Text Available The Siamese crocodile (Crocodylus siamensis and Saltwater crocodile (C. porosus are two of the most endangered animals in Thailand. Their numbers have been reduced severely by hunting and habitat fragmentation. A reintroduction plan involving captive-bred populations that are used commercially is important and necessary as a conservation strategy to aid in the recovery of wild populations. Here, the genetic diversity and population structure of 69 individual crocodiles, mostly members of captive populations, were analyzed using both mitochondrial D-loop DNA and microsatellite markers. The overall haplotype diversity was 0.924-0.971 and the mean expected heterozygosity across 22 microsatellite loci was 0.578-0.701 for the two species. This agreed with the star-like shaped topology of the haplotype network, which suggests a high level of genetic diversity. The mean ratio of the number of alleles to the allelic range (M ratio for the populations of both species was considerably lower than the threshold of 0.68, which was interpreted as indicative of a historical genetic bottleneck. Microsatellite markers provided evidence of introgression for three individual crocodiles, which suggest that hybridization might have occurred between C. siamensis and C. porosus. D-loop sequence analysis detected bi-directional hybridization between male and female individuals of the parent species. Therefore, identification of genetically non-hybrid and hybrid individuals is important for long-term conservation management. Relatedness values were low within the captive populations, which supported their genetic integrity and the viability of a breeding and reintroduction management plan. This work constitutes the first step in establishing an appropriate source population from a scientifically managed perspective for an in situ/ex situ conservation program and reintroduction of crocodile individuals to the wild in Thailand.

  17. 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.

  18. 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.

  19. 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.

  20. Which individuals to choose to update the reference population? Minimizing the loss of genetic diversity in animal genomic selection programs

    NARCIS (Netherlands)

    Eynard, Sonia E.; Croiseau, Pascal; Laloë, Denis; Fritz, Sebastien; Calus, Mario P.L.; Restoux, Gwendal

    2018-01-01

    Genomic selection (GS) is commonly used in livestock and increasingly in plant breeding. Relying on phenotypes and genotypes of a reference population, GS allows performance prediction for young individuals having only genotypes. This is expected to achieve fast high genetic gain but with a

  1. Genetic parameters for oocyte number and embryo production within a bovine ovum pick-up-in vitro production embryo-production program.

    Science.gov (United States)

    Merton, J S; Ask, B; Onkundi, D C; Mullaart, E; Colenbrander, B; Nielen, M

    2009-10-15

    Genetic factors influencing the outcome of bovine ovum pick-up-in vitro production (OPU-IVP) and its relation to female fertility were investigated. For the first time, genetic parameters were estimated for the number of cumulus-oocyte complexes (Ncoc), quality of cumulus-oocyte complexes (Qcoc), number and proportion of cleaved embryos at Day 4 (Ncleav(D4), Pcleav(D4)), and number and proportion of total and transferable embryos at Day 7 of culture (Nemb(D7), Pemb(D7) and NTemb(D7), PTemb(D7), respectively). Data were recorded by CRV (formally Holland Genetics) from the OPU-IVP program from January 1995 to March 2006. Data were collected from 1508 Holstein female donors, both cows and pregnant virgin heifers, with a total of 18,702 OPU sessions. Data were analyzed with repeated-measure sire models with permanent environment effect using ASREML (Holstein Friesian). Estimates of heritability were 0.25 for Ncoc, 0.09 for Qcoc, 0.19 for Ncleav(D4), 0.21 for Nemb(D7), 0.16 for NTemb(D7), 0.07 for Pcleav(D4), 0.12 for Pemb(D7), and 0.10 for PTemb(D7). Genetic correlation between Ncoc and Qcoc was close to zero, whereas genetic correlations between Ncoc and the number of embryos were positive and moderate to high for Nemb(D7) (0.47), NTemb(D7) (0.52), and Ncleav(D4) (0.85). Genetic correlations between Ncoc and percentages of embryos (Pcleav(D4), Pemb(D7), and PTemb(D7)) were all close to zero. Phenotypic correlations were in line with genetic correlations. Genetic and phenotypic correlations between Qcoc and all other traits were not significant except for the phenotypic correlations between Qcoc and number of embryos, which were negative and low to moderate for Nemb(D7) (-0.20), NTemb(D7) (-0.24), and Ncleav(D4) (-0.43). Results suggest that cumulus-oocyte complex (COC) quality, based on cumulus investment, is independent from the total number of COCs collected via OPU and that in general, a higher number of COCs will lead to a higher number of embryos produced. The

  2. The revised Bethesda guidelines: extent of utilization in a university hospital medical center with a cancer genetics program

    Directory of Open Access Journals (Sweden)

    Mukherjee Aparna

    2010-11-01

    Full Text Available Abstract Background In 1996, the National Cancer Institute hosted an international workshop to develop criteria to identify patients with colorectal cancer who should be offered microsatellite instability (MSI testing due to an increased risk for Hereditary Nonpolyposis Colorectal Cancer (HNPCC. These criteria were further modified in 2004 and became known as the revised Bethesda Guidelines. Our study aimed to retrospectively evaluate the percentage of patients diagnosed with HNPCC tumors in 2004 who met revised Bethesda criteria for MSI testing, who were referred for genetic counseling within our institution. Methods All HNPCC tumors diagnosed in 2004 were identified by accessing CoPath, an internal database. Both the Tumor Registry and patients' electronic medical records were accessed to collect all relevant family history information. The list of patients who met at least one of the revised Bethesda criteria, who were candidates for MSI testing, was then cross-referenced with the database of patients referred for genetic counseling within our institution. Results A total of 380 HNPCC-associated tumors were diagnosed at our institution during 2004 of which 41 (10.7% met at least one of the revised Bethesda criteria. Eight (19.5% of these patients were referred for cancer genetic counseling of which 2 (25% were seen by a genetics professional. Ultimately, only 4.9% of patients eligible for MSI testing in 2004 were seen for genetic counseling. Conclusion This retrospective study identified a number of barriers, both internal and external, which hindered the identification of individuals with HNPCC, thus limiting the ability to appropriately manage these high risk families.

  3. When public health and genetic privacy collide: positive and normative theories explaining how ACA's expansion of corporate wellness programs conflicts with GINA's privacy rules.

    Science.gov (United States)

    Bard, Jennifer S

    2011-01-01

    The Patient Protection and Affordable Care Act of 2010 (ACA) contains many provisions intended to increase access to and lower the cost of health care by adopting public health measures. One of these promotes the use of at-work wellness programs by both providing employers with grants to develop these programs and also increasing their ability to tie the price employees pay for health insurance for participating in these programs and meeting specific health goals. Yet despite ACA's specific alteration of three different statues which had in the past shielded employees from having to contribute to the cost of their health insurance based on their achieving employer-designated health markers, it chose to leave alone recently enacted rules implementing the Genetic Non-Discrimination Act (GINA), which prohibits employers from asking employees about their family health history in any context, including assessing their risk for setting wellness targets. This article reviews how both the changes made by ACA and the restrictions recently put place by GINA will affect the way employers are likely to structure Wellness Programs. It also considers how these changes reflect the competing social goals of both ACA, which seeks to expand access to the population by lowering costs, and GINA, which seeks to protect individuals from discrimination. It does so by analyzing both positive theories about how these new laws will function and normative theories explaining the likelihood of future friction between the interests of the population of the United States as a whole who are in need of increased and affordable access to health care, and of the individuals living in this country who risk discrimination, as science and medicine continue to make advances in linking genetic make-up to risk of future illness. © 2011 American Society of Law, Medicine & Ethics, Inc.

  4. HeurAA: accurate and fast detection of genetic variations with a novel heuristic amplicon aligner program for next generation sequencing.

    Directory of Open Access Journals (Sweden)

    Lőrinc S Pongor

    Full Text Available Next generation sequencing (NGS of PCR amplicons is a standard approach to detect genetic variations in personalized medicine such as cancer diagnostics. Computer programs used in the NGS community often miss insertions and deletions (indels that constitute a large part of known human mutations. We have developed HeurAA, an open source, heuristic amplicon aligner program. We tested the program on simulated datasets as well as experimental data from multiplex sequencing of 40 amplicons in 12 oncogenes collected on a 454 Genome Sequencer from lung cancer cell lines. We found that HeurAA can accurately detect all indels, and is more than an order of magnitude faster than previous programs. HeurAA can compare reads and reference sequences up to several thousand base pairs in length, and it can evaluate data from complex mixtures containing reads of different gene-segments from different samples. HeurAA is written in C and Perl for Linux operating systems, the code and the documentation are available for research applications at http://sourceforge.net/projects/heuraa/

  5. 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 breeding endeavours, are essential for modelling and predicting the economic impact of further genetic improvement. Materials and Methods The “South African Population” (plantation origin) breeding lines with the F1 generation (‘SSO’-series), F2 (‘A... trials SSO1 and SSO4, as representatives of the improvement. It was assumed that selective thinning of the ‘male families’ took place at 50%. (Male families are trees which contribute towards the pollen cloud. These families may be selectively thinned...

  6. 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.

  7. The Italian National External quality assessment program in molecular genetic testing: results of the VII round (2010-2011).

    Science.gov (United States)

    Censi, F; Tosto, F; Floridia, G; Marra, M; Salvatore, M; Baffico, A M; Grasso, M; Melis, M A; Pelo, E; Radice, P; Ravani, A; Rosatelli, C; Resta, N; Russo, S; Seia, M; Varesco, L; Falbo, V; Taruscio, D

    2013-01-01

    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.

  8. It's not too late for the harpy eagle (Harpia harpyja: high levels of genetic diversity and differentiation can fuel conservation programs.

    Directory of Open Access Journals (Sweden)

    Heather R L Lerner

    2009-10-01

    mitochondrial genetic diversity in combination with genetic differentiation among subgroups within regions and between regions highlight the importance of local population conservation in order to preserve maximal levels of genetic diversity in this species. Evidence of historically restricted female-mediated gene flow is an important consideration for captive-breeding programs.

  9. 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.

  10. Research on uranium resource models. Part IV. Logic: a computer graphics program to construct integrated logic circuits for genetic-geologic models. Progress report

    International Nuclear Information System (INIS)

    Scott, W.A.; Turner, R.M.; McCammon, R.B.

    1981-01-01

    Integrated logic circuits were described as a means of formally representing genetic-geologic models for estimating undiscovered uranium resources. The logic circuits are logical combinations of selected geologic characteristics judged to be associated with particular types of uranium deposits. Each combination takes on a value which corresponds to the combined presence, absence, or don't know states of the selected characteristic within a specified geographic cell. Within each cell, the output of the logic circuit is taken as a measure of the favorability of occurrence of an undiscovered deposit of the type being considered. In this way, geological, geochemical, and geophysical data are incorporated explicitly into potential uranium resource estimates. The present report describes how integrated logic circuits are constructed by use of a computer graphics program. A user's guide is also included

  11. Programming

    International Nuclear Information System (INIS)

    Jackson, M.A.

    1982-01-01

    The programmer's task is often taken to be the construction of algorithms, expressed in hierarchical structures of procedures: this view underlies the majority of traditional programming languages, such as Fortran. A different view is appropriate to a wide class of problem, perhaps including some problems in High Energy Physics. The programmer's task is regarded as having three main stages: first, an explicit model is constructed of the reality with which the program is concerned; second, this model is elaborated to produce the required program outputs; third, the resulting program is transformed to run efficiently in the execution environment. The first two stages deal in network structures of sequential processes; only the third is concerned with procedure hierarchies. (orig.)

  12. Programming

    OpenAIRE

    Jackson, M A

    1982-01-01

    The programmer's task is often taken to be the construction of algorithms, expressed in hierarchical structures of procedures: this view underlies the majority of traditional programming languages, such as Fortran. A different view is appropriate to a wide class of problem, perhaps including some problems in High Energy Physics. The programmer's task is regarded as having three main stages: first, an explicit model is constructed of the reality with which the program is concerned; second, thi...

  13. 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.

  14. 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.

  15. 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,...

  16. Increased natural reproduction and genetic diversity one generation after cessation of a steelhead trout (Oncorhynchus mykiss) conservation hatchery program.

    Science.gov (United States)

    Berejikian, Barry A; Van Doornik, Donald M

    2018-01-01

    Spatial and temporal fluctuations in productivity and abundance confound assessments of captive propagation programs aimed at recovery of Threatened and Endangered populations. We conducted a 17 year before-after-control-impact experiment to determine the effects of a captive rearing program for anadromous steelhead trout (Oncorhynchus mykiss) on a key indicator of natural spawner abundance (naturally produced nests or 'redds'). The supplemented population exhibited a significant (2.6-fold) increase in redd abundance in the generation following supplementation. Four non-supplemented (control) populations monitored over the same 17 year period exhibited stable or decreasing trends in redd abundance. Expected heterozygosity in the supplemented population increased significantly. Allelic richness increased, but to a lesser (non-significant) degree. Estimates of the effective number of breeders increased from a harmonic mean of 24.4 in the generation before supplementation to 38.9 after supplementation. Several non-conventional aspects of the captive rearing program may have contributed to the positive response in the natural population.

  17. Increased natural reproduction and genetic diversity one generation after cessation of a steelhead trout (Oncorhynchus mykiss conservation hatchery program.

    Directory of Open Access Journals (Sweden)

    Barry A Berejikian

    Full Text Available Spatial and temporal fluctuations in productivity and abundance confound assessments of captive propagation programs aimed at recovery of Threatened and Endangered populations. We conducted a 17 year before-after-control-impact experiment to determine the effects of a captive rearing program for anadromous steelhead trout (Oncorhynchus mykiss on a key indicator of natural spawner abundance (naturally produced nests or 'redds'. The supplemented population exhibited a significant (2.6-fold increase in redd abundance in the generation following supplementation. Four non-supplemented (control populations monitored over the same 17 year period exhibited stable or decreasing trends in redd abundance. Expected heterozygosity in the supplemented population increased significantly. Allelic richness increased, but to a lesser (non-significant degree. Estimates of the effective number of breeders increased from a harmonic mean of 24.4 in the generation before supplementation to 38.9 after supplementation. Several non-conventional aspects of the captive rearing program may have contributed to the positive response in the natural population.

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

    Science.gov (United States)

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

    2012-10-15

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

  19. 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.

  20. The Saudi Human Genome Program: An oasis in the desert of Arab medicine is providing clues to genetic disease.

    Science.gov (United States)

    Project Team, Saudi Genome

    2015-01-01

    Oil wells, endless deserts, stifling heat, masses of pilgrims, and wealthy-looking urban areas still dominate the widespread mental image of Saudi Arabia. Currently, this image is being extended to include a recent endeavor that is reserving a global share in the limelight as one of the top ten genomics projects currently underway: the Saudi Human Genome Program (SHGP). With sound funding, dedicated resources, and national determination, the SHGP targets the sequencing of 100,000 human genomes over the next five years to conduct world-class genomics-based biomedical research in the Saudi population. Why this project was conceived and thought to be feasible, what is the ultimate target, and how it operates are the questions we answer in this article.

  1. 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. © 2010 Blackwell Publishing Ltd.

  2. Characterization of the Genetic Program Linked to the Development of Atrial Fibrillation in CREM-IbΔC-X Mice.

    Science.gov (United States)

    Seidl, Matthias D; Stein, Juliane; Hamer, Sabine; Pluteanu, Florentina; Scholz, Beatrix; Wardelmann, Eva; Huge, Andreas; Witten, Anika; Stoll, Monika; Hammer, Elke; Völker, Uwe; Müller, Frank U

    2017-08-01

    Reduced expression of genes regulated by the transcription factors CREB/CREM (cAMP response element-binding protein/modulator) is linked to atrial fibrillation (AF) susceptibility in patients. Cardiomyocyte-directed expression of the inhibitory CREM isoform CREM-IbΔC-X in transgenic mice (TG) leads to spontaneous-onset AF preceded by atrial dilatation and conduction abnormalities. Here, we characterized the altered gene program linked to atrial remodeling and development of AF in CREM-TG mice. Atria of young (TGy, before AF onset) and old (TGo, after AF onset) TG mice were investigated by mRNA microarray profiling in comparison with age-matched wild-type controls (WTy/WTo). Proteomic alterations were profiled in young mice (8 TGy versus 8 WTy). Annotation of differentially expressed genes revealed distinct differences in biological functions and pathways before and after onset of AF. Alterations in metabolic pathways, some linked to altered peroxisome proliferator-activated receptor signaling, muscle contraction, and ion transport were already present in TGy. Electron microscopy revealed significant loss of sarcomeres and mitochondria and increased collagen and glycogen deposition in TG mice. Alterations in electrophysiological pathways became prominent in TGo, concomitant with altered gene expression of K + -channel subunits and ion channel modulators, relevant in human AF. The most prominent alterations of the gene program linked to CREM-induced atrial remodeling were identified in the expression of genes related to structure, metabolism, contractility, and electric activity regulation, suggesting that CREM transgenic mice are a valuable experimental model for human AF pathophysiology. © 2017 American Heart Association, Inc.

  3. Studying Air Quality Dynamics using A Linear Genetic Programming Approach over Remotely Sensed Atmospheric Parameters: case study (Cairo, Egypt)

    Science.gov (United States)

    El-Askary, H. M.; Sheta, W.; Prasad, A. K.; Ali, H.; Abdel rahman, M.; El-Desouki, A.; Kafatos, M.

    2011-12-01

    Water Vapor Low Mean, Atmospheric Water Vapor Mean, Mass Concentration Land Mean, Optical Depth Ratio Small Land and Ocean Mean, Small Mode Optical Depth Land and Ocean Mean, Cloud Top Pressure Day Mean, Cloud Top Pressure Mean, Cloud Top Temperature Mean. The suggested linear Genetic approach detected hidden anomalies and relationships that cannot be observed from the conventional statistical methods. A well-established model as an important contribution to show the relationships between particle size and the physical and chemical aerosols properties has been designed. Such coupling will provide insight into the micro physics of the phenomenon. The proposed research will reveal previously uncharacterized yet fundamental relations and dependencies among aerosols, cloud and meteorological related parameters. Moreover, it would aid in filling gaps of missing satellite parameters using other available ones.

  4. Genetics in Relation to Biology.

    Science.gov (United States)

    Stewart, J. Bird

    1987-01-01

    Claims that most instruction dealing with genetics is limited to sex education and personal hygiene. Suggests that the biology curriculum should begin to deal with other issues related to genetics, including genetic normality, prenatal diagnoses, race, and intelligence. Predicts these topics will begin to appear in British examination programs.…

  5. 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.

  6. 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

  7. 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. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

  8. A genetic study of dehydroepiandrosterone sulfate measured before and after a 20-week endurance exercise training program: the HERITAGE Family Study.

    Science.gov (United States)

    An, P; Rice, T; Gagnon, J; Hong, Y; Leon, A S; Skinner, J S; Wilmore, J H; Bouchard, C; Rao, D C

    2000-03-01

    Familial aggregation and possible major gene effects were evaluated for the baseline serum dehydroepiandrosterone sulfate (DHEAS) level and the change in DHEAS in response to a 20-week exercise training program in a sample of 481 individuals from 99 Caucasian families who were sedentary at baseline and who participated in the HERITAGE Family Study. Baseline DHEAS levels were not normally distributed, and were therefore logarithmically transformed and adjusted for the effects of age and sex prior to genetic analysis. The DHEAS response to training was computed as the simple difference, post-training minus baseline, and was adjusted for the baseline DHEAS level, age, and sex. Maximal (genetic and familial environmental) heritabilities (using a familial correlation model) reached 58% and 30% for the baseline and the response to training, respectively. Our estimate for the baseline is generally in agreement with previous reports, suggesting that the magnitude of the familial effect underlying this phenotype in these sedentary families is similar to that in the general population. However, segregation analysis showed no evidence for a multifactorial familial component in data for either the baseline or the response to training. Rather, a major additive gene controlling the baseline was found. For the response to training in the complete sample, transmission of the major effect from parents to offspring was ambiguous, but in a subset of 56 "responsive" families (with at least 1 family member whose response to training was greater than 1 standard deviation) this major effect was Mendelian in nature. The putative major genes accounted for 50% and 33% of the variance for the baseline and the response to training, respectively. The novel finding in this study is that the baseline DHEAS level and the change in DHEAS in response to training may be influenced by major gene effects.

  9. Genetic Mapping

    Science.gov (United States)

    ... greatly advanced genetics research. The improved quality of genetic data has reduced the time required to identify a ... cases, a matter of months or even weeks. Genetic mapping data generated by the HGP's laboratories is freely accessible ...

  10. The use of genetic programming in the analysis of quantitative gene expression profiles for identification of nodal status in bladder cancer

    International Nuclear Information System (INIS)

    Mitra, Anirban P; Almal, Arpit A; George, Ben; Fry, David W; Lenehan, Peter F; Pagliarulo, Vincenzo; Cote, Richard J; Datar, Ram H; Worzel, William P

    2006-01-01

    Previous studies on bladder cancer have shown nodal involvement to be an independent indicator of prognosis and survival. This study aimed at developing an objective method for detection of nodal metastasis from molecular profiles of primary urothelial carcinoma tissues. The study included primary bladder tumor tissues from 60 patients across different stages and 5 control tissues of normal urothelium. The entire cohort was divided into training and validation sets comprised of node positive and node negative subjects. Quantitative expression profiling was performed for a panel of 70 genes using standardized competitive RT-PCR and the expression values of the training set samples were run through an iterative machine learning process called genetic programming that employed an N-fold cross validation technique to generate classifier rules of limited complexity. These were then used in a voting algorithm to classify the validation set samples into those associated with or without nodal metastasis. The generated classifier rules using 70 genes demonstrated 81% accuracy on the validation set when compared to the pathological nodal status. The rules showed a strong predilection for ICAM1, MAP2K6 and KDR resulting in gene expression motifs that cumulatively suggested a pattern ICAM1>MAP2K6>KDR for node positive cases. Additionally, the motifs showed CDK8 to be lower relative to ICAM1, and ANXA5 to be relatively high by itself in node positive tumors. Rules generated using only ICAM1, MAP2K6 and KDR were comparably robust, with a single representative rule producing an accuracy of 90% when used by itself on the validation set, suggesting a crucial role for these genes in nodal metastasis. Our study demonstrates the use of standardized quantitative gene expression values from primary bladder tumor tissues as inputs in a genetic programming system to generate classifier rules for determining the nodal status. Our method also suggests the involvement of ICAM1, MAP2K6, KDR

  11. Trends in genome-wide and region-specific genetic diversity in the Dutch-Flemish Holstein-Friesian breeding program from 1986 to 2015.

    Science.gov (United States)

    Doekes, Harmen P; Veerkamp, Roel F; Bijma, Piter; Hiemstra, Sipke J; Windig, Jack J

    2018-04-11

    In recent decades, Holstein-Friesian (HF) selection schemes have undergone profound changes, including the introduction of optimal contribution selection (OCS; around 2000), a major shift in breeding goal composition (around 2000) and the implementation of genomic selection (GS; around 2010). These changes are expected to have influenced genetic diversity trends. Our aim was to evaluate genome-wide and region-specific diversity in HF artificial insemination (AI) bulls in the Dutch-Flemish breeding program from 1986 to 2015. Pedigree and genotype data (~ 75.5 k) of 6280 AI-bulls were used to estimate rates of genome-wide inbreeding and kinship and corresponding effective population sizes. Region-specific inbreeding trends were evaluated using regions of homozygosity (ROH). Changes in observed allele frequencies were compared to those expected under pure drift to identify putative regions under selection. We also investigated the direction of changes in allele frequency over time. Effective population size estimates for the 1986-2015 period ranged from 69 to 102. Two major breakpoints were observed in genome-wide inbreeding and kinship trends. Around 2000, inbreeding and kinship levels temporarily dropped. From 2010 onwards, they steeply increased, with pedigree-based, ROH-based and marker-based inbreeding rates as high as 1.8, 2.1 and 2.8% per generation, respectively. Accumulation of inbreeding varied substantially across the genome. A considerable fraction of markers showed changes in allele frequency that were greater than expected under pure drift. Putative selected regions harboured many quantitative trait loci (QTL) associated to a wide range of traits. In consecutive 5-year periods, allele frequencies changed more often in the same direction than in opposite directions, except when comparing the 1996-2000 and 2001-2005 periods. Genome-wide and region-specific diversity trends reflect major changes in the Dutch-Flemish HF breeding program. Introduction of

  12. Genetic privacy.

    Science.gov (United States)

    Sankar, Pamela

    2003-01-01

    During the past 10 years, the number of genetic tests performed more than tripled, and public concern about genetic privacy emerged. The majority of states and the U.S. government have passed regulations protecting genetic information. However, research has shown that concerns about genetic privacy are disproportionate to known instances of information misuse. Beliefs in genetic determinacy explain some of the heightened concern about genetic privacy. Discussion of the debate over genetic testing within families illustrates the most recent response to genetic privacy concerns.

  13. Operation planning for a pondage power station chain by means of linear programming and genetic optimisation; Einsatzplanung fuer eine Flusskraftwerkskette im Schwellbetrieb mittels LP und genetischer Optimierung

    Energy Technology Data Exchange (ETDEWEB)

    Mueller, H.; Huelsemann, M.

    1997-12-31

    This paper presents a system package which serves as a simulation and optimisation tool for daily operation planning for a hydroelectric cascade. The purpose of the planning is to maximise (the differentially weighted) production of electrical energy given a certain set of specifications and secondary conditions. Optimal operation management is achieved using a two-stage approach: first pre-optimisation by means of linear programming, followed by detail optimisation using a Genetic Algorithm based on a non-linear, dynamic model of the power station and reservoir chain. [Deutsch] Im Beitrag wird ein Systempaket als Simulations- und Optimierungswerkzeug zur taeglichen Betriebsplanung einer Wasserkraftwerkskaskade vorgestellt. Ziel der Wasserbewirtschaftung ist es, unter den gegebenen Vorgaben und Randbedingungen die (bewertete) Erzeugung elektrischer Energie zu maximieren. Das optimale Fahrplanmanagement wird durch einen zweistufigen Loesungsansatz realisiert: Mit einer Vor-Optimierung mittels Linearer Programmierung (LP), gefolgt von einer detaillierten Optimierung mit einem Genetischen Algorithmus, der auf ein nichtlineares, dynamisches Simulationsmodell fuer die Kette aus Kraftwerken und Stauraeumen zugreift. (orig./RHM)

  14. Mathematical Modelling of a Friction Stir Welding Process to Predict the Joint Strength of Two Dissimilar Aluminium Alloys Using Experimental Data and Genetic Programming

    Directory of Open Access Journals (Sweden)

    Mohammed Yunus

    2018-01-01

    Full Text Available Friction stir welding (FSW is the most popular and efficient method of solid-state joining for similar as well as dissimilar metals and alloys. It is mostly used in applications for aerospace, rail, automotive, and marine industries. Many researchers are currently working with different perspectives on this FSW process for various combinations of materials. The general input process parameters are the thickness of the plate, axial load, rotational speed, welding speed, and tilt angle. The output parameters are joint hardness, % of elongation, and impact and yield strengths. Genetic programming (GP is a relatively new method of evolutionary computing with the principal advantage of this approach being to evaluate efficacious predictive mathematical models or equations without any prior assumption regarding the possible form of the functional relationship. This paper both defines and illustrates how GP can be applied to the FSW process to derive precise relationships between the output and input parameters in order to obtain a generalized prediction model. A GP model will assist engineers in quantifying the performance of FSW, and the results from this study can then be utilized to estimate future requirements based on the historical data to provide a robust solution. The obtained results from the GP models showed good agreement with experimental and target data at an average prediction error of 0.72%.

  15. Comparative genomics of phylogenetically diverse unicellular eukaryotes provide new insights into the genetic basis for the evolution of the programmed cell death machinery.

    Science.gov (United States)

    Nedelcu, Aurora M

    2009-03-01

    Programmed cell death (PCD) represents a significant component of normal growth and development in multicellular organisms. Recently, PCD-like processes have been reported in single-celled eukaryotes, implying that some components of the PCD machinery existed early in eukaryotic evolution. This study provides a comparative analysis of PCD-related sequences across more than 50 unicellular genera from four eukaryotic supergroups: Unikonts, Excavata, Chromalveolata, and Plantae. A complex set of PCD-related sequences that correspond to domains or proteins associated with all main functional classes--from ligands and receptors to executors of PCD--was found in many unicellular lineages. Several PCD domains and proteins previously thought to be restricted to animals or land plants are also present in unicellular species. Noteworthy, the yeast, Saccharomyces cerevisiae--used as an experimental model system for PCD research, has a rather reduced set of PCD-related sequences relative to other unicellular species. The phylogenetic distribution of the PCD-related sequences identified in unicellular lineages suggests that the genetic basis for the evolution of the complex PCD machinery present in extant multicellular lineages has been established early in the evolution of eukaryotes. The shaping of the PCD machinery in multicellular lineages involved the duplication, co-option, recruitment, and shuffling of domains already present in their unicellular ancestors.

  16. 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 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.

  17. 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. Copyright © 2010 Elsevier Inc. All rights reserved.

  18. Genetic conservation and paddlefish propagation

    Science.gov (United States)

    Sloss, Brian L.; Klumb, Robert A.; Heist, Edward J.

    2009-01-01

    The conservation of genetic diversity of our natural resources is overwhelmingly one of the central foci of 21st century management practices. Three recommendations related to the conservation of paddlefish Polyodon spathula genetic diversity are to (1) identify genetic diversity at both nuclear and mitochondrial DNA loci using a suggested list of 20 sampling locations, (2) use genetic diversity estimates to develop genetic management units, and (3) identify broodstock sources to minimize effects of supplemental stocking on the genetic integrity of native paddlefish populations. We review previous genetic work on paddlefish and described key principles and concepts associated with maintaining genetic diversity within and among paddlefish populations and also present a genetic case study of current paddlefish propagation at the U.S. Fish and Wildlife Service Gavins Point National Fish Hatchery. This study confirmed that three potential sources of broodfish were genetically indistinguishable at the loci examined, allowing the management agencies cooperating on this program flexibility in sampling gametes. This study also showed significant bias in the hatchery occurred in terms of male reproductive contribution, which resulted in a shift in the genetic diversity of progeny compared to the broodfish. This shift was shown to result from differential male contributions, partially attributed to the mode of egg fertilization. Genetic insights enable implementation of a paddlefish propagation program within an adaptive management strategy that conserves inherent genetic diversity while achieving demographic goals.

  19. Genetic rescue and the increase of litter size in the recovery breeding program of the common hamster (Cricetus cricetus) in the Netherlands. Relatedness, inbreeding and heritability of litter size in a breeding program of an endangered rodent

    NARCIS (Netherlands)

    Haye, la M.J.J.; Koelewijn, H.P.; Siepel, H.; Verwimp, N.; Windig, J.J.

    2012-01-01

    Reduced genetic variation is a severe threat for long-term persistence of endangered animals. Immigration or translocation of new individuals may result in genetic rescue and increase the population viability of the endangered population or species. Unfortunately, studying genetic rescue in wild

  20. 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...

  1. 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

  2. Genetic modification and genetic determinism

    Science.gov (United States)

    Resnik, David B; Vorhaus, Daniel B

    2006-01-01

    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. PMID:16800884

  3. Education and certification of genetic counselors.

    Science.gov (United States)

    Katsichti, L; Hadzipetros-Bardanis, M; Bartsocas, C S

    1999-01-01

    Genetic counseling is defined by the American Society of Human Genetics as a communication process which deals with the human problems associated with the occurrence, or risk of occurrence, of a genetic disorder in a family. The first graduate program (Master's degree) in genetic counseling started in 1969 at Sarah Lawrence College, NY, USA, while in 1979 the National Society of Genetic Counseling (NSGC) was established. Today, there are 29 programs in U.S.A. offering a Master's degree in Genetic Counseling, five programs in Canada, one in Mexico, one in England and one in S. Africa. Most of these graduate programs offer two year training, consisting of graduate courses, seminars, research and practical training. Emphasis is given in human physiology, biochemistry, clinical genetics, cytogenetics, molecular and biochemical genetics, population genetics and statistics, prenatal diagnosis, teratology and genetic counseling in relation to psychosocial and ethical issues. Certification for eligible candidates is available through the American Board of Medical Genetics (ABMG). Requirements for certification include a master's degree in human genetics, training at sites accredited by the ABMG, documentation of genetic counseling experience, evidence of continuing education and successful completion of a comprehensive ABMG certification examination. As professionals, genetic counselors should maintain expertise, should insure mechanisms for professional advancement and should always maintain the ability to approach their patients.

  4. From Genetics to Genetic Algorithms

    Indian Academy of Sciences (India)

    Genetic algorithms (GAs) are computational optimisation schemes with an ... The algorithms solve optimisation problems ..... Genetic Algorithms in Search, Optimisation and Machine. Learning, Addison-Wesley Publishing Company, Inc. 1989.

  5. From Genetics to Genetic Algorithms

    Indian Academy of Sciences (India)

    artificial genetic system) string feature or ... called the genotype whereas it is called a structure in artificial genetic ... assigned a fitness value based on the cost function. Better ..... way it has produced complex, intelligent living organisms capable of ...

  6. Acceptance of Referral for Cancer-Risk Counseling in Population of Women Undergoing Breast Biopsy: Variables Predicting Followup at a Cancer Genetics Program

    National Research Council Canada - National Science Library

    O'Neill, Suzanne

    2001-01-01

    ..., Shattuck-Eidens, Frank, and BRCAPRO models. Questionnaires assessing psychological status, and knowledge and attitudes about breast cancer, cancer risk counseling, and genetic testing were used to identify predictors of referral uptake...

  7. About Genetic Counselors

    Science.gov (United States)

    ... clinical care in many areas of medicine. Assisted Reproductive Technology/Infertility Genetics Cancer Genetics Cardiovascular Genetics Cystic Fibrosis Genetics Fetal Intervention and Therapy Genetics Hematology Genetics Metabolic Genetics ...

  8. 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

  9. Knowledge of Genetics and Attitudes toward Genetic Testing among College Students in Saudi Arabia.

    Science.gov (United States)

    Olwi, Duaa; Merdad, Leena; Ramadan, Eman

    2016-01-01

    Genetic testing has been gradually permeating the practice of medicine. Health-care providers may be confronted with new genetic approaches that require genetically informed decisions which will be influenced by patients' knowledge of genetics and their attitudes toward genetic testing. This study assesses the knowledge of genetics and attitudes toward genetic testing among college students. A cross-sectional study was conducted using a multistage stratified sample of 920 senior college students enrolled at King Abdulaziz University, Saudi Arabia. Information regarding knowledge of genetics, attitudes toward genetic testing, and sociodemographic data were collected using a self-administered questionnaire. In general, students had a good knowledge of genetics but lacked some fundamentals of genetics. The majority of students showed positive attitudes toward genetic testing, but some students showed negative attitudes toward certain aspects of genetic testing such as resorting to abortion in the case of an untreatable major genetic defect in an unborn fetus. The main significant predictors of knowledge were faculty, gender, academic year, and some prior awareness of 'genetic testing'. The main significant predictors of attitudes were gender, academic year, grade point average, and some prior awareness of 'genetic testing'. The knowledge of genetics among college students was higher than has been reported in other studies, and the attitudes toward genetic testing were fairly positive. Genetics educational programs that target youths may improve knowledge of genetics and create a public perception that further supports genetic testing. © 2016 S. Karger AG, Basel.

  10. Individual genetic variations related to satiety and appetite control increase risk of obesity in preschool-age children in the STRONG kids program.

    Science.gov (United States)

    Wang, Yingying; Wang, Anthony; Donovan, Sharon M; Teran-Garcia, Margarita

    2013-01-01

    The burden of the childhood obesity epidemic is well recognized; nevertheless, the genetic markers and gene-environment interactions associated with the development of common obesity are still unknown. In this study, candidate genes associated to satiety and appetite control pathways with obesity-related traits were tested in Caucasian preschoolers from the STRONG Kids project. Eight genetic variants in genes related to obesity (BDNF, LEPR, FTO, PCSK1, POMC, TUB, LEP, and MC4R) were genotyped in 128 children from the STRONG Kids project (mean age 39.7 months). Data were analyzed for individual associations and to test for genetic predisposition scores (GPSs) with body mass index (BMI) and anthropometric traits (Z-scores, e.g. height-for-age Z-score, HAZ). Covariates included age, sex, and breastfeeding (BF) duration. Obesity and overweight prevalence was 6.3 and 19.5%, respectively, according to age- and sex-specific BMI percentiles. Individual genetic associations of MC4R and LEPR markers with HAZ were strengthened when BF duration was included as a covariate. Our GPSs show that, as the number of risk alleles increased, the risk of higher BMI and HAZ also increased. Overall, the GPSs assembled were able to explain 2-3% of the variability in BMI and HAZ phenotypes. Genetic associations with common obesity-related phenotypes were found in the STRONG Kids project. GPSs assembled for specific candidate genes were associated with BMI and HAZ phenotypes. © 2013 S. Karger AG, Basel.

  11. Adults' perceptions of genetic counseling and genetic testing.

    Science.gov (United States)

    Houfek, Julia Fisco; Soltis-Vaughan, Brigette S; Atwood, Jan R; Reiser, Gwendolyn M; Schaefer, G Bradley

    2015-02-01

    This study described the perceptions of genetic counseling and testing of adults (N = 116) attending a genetic education program. Understanding perceptions of genetic counseling, including the importance of counseling topics, will contribute to patient-focused care as clinical genetic applications for common, complex disorders evolve. Participants completed a survey addressing: the importance of genetic counseling topics, benefits and negative effects of genetic testing, and sharing test results. Topics addressing practical information about genetic conditions were rated most important; topics involving conceptual genetic/genomic principles were rated least important. The most frequently identified benefit and negative effect of testing were prevention/early detection/treatment and psychological distress. Participants perceived that they were more likely to share test results with first-degree than other relatives. Findings suggest providing patients with practical information about genetic testing and genetic contributions to disease, while also determining whether their self-care abilities would be enhanced by teaching genetic/genomic principles. Copyright © 2014 Elsevier Inc. All rights reserved.

  12. 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.

  13. 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)

  14. Genetic Romanticism

    DEFF Research Database (Denmark)

    Tupasela, Aaro

    2016-01-01

    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...

  15. 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.

  16. Genomic selection strategies in breeding programs: Strong positive interaction between application of genotypic information and intensive use of young bulls on genetic gain

    DEFF Research Database (Denmark)

    Buch, Line Hjortø; Sørensen, Morten Kargo; Berg, Peer

    2012-01-01

    We tested the following hypotheses: (i) breeding schemes with genomic selection are superior to breeding schemes without genomic selection regarding annual genetic gain of the aggregate genotype (ΔGAG), annual genetic gain of the functional traits and rate of inbreeding per generation (ΔF), (ii......) a positive interaction exists between the use of genotypic information and a short generation interval on ΔGAG and (iii) the inclusion of an indicator trait in the selection index will only result in a negligible increase in ΔGAG if genotypic information about the breeding goal trait is known. We examined......, greater contributions of the functional trait to ΔGAG and lower ΔF than the two breeding schemes without genomic selection. Thus, the use of genotypic information may lead to more sustainable breeding schemes. In addition, a short generation interval increases the effect of using genotypic information...

  17. National Hansen's Disease (Leprosy) Program

    Science.gov (United States)

    ... Caring and Curing Since 1894 National Hansen's Disease (Leprosy) Program Caring and Curing Since 1894 A genetic ... Louisiana New York Texas The National Hansen's Disease (Leprosy) Program The National Hansen's Disease Program is the ...

  18. 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.

  19. 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

  20. Evolutionary genetics

    National Research Council Canada - National Science Library

    Maynard Smith, John

    1989-01-01

    .... It differs from other textbooks of population genetics in applying the basic theory to topics, such as social behaviour, molecular evolution, reiterated DNA, and sex, which are the main subjects...

  1. Genetic Discrimination

    Science.gov (United States)

    ... Care Genomic Medicine Working Group New Horizons and Research Patient Management Policy and Ethics Issues Quick Links for Patient Care Education All About the Human Genome Project Fact Sheets Genetic Education Resources for ...

  2. Arthropod Genetics.

    Science.gov (United States)

    Zumwalde, Sharon

    2000-01-01

    Introduces an activity on arthropod genetics that involves phenotype and genotype identification of the creature and the construction process. Includes a list of required materials and directions to build a model arthropod. (YDS)

  3. Desktop Genetics

    OpenAIRE

    Hough, Soren H; Ajetunmobi, Ayokunmi; Brody, Leigh; Humphryes-Kirilov, Neil; Perello, Edward

    2016-01-01

    Desktop Genetics is a bioinformatics company building a gene-editing platform for personalized medicine. The company works with scientists around the world to design and execute state-of-the-art clustered regularly interspaced short palindromic repeats (CRISPR) experiments. Desktop Genetics feeds the lessons learned about experimental intent, single-guide RNA design and data from international genomics projects into a novel CRISPR artificial intelligence system. We believe that machine learni...

  4. Mammalian genetics and biostatistics

    International Nuclear Information System (INIS)

    Grahn, D.; Carnes, B.A.; Farrington, B.H.; Lee, C.H.

    1985-01-01

    This program seeks to assess genetic hazards of single, weekly, and continuous doses of 60 Co gamma rays and single and weekly doses of fission neutrons to provide a basis for estimating relative biological effectiveness (RBE) of fission neutrons, to develop detailed dose-response data at low doses as a basis for studying relationships between linear energy transfer (LET) and the sensitivity of various cell stages, and to develop improved statistical approaches to analytical issues in chemical and radiation toxicology. 3 refs

  5. La genética comunitaria en los programas de diagnóstico prenatal Community genetics in prenatal diagnosis programs

    Directory of Open Access Journals (Sweden)

    Yanet Hernández Triguero

    2013-06-01

    Full Text Available Introducción: la creación de centros para el desarrollo de la Genética comunitaria, en todos los municipios del país, ha hecho posible el incremento de la cobertura de atención de los servicios de genética médica en la atención primaria. Objetivo: evaluar los resultados obtenidos en el funcionamiento prenatal del Programa Cubano de Diagnóstico, Manejo y Prevención de Enfermedades Genéticas y Defectos Congénitos. Material y métodos: se realizó un estudio descriptivo, retrospectivo y de corte longitudinal que incluyó el total de gestantes captadas desde el 1ro. de enero de 2007 hasta el 31 de diciembre de 2011, en el municipio La Palma. Resultados: de 2016 gestantes, el 51.7% fueron clasificadas como riesgo genético incrementado. En este grupo, la adolescencia (29.4% y la edad materna avanzada (15.8% fueron los principales factores de riesgo genético encontrados. Se realizaron 1720 exámenes de ecografía, entre las 11 y 13.6 semanas, examen que logra una cobertura del 94.8%. Se detectaron 47 portadoras de hemoglobina AS o AC. Se determinó el valor de la alfafetoproteína en suero materno, el 7.1 % mostró cifras elevadas y la amenaza de aborto constituyó la primera causa de esta alteración. Se diagnosticaron prenatalmente, por ecografía del segundo trimestre, 20 gestantes que presentaron fetos con defectos congénitos, lográndose una cobertura de 99,5%. Conclusiones: el enfoque comunitario de la genética y el trabajo coordinado con la atención primaria de salud permiten confeccionar estrategias dirigidas al control y disminución de los riesgos de defectos congénitos y enfermedades comunes en la población.Introduction: the creation of centers to the development of community genetics all over the municipalities of the country has made possible an increased coverage of medical genetics services in Primary Health Care. Objective: to assess the results obtained in the establishment of Cuban Prenatal Diagnosis, Management and

  6. J. Genet. classic 101

    Indian Academy of Sciences (India)

    Journal of Genetics, Vol. 85, No. 2, August 2006. 101. Page 2. J. Genet. classic. 102. Journal of Genetics, Vol. 85, No. 2, August 2006. Page 3. J. Genet. classic. Journal of Genetics, Vol. 85, No. 2, August 2006. 103. Page 4. J. Genet. classic. 104. Journal of Genetics, Vol. 85, No. 2, August 2006. Page 5. J. Genet. classic.

  7. J. Genet. classic 37

    Indian Academy of Sciences (India)

    Unknown

    Journal of Genetics, Vol. 84, No. 1, April 2005. 37. Page 2. J. Genet. classic. Journal of Genetics, Vol. 84, No. 1, April 2005. 38. Page 3. J. Genet. classic. Journal of Genetics, Vol. 84, No. 1, April 2005. 39. Page 4. J. Genet. classic. Journal of Genetics, Vol. 84, No. 1, April 2005. 40. Page 5. J. Genet. classic. Journal of ...

  8. Assessment of the genetic diversity and pattern of relationship of ...

    African Journals Online (AJOL)

    An understanding of the extent, distribution and patterns of genetic variation is useful for estimation of any possible loss of genetic diversity and assessment of genetic variability and its potential use in breeding programs, including establishment of heterotic groups. This study assessed patterns of genetic diversity and ...

  9. 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...

  10. 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...

  11. Desktop Genetics.

    Science.gov (United States)

    Hough, Soren H; Ajetunmobi, Ayokunmi; Brody, Leigh; Humphryes-Kirilov, Neil; Perello, Edward

    2016-11-01

    Desktop Genetics is a bioinformatics company building a gene-editing platform for personalized medicine. The company works with scientists around the world to design and execute state-of-the-art clustered regularly interspaced short palindromic repeats (CRISPR) experiments. Desktop Genetics feeds the lessons learned about experimental intent, single-guide RNA design and data from international genomics projects into a novel CRISPR artificial intelligence system. We believe that machine learning techniques can transform this information into a cognitive therapeutic development tool that will revolutionize medicine.

  12. An investigation of genetic algorithms

    International Nuclear Information System (INIS)

    Douglas, S.R.

    1995-04-01

    Genetic algorithms mimic biological evolution by natural selection in their search for better individuals within a changing population. they can be used as efficient optimizers. This report discusses the developing field of genetic algorithms. It gives a simple example of the search process and introduces the concept of schema. It also discusses modifications to the basic genetic algorithm that result in species and niche formation, in machine learning and artificial evolution of computer programs, and in the streamlining of human-computer interaction. (author). 3 refs., 1 tab., 2 figs

  13. 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.

  14. 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.

  15. New Genetics

    Science.gov (United States)

    ... of the booklet. » more Chapter 1: How Genes Work Covers DNA, RNA, transcription, RNA splicing, translation, ribosomes, antibiotics, genetic diseases, gene chips. » more Chapter 2: RNA and DNA Revealed: New Roles, New Rules Covers microRNAs, RNAi, epigenetics, telomeres, mtDNA, recombinant DNA. » ...

  16. Genetic effects

    International Nuclear Information System (INIS)

    Kato, Hiroo

    1975-01-01

    In 1948-1953 a large scale field survey was conducted to investigate the possible genetic effects of A-bomb radiation on over 70,000 pregnancy terminations in the cities of Hiroshima and Nagasaki. The indices of possible genetic effect including sex ratio, birth weight, frequency of malformation, stillbirth, neonatal death, deaths within 9 months and anthropometric measurements at 9 months of age for these children were investigated in relation to their parent's exposure status to the A-bomb. There were no detectable genetic effects in this sample, except for a slight change in sex ratio which was in the direction to be expected if exposure had induced sex-linked lethal mutations. However, continued study of the sex ratio, based upon birth certificates in Hiroshima and Nagasaki for 1954-1962, did not confirm the earlier trend. Mortality in these children of A-bomb survivors is being followed using a cohort of 54,000 subjects. No clearly significant effect of parental exposure on survival of the children has been demonstrated up to 1972 (age 17 on the average). On the basis of the regression data, the minimal genetic doubling dose of this type of radiation for mutations resulting in death is estimated at 46 rem for the father and 125 rem for the mother. (auth.)

  17. Melanoma genetics

    DEFF Research Database (Denmark)

    Read, Jazlyn; Wadt, Karin A W; Hayward, Nicholas K

    2015-01-01

    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 herita......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...... 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...... polygenic component to susceptibility, and a unique level of personal melanoma risk influenced by multiple low-risk alleles and genetic modifiers. In addition to conferring a risk of cutaneous melanoma, some 'melanoma' predisposition genes have been linked to other cancers, with cancer clustering observed...

  18. Genetic Recombination

    Science.gov (United States)

    Whitehouse, H. L. K.

    1973-01-01

    Discusses the mechanisms of genetic recombination with particular emphasis on the study of the fungus Sordaria brevicollis. The study of recombination is facilitated by the use of mutants of this fungus in which the color of the ascospores is affected. (JR)

  19. Genetic analysis

    NARCIS (Netherlands)

    Koornneef, M.; Alonso-Blanco, C.; Stam, P.

    2006-01-01

    The Mendelian analysis of genetic variation, available as induced mutants or as natural variation, requires a number of steps that are described in this chapter. These include the determination of the number of genes involved in the observed trait's variation, the determination of dominance

  20. Molecular genetics

    International Nuclear Information System (INIS)

    Parkinson, D.R.; Krontiris, T.G.

    1986-01-01

    In this chapter the authors review new findings concerning the molecular genetics of malignant melanoma in the context of other information obtained from clinical, epidemiologic, and cytogenetic studies in this malignancy. These new molecular approaches promise to provide a more complete understanding of the mechanisms involved in the development of melanoma, thereby suggesting new methods for its treatment and prevention

  1. J. Genet. classic 235

    Indian Academy of Sciences (India)

    Unknown

    Journal of Genetics, Vol. 83, No. 3, December 2004. 235. Page 2. J. Genet. classic. Journal of Genetics, Vol. 83, No. 3, December 2004. 236. Page 3. J. Genet. classic. Journal of Genetics, Vol. 83, No. 3, December 2004. 237. Page 4. J. Genet. classic. Journal of Genetics, Vol. 83, No. 3, December 2004. 238. Page 5 ...

  2. Genetic effects

    International Nuclear Information System (INIS)

    Bender, M.A.; Abrahamson, S.; Denniston, C.; Schull, W.J.

    1989-01-01

    In this chapter, we present a comprehensive analysis of the major classes of genetic diseases that would be increased as a result of an increased gonadal radiation exposure to a human population. The risk analysis takes on two major forms: the increase in genetic disease that would be observed in the immediate offspring of the exposed population, and the subsequent transmission of the newly induced mutations through future generations. The major classes of genetic disease will be induced at different frequencies, and will also impact differentially in terms of survivability and fertility on the affected individuals and their descendants. Some classes of disease will be expected to persist for only a few generations at most. Other types of genetic disease will persist through a longer period. The classes of genetic diseases studied are: dominant gene mutation, X-linked gene mutation, chromosome disorders and multifactorial disorders which involve the interaction of many mutant genes and environmental factors. For each of these classes we have derived the general equations of mutation induction for the male and female germ cells of critical importance in the mutation process. The frequency of induced mutations will be determined initially by the dose received, the type of radiation and, to some extent at high dose, by the manner in which the dose is received. We have used the modeling analyses to predict the outcomes for two nuclear power plant accident scenarios, the first in which the population receives a chronic dose of 0.1 Gy (10 rad) over a 50-year period, the second in which an equivalent population receives an acute dose of 2 Gy. In both cases the analyses are projected over a period of five generations

  3. Mapping public policy on genetics.

    Science.gov (United States)

    Weisfeld, N E

    2002-06-01

    The mapping of the human genome and related advances in genetics are stimulating the development of public policies on genetics. Certain notions that currently prevail in public policy development overall--including the importance of protecting privacy of information, an interest in cost-effectiveness, and the power of the anecdote--will help determine the future of public policy on genetics. Information areas affected include discrimination by insurers and employers, confidentiality, genetic databanks, genetic testing in law enforcement, and court-ordered genetic testing in civil cases. Service issues address clinical standards, insurance benefits, allocation of resources, and screening of populations at risk. Supply issues encompass funding of research and clinical positions. Likely government actions include, among others: (1) Requiring individual consent for the disclosure of personal information, except when such consent would impose inordinate costs; (2) licensing genetic databases; (3) allowing courts to use personal information in cases where a refusal to use such information would offend the public; (4) mandating health insurers to pay for cost-effective genetic services; (5) funding pharmaceutical research to develop tailored products to prevent or treat diseases; and (6) funding training programs.

  4. 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.

  5. Genetic diversity of sweet potatoes collection from Northeastern Brazil

    African Journals Online (AJOL)

    Ana Veruska Cruz da Silva Muniz

    2014-02-24

    Feb 24, 2014 ... RAPD was efficient for the analysis of genetic diversity to identify groups and measure the genetic distance between ..... management program. We recommend ... The author(s) have not declared any conflict of interests.

  6. 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.

  7. Analysis of genetic structure and relationship among nine ...

    Indian Academy of Sciences (India)

    These results indicated that the clustering analysis using the Structure program might provide an ..... of the current genetic relations among the breeds, and con- tribute to ... sis of the genetic structure of the Canary goat populations using.

  8. Genetic diversity of Colletotrichum gloeosporioides in Nigeria using ...

    African Journals Online (AJOL)

    fmodupe

    2012-04-24

    Apr 24, 2012 ... gloeosporioides isolates and was effective in establishing genetic relationships ... Key words: Anthracnose disease, pathotypes, genetic diversity, amplified ..... isolates to use in an anthracnose resistance screening program.

  9. Genetic divergence of roundup ready (RR) soybean cultivars ...

    African Journals Online (AJOL)

    The aim of this study was to estimate the genetic diversity in 74 RR soybean cultivars from different Brazilian breeding programs. ... chosen SSR markers were effective in assessing the genetic diversity among genotypes, besides proving to be ...

  10. Microsatellite DNA typing for assessment of genetic variability in ...

    Indian Academy of Sciences (India)

    these microsatellite loci in measurement of genetic diversity indices in other Indian cattle breeds too. Various .... enced a recent reduction in the effective population size or a genetic ... by using the m p val.exe program (Garza and Williamson.

  11. Analysis of genetic diversity and construction of core collection of ...

    African Journals Online (AJOL)

    Jane

    2011-06-03

    Jun 3, 2011 ... Genetic diversity of 73 local mulberry varieties from Shanxi Province were screened using ISSR ... number effective of alleles, Nei's genetic diversity index and Shannon's ...... resources conservation program of the Agriculture.

  12. 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.

  13. Molecular-genetic aspects of the endometrium state on the day of the tentative implantation window in women with recurrent miscarriage in the programs of assisted reproductive technologies

    Directory of Open Access Journals (Sweden)

    K. P. Golovatyuk

    2017-09-01

    Full Text Available More than 50% of pregnant women after the programs of assisted reproductive technologies (ART face the problem of recurrent miscarriage (RMC, especially in the first trimester. Significant role in the development of RMC has infectious factor and chronic inflammation in the endometrium. The aim: to reveal the peculiarities of immune response mRNA genes of the inflammatory component expression in the period of the tentative implantation window (TIW in women with RMC in ART programs. Material and methods. The main group consisted of 240 patients with RMC in ART programs; the control group included 100 conditionally healthy fertile women. On the ground of PCR reverse transcription, the mRNA of the IL-1β, IL-2, IL-10, Foxp3, TLR9, IL-2Rα cytokine genes was examined in endometrial samples obtained with the help of  biopsy on the TIW day. Results. Analysis of the transcriptional profile of the immune response genes in the endometrium on TIW day revealed that the relative level of mRNA expression of the IL-1β, IL-2, Foxp3, TLR9, IL-2Rα genes did not differ significantly in the main and control groups. Statistically significant decrease in mRNA expression of IL-10 gene was observed in women with RPL. Conclusions. A feature of mRNA expression of the inflammatory component of the immune response in TIW period in women with RMC in ART programs is a decrease in the expression level of the IL-10 gene mRNA, which may be one of the reasons for the unfavorable outcomes of the onset  pregnancy.

  14. Plants and Photosynthesis: Level III, Unit 3, Lesson 1; The Human Digestive System: Lesson 2; Functions of the Blood: Lesson 3; Human Circulation and Respiration: Lesson 4; Reproduction of a Single Cell: Lesson 5; Reproduction by Male and Female Cells: Lesson 6; The Human Reproductive System: Lesson 7; Genetics and Heredity: Lesson 8; The Nervous System: Lesson 9; The Glandular System: Lesson 10. Advanced General Education Program. A High School Self-Study Program.

    Science.gov (United States)

    Manpower Administration (DOL), Washington, DC. Job Corps.

    This self-study program for the high-school level contains lessons in the following subjects: Plants and Photosynthesis; The Human Digestive System; Functions of the Blood; Human Circulation and Respiration; Reproduction of a Single Cell; Reproduction by Male and Female Cells; The Human Reproductive System; Genetics and Heredity; The Nervous…

  15. 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.

  16. Genetic effects

    International Nuclear Information System (INIS)

    Abrahamson, S.; Bender, M.; Denniston, C.; Schull, W.

    1985-01-01

    Modeling analyses are used to predict the outcomes for two nuclear power plant accident scenarios, the first in which the population received a chronic dose of 0.1 Gy (10 rad) over a 50 year period, the second in which an equivalent population receives acute dose of 2 Gy. In both cases the analyses are projected over a period of five generations. The risk analysis takes on two major forms: the increase in genetic disease that would be observed in the immediate offspring of the exposed population, and the subsequent transmission of the newly induced mutations through future generations. The classes of genetic diseases studied are: dominant gene mutation, X-linked gene mutation, chromosome disorders and multifactorial disorders which involve the interaction of many mutant genes and environmental factors. 28 references, 3 figures, 5 tables

  17. Community Genetics: a new discipline and its application in Brazil

    Directory of Open Access Journals (Sweden)

    Antonio Sérgio Ramalho

    Full Text Available Community genetics is a new discipline which aims to provide genetic services to the community as a whole. As a science, community genetics encompasses all research needed to develop and evaluate its application. There is no question that the development of community genetics is necessary in Brazil. The implementation of such programs in our country, especially for hemoglobinopathies, has been recommended by the World Health Organization and other international organizations. Apart from the need for and appeal of community genetics programs, some aspects require serious review. This article discusses various cultural, social, psychological, and economic factors that can make genetic screening an invasion of individual privacy

  18. Community Genetics: a new discipline and its application in Brazil

    Directory of Open Access Journals (Sweden)

    Ramalho Antonio Sérgio

    2000-01-01

    Full Text Available Community genetics is a new discipline which aims to provide genetic services to the community as a whole. As a science, community genetics encompasses all research needed to develop and evaluate its application. There is no question that the development of community genetics is necessary in Brazil. The implementation of such programs in our country, especially for hemoglobinopathies, has been recommended by the World Health Organization and other international organizations. Apart from the need for and appeal of community genetics programs, some aspects require serious review. This article discusses various cultural, social, psychological, and economic factors that can make genetic screening an invasion of individual privacy

  19. Cancer Genetics Services Directory

    Science.gov (United States)

    ... Services Directory Cancer Prevention Overview Research NCI Cancer Genetics Services Directory This directory lists professionals who provide services related to cancer genetics (cancer risk assessment, genetic counseling, genetic susceptibility testing, ...

  20. Genetic Parameters of Common Wheat in Nepal

    OpenAIRE

    Bal Krishna Joshi; Dhruba Bahadur Thapa; Madan Raj Bhatta

    2015-01-01

    Knowledge on variation within traits and their genetics are prerequisites in crop improvement program. Thus, in present paper we aimed to estimate genetic and environmental indices of common wheat genotypes. For the purpose, eight quantitative traits were measured from 30 wheat genotypes, which were in randomized complete block design with 3 replicates. Components of variance and covariance were estimated along with heritability, genetic gain, realized heritability, coheritability and correla...

  1. Boolean Queries Optimization by Genetic Algorithms

    Czech Academy of Sciences Publication Activity Database

    Húsek, Dušan; Owais, S.S.J.; Krömer, P.; Snášel, Václav

    2005-01-01

    Roč. 15, - (2005), s. 395-409 ISSN 1210-0552 R&D Projects: GA AV ČR 1ET100300414 Institutional research plan: CEZ:AV0Z10300504 Keywords : evolutionary algorithms * genetic algorithms * genetic programming * information retrieval * Boolean query Subject RIV: BB - Applied Statistics, Operational Research

  2. 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 ...

  3. Epigenetics of the yeast galactose genetic switch

    Indian Academy of Sciences (India)

    Prakash

    wiped out if the genetic program is not equipped to adapt to ... In this article we review some of the recent attempts made to understand the importance ..... Induction kinetics of GAL gene expression in these two cultures was determined.

  4. Genetics of Vitiligo

    Science.gov (United States)

    Spritz, Richard; Andersen, Genevieve

    2016-01-01

    Synopsis Vitiligo is “complex disorder” (also termed polygenic and multifactorial), reflecting simultaneous contributions of multiple genetic risk factors and environmental triggers. Large-scale genome-wide association studies, principally in European-derived whites and in Chinese, have discovered approximately 50 different genetic loci that contribute to vitiligo risk, some of which also contribute to other autoimmune diseases that are epidemiologically associated with vitiligo. At many of these vitiligo susceptibility loci the corresponding relevant genes have now been identified, and for some of these genes the specific DNA sequence variants that contribute to vitiligo risk are also now known. A large fraction of these genes encode proteins involved in immune regulation, a number of others play roles in cellular apoptosis, and still others are involved in regulating functions of melanocytes. For this last group, there appears to be an opposite relationship between susceptibility to vitiligo and susceptibility to melanoma, suggesting that vitiligo may engage a normal mechanism of immune surveillance for melanoma. While many of the specific biologic mechanisms through which these genetic factors operate to cause vitiligo remain to be elucidated, it is now clear that vitiligo is an autoimmune disease involving a complex relationship between programming and function of the immune system, aspects of the melanocyte autoimmune target, and dysregulation of the immune response. PMID:28317533

  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. 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.

    Science.gov (United States)

    Rank, Melanie; Siegrist, Monika; Wilks, Désirée C; Haller, Bernhard; Wolfarth, Bernd; Langhof, Helmut; Halle, Martin

    2012-03-19

    -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. NCT01067157.

  7. 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.

  8. Molecular genetics

    International Nuclear Information System (INIS)

    Kubitschek, H.E.

    1975-01-01

    Progress is reported on studies on the nature and action of lethal and mutagenic lesions in DNA and the mechanisms by which these are produced in bacteria by ionizing radiation or by decay of radioisotopes incorporated in DNA. Studies of radioisotope decay provide the advantages that the original lesion is localized in the genetic material and the immediate physical and chemical changes that occur at decay are known. Specific types of DNA damage were related to characteristic decay properties of several radioisotopes. Incorporated 125 I, for example, induces a double-stranded break in DNA with almost every decay, but causes remarkably little damage of any other kind to the DNA. (U.S.)

  9. 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.

  10. Proinflammatory Status, Genetics and Atherosclerosis

    Czech Academy of Sciences Publication Activity Database

    Poledne, R.; Lorenzová, A.; Stávek, P.; Valenta, Zdeněk; Hubáček, J.; Suchánek, R.; Piťha, J.

    2009-01-01

    Roč. 58, Suppl. 2 (2009), S111-S118 ISSN 0862-8408 R&D Projects: GA MŠk(CZ) 1M06014 Grant - others:GA MŠk(CZ) 1M0510 Program:1M Institutional research plan: CEZ:AV0Z10300504 Keywords : atherosclerosis * inflammation * C-reactive protein * genetics Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 1.430, year: 2009 http://www.biomed.cas.cz/physiolres/pdf/58%20Suppl%202/58_S111.pdf

  11. 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 ...

  12. Analyzing Population Genetics Data: A Comparison of the Software

    Science.gov (United States)

    Choosing a software program for analyzing population genetic data can be a challenge without prior knowledge of the methods used by each program. There are numerous web sites listing programs by type of data analyzed, type of analyses performed, or other criteria. Even with programs categorized in ...

  13. Inspirations in medical genetics.

    Science.gov (United States)

    Asadollahi, Reza

    2016-02-01

    There are abundant instances in the history of genetics and medical genetics to illustrate how curiosity, charisma of mentors, nature, art, the saving of lives and many other matters have inspired great discoveries. These achievements from deciphering genetic concepts to characterizing genetic disorders have been crucial for management of the patients. There remains, however, a long pathway ahead. © The Author(s) 2014.

  14. 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.

  15. What Is Genetic Ancestry Testing?

    Science.gov (United States)

    ... What is genetic ancestry testing? What is genetic ancestry testing? Genetic ancestry testing, or genetic genealogy, is ... with other groups. For more information about genetic ancestry testing: The University of Utah provides video tutorials ...

  16. Public health genetic counselors: activities, skills, and sources of learning.

    Science.gov (United States)

    McWalter, Kirsty M; Sdano, Mallory R; Dave, Gaurav; Powell, Karen P; Callanan, Nancy

    2015-06-01

    Specialization within genetic counseling is apparent, with 29 primary specialties listed in the National Society of Genetic Counselors' 2012 Professional Status Survey (PSS). PSS results show a steady proportion of genetic counselors primarily involved in public health, yet do not identify all those performing public health activities. Little is known about the skills needed to perform activities outside of "traditional" genetic counselor roles and the expertise needed to execute those skills. This study aimed to identify genetic counselors engaging in public health activities, the skills used, and the most influential sources of learning for those skills. Participants (N = 155) reported involvement in several public health categories: (a) Education of Public and/or Health Care Providers (n = 80, 52 %), (b) Population-Based Screening Programs (n = 70, 45 %), (c) Lobbying/Public Policy (n = 62, 40 %), (d) Public Health Related Research (n = 47, 30 %), and (e) State Chronic Disease Programs (n = 12, 8 %). Regardless of category, "on the job" was the most common primary source of learning. Genetic counseling training program was the most common secondary source of learning. Results indicate that the number of genetic counselors performing public health activities is likely higher than PSS reports, and that those who may not consider themselves "public health genetic counselors" do participate in public health activities. Genetic counselors learn a diverse skill set in their training programs; some skills are directly applicable to public health genetics, while other public health skills require additional training and/or knowledge.

  17. Cancer Genetics and Signaling | Center for Cancer Research

    Science.gov (United States)

    The Cancer, Genetics, and Signaling (CGS) Group at the National Cancer Institute at Frederick  offers a competitive postdoctoral training and mentoring program focusing on molecular and genetic aspects of cancer. The CGS Fellows Program is designed to attract and train exceptional postdoctoral fellows interested in pursuing independent research career tracks. CGS Fellows participate in a structured mentoring program designed for scientific and career development and transition to independent positions.

  18. 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

  19. Genetics and bioethics: how our thinking has changed since 1969.

    Science.gov (United States)

    Walters, LeRoy

    2012-02-01

    In 1969, the field of human genetics was in its infancy. Amniocentesis was a new technique for prenatal diagnosis, and a newborn genetic screening program had been established in one state. There were also concerns about the potential hazards of genetic engineering. A research group at the Hastings Center and Paul Ramsey pioneered in the discussion of genetics and bioethics. Two principal techniques have emerged as being of enduring importance: human gene transfer research and genetic testing and screening. This essay tracks the development and use of these techniques and considers the ethical issues that they raise.

  20. Radiation genetics. Status and prospects

    International Nuclear Information System (INIS)

    Svyatova, G.S.; Abil'dinova, G.Zh.; Berezina, G.M.

    1997-01-01

    In Republic of Kazakhstan on the base of Republican Scientific and Research Center for Mother and Child Health Protection the comprehensive medical-genetical testing of rural population living in immediate proximity from Semipalatinsk test site is carried out. Besides of general medical-genetic characteristics of examined population the frequency and structure of congenital diseases of newborns from 1970 to 1995 were determined. 67.5 thousand parturitions outcomes in researched area and 21.5 thousand ones in control district (Akmola region) are studied. Both the frequency and the structure of chromosomal aberration of population living on contaminated by radionuclides territories is researched as well. Perspective trends in field of clinical radiation genetics are outlined, there are as follows: - application of early diagnostics and prophylaxis of radiation-induced pathology of both the stochastic and nonstochastic characters; - conducting of biologic dosimetry; - wide application of peri-conception prophylaxis of genetic disorders; - application of anti-mutagens and special food-stuffs making for both the reducing of the absorption and the accumulation of radionuclides in organism; - introduction of long-term programs of correction of developing pathologies caused by multifactorial influence of environment

  1. 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...

  2. 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.

  3. Genetics Home Reference: SADDAN

    Science.gov (United States)

    ... view the expand/collapse boxes. Description SADDAN (severe achondroplasia with developmental delay and acanthosis nigricans) is a ... Genetic Testing (1 link) Genetic Testing Registry: Severe achondroplasia with developmental delay and acanthosis nigricans Other Diagnosis ...

  4. 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 ...

  5. Genetic Testing for ALS

    Science.gov (United States)

    ... genetic counselor can help you work through the pros and cons of genetic testing based on your ... showing symptoms or what their progression will be. Technology is changing rapidly and costs of testing are ...

  6. 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 ...

  7. 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...

  8. Evaluating human genetic diversity

    National Research Council Canada - National Science Library

    This book assesses the scientific value and merit of research on human genetic differences--including a collection of DNA samples that represents the whole of human genetic diversity--and the ethical...

  9. Genetics Home Reference: osteopetrosis

    Science.gov (United States)

    ... A characteristic of X-linked inheritance is that fathers cannot pass X-linked traits to their sons. ... infantile neuroaxonal dystrophy Genetic Testing Registry: Osteopetrosis autosomal dominant type 1 Genetic Testing Registry: Osteopetrosis autosomal dominant ...

  10. Genetics and Man

    Science.gov (United States)

    Carter, C. O.

    1973-01-01

    Can genetic evolution be controlled by man in a manner which does not violate a civilized, humane, and democratic ethos? The genetics of health and illhealth and of normal variation are discussed with respect to this question. (PEB)

  11. Genetic Science Learning Center

    Science.gov (United States)

    Genetic Science Learning Center Making science and health easy for everyone to understand Home News Our Team What We Do ... Collaboration Conferences Current Projects Publications Contact The Genetic Science Learning Center at The University of Utah is a ...

  12. Genetics Home Reference: homocystinuria

    Science.gov (United States)

    ... an increased risk of abnormal blood clotting, and brittle bones that are prone to fracture ( osteoporosis ) or other ... information about a genetic condition can statistics provide? Why are some genetic conditions more common in particular ...

  13. Protecting genetic privacy.

    Science.gov (United States)

    Roche, P A; Annas, G J

    2001-05-01

    This article outlines the arguments for and against new rules to protect genetic privacy. We explain why genetic information is different to other sensitive medical information, why researchers and biotechnology companies have opposed new rules to protect genetic privacy (and favour anti-discrimination laws instead), and discuss what can be done to protect privacy in relation to genetic-sequence information and to DNA samples themselves.

  14. Genetic Pathways to Insomnia

    OpenAIRE

    Mackenzie J. Lind; Philip R. Gehrman

    2016-01-01

    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 identif...

  15. The genetic difference principle.

    Science.gov (United States)

    Farrelly, Colin

    2004-01-01

    In the newly emerging debates about genetics and justice three distinct principles have begun to emerge concerning what the distributive aim of genetic interventions should be. These principles are: genetic equality, a genetic decent minimum, and the genetic difference principle. In this paper, I examine the rationale of each of these principles and argue that genetic equality and a genetic decent minimum are ill-equipped to tackle what I call the currency problem and the problem of weight. The genetic difference principle is the most promising of the three principles and I develop this principle so that it takes seriously the concerns of just health care and distributive justice in general. Given the strains on public funds for other important social programmes, the costs of pursuing genetic interventions and the nature of genetic interventions, I conclude that a more lax interpretation of the genetic difference principle is appropriate. This interpretation stipulates that genetic inequalities should be arranged so that they are to the greatest reasonable benefit of the least advantaged. Such a proposal is consistent with prioritarianism and provides some practical guidance for non-ideal societies--that is, societies that do not have the endless amount of resources needed to satisfy every requirement of justice.

  16. Phenylketonuria Genetic Screening Simulation

    Science.gov (United States)

    Erickson, Patti

    2012-01-01

    After agreeing to host over 200 students on a daylong genetics field trip, the author needed an easy-to-prepare genetics experiment to accompany the DNA-necklace and gel-electrophoresis activities already planned. One of the student's mothers is a pediatric physician at the local hospital, and she suggested exploring genetic-disease screening…

  17. Genetics Home Reference

    Science.gov (United States)

    ... Page Search Home Health Conditions Genes Chromosomes & mtDNA Resources Help Me Understand Genetics Share: Email Facebook Twitter Genetics Home Reference provides consumer-friendly information about the effects of genetic variation on human health. Health Conditions More than 1,200 health ...

  18. The molecular genetics of holoprosencephaly.

    Science.gov (United States)

    Roessler, Erich; Muenke, Maximilian

    2010-02-15

    Holoprosencephaly (HPE) has captivated the imagination of Man for millennia because its most extreme manifestation, the single-eyed cyclopic newborn infant, brings to mind the fantastical creature Cyclops from Greek mythology. Attempting to understand this common malformation of the forebrain in modern medical terms requires a systematic synthesis of genetic, cytogenetic, and environmental information typical for studies of a complex disorder. However, even with the advances in our understanding of HPE in recent years, there are significant obstacles remaining to fully understand its heterogeneity and extensive variability in phenotype. General lessons learned from HPE will likely be applicable to other malformation syndromes. Here we outline the common, and rare, genetic and environmental influences on this conserved developmental program of forebrain development and illustrate the similarities and differences between these malformations in humans and those of animal models. 2010 Wiley-Liss, Inc.

  19. Preimplantation Genetic Screening and Preimplantation Genetic Diagnosis.

    Science.gov (United States)

    Sullivan-Pyke, Chantae; Dokras, Anuja

    2018-03-01

    Preimplantation genetic testing encompasses preimplantation genetic screening (PGS) and preimplantation genetic diagnosis (PGD). PGS improves success rates of in vitro fertilization by ensuring the transfer of euploid embryos that have a higher chance of implantation and resulting in a live birth. PGD enables the identification of embryos with specific disease-causing mutations and transfer of unaffected embryos. The development of whole genome amplification and genomic tools, including single nucleotide polymorphism microarrays, comparative genomic hybridization microarrays, and next-generation sequencing, has led to faster, more accurate diagnoses that translate to improved pregnancy and live birth rates. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. What Is Genetic Ancestry Testing?

    Science.gov (United States)

    ... consumer genetic testing? What kinds of direct-to-consumer genetic tests are available? What is genetic ancestry testing? What are the benefits and risks of direct-to-consumer genetic testing? ...

  1. Prenatal Genetic Counseling (For Parents)

    Science.gov (United States)

    ... Videos for Educators Search English Español Prenatal Genetic Counseling KidsHealth / For Parents / Prenatal Genetic Counseling What's in ... can they help your family? What Is Genetic Counseling? Genetic counseling is the process of: evaluating family ...

  2. All about Genetics (For Parents)

    Science.gov (United States)

    ... Videos for Educators Search English Español All About Genetics KidsHealth / For Parents / All About Genetics What's in ... the way they pick up special laboratory dyes. Genetic Problems Errors in the genetic code or "gene ...

  3. 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.

  4. Molecular genetics made simple

    Science.gov (United States)

    Kassem, Heba Sh.; Girolami, Francesca; Sanoudou, Despina

    2012-01-01

    Abstract 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. PMID:25610837

  5. 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...

  6. MDM2 phenotypic and genotypic profiling, respective to TP53 genetic status, in diffuse large B-cell lymphoma patients treated with rituximab-CHOP immunochemotherapy: a report from the International DLBCL Rituximab-CHOP Consortium Program

    NARCIS (Netherlands)

    Xu-Monette, Z.Y.; Moller, M.B.; Tzankov, A.; Montes-Moreno, S.; Hu, W.; Manyam, G.C.; Kristensen, L.; Fan, L.; Visco, C.; Dybkaer, K.; Chiu, A.; Tam, W.; Zu, Y.; Bhagat, G.; Richards, K.L.; Hsi, E.D.; Choi, W.W.; Krieken, J.H.J.M. van; Huang, Q.; Huh, J.; Ai, W.; Ponzoni, M.; Ferreri, A.J.; Wu, L.; Zhao, X.; Bueso-Ramos, C.E.; Wang, S.A.; Go, R.S.; Li, Y.; Winter, J.N.; Piris, M.A.; Medeiros, L.J.; Young, K.H.

    2013-01-01

    MDM2 is a key negative regulator of the tumor suppressor p53, however, the prognostic significance of MDM2 overexpression in diffuse large B-cell lymphoma (DLBCL) has not been defined convincingly. In a p53 genetically-defined large cohort of de novo DLBCL patients treated with rituximab,

  7. Genetic parameters in a Swine Population

    Directory of Open Access Journals (Sweden)

    Dana Popa

    2010-05-01

    Full Text Available The estimation of the variance-covariance components is a very important step in animal breeding because these components are necessary for: estimation of the genetic parameters, prediction of the breeding value and design of animal breeding programs. The estimation of genetic parameters is the first step in the development of a swine breeding program, using artificial insemination. Various procedures exist for estimation of heritability. There are three major procedures used for estimating heritability: analysis of variance (ANOVA, parents-offspring regression and restricted maximum likelihood (REML. By using ANOVA methodology or regression method it is possible to obtain aberrant values of genetic parameters (negative or over unit value of heritability coefficient, for example which can not be interpreting because is out of biological limits.

  8. Fuzzy Information Retrieval Using Genetic Algorithms and Relevance Feedback.

    Science.gov (United States)

    Petry, Frederick E.; And Others

    1993-01-01

    Describes an approach that combines concepts from information retrieval, fuzzy set theory, and genetic programing to improve weighted Boolean query formulation via relevance feedback. Highlights include background on information retrieval systems; genetic algorithms; subproblem formulation; and preliminary results based on a testbed. (Contains 12…

  9. Management intensity and genetics affect loblolly pine seedling performance

    Science.gov (United States)

    Scott D. Roberts; Randall J. Rousseau; B. Landis Herrin

    2012-01-01

    Capturing potential genetic gains from tree improvement programs requires selection of the appropriate genetic stock and application of appropriate silvicultural management techniques. Limited information is available on how specific loblolly pine varietal genotypes perform under differing growing environments and management approaches. This study was established in...

  10. 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

  11. Genetic variability and heritability studies of some reproductive traits ...

    African Journals Online (AJOL)

    GRACE

    2006-07-03

    Jul 3, 2006 ... The success of most crop improvement programs largely depends upon the genetic variability and the heritability of desirable traits. The magnitude and type of genetic variability help the breeder to determine the selection criteria and breeding schemes to be used for improvement purposes. A screen.

  12. Genetic diversity analysis of rice cultivars from various origins using ...

    African Journals Online (AJOL)

    Genetic diversity is of paramount importance for the success of any plant breeding program. An experiment was conducted to assess the extent of genetic diversity and similarity of 24 rice cultivars from various origins using 29 simple sequence repeat (SSR) markers. A total of 144 alleles were detected at the 29 SSR primer ...

  13. Portfolio selection using genetic algorithms | Yahaya | International ...

    African Journals Online (AJOL)

    In this paper, one of the nature-inspired evolutionary algorithms – a Genetic Algorithms (GA) was used in solving the portfolio selection problem (PSP). Based on a real dataset from a popular stock market, the performance of the algorithm in relation to those obtained from one of the popular quadratic programming (QP) ...

  14. Journal of Genetics | Indian Academy of Sciences

    Indian Academy of Sciences (India)

    ... Refresher Courses · Symposia · Live Streaming. Home; Journals; Journal of Genetics; Volume 84; Issue 1. Exact Tandem Repeats Analyzer (E-TRA): A new program for DNA sequence mining. Mehmet Karaca Mehmet Bilgen A. Naci Onus Ayse Gul Ince Safinaz Y. Elmasulu. Research Article Volume 84 Issue 1 April 2005 ...

  15. Phenotypic and molecular evaluation of genetic diversity of rapeseed

    African Journals Online (AJOL)

    STORAGESEVER

    2009-10-05

    Oct 5, 2009 ... basis of elite oilseed rape breeding material has been narrowed by an intensive .... breeding programs was the basic reason for detailed genetic analysis. ...... A periodical of Scientific Research on Field and. Vegetable Crops ...

  16. Genetic diversity assessment of farmers' and improved potato ...

    African Journals Online (AJOL)

    Biniam M

    2016-08-31

    Aug 31, 2016 ... 2010) but with the new molecular technologies in breeding programs ... genetic characterization with each having its own pros and cons (Nováková et al., 2010). Simple ..... Education Commission for funding the field work and.

  17. Multiple-trait genetic evaluation using genomic matrix

    African Journals Online (AJOL)

    Jane

    2011-07-06

    Jul 6, 2011 ... relationships was estimated through computer simulation and was compared with the accuracy of ... programs, detect animals with superior genetic and select ... genomic matrices in the mixed model equations of BLUP.

  18. Assessment of the genetic diversity of Kenyan coconut germplasm ...

    African Journals Online (AJOL)

    HP-PROBOOK

    2016-10-05

    Oct 5, 2016 ... Genetic diversity and relationship among 48 coconut individuals (Cocos nucifera L.) collections from ... Cluster analysis was constructed using DARwin program version 6.0. ... effective crop improvement programme.

  19. Genetic diversity study of common bean (Phaseolus vulgaris L ...

    African Journals Online (AJOL)

    SAM

    2014-09-03

    Sep 3, 2014 ... Key words: Genetic diversity, ISSR, Phaseolus vulgaris. INTRODUCTION ..... effective germplasm conservation and for setting germ- plasm collection ... conservation and research programs of the species. Furthermore, the ...

  20. Analysis of genetic diversity in chickpea ( Cicer arietinum L ...

    African Journals Online (AJOL)

    Genetic diversity of seven chickpea (Cicer arietinum L.) cultivars of Pakistani origin ... effective method to determine the variations among the chickpea cultivars. ... to broaden the germplasm base in the future for chickpea breeding programs.

  1. Assessing the genetic diversity of 48 groundnut ( Arachis hypogaea ...

    African Journals Online (AJOL)

    Assessing the genetic diversity of 48 groundnut ( Arachis hypogaea L. ) ... both at the phenotypic and molecular level is important in all plant breeding programs. ... other and could therefore serve as effective parental material for future work.

  2. Analysis of genetic diversity and estimation of inbreeding coefficient ...

    African Journals Online (AJOL)

    STORAGESEVER

    2010-01-18

    Jan 18, 2010 ... Key words: Genetic diversity, microsatellite markers, Caspian horse breed. INTRODUCTION ... heterozygosity, observed and effective number of alleles at each ... computer program version 1.31 (Yeh et al., 1999). Based on ...

  3. Determination of genetic variability of Asian rice (Oryza sativa L ...

    African Journals Online (AJOL)

    PRECIOUS

    2009-11-02

    Nov 2, 2009 ... diversity and relationship among thirty-five Asian cultivars of rice including 19 aromatic, 13 non- ... are promising and effective tools for measuring genetic .... efficients were employed by using Simqual sub-program in similarity.

  4. Genetic diversity of Bambara groundnut (Vigna subterranea (L ...

    African Journals Online (AJOL)

    FORRESTER

    2015-01-28

    Jan 28, 2015 ... The existence of genetic diversity in germplasm collections is crucial for cultivar development. ... program for Bambara groundnut, a thorough under- ..... na* = Observed number of alleles; ne* = Effective number of alleles ...

  5. 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.

  6. Genetic parameters and estimated genetic gains in young rubber tree progenies

    Directory of Open Access Journals (Sweden)

    Cecília Khusala Verardi

    2013-04-01

    Full Text Available The objective of this work was to assess the genetic parameters and to estimate genetic gains in young rubber tree progenies. The experiments were carried out during three years, in a randomized block design, with six replicates and ten plants per plot, in three representative Hevea crop regions of the state of São Paulo, Brazil. Twenty-two progenies were evaluated, from three to five years old, for rubber yield and annual girth growth. Genetic gain was estimated with the multi-effect index (MEI. Selection by progenies means provided greater estimated genetic gain than selection based on individuals, since heritability values of progeny means were greater than the ones of individual heritability, for both evaluated variables, in all the assessment years. The selection of the three best progenies for rubber yield provided a selection gain of 1.28 g per plant. The genetic gains estimated with MEI using data from early assessments (from 3 to 5-year-old were generally high for annual girth growth and rubber yield. The high genetic gains for annual girth growth in the first year of assessment indicate that progenies can be selected at the beginning of the breeding program. Population effective size was consistent with the three progenies selected, showing that they were not related and that the population genetic variability is ensured. Early selection with the genetic gains estimated by MEI can be made on rubber tree progenies.

  7. 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.

  8. Preimplantation genetic screening.

    Science.gov (United States)

    Harper, Joyce C

    2018-03-01

    Preimplantation genetic diagnosis was first successfully performed in 1989 as an alternative to prenatal diagnosis for couples at risk of transmitting a genetic or chromosomal abnormality, such as cystic fibrosis, to their child. From embryos generated in vitro, biopsied cells are genetically tested. From the mid-1990s, this technology has been employed as an embryo selection tool for patients undergoing in vitro fertilisation, screening as many chromosomes as possible, in the hope that selecting chromosomally normal embryos will lead to higher implantation and decreased miscarriage rates. This procedure, preimplantation genetic screening, was initially performed using fluorescent in situ hybridisation, but 11 randomised controlled trials of screening using this technique showed no improvement in in vitro fertilisation delivery rates. Progress in genetic testing has led to the introduction of array comparative genomic hybridisation, quantitative polymerase chain reaction, and next generation sequencing for preimplantation genetic screening, and three small randomised controlled trials of preimplantation genetic screening using these new techniques indicate a modest benefit. Other trials are still in progress but, regardless of their results, preimplantation genetic screening is now being offered globally. In the near future, it is likely that sequencing will be used to screen the full genetic code of the embryo.

  9. 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)

  10. Programming languages for circuit design.

    Science.gov (United States)

    Pedersen, Michael; Yordanov, Boyan

    2015-01-01

    This chapter provides an overview of a programming language for Genetic Engineering of Cells (GEC). A GEC program specifies a genetic circuit at a high level of abstraction through constraints on otherwise unspecified DNA parts. The GEC compiler then selects parts which satisfy the constraints from a given parts database. GEC further provides more conventional programming language constructs for abstraction, e.g., through modularity. The GEC language and compiler is available through a Web tool which also provides functionality, e.g., for simulation of designed circuits.

  11. 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).

  12. The Genetic Activity Profile database.

    Science.gov (United States)

    Waters, M D; Stack, H F; Garrett, N E; Jackson, M A

    1991-12-01

    A graphic approach termed a Genetic Activity Profile (GAP) has been developed to display a matrix of data on the genetic and related effects of selected chemical agents. The profiles provide a visual overview of the quantitative (doses) and qualitative (test results) data for each chemical. Either the lowest effective dose (LED) or highest ineffective dose (HID) is recorded for each agent and bioassay. Up to 200 different test systems are represented across the GAP. Bioassay systems are organized according to the phylogeny of the test organisms and the end points of genetic activity. The methodology for the production and evaluation of GAPs has been developed in collaboration with the International Agency for Research on Cancer. Data on individual chemicals have been compiled by IARC and by the U.S. Environmental Protection Agency. Data are available on 299 compounds selected from volumes 1-50 of the IARC Monographs and on 115 compounds identified as Superfund Priority Substances. Software to display the GAPs on an IBM-compatible personal computer is available from the authors. Structurally similar compounds frequently display qualitatively and quantitatively similar GAPs. By examining the patterns of GAPs of pairs and groups of chemicals, it is possible to make more informed decisions regarding the selection of test batteries to be used in evaluating chemical analogs. GAPs have provided useful data for the development of weight-of-evidence hazard ranking schemes. Also, some knowledge of the potential genetic activity of complex environmental mixtures may be gained from assessing the GAPs of component chemicals. The fundamental techniques and computer programs devised for the GAP database may be used to develop similar databases in other disciplines.

  13. Genetic predictors of obesity development

    Directory of Open Access Journals (Sweden)

    Svetlana V. Borodina

    2016-05-01

    Full Text Available The most common reasons that cause obesity are eating disorders (overeating, genetic predisposition, sedentary lifestyle (lack of exercise, disorders of the endocrine system, and environmental factors. There is evidence of an obvious relationship of high consumption of sugary drinks and weight gain. Since 1990, there has been considerable growth in the number of obese people in the first place associated with the promotion of soft drinks. According to a study in Finnish diabetes prevention average physical activity and change of diet (1200-1800 kcal of total fat intake with less than 30% saturated fat, including less than 10%, leading to long-term loss of excess weight (within 4 years. Many studies have demonstrated the impossibility of a single template approach to the determination of optimal diets for patients with overweight and obesity which has been shown in various studies on gene polymorphisms are associated with obesity, and their interaction. This article provides an overview of current data on the genetics of obesity covering the main provisions of the study of candidate genes, such as PPARG, FABP2, ADRB 2, ADRB3. The role nutrigenetics in the creation of individual programs of weight control and weight loss. But the question of the direct role of genetic factors in the development of obesity remains controversial, since one can not ignore the impact of environmental factors, such as lifestyle, diet, physical activity, stress, and harmful habits. To understand the mechanism of the relationship between genetic factors, environmental factors, and obesity, one needs to carry out research not only on the population level, but also in certain groups of people (ethnic, racial, age.

  14. Towards a genetic architecture of cryptic genetic variation

    Indian Academy of Sciences (India)

    Home; Journals; Journal of Genetics; Volume 84; Issue 3. Towards a genetic architecture of cryptic genetic variation and genetic assimilation: the contribution of K. G. Bateman. Ian Dworkin. Commentary on J. Genet. Classic Volume 84 Issue 3 December 2005 pp 223-226 ...

  15. Integrated analysis of genetic data with R

    Directory of Open Access Journals (Sweden)

    Zhao Jing

    2006-01-01

    Full Text Available Abstract Genetic data are now widely available. There is, however, an apparent lack of concerted effort to produce software systems for statistical analysis of genetic data compared with other fields of statistics. It is often a tremendous task for end-users to tailor them for particular data, especially when genetic data are analysed in conjunction with a large number of covariates. Here, R http://www.r-project.org, a free, flexible and platform-independent environment for statistical modelling and graphics is explored as an integrated system for genetic data analysis. An overview of some packages currently available for analysis of genetic data is given. This is followed by examples of package development and practical applications. With clear advantages in data management, graphics, statistical analysis, programming, internet capability and use of available codes, it is a feasible, although challenging, task to develop it into an integrated platform for genetic analysis; this will require the joint efforts of many researchers.

  16. Genetic Testing Registry

    Science.gov (United States)

    ... RefSeqGene UniGene All Genes & Expression Resources... Genetics & Medicine Bookshelf Database of Genotypes and Phenotypes (dbGaP) Genetic Testing ... ProtMap HomoloGene Protein Clusters All Homology Resources... Literature Bookshelf E-Utilities Journals in NCBI Databases MeSH Database ...

  17. Genetics in the courts

    Energy Technology Data Exchange (ETDEWEB)

    Coyle, Heather; Drell, Dan

    2000-12-01

    Various: (1)TriState 2000 Genetics in the Courts (2) Growing impact of the new genetics on the courts (3)Human testing (4) Legal analysis - in re G.C. (5) Legal analysis - GM ''peanots'', and (6) Legal analysis for State vs Miller

  18. Quo Vadis, Medical Genetics?

    Science.gov (United States)

    Czeizel, Andrew E.

    The beginning of human genetics and its medical part: medical genetics was promising in the early decades of this century. Many genetic diseases and defects with Mendelian origin were identified and it helped families with significant genetic burden to limit their child number. Unfortunately this good start was shadowed by two tragic events. On the one hand, in the 1930s and early 1940s the German fascism brought about the dominance of an unscientific eugenics to mask vile political crimes. People with genetic diseases-defects were forced to sterilisation and several of them were killed. On the other hand, in the 1950s lysenkoism inhibitied the evolution of genetics in the Soviet Union and their satelite countries. Lysenko's doctrine declared genetics as a product of imperialism and a guilty science, therefore leading geneticists were ousted form their posts and some of them were executed or put in prison. Past decades genetics has resulted fantastic new results and achieved a leading position within the natural sciences. To my mind, however, the expected wider use of new eugenics indicates a new tragedy and this Cassandra's prediction is the topic of this presentation.

  19. Formal genetic maps

    African Journals Online (AJOL)

    Mohammad Saad Zaghloul Salem

    2014-12-24

    Dec 24, 2014 ... ome/transcriptome/proteome, experimental induced maps that are intentionally designed and con- ... genetic maps imposed their application in nearly all fields of medical genetics including ..... or genes located adjacent to, or near, them. ...... types of markers, e.g., clinical markers (eye color), genomic.

  20. Easy calculations of lod scores and genetic risks on small computers.

    Science.gov (United States)

    Lathrop, G M; Lalouel, J M

    1984-01-01

    A computer program that calculates lod scores and genetic risks for a wide variety of both qualitative and quantitative genetic traits is discussed. An illustration is given of the joint use of a genetic marker, affection status, and quantitative information in counseling situations regarding Duchenne muscular dystrophy. PMID:6585139

  1. 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.

  2. Molecular and genetic basis for partial resistance of western white pine against Cronartium ribicola.

    Science.gov (United States)

    Jun-Jun Liu; Arezoo Zamany; Richard. Sniezko

    2012-01-01

    Western white pine (Pinus monticola Douglas ex D. Don) is an important forest species in North America. Forest genetics programs have been breeding for durable genetic resistance against white pine blister rust (WPBR) caused by Cronartium ribicola in the past few decades. As various genetic resistance resources are screened and...

  3. 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«.

  4. Experimental game theory and behavior genetics.

    Science.gov (United States)

    Cesarini, David; Dawes, Christopher T; Johannesson, Magnus; Lichtenstein, Paul; Wallace, Björn

    2009-06-01

    We summarize the findings from a research program studying the heritability of behavior in a number of widely used economic games, including trust, dictator, and ultimatum games. Results from the standard behavior genetic variance decomposition suggest that strategies and fundamental economic preference parameters are moderately heritable, with estimates ranging from 18 to 42%. In addition, we also report new evidence on so-called "hyperfair" preferences in the ultimatum game. We discuss the implications of our findings with special reference to current efforts that seek to understand the molecular genetic architecture of complex social behaviors.

  5. Cryptic Genetic Variation in Evolutionary Developmental Genetics

    Directory of Open Access Journals (Sweden)

    Annalise B. Paaby

    2016-06-01

    Full Text Available Evolutionary developmental genetics has traditionally been conducted by two groups: Molecular evolutionists who emphasize divergence between species or higher taxa, and quantitative geneticists who study variation within species. Neither approach really comes to grips with the complexities of evolutionary transitions, particularly in light of the realization from genome-wide association studies that most complex traits fit an infinitesimal architecture, being influenced by thousands of loci. This paper discusses robustness, plasticity and lability, phenomena that we argue potentiate major evolutionary changes and provide a bridge between the conceptual treatments of macro- and micro-evolution. We offer cryptic genetic variation and conditional neutrality as mechanisms by which standing genetic variation can lead to developmental system drift and, sheltered within canalized processes, may facilitate developmental transitions and the evolution of novelty. Synthesis of the two dominant perspectives will require recognition that adaptation, divergence, drift and stability all depend on similar underlying quantitative genetic processes—processes that cannot be fully observed in continuously varying visible traits.

  6. Genetics of aggression.

    Science.gov (United States)

    Anholt, Robert R H; Mackay, Trudy F C

    2012-01-01

    Aggression mediates competition for food, mating partners, and habitats and, among social animals, establishes stable dominance hierarchies. In humans, abnormal aggression is a hallmark of neuropsychiatric disorders and can be elicited by environmental factors acting on an underlying genetic susceptibility. Identifying the genetic architecture that predisposes to aggressive behavior in people is challenging because of difficulties in quantifying the phenotype, genetic heterogeneity, and uncontrolled environmental conditions. Studies on mice have identified single-gene mutations that result in hyperaggression, contingent on genetic background. These studies can be complemented by systems genetics approaches in Drosophila melanogaster, in which mutational analyses together with genome-wide transcript analyses, artificial selection studies, and genome-wide analysis of epistasis have revealed that a large segment of the genome contributes to the manifestation of aggressive behavior with widespread epistatic interactions. Comparative genomic analyses based on the principle of evolutionary conservation are needed to enable a complete dissection of the neurogenetic underpinnings of this universal fitness trait.

  7. Genetic improvement of vegetables

    International Nuclear Information System (INIS)

    Jaramillo Vasquez, J.G.

    2001-01-01

    Some genetic bases of the improvement of vegetables are given. The objectives of the genetic improvement and the fundamental stages of this process are done. The sources of genetic variation are indicated and they are related the reproduction systems of the main horticultural species. It is analyzed the concept of genetic inheritance like base to determine the procedures more appropriate of improvement. The approaches are discussed, has more than enough phenotypic value, genetic action and genotypic variance; Equally the heredability concepts and value of improvement. The conventional methods of improvement are described, like they are: the introduction of species or varieties, the selection, the pure line, the pedigree method, the selection for families, the recurrent selection, the selection for unique seed, the haploids method, the selection for heterosis and the synthetic varieties

  8. 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.......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...

  9. Genetics Home Reference: isolated growth hormone deficiency

    Science.gov (United States)

    ... can be inherited? More about Inheriting Genetic Conditions Diagnosis & Management Resources Genetic Testing (4 links) Genetic Testing Registry: Ateleiotic dwarfism Genetic Testing Registry: Autosomal dominant isolated somatotropin deficiency ...

  10. Genetics of healthy aging in Europe: the EU-integrated project GEHA (GEnetics of Healthy Aging)

    DEFF Research Database (Denmark)

    Franceschi, Claudio; Bezrukov, Vladyslav; Blanché, Hélène

    2007-01-01

    The aim of the 5-year European Union (EU)-Integrated Project GEnetics of Healthy Aging (GEHA), constituted by 25 partners (24 from Europe plus the Beijing Genomics Institute from China), is to identify genes involved in healthy aging and longevity, which allow individuals to survive to advanced old......DNA). The genetic analysis will be performed by 9 high-throughput platforms, within the framework of centralized databases for phenotypic, genetic, and mtDNA data. Additional advanced approaches (bioinformatics, advanced statistics, mathematical modeling, functional genomics and proteomics, molecular biology...... age in good cognitive and physical function and in the absence of major age-related diseases. To achieve this aim a coherent, tightly integrated program of research that unites demographers, geriatricians, geneticists, genetic epidemiologists, molecular biologists, bioinfomaticians, and statisticians...

  11. Genetic Breeding and Diversity of the Genus Passiflora: Progress and Perspectives in Molecular and Genetic Studies

    Directory of Open Access Journals (Sweden)

    Carlos Bernard M. Cerqueira-Silva

    2014-08-01

    Full Text Available Despite the ecological and economic importance of passion fruit (Passiflora spp., molecular markers have only recently been utilized in genetic studies of this genus. In addition, both basic genetic researches related to population studies and pre-breeding programs of passion fruit remain scarce for most Passiflora species. Considering the number of Passiflora species and the increasing use of these species as a resource for ornamental, medicinal, and food purposes, the aims of this review are the following: (i to present the current condition of the passion fruit crop; (ii to quantify the applications and effects of using molecular markers in studies of Passiflora; (iii to present the contributions of genetic engineering for passion fruit culture; and (iv to discuss the progress and perspectives of this research. Thus, the present review aims to summarize and discuss the relationship between historical and current progress on the culture, breeding, and molecular genetics of passion fruit.

  12. Genetic variation and its maintenance

    International Nuclear Information System (INIS)

    Roberts, D.F.; De Stefano, G.F.

    1986-01-01

    This book contains several papers divided among three sections. The section titles are: Genetic Diversity--Its Dimensions; Genetic Diversity--Its Origin and Maintenance; and Genetic Diversity--Applications and Problems of Complex Characters

  13. Genetics Home Reference: Farber lipogranulomatosis

    Science.gov (United States)

    ... features. Type 1 is the most common, or classical, form of this condition and is associated with ... be inherited? More about Inheriting Genetic Conditions Diagnosis & Management Resources Genetic Testing (1 link) Genetic Testing Registry: ...

  14. Functional Programming

    OpenAIRE

    Chitil, Olaf

    2009-01-01

    Functional programming is a programming paradigm like object-oriented programming and logic programming. Functional programming comprises both a specific programming style and a class of programming languages that encourage and support this programming style. Functional programming enables the programmer to describe an algorithm on a high-level, in terms of the problem domain, without having to deal with machine-related details. A program is constructed from functions that only map inputs to ...

  15. Genetic heterogeneity of retinitis pigmentosa

    OpenAIRE

    Hartono, Hartono

    2015-01-01

    Genetic heterogeneity is a phenomenon in which a genetic disease can be transmitted by several modes of inheritance. The understanding of genetic heterogeneity is important in giving genetic counselling.The presence of genetic heterogeneity can be explained by the existence of:1.different mutant alleles at a single locus, and2.mutant alleles at different loci affecting the same enzyme or protein, or affecting different enzymes or proteins.To have an overall understanding of genetic heterogene...

  16. Genetic variability in local Brazilian horse lines using microsatellite markers.

    Science.gov (United States)

    Silva, A C M; Paiva, S R; Albuquerque, M S M; Egito, A A; Santos, S A; Lima, F C; Castro, S T; Mariante, A S; Correa, P S; McManus, C M

    2012-04-10

    Genetic variability at 11 microsatellite markers was analyzed in five naturalized/local Brazilian horse breeds or genetic groups. Blood samples were collected from 328 animals of the breeds Campeira (Santa Catarina State), Lavradeira (Roraima State), Pantaneira (Pantanal Mato-Grossense), Mangalarga Marchador (Minas Gerais State), as well as the genetic group Baixadeiro (Maranhão State), and the exotic breeds English Thoroughbred and Arab. We found significant genetic variability within evaluated microsatellite loci, with observed heterozygosis varying between 0.426 and 0.768 and polymorphism information content values of 0.751 to 0.914. All breeds showed high inbreeding coefficients and were not in Hardy-Weinberg equilibrium. The smallest genetic distance was seen between the Pantaneira and Arab breeds. The principal component analyzes and Bayesian approach demonstrated that the exotic breeds have had a significant influence on the genetic formation of the local breeds, with introgression of English Throroughbred in Pantaneira and Lavradeira, as well as genetic proximity between the Arab, Pantaneira and Mangalarga Marchador populations. This study shows the need to conserve traits acquired by naturalized horse breeds over centuries of natural selection in Brazil due to the genetic uniqueness of each group, suggesting a reduced gene flow between them. These results reinforce the need to include these herds in animal genetic resource conservation programs to maximize the genetic variability and conserve useful allele combinations.

  17. Genetic diversity of six populations of red hybrid tilapia, using microsatellites genetic markers

    Directory of Open Access Journals (Sweden)

    Boris Briñez R.

    2011-05-01

    Full Text Available Objective. To determine and evaluate the genetic diversity of six populations of red hybrid tilapia, with the purpose to assess the potential benefit of a future breeding program conducted at the Research Center for Aquaculture (Ceniacua, Colombia. Material and methods. A total of 300 individuals, representing a wide genetic variability, were genotyped using a fluorescent microsatellite marker set of 5 gene-based SSRs in 6 different farms belonging to 4 States of Colombia. Results. The result showed that the mean number of alleles per locus per population was 8.367. The population 5 had the highest mean number of alleles with 9.6 alleles, followed by population 4 with 9.4 alleles, population 2 with 9.2, population 3 with 8.0, population 1 with 7.2 and population 6 with 6.8 alleles. The analysis of the distribution of genetic variation was (17.32% among population, while among individuals within populations was (28.55% and within individuals was high (54.12%. The standard diversity indices showed that population 4 was the more variable (mean He=0.837 followed by population 1 (mean He=0.728, population 3 (mean He=0.721, population 5 (mean He=0.705, population 2 (mean He=0.690, population 6 (mean He=0.586. Highly significant deviations from Hardy–Weinberg, exhibited all of the populations, mostly due to deficits of heterozygotes. Genotype frequencies at loci UNH 106 of population 5 and loci UNH 172 of population 6 were Hardy-Weinberg equilibrium (HWE. Conclusions. The results of this study, contribute to the genetic breeding program of Tilapia, conduced by the Research Center for Aquaculture. The Fst distance showed that the samples are differentiated genetically and it is possible to use at the beginning of the genetic program. However, it is recommended to introduce others individuals to the crossbreeding program.

  18. Genetic effects of radiation

    International Nuclear Information System (INIS)

    Selby, P.B.

    1977-01-01

    Many of the most important findings concerning the genetic effects of radiation have been obtained in the Biology Division of Oak Ridge National Laboratory. The paper focuses on some of the major discoveries made in the Biology Division and on a new method of research that assesses damage to the skeletons of mice whose fathers were irradiated. The results discussed have considerable influence upon estimates of genetic risk in humans from radiation, and an attempt is made to put the estimated amount of genetic damage caused by projected nuclear power development into its proper perspective

  19. Genetically Engineered Cyanobacteria

    Science.gov (United States)

    Zhou, Ruanbao (Inventor); Gibbons, William (Inventor)

    2015-01-01

    The disclosed embodiments provide cyanobacteria spp. that have been genetically engineered to have increased production of carbon-based products of interest. These genetically engineered hosts efficiently convert carbon dioxide and light into carbon-based products of interest such as long chained hydrocarbons. Several constructs containing polynucleotides encoding enzymes active in the metabolic pathways of cyanobacteria are disclosed. In many instances, the cyanobacteria strains have been further genetically modified to optimize production of the carbon-based products of interest. The optimization includes both up-regulation and down-regulation of particular genes.

  20. Statistics for Learning Genetics

    Science.gov (United States)

    Charles, Abigail Sheena

    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 statistically-based genetics problems. This issue is at the emerging edge of modern college-level genetics instruction, and this study attempts to identify key theoretical components for creating a specialized biological statistics curriculum. The goal of this curriculum will be to prepare biology students with the skills for assimilating quantitatively-based genetic processes, increasingly at the forefront of modern genetics. To fulfill this, two college level classes at two universities were surveyed. One university was located in the northeastern US and the other in the West Indies. There was a sample size of 42 students and a supplementary interview was administered to a select 9 students. Interviews were also administered to professors in the field in order to gain insight into the teaching of statistics in genetics. Key findings indicated that students had very little to no background in statistics (55%). Although students did perform well on exams with 60% of the population receiving an A or B grade, 77% of them did not offer good explanations on a probability question associated with the normal distribution provided in the survey. The scope and presentation of the applicable statistics/mathematics in some of the most used textbooks in genetics teaching, as well as genetics syllabi used by instructors do not help the issue. It was found that the text books, often times, either did not give effective explanations for students, or completely left out certain topics. The omission of certain statistical/mathematical oriented topics was seen to be also true with the genetics syllabi reviewed for this study. Nonetheless

  1. Clinical and genetic examinations of children with one parent whose gonads were therapeutically irradiated before conception

    International Nuclear Information System (INIS)

    Neumeister, K.; Herrmann, T.; Koelling, H.L.; Oelssner, W.; Schoeneich, R.

    1978-01-01

    A systematic program for investigating genetic radiation hazards is outlined. The program is aimed at obtaining clinical, genetic and biochemical data on children with one parent whose gonads were exposed to therapeutic radiation before conception. First results obtained show that there is no contraindication against radiotherapy. However, it is recommended to consult a geneticist in such cases. (author)

  2. gPGA: GPU Accelerated Population Genetics Analyses.

    Directory of Open Access Journals (Sweden)

    Chunbao Zhou

    Full Text Available The isolation with migration (IM model is important for studies in population genetics and phylogeography. IM program applies the IM model to genetic data drawn from a pair of closely related populations or species based on Markov chain Monte Carlo (MCMC simulations of gene genealogies. But computational burden of IM program has placed limits on its application.With strong computational power, Graphics Processing Unit (GPU has been widely used in many fields. In this article, we present an effective implementation of IM program on one GPU based on Compute Unified Device Architecture (CUDA, which we call gPGA.Compared with IM program, gPGA can achieve up to 52.30X speedup on one GPU. The evaluation results demonstrate that it allows datasets to be analyzed effectively and rapidly for research on divergence population genetics. The software is freely available with source code at https://github.com/chunbaozhou/gPGA.

  3. Preimplantation genetic diagnosis

    DEFF Research Database (Denmark)

    Bay, Bjorn; Ingerslev, Hans Jakob; Lemmen, Josephine Gabriela

    2016-01-01

    OBJECTIVE: To study whether women conceiving after preimplantation genetic diagnosis (PGD) and their children have greater risks of adverse pregnancy and birth outcomes compared with children conceived spontaneously or after IVF with or without intracytoplasmic sperm injection (ICSI). DESIGN...

  4. Genetics and Neuromuscular Diseases

    Science.gov (United States)

    ... Testing that reveals a young child’s genet- ic destiny may affect relationships within the family or may ... linked inheritance don’t apply at all. An embryo receives its mitochondria from the mother’s egg cell, ...

  5. LSD and Genetic Damage

    Science.gov (United States)

    Dishotsky, Norman I.; And Others

    1971-01-01

    Reviews studies of the effects of lysergic acid diethylamide (LSD) on man and other organisms. Concludes that pure LSD injected in moderate doses does not cause chromosome or detectable genetic damage and is not a teratogen or carcinogen. (JM)

  6. Genetics Home Reference: piebaldism

    Science.gov (United States)

    ... be a feature of other conditions, such as Waardenburg syndrome ; these conditions have other genetic causes and additional ... 140S. Review. Citation on PubMed Spritz RA. Piebaldism, Waardenburg syndrome, and related disorders of melanocyte development. Semin Cutan ...

  7. Genetics Home Reference: sialuria

    Science.gov (United States)

    ... inheritance of sialuria, an inborn error of feedback inhibition. Am J Hum Genet. 2001 Jun;68(6): ... Links Data Files & API Site Map Subscribe Customer Support USA.gov Copyright Privacy Accessibility FOIA Viewers & Players ...

  8. 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...... to the number of patients suffering from the disease. This hypothesis is based on a study of bipolar disorder....

  9. Genetics of Diabetes

    Science.gov (United States)

    ... A A A Listen En Español Genetics of Diabetes You've probably wondered how you developed diabetes. ... to develop diabetes than others. What Leads to Diabetes? Type 1 and type 2 diabetes have different ...

  10. [The genetics of addictions].

    Science.gov (United States)

    Ibañez Cuadrado, Angela

    2008-01-01

    The addictions are common chronic psychiatric diseases which represent a serious worldwide public-health problem. They have a high prevalence and negative effects at individual, family and societal level, with a high sanitary cost. Epidemiological genetic research has revealed that addictions are moderately to highly heritable. Also the investigation has evidenced that environmental and genetic factors contribute to individual differences in vulnerability to addictions. Advances in the neurobiology of addiction joined to the development of new molecular genetic technologies, have led to the identification of a variety of underlying genes and pathways in addiction process, leading to the description of common molecular mechanisms in substance and behaviour dependencies. Identifying gene-environment interactions is a crucial issue in future research. Other major goal in genetic research is the identification of new therapeutic targets for treatment and prevention.

  11. Genetics for the ophthalmologist

    Directory of Open Access Journals (Sweden)

    Karthikeyan A Sadagopan

    2012-01-01

    Full Text Available The eye has played a major role in human genomics including gene therapy. It is the fourth most common organ system after integument (skin, hair and nails, nervous system, and musculoskeletal system to be involved in genetic disorders. The eye is involved in single gene disorders and those caused by multifactorial etiology. Retinoblastoma was the first human cancer gene to be cloned. Leber hereditary optic neuropathy was the first mitochondrial disorder described. X-Linked red-green color deficiency was the first X-linked disorder described. The eye, unlike any other body organ, allows directly visualization of genetic phenomena such as skewed X-inactivation in the fundus of a female carrier of ocular albinism. Basic concepts of genetics and their application to clinical ophthalmological practice are important not only in making a precise diagnosis and appropriate referral, but also in management and genetic counseling.

  12. Genetics Home Reference: sitosterolemia

    Science.gov (United States)

    ... also helps regulate cholesterol levels in a similar fashion; normally about 50 percent of cholesterol in the ... 10 All Bulletins Features What is direct-to-consumer genetic testing? What are genome editing and CRISPR- ...

  13. Review of genetic concepts

    International Nuclear Information System (INIS)

    Robinson, A.

    1984-01-01

    In recent years, practitioners of medicine have become increasingly aware of the importance of genetics in the understanding of physical and mental health and in the management of disease. The last decades have witnessed unprecedented developments in genetics that have increased our understanding of the basic processes of heredity enormously. New techniques and understanding have provided insights directly applicable to medicine. The fundamental fact of heredity may be considered the ability of living organisms to produce offspring that resemble their parents more than others. One of the basic characteristics of the human condition is the uniqueness and diversity of all individuals. This results from their genetic individuality (with the exception of identical twins) and the interaction of the genetic constitution (the genome) with the environment, which is generally unique to the individual as well. In short, the interaction of genes with the environment is what confers biologic uniqueness to all humans

  14. Specific Genetic Disorders

    Science.gov (United States)

    ... Care Genomic Medicine Working Group New Horizons and Research Patient Management Policy and Ethics Issues Quick Links for Patient Care Education All About the Human Genome Project Fact Sheets Genetic Education Resources for ...

  15. Genetic Mutations in Cancer

    Science.gov (United States)

    Many different types of genetic mutations are found in cancer cells. This infographic outlines certain types of alterations that are present in cancer, such as missense, nonsense, frameshift, and chromosome rearrangements.

  16. Genetic Sample Inventory - NRDA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This database archives genetic tissue samples from marine mammals collected in the North-Central Gulf of Mexico from 2010-2015. The collection includes samples from...

  17. Regulation of Genetic Tests

    Science.gov (United States)

    ... for Genomics Research Intellectual Property Issues in Genetics Archive Online Bioethics Resources Privacy in Genomics Regulation of ... are not regulated, meaning that they go to market without any independent analysis to verify the claims ...

  18. Genetics of osteoarthritis.

    Science.gov (United States)

    Rodriguez-Fontenla, Cristina; Gonzalez, Antonio

    2015-01-01

    Osteoarthritis (OA) is a complex disease caused by the interaction of multiple genetic and environmental factors. This review focuses on the studies that have contributed to the discovery of genetic susceptibility factors in OA. The most relevant associations discovered until now are discussed in detail: GDF-5, 7q22 locus, MCF2L, DOT1L, NCOA3 and also some important findings from the arcOGEN study. Moreover, the different approaches that can be used to minimize the specific problems of the study of OA genetics are discussed. These include the study of microsatellites, phenotype standardization and other methods such as meta-analysis of GWAS and gene-based analysis. It is expected that these new approaches contribute to finding new susceptibility genetic factors for OA. Copyright © 2014 Elsevier España, S.L.U. All rights reserved.

  19. Evaluating human genetic diversity

    National Research Council Canada - National Science Library

    ... into human evolution and origins and serving as a springboard for important medical research. It also addresses issues of confidentiality and individual privacy for participants in genetic diversity research studies.

  20. Genetics Home Reference: hypercholesterolemia

    Science.gov (United States)

    ... Encyclopedia: Familial hypercholesterolemia Encyclopedia: High blood cholesterol and triglycerides Encyclopedia: Xanthoma Health Topic: Cholesterol Health Topic: High Cholesterol in Children and Teens Health Topic: Lipid Metabolism Disorders Genetic and Rare Diseases Information Center (1 ...

  1. Genetics of bipolar disorder

    Directory of Open Access Journals (Sweden)

    Kerner B

    2014-02-01

    Full Text Available Berit Kerner Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA Abstract: Bipolar disorder is a common, complex genetic disorder, but the mode of transmission remains to be discovered. Many researchers assume that common genomic variants carry some risk for manifesting the disease. The research community has celebrated the first genome-wide significant associations between common single nucleotide polymorphisms (SNPs and bipolar disorder. Currently, attempts are under way to translate these findings into clinical practice, genetic counseling, and predictive testing. However, some experts remain cautious. After all, common variants explain only a very small percentage of the genetic risk, and functional consequences of the discovered SNPs are inconclusive. Furthermore, the associated SNPs are not disease specific, and the majority of individuals with a “risk” allele are healthy. On the other hand, population-based genome-wide studies in psychiatric disorders have rediscovered rare structural variants and mutations in genes, which were previously known to cause genetic syndromes and monogenic Mendelian disorders. In many Mendelian syndromes, psychiatric symptoms are prevalent. Although these conditions do not fit the classic description of any specific psychiatric disorder, they often show nonspecific psychiatric symptoms that cross diagnostic boundaries, including intellectual disability, behavioral abnormalities, mood disorders, anxiety disorders, attention deficit, impulse control deficit, and psychosis. Although testing for chromosomal disorders and monogenic Mendelian disorders is well established, testing for common variants is still controversial. The standard concept of genetic testing includes at least three broad criteria that need to be fulfilled before new genetic tests should be introduced: analytical validity, clinical validity, and clinical utility. These criteria are

  2. Genetics and developmental biology

    International Nuclear Information System (INIS)

    Barnett, W.E.

    1975-01-01

    Progress is reported on research activities in the fields of mutagenesis in Haemophilus influenzae and Escherichia coli; radioinduced chromosomal aberrations in mammalian germ cells; effects of uv radiation on xeroderma pigmentosum skin cells; mutations in Chinese hamster ovary cells; radioinduced hemoglobin variants in the mouse; analysis of mutants in yeast; Drosophila genetics; biochemical genetics of Neurospora; DNA polymerase activity in Xenopus laevis oocytes; uv-induced damage in Bacillus subtilis; and others

  3. Christianity, health, and genetics.

    Science.gov (United States)

    Smith, David H

    2009-02-15

    Health is an intrinsic value that Christians should respect, but it is not the highest value. Christians should be willing to jeopardize their own health for the health of others, and should repudiate any idea that genetic problems are the result of sin. Rather, sin leads us to make genetic problems harder to live with than they should be. (c) 2009 Wiley-Liss, Inc.

  4. Somatic and genetic effects

    International Nuclear Information System (INIS)

    Broerse, J.J.; Barendsen, G.W.; Kal, H.B.; Kogel, A.J. van der

    1983-01-01

    This book contains the extended abstracts of the contributions of the poster workshop sessions on somatic and genetic effects of the 7th international congress of radiation research. They cover the following main topics: haematopoietic and immune systems, mechanisms of late effects in various tissues, endogenous and exogenous factors in radiation carcinogenesis, teratogenic effects, genetic effects, in vitro transformation, tumour induction in different tissues, carcinogenesis in incorporated tissues, cancer epidemology and risk assessment. refs.; figs.; tabs

  5. Genetic algorithms applied to nuclear reactor design optimization

    International Nuclear Information System (INIS)

    Pereira, C.M.N.A.; Schirru, R.; Martinez, A.S.

    2000-01-01

    A genetic algorithm is a powerful search technique that simulates natural evolution in order to fit a population of computational structures to the solution of an optimization problem. This technique presents several advantages over classical ones such as linear programming based techniques, often used in nuclear engineering optimization problems. However, genetic algorithms demand some extra computational cost. Nowadays, due to the fast computers available, the use of genetic algorithms has increased and its practical application has become a reality. In nuclear engineering there are many difficult optimization problems related to nuclear reactor design. Genetic algorithm is a suitable technique to face such kind of problems. This chapter presents applications of genetic algorithms for nuclear reactor core design optimization. A genetic algorithm has been designed to optimize the nuclear reactor cell parameters, such as array pitch, isotopic enrichment, dimensions and cells materials. Some advantages of this genetic algorithm implementation over a classical method based on linear programming are revealed through the application of both techniques to a simple optimization problem. In order to emphasize the suitability of genetic algorithms for design optimization, the technique was successfully applied to a more complex problem, where the classical method is not suitable. Results and comments about the applications are also presented. (orig.)

  6. Contemporary Genetics for Gender Researchers: Not Your Grandma's Genetics Anymore

    Science.gov (United States)

    Salk, Rachel H.; Hyde, Janet S.

    2012-01-01

    Over the past century, much of genetics was deterministic, and feminist researchers framed justified criticisms of genetics research. However, over the past two decades, genetics research has evolved remarkably and has moved far from earlier deterministic approaches. Our article provides a brief primer on modern genetics, emphasizing contemporary…

  7. 50. Brazilian congress on genetics. 50 years developing genetics. Abstracts

    International Nuclear Information System (INIS)

    2004-01-01

    Use of radioisotopes and ionizing radiations in genetics is presented. Several aspects related to men, animals,plants and microorganisms are reported highlighting biological radiation effects, evolution, mutagenesis and genetic engineering. Genetic mapping, gene mutations, genetic diversity, DNA damages, plant cultivation and plant grow are studied as well

  8. Genetics & sport: bioethical concerns.

    Science.gov (United States)

    Miah, Andy

    2012-12-01

    This paper provides an overview of the ethical issues pertaining to the use of genetic insights and techniques in sport. Initially, it considers a range of scientific findings that have stimulated debate about the ethical issues associated with genetics applied to sport. It also outlines some of the early policy responses to these discoveries from world leading sports organizations, along with knowledge about actual use of gene technologies in sport. Subsequently, it considers the challenges with distinguishing between therapeutic use and human enhancement within genetic science, which is a particularly important issue for the world of sport. Next, particular attention is given to the use of genetic information, which raises questions about the legitimacy and reliability of genetic tests, along with the potential public value of having DNA databanks to economize in health care. Finally, the ethics of gene transfer are considered, inviting questions into the values of sport and humanity. It argues that, while gene modification may seem conceptually similar to other forms of doping, the requirements upon athletes are such that new forms of enhancement become increasingly necessary to discover. Insofar as genetic science is able to create safer, more effective techniques of human modification, then it may be an appealing route through which to modify athletes to safeguard the future of elite sports as enterprises of human excellence.

  9. Genetic and environmental interactions

    International Nuclear Information System (INIS)

    Strong, L.C.

    1977-01-01

    Cancer may result from a multistage process occurring over a long period of time. Presumably, initial and progressive stages of carcinogenesis may be modified by both genetic and environmental factors. Theoretically, genetic factors may alter susceptibility to the carcinogenic effects of an environmental agent at the initial exposure due to variation in metabolism of the carcinogen or variation in specific target cell response to the active carcinogen, or during the latent phase due to numerous factors that might increase the probability of tumor expression, including growth-promoting factors or immunodeficiency states. Observed genetic and environmental interactions in carcinogenesis include an association between genetically determined inducibility of aryl hydrocarbon hydroxylase and smoking-related cancers, familial susceptibility to certain environmental carcinogens, an association between hereditary disorders of mutagenesis and carcinogenesis, and enhancement of tissue-specific, dominantly inherited tumor predisposition by radiation. Multiple primary tumors occur frequently in genetically predisposed individuals. Specific markers for susceptibility must be sought in order that high-risk individuals be identified and appropriate measures taken for early cancer detection or prevention. Study of the nature of the genetically determined susceptibility and interactions with environmental agents may be revealing in the understanding of carcinogenesis in general

  10. High genetic diversity of Jatropha curcas assessed by ISSR.

    Science.gov (United States)

    Díaz, B G; Argollo, D M; Franco, M C; Nucci, S M; Siqueira, W J; de Laat, D M; Colombo, C A

    2017-05-31

    Jatropha curcas L. is a highly promising oilseed for sustainable production of biofuels and bio-kerosene due to its high oil content and excellent quality. However, it is a perennial and incipiently domesticated species with none stable cultivar created until now despite genetic breeding programs in progress in several countries. Knowledge of the genetic structure and diversity of the species is a necessary step for breeding programs. The molecular marker can be used as a tool for speed up the process. This study was carried out to assess genetic diversity of a germplasm bank represented by J. curcas accessions from different provenance beside interspecific hybrid and backcrosses generated by IAC breeding programs using inter-simple sequence repeat markers. The molecular study revealed 271 bands of which 98.9% were polymorphic with an average of 22.7 polymorphic bands per primer. Genetic diversity of the germplasm evaluated was slightly higher than other germplasm around the world and ranged from 0.55 to 0.86 with an average of 0.59 (Jaccard index). Cluster analysis (UPGMA) revealed no clear grouping as to the geographical origin of accessions, consistent with genetic structure analysis using the Structure software. For diversity analysis between groups, accessions were divided into eight groups by origin. Nei's genetic distance between groups was 0.14. The results showed the importance of Mexican accessions, congeneric wild species, and interspecific hybrids for conservation and development of new genotypes in breeding programs.

  11. Genetics, genomes and cloning the biotechnology revolution

    CERN Document Server

    CERN. Geneva

    1999-01-01

    As this century draws to a close, spectacular advances in the fields of genomics and genetics are opening up dramatic new horizons for medicine. For much of the 20th century, genetic research has focused on rare diseases caused by mutations in a particular gene. However, more recently it has been realised that common genetic variations (polymorphisms), interacting with the environment, can influence an individual's susceptibility to diseases widely represented in our populations (e.g. mental illness and asthma), redefining the term "genetic disease". Officially starting in 1990, the Human Genome Project was a $3-billion, 15-year program to find the estimated 80,000 human genes and determine the sequence of the 3 billion DNA building blocks that underlie all of human biology and its diversity. The resulting boom in genetic information and technologies, not only from humans, but from many other organisms, means that we now have new tools to understand and treat normal and disease states. This information is bei...

  12. Molecular genetics of breast cancer

    International Nuclear Information System (INIS)

    Radice, P.; Pierotti, M. A.

    1997-01-01

    In the last two decades, molecular studies have enlightened the complexity of the genetic alterations that occur in breast cancer cells. To date, more than 40 different genes or loci have been found to be altered in breast carcinomas. Although some of these genes, as for example ERBB2, appear to be mutated in a high proportion of cases, their mechanism of action and their role in the different stages of cancer development are still poorly understood. More recently, two major determinants of the inherited predisposition to breast cancer, BRCA1 and BRCA2, have been isolated. As a consequence, it is now possible to screen families with a positive history of breast carcinomas for the identification of mutations carriers, in order to address these individuals into adequate programs of cancer surveillance and prevention

  13. 75 FR 11840 - Biorefinery Assistance Program

    Science.gov (United States)

    2010-03-12

    ... 0570-0055. Nondiscrimination Statement USDA prohibits discrimination in all its programs and activities..., sex, marital status, familial status, parental status, religion, sexual orientation, genetic... of discrimination, write to USDA, Director, Office of Civil Rights, 1400 Independence Avenue, SW...

  14. Evolution of Strategies for "Prisoner's Dilemma" using Genetic Algorithm

    OpenAIRE

    Heinz, Jan

    2010-01-01

    The subject of this thesis is the software application "Prisoner's Dilemma". The program creates a population of players of "Prisoner's Dilemma", has them play against each other, and - based on their results - performs an evolution of their strategies by means of a genetic algorithm (selection, mutation, and crossover). The program was written in Microsoft Visual Studio, in the C++ programming language, and its interface makes use of the .NET Framework. The thesis includes examples of strate...

  15. [Genetic aspects of genealogy].

    Science.gov (United States)

    Tetushkin, E Iu

    2011-11-01

    The supplementary historical discipline genealogy is also a supplementary genetic discipline. In its formation, genetics borrowed from genealogy some methods of pedigree analysis. In the 21th century, it started receiving contribution from computer-aided genealogy and genetic (molecular) genealogy. The former provides novel tools for genetics, while the latter, which employing genetic methods, enriches genetics with new evidence. Genealogists formulated three main laws ofgenealogy: the law of three generations, the law of doubling the ancestry number, and the law of declining ancestry. The significance and meaning of these laws can be fully understood only in light of genetics. For instance, a controversy between the exponential growth of the number of ancestors of an individual, i.e., the law of doubling the ancestry number, and the limited number of the humankind is explained by the presence of weak inbreeding because of sibs' interference; the latter causes the pedigrees' collapse, i.e., explains also the law of diminishing ancestry number. Mathematic modeling of pedigrees' collapse presented in a number of studies showed that the number of ancestors of each individual attains maximum in a particular generation termed ancestry saturated generation. All representatives of this and preceding generation that left progeny are common ancestors of all current members of the population. In subdivided populations, these generations are more ancient than in panmictic ones, whereas in small isolates and social strata with limited numbers of partners, they are younger. The genealogical law of three generations, according to which each hundred years contain on average three generation intervals, holds for generation lengths for Y-chromosomal DNA, typically equal to 31-32 years; for autosomal and mtDNA, this time is somewhat shorter. Moving along ascending lineas, the number of genetically effective ancestors transmitting their DNA fragment to descendants increases far

  16. Genetics of human hydrocephalus

    Science.gov (United States)

    Williams, Michael A.; Rigamonti, Daniele

    2006-01-01

    Human hydrocephalus is a common medical condition that is characterized by abnormalities in the flow or resorption of cerebrospinal fluid (CSF), resulting in ventricular dilatation. Human hydrocephalus can be classified into two clinical forms, congenital and acquired. Hydrocephalus is one of the complex and multifactorial neurological disorders. A growing body of evidence indicates that genetic factors play a major role in the pathogenesis of hydrocephalus. An understanding of the genetic components and mechanism of this complex disorder may offer us significant insights into the molecular etiology of impaired brain development and an accumulation of the cerebrospinal fluid in cerebral compartments during the pathogenesis of hydrocephalus. Genetic studies in animal models have started to open the way for understanding the underlying pathology of hydrocephalus. At least 43 mutants/loci linked to hereditary hydrocephalus have been identified in animal models and humans. Up to date, 9 genes associated with hydrocephalus have been identified in animal models. In contrast, only one such gene has been identified in humans. Most of known hydrocephalus gene products are the important cytokines, growth factors or related molecules in the cellular signal pathways during early brain development. The current molecular genetic evidence from animal models indicate that in the early development stage, impaired and abnormal brain development caused by abnormal cellular signaling and functioning, all these cellular and developmental events would eventually lead to the congenital hydrocephalus. Owing to our very primitive knowledge of the genetics and molecular pathogenesis of human hydrocephalus, it is difficult to evaluate whether data gained from animal models can be extrapolated to humans. Initiation of a large population genetics study in humans will certainly provide invaluable information about the molecular and cellular etiology and the developmental mechanisms of human

  17. Genetic population structure of muskellunge in the Great Lakes

    Science.gov (United States)

    Kapuscinski, Kevin L.; Sloss, Brian L.; Farrell, John M.

    2013-01-01

    We quantified genetic relationships among Muskellunge Esox masquinongy from 15 locations in the Great Lakes to determine the extent and distribution of measurable population structure and to identify appropriate spatial scales for fishery management and genetic conservation. We hypothesized that Muskellunge from each area represented genetically distinct populations, which would be evident from analyses of genotype data. A total of 691 Muskellunge were sampled (n = 10–127/site) and genetic data were collected at 13 microsatellite loci. Results from a suite of analyses (including pairwise genetic differentiation, Bayesian admixture prediction, analysis of molecular variance, and tests of isolation by distance) indicated the presence of nine distinct genetic groups, including two that were approximately 50 km apart. Geographic proximity and low habitat complexity seemed to facilitate genetic similarity among areas, whereas Muskellunge from areas of greater habitat heterogeneity exhibited high differentiation. Muskellunge from most areas contained private alleles, and mean within-area genetic variation was similar to that reported for other freshwater fishes. Management programs aimed at conserving the broader diversity and long-term sustainability of Muskellunge could benefit by considering the genetically distinct groups as independent fisheries, and individual spawning and nursery habitats could subsequently be protected to conserve the evolutionary potential of Muskellunge.

  18. How Are Genetic Conditions Treated or Managed?

    Science.gov (United States)

    ... mtDNA Resources Help Me Understand Genetics Share: Email Facebook Twitter Home Help Me Understand Genetics Genetic Consultation How are genetic conditions treated or managed? How are genetic conditions treated or managed? Many ...

  19. Integrated genetic analysis microsystems

    International Nuclear Information System (INIS)

    Lagally, Eric T; Mathies, Richard A

    2004-01-01

    With the completion of the Human Genome Project and the ongoing DNA sequencing of the genomes of other animals, bacteria, plants and others, a wealth of new information about the genetic composition of organisms has become available. However, as the demand for sequence information grows, so does the workload required both to generate this sequence and to use it for targeted genetic analysis. Microfabricated genetic analysis systems are well poised to assist in the collection and use of these data through increased analysis speed, lower analysis cost and higher parallelism leading to increased assay throughput. In addition, such integrated microsystems may point the way to targeted genetic experiments on single cells and in other areas that are otherwise very difficult. Concomitant with these advantages, such systems, when fully integrated, should be capable of forming portable systems for high-speed in situ analyses, enabling a new standard in disciplines such as clinical chemistry, forensics, biowarfare detection and epidemiology. This review will discuss the various technologies available for genetic analysis on the microscale, and efforts to integrate them to form fully functional robust analysis devices. (topical review)

  20. Genetics of gallstone disease.

    Directory of Open Access Journals (Sweden)

    Mittal B

    2002-04-01

    Full Text Available Gallstone disease is a complex disorder where both environmental and genetic factors contribute towards susceptibility to the disease. Epidemiological and family studies suggest a strong genetic component in the causation of this disease. Several genetically derived phenotypes in the population are responsible for variations in lipoprotein types, which in turn affect the amount of cholesterol available in the gall bladder. The genetic polymorphisms in various genes for apo E, apo B, apo A1, LDL receptor, cholesteryl ester transfer and LDL receptor-associated protein have been implicated in gallstone formation. However, presently available information on genetic differences is not able to account for a large number of gallstone patients. The molecular studies in the animal models have not only confirmed the present paradigm of gallstone formation but also helped in identification of novel genes in humans, which might play an important role in pathogenesis of the disease. Precise understanding of such genes and their molecular mechanisms may provide the basis of new targets for rational drug designs and dietary interventions.

  1. Genetic classes and genetic categories : Protecting genetic groups through data protection law

    NARCIS (Netherlands)

    Hallinan, Dara; de Hert, Paul; Taylor, L.; Floridi, L.; van der Sloot, B.

    2017-01-01

    Each person shares genetic code with others. Thus, one individual’s genome can reveal information about other individuals. When multiple individuals share aspects of genetic architecture, they form a ‘genetic group’. From a social and legal perspective, two types of genetic group exist: Those which

  2. ADAM: A computer program to simulate selective-breeding schemes for animals

    DEFF Research Database (Denmark)

    Pedersen, L D; Sørensen, A C; Henryon, M

    2009-01-01

    ADAM is a computer program that models selective breeding schemes for animals using stochastic simulation. The program simulates a population of animals and traces the genetic changes in the population under different selective breeding scenarios. It caters to different population structures......, genetic models, selection strategies, and mating designs. ADAM can be used to evaluate breeding schemes and generate genetic data to test statistical tools...

  3. Genetic and physiology basis of the quality of livestock products.

    Directory of Open Access Journals (Sweden)

    Marcello Mele

    2011-02-01

    Full Text Available The animal research gives more attention, for more than twenty years, to the improvement of food quality, because this aspect plays an important role in the consumer choice. In this paper are browsed the principal foods of animal origin (milk, meat and eggs, paying attention on the actual genetic and physiologic knowledge, which influence the quality characteristic. Particularly, we examined the role of Quantitative Genetic in bovine and swine and the growing knowledge about animal genomes and individuation of QTL. Information on genomic regions that control QTL, allow to organize genetic improvement programs, using Markers Assisted Selection (MAS and Markers Assisted Introgression (MAI. Moreover are reported the knowledge about metabolic processes that influence quality especially on lipid and protein component. About other productions are considered the physiology of eggs production and the genetic improvement of hens. Finally the qualitative aspects about poultry and rabbit meat and the actual genetic improvement strategy are reported.

  4. The importance and implication of genetic resources in agriculture

    Directory of Open Access Journals (Sweden)

    Milošević Mirjana

    2010-01-01

    Full Text Available The maintenance and preservation of biodiversity is going through the processes of conservation and restoration of disturbed ecosystems and habitats, as well as the preservation and recovery of species. Genetic diversity means the variety and total number of genes contained in plant and animal species and microorganisms. Genetic diversity is the basic unit of diversity, which is responsible for differences between individuals, populations and species. Genetic diversity is very important for the preservation of biodiversity and can be saved in several ways. Part of the germplasm is maintained through breeding programs as they evaluate germplasm stored and used as a source of needed diversity. The Convention on Biological Diversity is one of the most important international agreements to protect nature and conserve genetic resources. International treaties governing the use of genetic resources for food and agriculture are a way to ensure the conservation and sustainable use of plant resources for food and agriculture, and to regulate the rights of farmers.

  5. Stochastic search in structural optimization - Genetic algorithms and simulated annealing

    Science.gov (United States)

    Hajela, Prabhat

    1993-01-01

    An account is given of illustrative applications of genetic algorithms and simulated annealing methods in structural optimization. The advantages of such stochastic search methods over traditional mathematical programming strategies are emphasized; it is noted that these methods offer a significantly higher probability of locating the global optimum in a multimodal design space. Both genetic-search and simulated annealing can be effectively used in problems with a mix of continuous, discrete, and integer design variables.

  6. Genetics of eosinophilic esophagitis.

    Science.gov (United States)

    Kottyan, L C; Rothenberg, M E

    2017-05-01

    Eosinophilic esophagitis (EoE) is a chronic, allergic disease associated with marked mucosal eosinophil accumulation. EoE disease risk is multifactorial and includes environmental and genetic factors. This review will focus on the contribution of genetic variation to EoE risk, as well as the experimental tools and statistical methodology used to identify EoE risk loci. Specific disease-risk loci that are shared between EoE and other allergic diseases (TSLP, LRRC32) or unique to EoE (CAPN14), as well as Mendellian Disorders associated with EoE, will be reviewed in the context of the insight that they provide into the molecular pathoetiology of EoE. We will also discuss the clinical opportunities that genetic analyses provide in the form of decision support tools, molecular diagnostics, and novel therapeutic approaches.

  7. Archaeal extrachromosomal genetic elements

    DEFF Research Database (Denmark)

    Wang, Haina; Peng, Nan; Shah, Shiraz Ali

    2015-01-01

    SUMMARY: Research on archaeal extrachromosomal genetic elements (ECEs) has progressed rapidly in the past decade. To date, over 60 archaeal viruses and 60 plasmids have been isolated. These archaeal viruses exhibit an exceptional diversity in morphology, with a wide array of shapes, such as spind......SUMMARY: Research on archaeal extrachromosomal genetic elements (ECEs) has progressed rapidly in the past decade. To date, over 60 archaeal viruses and 60 plasmids have been isolated. These archaeal viruses exhibit an exceptional diversity in morphology, with a wide array of shapes...... on archaeal ECEs has just started to unravel the molecular biology of these genetic entities and their interactions with archaeal hosts, it is expected to accelerate in the next decade....

  8. Crystal Genetics, Inc.

    Science.gov (United States)

    Kermani, Bahram G

    2016-07-01

    Crystal Genetics, Inc. is an early-stage genetic test company, focused on achieving the highest possible clinical-grade accuracy and comprehensiveness for detecting germline (e.g., in hereditary cancer) and somatic (e.g., in early cancer detection) mutations. Crystal's mission is to significantly improve the health status of the population, by providing high accuracy, comprehensive, flexible and affordable genetic tests, primarily in cancer. Crystal's philosophy is that when it comes to detecting mutations that are strongly correlated with life-threatening diseases, the detection accuracy of every single mutation counts: a single false-positive error could cause severe anxiety for the patient. And, more importantly, a single false-negative error could potentially cost the patient's life. Crystal's objective is to eliminate both of these error types.

  9. Whakapapa, genealogy and genetics.

    Science.gov (United States)

    Evans, Donald

    2012-05-01

    This paper provides part of an analysis of the use of the Maori term whakapapa in a study designed to test the compatibility and commensurability of views of members of the indigenous culture of New Zealand with other views of genetic technologies extant in the country. It is concerned with the narrow sense of whakapapa as denoting biological ancestry, leaving the wider sense of whakapapa as denoting cultural identity for discussion elsewhere. The phenomenon of genetic curiosity is employed to facilitate this comparison. Four levels of curiosity are identified, in the Maori data, which penetrate more or less deeply into the psyche of individuals, affecting their health and wellbeing. These phenomena are compared with non-Maori experiences and considerable commonalities are discovered together with a point of marked difference. The results raise important questions for the ethical application of genetic technologies. © 2010 Blackwell Publishing Ltd.

  10. Genetic autonomic disorders.

    Science.gov (United States)

    Axelrod, Felicia B

    2013-03-01

    Genetic disorders affecting the autonomic nervous system can result in abnormal development of the nervous system or they can be caused by neurotransmitter imbalance, an ion-channel disturbance or by storage of deleterious material. The symptoms indicating autonomic dysfunction, however, will depend upon whether the genetic lesion has disrupted peripheral or central autonomic centers or both. Because the autonomic nervous system is pervasive and affects every organ system in the body, autonomic dysfunction will result in impaired homeostasis and symptoms will vary. The possibility of genetic confirmation by molecular testing for specific diagnosis is increasing but treatments tend to remain only supportive and directed toward particular symptoms. Copyright © 2013 Elsevier Inc. All rights reserved.

  11. Genetic consequences of trumpeter swan (Cygnus buccinator) reintroductions

    Science.gov (United States)

    Ransler, F.A.; Quinn, T.W.; Oyler-McCance, S.J.

    2011-01-01

    Relocation programs are often initiated to restore threatened species to previously occupied portions of their range. A primary challenge of restoration efforts is to translocate individuals in a way that prevents loss of genetic diversity and decreases differentiation relative to source populations-a challenge that becomes increasingly difficult when remnant populations of the species are already genetically depauperate. Trumpeter swans were previously extirpated in the entire eastern half of their range. Physical translocations of birds over the last 70 years have restored the species to portions of its historical range. Despite the long history of management, there has been little monitoring of the genetic outcomes of these restoration attempts. We assessed the consequences of this reintroduction program by comparing patterns of genetic variation at 17 microsatellite loci across four restoration flocks (three wild-released, one captive) and their source populations. We found that a wild-released population established from a single source displayed a trend toward reduced genetic diversity relative to and significant genetic differentiation from its source population, though small founder population effects may also explain this pattern. Wild-released flocks restored from multiple populations maintained source levels of genetic variation and lacked significant differentiation from at least one of their sources. Further, the flock originating from a single source revealed significantly lower levels of genetic variation than those established from multiple sources. The distribution of genetic variation in the captive flock was similar to its source. While the case of trumpeter swans provides evidence that restorations from multiple versus single source populations may better preserve natural levels of genetic diversity, more studies are needed to understand the general applicability of this management strategy. ?? 2010 Springer Science+Business Media B.V. (outside

  12. Burkholderia thailandensis: Genetic Manipulation.

    Science.gov (United States)

    Garcia, Erin C

    2017-05-16

    Burkholderia thailandensis is a Gram-negative bacterium endemic to Southeast Asian and northern Australian soils. It is non-pathogenic; therefore, it is commonly used as a model organism for the related human pathogens Burkholderia mallei and Burkholderia pseudomallei. B. thailandensis is relatively easily genetically manipulated and a variety of robust genetic tools can be used in this organism. This unit describes protocols for conjugation, natural transformation, mini-Tn7 insertion, and allelic exchange in B. thailandensis. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

  13. Genetic and epigenetic factors: Role in male infertility

    Directory of Open Access Journals (Sweden)

    M B Shamsi

    2011-01-01

    Full Text Available Genetic factors contribute upto 15%-30% cases of male infertility. Formation of spermatozoa occurs in a sequential manner with mitotic, meiotic, and postmeiotic differentiation phases each of which is controlled by an intricate genetic program. Genes control a variety of physiologic processes, such as hypothalamus-pituitary-gonadal axis, germ cell development, and differentiation. In the era of assisted reproduction technology, it is important to understand the genetic basis of infertility to provide maximum adapted therapeutics and counseling to the couple.

  14. Genetic diversity and landscape genetic structure of otter (Lutra lutra) populations in Europe

    DEFF Research Database (Denmark)

    Mucci, Nadia; Arrendal, Johanna; Ansorge, Hermann

    2010-01-01

    Eurasian otter populations strongly declined and partially disappeared due to global and local causes (habitat destruction, water pollution, human persecution) in parts of their continental range. Conservation strategies, based on reintroduction projects or restoration of dispersal corridors...... and landscape genetic analyses however indicate that local populations are genetically differentiated, perhaps as consequence of post-glacial demographic fluctuations and recent isolation. These results delineate a framework that should be used for implementing conservation programs in Europe, particularly...

  15. Basic concepts of medical genetics, formal genetics, Part 1

    African Journals Online (AJOL)

    Mohammad Saad Zaghloul Salem

    2013-11-15

    Nov 15, 2013 ... maps of gene loci based on information gathered, formerly, ... represented as figure or text interface data. Relevant ... The Egyptian Journal of Medical Human Genetics ... prophylactic management and genetic counseling. 17.

  16. Genetic Causes of Rickets

    Science.gov (United States)

    Acar, Sezer; Demir, Korcan; Shi, Yufei

    2017-01-01

    Rickets is a metabolic bone disease that develops as a result of inadequate mineralization of growing bone due to disruption of calcium, phosphorus and/or vitamin D metabolism. Nutritional rickets remains a significant child health problem in developing countries. In addition, several rare genetic causes of rickets have also been described, which can be divided into two groups. The first group consists of genetic disorders of vitamin D biosynthesis and action, such as vitamin D-dependent rickets type 1A (VDDR1A), vitamin D-dependent rickets type 1B (VDDR1B), vitamin D-dependent rickets type 2A (VDDR2A), and vitamin D-dependent rickets type 2B (VDDR2B). The second group involves genetic disorders of excessive renal phosphate loss (hereditary hypophosphatemic rickets) due to impairment in renal tubular phosphate reabsorption as a result of FGF23-related or FGF23-independent causes. In this review, we focus on clinical, laboratory and genetic characteristics of various types of hereditary rickets as well as differential diagnosis and treatment approaches. PMID:29280738

  17. Genetics Home Reference: citrullinemia

    Science.gov (United States)

    ... belongs to a class of genetic diseases called urea cycle disorders. Learn more about the genes associated with citrullinemia ... GeneReview: Citrin Deficiency GeneReview: Citrullinemia Type I GeneReview: Urea Cycle Disorders Overview MedlinePlus Encyclopedia: Hereditary Urea Cycle Abnormality National ...

  18. Genetic risks from radiation

    International Nuclear Information System (INIS)

    Selby, P.B.

    Two widely-recognized committees, UNSCEAR and BEIR, have reevaluated their estimates of genetic risks from radiation. Their estimates for gene mutations are based on two different approaches, one being the doubling-dose approach and the other being a new direct approach based on an empirical determination of the amount of dominant induced damage in the skeletons of mice in the first generation following irradiation. The estimates made by these committees are in reasonably good agreement and suggest that the genetic risks from present exposures resultng from nuclear power production are small. There is room for much improvement in the reliability of the risk estimates. The relatively new approach of measuring the amount of induced damage to the mouse skeleton shows great promise of improving knowledge about how changes in the mutation frequency affect the incidence of genetic disorders. Such findings may have considerable influence on genetic risk estimates for radiation and on the development of risk estimates for other less-well-understood environmental mutagens. (author)

  19. Genetics and acronyms

    Directory of Open Access Journals (Sweden)

    Giovanni Corsello

    2014-06-01

    Full Text Available In a global society as the present, the nomenclature and terminology of diseases must be universally accepted among the specialists. This sentence is particularly true in some fields of medicine, as genetics, in which the progress of knowledge has been particularly rapid in last years.Many genetic disorders were termed using the names of the doctor (or the doctors who discovered and described them.The name of doctors and specialist were also frequently used to term sign and symptoms of diseases, including genetic syndromes.More rarely, a new disease received the name of the first patients described.In some cases the authors clearly proposed acronyms, that rapidly diffused as a good method to term genetic diseases and syndromes.Acronyms can be originated from the initial of main signs and symptoms; in some instances the acronym reproduces a word with other kind of semantic suggestions; some acronyms in their list of initials show also numbers, while others show also the initial of the words related to the physiopathology of disease.In more recent years acronyms were proposed to mark multicentric studies. Proceedings of the 10th International Workshop on Neonatology · Cagliari (Italy · October 22nd-25th, 2014 · The last ten years, the next ten years in Neonatology Guest Editors: Vassilios Fanos, Michele Mussap, Gavino Faa, Apostolos Papageorgiou

  20. Genetic pathways to Neurodegeneration

    Indian Academy of Sciences (India)

    Renu

    The extensive resource on ataxia has led to the development of a clinico-genetic ... Keywords: Cerebellar ataxias, SCAs, ARCAs, NGS, Gene network, iPSCs, .... Besides, mutations in different regions of the same gene result in different ..... integration with population data can also allow focussed testing/screening in specific.