Applications of a formal approach to decipher discrete genetic networks.

Science.gov (United States)

Corblin, Fabien; Fanchon, Eric; Trilling, Laurent

2010-07-20

A growing demand for tools to assist the building and analysis of biological networks exists in systems biology. We argue that the use of a formal approach is relevant and applicable to address questions raised by biologists about such networks. The behaviour of these systems being complex, it is essential to exploit efficiently every bit of experimental information. In our approach, both the evolution rules and the partial knowledge about the structure and the behaviour of the network are formalized using a common constraint-based language. In this article our formal and declarative approach is applied to three biological applications. The software environment that we developed allows to specifically address each application through a new class of biologically relevant queries. We show that we can describe easily and in a formal manner the partial knowledge about a genetic network. Moreover we show that this environment, based on a constraint algorithmic approach, offers a wide variety of functionalities, going beyond simple simulations, such as proof of consistency, model revision, prediction of properties, search for minimal models relatively to specified criteria. The formal approach proposed here deeply changes the way to proceed in the exploration of genetic and biochemical networks, first by avoiding the usual trial-and-error procedure, and second by placing the emphasis on sets of solutions, rather than a single solution arbitrarily chosen among many others. Last, the constraint approach promotes an integration of model and experimental data in a single framework.

A “genetics first” approach to selection

Science.gov (United States)

A different approach for using genomic information in genetic improvement is proposed. Past research in population genetics and animal breeding combined with information on sequence variants suggest the possibility that selection might be able to capture a portion of inbreeding and heterosis effect...

An imaging genetics approach to understanding social influence

OpenAIRE

Emily eFalk; Emily eFalk; Baldwin eWay; Agnes eJasinska

2012-01-01

Normative social influences shape nearly every aspect of our lives, yet the biological processes mediating the impact of these social influences on behavior remain incompletely understood. In this Hypothesis, we outline a theoretical framework and an integrative research approach to the study of social influences on the brain and genetic moderators of such effects. First, we review neuroimaging evidence linking social influence and conformity to the brain’s reward system. We next review neur...

An imaging genetics approach to understanding social influence

OpenAIRE

Falk, Emily B.; Way, Baldwin M.; Jasinska, Agnes J.

2012-01-01

Normative social influences shape nearly every aspect of our lives, yet the biological processes mediating the impact of these social influences on behavior remain incompletely understood. In this Hypothesis, we outline a theoretical framework and an integrative research approach to the study of social influences on the brain and genetic moderators of such effects. First, we review neuroimaging evidence linking social influence and conformity to the brain's reward system. We next review neuro...

Review: domestic animal forensic genetics - biological evidence, genetic markers, analytical approaches and challenges.

Science.gov (United States)

Kanthaswamy, S

2015-10-01

This review highlights the importance of domestic animal genetic evidence sources, genetic testing, markers and analytical approaches as well as the challenges this field is facing in view of the de facto 'gold standard' human DNA identification. Because of the genetic similarity between humans and domestic animals, genetic analysis of domestic animal hair, saliva, urine, blood and other biological material has generated vital investigative leads that have been admitted into a variety of court proceedings, including criminal and civil litigation. Information on validated short tandem repeat, single nucleotide polymorphism and mitochondrial DNA markers and public access to genetic databases for forensic DNA analysis is becoming readily available. Although the fundamental aspects of animal forensic genetic testing may be reliable and acceptable, animal forensic testing still lacks the standardized testing protocols that human genetic profiling requires, probably because of the absence of monetary support from government agencies and the difficulty in promoting cooperation among competing laboratories. Moreover, there is a lack in consensus about how to best present the results and expert opinion to comply with court standards and bear judicial scrutiny. This has been the single most persistent challenge ever since the earliest use of domestic animal forensic genetic testing in a criminal case in the mid-1990s. Crime laboratory accreditation ensures that genetic test results have the courts' confidence. Because accreditation requires significant commitments of effort, time and resources, the vast majority of animal forensic genetic laboratories are not accredited nor are their analysts certified forensic examiners. The relevance of domestic animal forensic genetics in the criminal justice system is undeniable. However, further improvements are needed in a wide range of supporting resources, including standardized quality assurance and control protocols for sample

Air data system optimization using a genetic algorithm

Science.gov (United States)

Deshpande, Samir M.; Kumar, Renjith R.; Seywald, Hans; Siemers, Paul M., III

1992-01-01

An optimization method for flush-orifice air data system design has been developed using the Genetic Algorithm approach. The optimization of the orifice array minimizes the effect of normally distributed random noise in the pressure readings on the calculation of air data parameters, namely, angle of attack, sideslip angle and freestream dynamic pressure. The optimization method is applied to the design of Pressure Distribution/Air Data System experiment (PD/ADS) proposed for inclusion in the Aeroassist Flight Experiment (AFE). Results obtained by the Genetic Algorithm method are compared to the results obtained by conventional gradient search method.

Test interval optimization of safety systems of nuclear power plant using fuzzy-genetic approach

International Nuclear Information System (INIS)

Durga Rao, K.; Gopika, V.; Kushwaha, H.S.; Verma, A.K.; Srividya, A.

2007-01-01

Probabilistic safety assessment (PSA) is the most effective and efficient tool for safety and risk management in nuclear power plants (NPP). PSA studies not only evaluate risk/safety of systems but also their results are very useful in safe, economical and effective design and operation of NPPs. The latter application is popularly known as 'Risk-Informed Decision Making'. Evaluation of technical specifications is one such important application of Risk-Informed decision making. Deciding test interval (TI), one of the important technical specifications, with the given resources and risk effectiveness is an optimization problem. Uncertainty is inherently present in the availability parameters such as failure rate and repair time due to the limitation in assessing these parameters precisely. This paper presents a solution to test interval optimization problem with uncertain parameters in the model with fuzzy-genetic approach along with a case of application from a safety system of Indian pressurized heavy water reactor (PHWR)

Simulation Approach for Timing Analysis of Genetic Logic Circuits

DEFF Research Database (Denmark)

Baig, Hasan; Madsen, Jan

2017-01-01

in a manner similar to electronic logic circuits, but they are much more stochastic and hence much harder to characterize. In this article, we introduce an approach to analyze the threshold value and timing of genetic logic circuits. We show how this approach can be used to analyze the timing behavior...... of single and cascaded genetic logic circuits. We further analyze the timing sensitivity of circuits by varying the degradation rates and concentrations. Our approach can be used not only to characterize the timing behavior but also to analyze the timing constraints of cascaded genetic logic circuits...

Genetic algorithms for adaptive real-time control in space systems

Science.gov (United States)

Vanderzijp, J.; Choudry, A.

1988-01-01

Genetic Algorithms that are used for learning as one way to control the combinational explosion associated with the generation of new rules are discussed. The Genetic Algorithm approach tends to work best when it can be applied to a domain independent knowledge representation. Applications to real time control in space systems are discussed.

Genetic and neural approaches to nuclear transient identification

International Nuclear Information System (INIS)

Almeida, Jose Carlos Soares de; Mol, Antonio Carlos de Abreu; Pereira, Claudio Marcio Nascimento Abreu; Lapa, Celso Marcelo Franklin

2005-01-01

This work presents two approaches for pattern recognition to the same set of reactor signals. The first one describes a possibilistic approach optimized by genetic algorithm. The use of a possibilistic classification provides a natural and consistent classification rules, leading naturally to a good heuristic to handle the 'don't know' response, in case of unrecognized transient, which is fairly desirable in transient classification systems where safety is critical, since wrong or not reliable classifications can be catastrophic. Application of the proposed approach to a nuclear transient identification problem reveals good capability of the genetic algorithm in learning optimized possibilistic classification rules for efficient diagnosis including 'don't know' response. The second one uses two multilayer neural networks (NN). The first NN is responsible for the dynamic identification. This NN uses, as input, a short set (in a moving time window) of recent measurements of each variable avoiding the necessity of using starting events. The second NN is used to validate the instantaneous identification (from the first net) through the validation of each variable. This net is responsible for allowing the system to provide a 'don't know' response. In order to validate both methods, a Nuclear Power Plant (NPP) transient identification problem comprising postulated accidents, simulated for a pressurized water reactor, was proposed in the validation process it has been considered noisy data in order to evaluate the method robustness. Obtained results reveal the ability of the methods in dealing with both dynamic identification of transients and correct 'don't know' response. (author)

Molecular approaches for genetic improvement of seed quality and characterization of genetic diversity in soybean: a critical review.

Science.gov (United States)

Tripathi, Niraj; Khare, Dhirendra

2016-10-01

Soybean is an economically important leguminous crop. Genetic improvements of soybeans have focused on enhancement of seed and oil yield, development of varieties suited to different cropping systems, and breeding resistant/tolerant varieties for various biotic and abiotic stresses. Plant breeders have used conventional breeding techniques for the improvement of these traits in soybean. The conventional breeding process can be greatly accelerated through the application of molecular and genomic approaches. Molecular markers have proved to be a new tool in soybean breeding by enhancing selection efficiency in a rapid and time-bound manner. An overview of molecular approaches for the genetic improvement of soybean seed quality parameters, considering recent applications of marker-assisted selection and 'omics' research, is provided in this article.

Reverse Genetics Approaches for the Development of Influenza Vaccines

Science.gov (United States)

Nogales, Aitor; Martínez-Sobrido, Luis

2016-01-01

Influenza viruses cause annual seasonal epidemics and occasional pandemics of human respiratory disease. Influenza virus infections represent a serious public health and economic problem, which are most effectively prevented through vaccination. However, influenza viruses undergo continual antigenic variation, which requires either the annual reformulation of seasonal influenza vaccines or the rapid generation of vaccines against potential pandemic virus strains. The segmented nature of influenza virus allows for the reassortment between two or more viruses within a co-infected cell, and this characteristic has also been harnessed in the laboratory to generate reassortant viruses for their use as either inactivated or live-attenuated influenza vaccines. With the implementation of plasmid-based reverse genetics techniques, it is now possible to engineer recombinant influenza viruses entirely from full-length complementary DNA copies of the viral genome by transfection of susceptible cells. These reverse genetics systems have provided investigators with novel and powerful approaches to answer important questions about the biology of influenza viruses, including the function of viral proteins, their interaction with cellular host factors and the mechanisms of influenza virus transmission and pathogenesis. In addition, reverse genetics techniques have allowed the generation of recombinant influenza viruses, providing a powerful technology to develop both inactivated and live-attenuated influenza vaccines. In this review, we will summarize the current knowledge of state-of-the-art, plasmid-based, influenza reverse genetics approaches and their implementation to provide rapid, convenient, safe and more effective influenza inactivated or live-attenuated vaccines. PMID:28025504

A multiobjective approach to the genetic code adaptability problem.

Science.gov (United States)

de Oliveira, Lariza Laura; de Oliveira, Paulo S L; Tinós, Renato

2015-02-19

The organization of the canonical code has intrigued researches since it was first described. If we consider all codes mapping the 64 codes into 20 amino acids and one stop codon, there are more than 1.51×10(84) possible genetic codes. The main question related to the organization of the genetic code is why exactly the canonical code was selected among this huge number of possible genetic codes. Many researchers argue that the organization of the canonical code is a product of natural selection and that the code's robustness against mutations would support this hypothesis. In order to investigate the natural selection hypothesis, some researches employ optimization algorithms to identify regions of the genetic code space where best codes, according to a given evaluation function, can be found (engineering approach). The optimization process uses only one objective to evaluate the codes, generally based on the robustness for an amino acid property. Only one objective is also employed in the statistical approach for the comparison of the canonical code with random codes. We propose a multiobjective approach where two or more objectives are considered simultaneously to evaluate the genetic codes. In order to test our hypothesis that the multiobjective approach is useful for the analysis of the genetic code adaptability, we implemented a multiobjective optimization algorithm where two objectives are simultaneously optimized. Using as objectives the robustness against mutation with the amino acids properties polar requirement (objective 1) and robustness with respect to hydropathy index or molecular volume (objective 2), we found solutions closer to the canonical genetic code in terms of robustness, when compared with the results using only one objective reported by other authors. Using more objectives, more optimal solutions are obtained and, as a consequence, more information can be used to investigate the adaptability of the genetic code. The multiobjective approach

Robust reactor power control system design by genetic algorithm

Energy Technology Data Exchange (ETDEWEB)

Lee, Yoon Joon; Cho, Kyung Ho; Kim, Sin [Cheju National University, Cheju (Korea, Republic of)

1998-12-31

The H{sub {infinity}} robust controller for the reactor power control system is designed by use of the mixed weight sensitivity. The system is configured into the typical two-port model with which the weight functions are augmented. Since the solution depends on the weighting functions and the problem is of nonconvex, the genetic algorithm is used to determine the weighting functions. The cost function applied in the genetic algorithm permits the direct control of the power tracking performances. In addition, the actual operating constraints such as rod velocity and acceleration can be treated as design parameters. Compared with the conventional approach, the controller designed by the genetic algorithm results in the better performances with the realistic constraints. Also, it is found that the genetic algorithm could be used as an effective tool in the robust design. 4 refs., 6 figs. (Author)

Robust reactor power control system design by genetic algorithm

Energy Technology Data Exchange (ETDEWEB)

Lee, Yoon Joon; Cho, Kyung Ho; Kim, Sin [Cheju National University, Cheju (Korea, Republic of)

1997-12-31

The H{sub {infinity}} robust controller for the reactor power control system is designed by use of the mixed weight sensitivity. The system is configured into the typical two-port model with which the weight functions are augmented. Since the solution depends on the weighting functions and the problem is of nonconvex, the genetic algorithm is used to determine the weighting functions. The cost function applied in the genetic algorithm permits the direct control of the power tracking performances. In addition, the actual operating constraints such as rod velocity and acceleration can be treated as design parameters. Compared with the conventional approach, the controller designed by the genetic algorithm results in the better performances with the realistic constraints. Also, it is found that the genetic algorithm could be used as an effective tool in the robust design. 4 refs., 6 figs. (Author)

Therapeutic approaches to genetic disorders

African Journals Online (AJOL)

salah

Although prevention is the ideal goal for genetic disorders, various types of therapeutic ... The patient being ... pirical or aimed at controlling or mediating signs and symptoms without care. ... plications and gene therapy approaches .... genes family, have opened a wide and .... cancer where nanoparticles are used to.

Neuro-genetic hybrid approach for the solution of non-convex economic dispatch problem

International Nuclear Information System (INIS)

Malik, T.N.; Asar, A.U.

2009-01-01

ED (Economic Dispatch) is non-convex constrained optimization problem, and is used for both on line and offline studies in power system operation. Conventionally, it is solved as convex problem using optimization techniques by approximating generator input/output characteristic. Curves of monotonically increasing nature thus resulting in an inaccurate dispatch. The GA (Genetic Algorithm) has been used for the solution of this problem owing to its inherent ability to address the convex and non-convex problems equally. This approach brings the solution to the global minimum region of search space in a short time and then takes longer time to converge to near optimal results. GA based hybrid approaches are used to fine tune the near optimal results produced by GA. This paper proposes NGH (Neuro Genetic Hybrid) approach to solve the economic dispatch with valve point effect. The proposed approach combines the GA with the ANN (Artificial Neural Network) using SI (Swarm Intelligence) learning rule. The GA acts as a global optimizer and the neural network fine tunes the GA results to the desired targets. Three machines standard test system has been tested for validation of the approach. Comparing the results with GA and NGH model based on back-propagation learning, the proposed approach gives contrast improvements showing the promise of the approach. (author)

Comparative Approaches to Genetic Discrimination: Chasing Shadows?

Science.gov (United States)

Joly, Yann; Feze, Ida Ngueng; Song, Lingqiao; Knoppers, Bartha M

2017-05-01

Genetic discrimination (GD) is one of the most pervasive issues associated with genetic research and its large-scale implementation. An increasing number of countries have adopted public policies to address this issue. Our research presents a worldwide comparative review and typology of these approaches. We conclude with suggestions for public policy development. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dynamic traffic assignment : genetic algorithms approach

Science.gov (United States)

1997-01-01

Real-time route guidance is a promising approach to alleviating congestion on the nations highways. A dynamic traffic assignment model is central to the development of guidance strategies. The artificial intelligence technique of genetic algorithm...

Optimization of Neuro-Fuzzy System Using Genetic Algorithm for Chromosome Classification

Directory of Open Access Journals (Sweden)

M. Sarosa

2013-09-01

Full Text Available Neuro-fuzzy system has been shown to provide a good performance on chromosome classification but does not offer a simple method to obtain the accurate parameter values required to yield the best recognition rate. This paper presents a neuro-fuzzy system where its parameters can be automatically adjusted using genetic algorithms. The approach combines the advantages of fuzzy logic theory, neural networks, and genetic algorithms. The structure consists of a four layer feed-forward neural network that uses a GBell membership function as the output function. The proposed methodology has been applied and tested on banded chromosome classification from the Copenhagen Chromosome Database. Simulation result showed that the proposed neuro-fuzzy system optimized by genetic algorithms offers advantages in setting the parameter values, improves the recognition rate significantly and decreases the training/testing time which makes genetic neuro-fuzzy system suitable for chromosome classification.

Systems genetics of complex diseases using RNA-sequencing methods

DEFF Research Database (Denmark)

Mazzoni, Gianluca; Kogelman, Lisette; Suravajhala, Prashanth

2015-01-01

Next generation sequencing technologies have enabled the generation of huge quantities of biological data, and nowadays extensive datasets at different ‘omics levels have been generated. Systems genetics is a powerful approach that allows to integrate different ‘omics level and understand the bio...

Approaches to quality management and accreditation in a genetic testing laboratory

Science.gov (United States)

Berwouts, Sarah; Morris, Michael A; Dequeker, Elisabeth

2010-01-01

Medical laboratories, and specifically genetic testing laboratories, provide vital medical services to different clients: clinicians requesting a test, patients from whom the sample was collected, public health and medical-legal instances, referral laboratories and authoritative bodies. All expect results that are accurate and obtained in an efficient and effective manner, within a suitable time frame and at acceptable cost. There are different ways of achieving the end results, but compliance with International Organization for Standardization (ISO) 15189, the international standard for the accreditation of medical laboratories, is becoming progressively accepted as the optimal approach to assuring quality in medical testing. We present recommendations and strategies designed to aid genetic testing laboratories with the implementation of a quality management system, including key aspects such as document control, external quality assessment, internal quality control, internal audit, management review, validation, as well as managing the human side of change. The focus is on pragmatic approaches to attain the levels of quality management and quality assurance required for accreditation according to ISO 15189, within the context of genetic testing. Attention is also given to implementing efficient and effective quality improvement. PMID:20720559

A Genetic Algorithm Approach to the Optimization of a Radioactive Waste Treatment System

International Nuclear Information System (INIS)

Yang, Yeongjin; Lee, Kunjai; Koh, Y.; Mun, J.H.; Kim, H.S.

1998-01-01

This study is concerned with the applications of goal programming and genetic algorithm techniques to the analysis of management and operational problems in the radioactive waste treatment system (RWTS). A typical RWTS is modeled and solved by goal program and genetic algorithm to study and resolve the effects of conflicting objectives such as cost, limitation of released radioactivity to the environment, equipment utilization and total treatable radioactive waste volume before discharge and disposal. The developed model is validated and verified using actual data obtained from the RWTS at Kyoto University in Japan. The solution by goal programming and genetic algorithm would show the optimal operation point which is to maximize the total treatable radioactive waste volume and minimize the released radioactivity of liquid waste even under the restricted resources. The comparison of two methods shows very similar results. (author)

A Hybrid Genetic Algorithm Approach for Optimal Power Flow

Directory of Open Access Journals (Sweden)

Sydulu Maheswarapu

2011-08-01

Full Text Available This paper puts forward a reformed hybrid genetic algorithm (GA based approach to the optimal power flow. In the approach followed here, continuous variables are designed using real-coded GA and discrete variables are processed as binary strings. The outcomes are compared with many other methods like simple genetic algorithm (GA, adaptive genetic algorithm (AGA, differential evolution (DE, particle swarm optimization (PSO and music based harmony search (MBHS on a IEEE30 bus test bed, with a total load of 283.4 MW. Its found that the proposed algorithm is found to offer lowest fuel cost. The proposed method is found to be computationally faster, robust, superior and promising form its convergence characteristics.

Molecular marker systems for Oenothera genetics.

Science.gov (United States)

Rauwolf, Uwe; Golczyk, Hieronim; Meurer, Jörg; Herrmann, Reinhold G; Greiner, Stephan

2008-11-01

The genus Oenothera has an outstanding scientific tradition. It has been a model for studying aspects of chromosome evolution and speciation, including the impact of plastid nuclear co-evolution. A large collection of strains analyzed during a century of experimental work and unique genetic possibilities allow the exchange of genetically definable plastids, individual or multiple chromosomes, and/or entire haploid genomes (Renner complexes) between species. However, molecular genetic approaches for the genus are largely lacking. In this study, we describe the development of efficient PCR-based marker systems for both the nuclear genome and the plastome. They allow distinguishing individual chromosomes, Renner complexes, plastomes, and subplastomes. We demonstrate their application by monitoring interspecific exchanges of genomes, chromosome pairs, and/or plastids during crossing programs, e.g., to produce plastome-genome incompatible hybrids. Using an appropriate partial permanent translocation heterozygous hybrid, linkage group 7 of the molecular map could be assigned to chromosome 9.8 of the classical Oenothera map. Finally, we provide the first direct molecular evidence that homologous recombination and free segregation of chromosomes in permanent translocation heterozygous strains is suppressed.

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

Recent insights into the genetic basis of systemic lupus erythematosus

OpenAIRE

Moser, Kathy L.; Kelly, Jennifer A.; Lessard, Christopher J.; Harley, John B.

2009-01-01

Genetic variation was first shown to be part of the cause of systemic lupus erythematosus (SLE or lupus) in the 1970s with associations in the human leukocyte antigen (HLA) region. Almost four decades later, and with the help of increasingly powerful genetic approaches, more than 25 genes are now known to contribute to the mechanisms that predispose individuals to lupus. Over half of these loci have been discovered in the past two years, underscoring the extraordinary success of recent genome...

Modeling AEC—New Approaches to Study Rare Genetic Disorders

Science.gov (United States)

Koch, Peter J.; Dinella, Jason; Fete, Mary; Siegfried, Elaine C.; Koster, Maranke I.

2015-01-01

Ankyloblepharon-ectodermal defects-cleft lip/palate (AEC) syndrome is a rare monogenetic disorder that is characterized by severe abnormalities in ectoderm-derived tissues, such as skin and its appendages. A major cause of morbidity among affected infants is severe and chronic skin erosions. Currently, supportive care is the only available treatment option for AEC patients. Mutations in TP63, a gene that encodes key regulators of epidermal development, are the genetic cause of AEC. However, it is currently not clear how mutations in TP63 lead to the various defects seen in the patients’ skin. In this review, we will discuss current knowledge of the AEC disease mechanism obtained by studying patient tissue and genetically engineered mouse models designed to mimic aspects of the disorder. We will then focus on new approaches to model AEC, including the use of patient cells and stem cell technology to replicate the disease in a human tissue culture model. The latter approach will advance our understanding of the disease and will allow for the development of new in vitro systems to identify drugs for the treatment of skin erosions in AEC patients. Further, the use of stem cell technology, in particular induced pluripotent stem cells (iPSC), will enable researchers to develop new therapeutic approaches to treat the disease using the patient’s own cells (autologous keratinocyte transplantation) after correction of the disease-causing mutations. PMID:24665072

Genetic algorithm and neural network hybrid approach for job-shop scheduling

OpenAIRE

Zhao, Kai; Yang, Shengxiang; Wang, Dingwei

1998-01-01

Copyright @ 1998 ACTA Press This paper proposes a genetic algorithm (GA) and constraint satisfaction adaptive neural network (CSANN) hybrid approach for job-shop scheduling problems. In the hybrid approach, GA is used to iterate for searching optimal solutions, CSANN is used to obtain feasible solutions during the iteration of genetic algorithm. Simulations have shown the valid performance of the proposed hybrid approach for job-shop scheduling with respect to the quality of solutions and ...

A possibilistic approach for transient identification with 'don't know' response capability optimized by genetic algorithm

International Nuclear Information System (INIS)

Almeida, Jose Carlos S. de; Schirru, Roberto; Pereira, Claudio M.N.A.; Universidade Federal, Rio de Janeiro, RJ

2002-01-01

This work describes a possibilistic approach for transient identification based on the minimum centroids set method, proposed in previous work, optimized by genetic algorithm. The idea behind this method is to split the complex classification problem into small and simple ones, so that the performance in the classification can be increased. In order to accomplish that, a genetic algorithm is used to learn, from realistic simulated data, the optimized time partitions, which the robustness and correctness in the classification are maximized. The use of a possibilistic classification approach propitiates natural and consistent classification rules, leading naturally to a good heuristic to handle the 'don't know 'response, in case of unrecognized transient, which is fairly desirable in transient classification systems where safety is critical. Application of the proposed approach to a nuclear transient indentification problem reveals good capability of the genetic algorithm in learning optimized possibilistic classification rules for efficient diagnosis including 'don't know' response. Obtained results are shown and commented. (author)

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...

Genetic variations in the serotoninergic system contribute to body-mass index in Chinese adolescents.

Directory of Open Access Journals (Sweden)

Chunhui Chen

Full Text Available OBJECTIVE: Obesity has become a worldwide health problem in the past decades. Human and animal studies have implicated serotonin in appetite regulation, and behavior genetic studies have shown that body mass index (BMI has a strong genetic component. However, the roles of genes related to the serotoninergic (5-hydroxytryptamine,5-HT system in obesity/BMI are not well understood, especially in Chinese subjects. SUBJECTS AND DESIGN: With a sample of 478 healthy Chinese volunteers, this study investigated the relation between BMI and genetic variations of the serotoninergic system as characterized by 136 representative polymorphisms. We used a system-level approach to identify SNPs associated with BMI, then estimated their overall contribution to BMI by multiple regression and verified it by permutation. RESULTS: We identified 12 SNPs that made statistically significant contributions to BMI. After controlling for gender and age, four of these SNPs accounted for 7.7% additional variance of BMI. Permutation analysis showed that the probability of obtaining these findings by chance was low (p = 0.015, permuted for 1000 times. CONCLUSION: These results showed that genetic variations in the serotoninergic system made a moderate contribution to individual differences in BMI among a healthy Chinese sample, suggesting that a similar approach can be used to study obesity.

Optimal Design of Pumped Pipeline Systems Using Genetic Algorithm and Mathematical Optimization

Directory of Open Access Journals (Sweden)

Mohammadhadi Afshar

2007-12-01

Full Text Available In recent years, much attention has been paid to the optimal design of pipeline systems. In this study, the problem of pipeline system optimal design has been solved through genetic algorithm and mathematical optimization. Pipe diameters and their thicknesses are considered as decision variables to be designed in a manner that water column separation and excessive pressures are avoided in the event of pump failure. Capabilities of the genetic algorithm and the mathematical programming method are compared for the problem under consideration. For simulation of transient streams, explicit characteristic method is used in which devices such as pumps are defined as boundary conditions of the equations defining the hydraulic behavior of pipe segments. The problem of optimal design of pipeline systems is a constrained problem which is converted to an unconstrained optimization problem using an external penalty function approach. The efficiency of the proposed approaches is verified in one example and the results are presented.

Production of amino acids - Genetic and metabolic engineering approaches.

Science.gov (United States)

Lee, Jin-Ho; Wendisch, Volker F

2017-12-01

The biotechnological production of amino acids occurs at the million-ton scale and annually about 6milliontons of l-glutamate and l-lysine are produced by Escherichia coli and Corynebacterium glutamicum strains. l-glutamate and l-lysine production from starch hydrolysates and molasses is very efficient and access to alternative carbon sources and new products has been enabled by metabolic engineering. This review focusses on genetic and metabolic engineering of amino acid producing strains. In particular, rational approaches involving modulation of transcriptional regulators, regulons, and attenuators will be discussed. To address current limitations of metabolic engineering, this article gives insights on recent systems metabolic engineering approaches based on functional tools and method such as genome reduction, amino acid sensors based on transcriptional regulators and riboswitches, CRISPR interference, small regulatory RNAs, DNA scaffolding, and optogenetic control, and discusses future prospects. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Decision Support System Based on Genetic Algorithm (Case Study: Scheduling in Supply Chain

Directory of Open Access Journals (Sweden)

Mohammad Ali Beheheshtinia

2016-10-01

Full Text Available Nowadays, the application of effective and efficient decisions on complex issues require the use of decision support systems. This Paper provided a decision support system based on the genetic algorithm for production and transportation scheduling problem in a supply chain. It is assumed that there are number of orders that should be produced by suppliers and should be transported to the plant by a transportation fleet. The aim is to assign orders to the suppliers, specify the order of their production, allocate processed orders to the vehicles for transport and to arrange them in a way that minimizes the total delivery time. It has been shown that the complexity of the problem was related to Np-hard and there was no possibility of using accurate methods to solve the problem in a reasonable time. So, the genetic algorithm was used in this paper to solve the problem. By using this decision support system, a new approach to supply chain management was proposed. The analysis of the approach proposed in this study compared to the conventional approaches by the decision support system indicated the preference of our proposed approach

Synthetic biology approaches in cancer immunotherapy, genetic network engineering, and genome editing.

Science.gov (United States)

Chakravarti, Deboki; Cho, Jang Hwan; Weinberg, Benjamin H; Wong, Nicole M; Wong, Wilson W

2016-04-18

Investigations into cells and their contents have provided evolving insight into the emergence of complex biological behaviors. Capitalizing on this knowledge, synthetic biology seeks to manipulate the cellular machinery towards novel purposes, extending discoveries from basic science to new applications. While these developments have demonstrated the potential of building with biological parts, the complexity of cells can pose numerous challenges. In this review, we will highlight the broad and vital role that the synthetic biology approach has played in applying fundamental biological discoveries in receptors, genetic circuits, and genome-editing systems towards translation in the fields of immunotherapy, biosensors, disease models and gene therapy. These examples are evidence of the strength of synthetic approaches, while also illustrating considerations that must be addressed when developing systems around living cells.

Comparison of weighting approaches for genetic risk scores in gene-environment interaction studies.

Science.gov (United States)

Hüls, Anke; Krämer, Ursula; Carlsten, Christopher; Schikowski, Tamara; Ickstadt, Katja; Schwender, Holger

2017-12-16

Weighted genetic risk scores (GRS), defined as weighted sums of risk alleles of single nucleotide polymorphisms (SNPs), are statistically powerful for detection gene-environment (GxE) interactions. To assign weights, the gold standard is to use external weights from an independent study. However, appropriate external weights are not always available. In such situations and in the presence of predominant marginal genetic effects, we have shown in a previous study that GRS with internal weights from marginal genetic effects ("GRS-marginal-internal") are a powerful and reliable alternative to single SNP approaches or the use of unweighted GRS. However, this approach might not be appropriate for detecting predominant interactions, i.e. interactions showing an effect stronger than the marginal genetic effect. In this paper, we present a weighting approach for such predominant interactions ("GRS-interaction-training") in which parts of the data are used to estimate the weights from the interaction terms and the remaining data are used to determine the GRS. We conducted a simulation study for the detection of GxE interactions in which we evaluated power, type I error and sign-misspecification. We compared this new weighting approach to the GRS-marginal-internal approach and to GRS with external weights. Our simulation study showed that in the absence of external weights and with predominant interaction effects, the highest power was reached with the GRS-interaction-training approach. If marginal genetic effects were predominant, the GRS-marginal-internal approach was more appropriate. Furthermore, the power to detect interactions reached by the GRS-interaction-training approach was only slightly lower than the power achieved by GRS with external weights. The power of the GRS-interaction-training approach was confirmed in a real data application to the Traffic, Asthma and Genetics (TAG) Study (N = 4465 observations). When appropriate external weights are unavailable, we

Automatic Laser Pointer Detection Algorithm for Environment Control Device Systems Based on Template Matching and Genetic Tuning of Fuzzy Rule-Based Systems

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F.

2012-04-01

Full Text Available In this paper we propose a new approach for laser-based environment device control systems based on the automatic design of a Fuzzy Rule-Based System for laser pointer detection. The idea is to improve the success rate of the previous approaches decreasing as much as possible the false offs and increasing the success rate in images with laser spot, i.e., the detection of a false laser spot (since this could lead to dangerous situations. To this end, we propose to analyze both, the morphology and color of a laser spot image together, thus developing a new robust algorithm. Genetic Fuzzy Systems have also been employed to improve the laser spot system detection by means of a fine tuning of the involved membership functions thus reducing the system false offs, which is the main objective in this problem. The system presented in this paper, makes use of a Fuzzy Rule-Based System adjusted by a Genetic Algorithm, which, based on laser morphology and color analysis, shows a better success rate than previous approaches.

On Generating Optimal Signal Probabilities for Random Tests: A Genetic Approach

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M. Srinivas

1996-01-01

Full Text Available Genetic Algorithms are robust search and optimization techniques. A Genetic Algorithm based approach for determining the optimal input distributions for generating random test vectors is proposed in the paper. A cost function based on the COP testability measure for determining the efficacy of the input distributions is discussed. A brief overview of Genetic Algorithms (GAs and the specific details of our implementation are described. Experimental results based on ISCAS-85 benchmark circuits are presented. The performance of our GAbased approach is compared with previous results. While the GA generates more efficient input distributions than the previous methods which are based on gradient descent search, the overheads of the GA in computing the input distributions are larger.

Systemic approaches to biodegradation.

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Trigo, Almudena; Valencia, Alfonso; Cases, Ildefonso

2009-01-01

Biodegradation, the ability of microorganisms to remove complex chemicals from the environment, is a multifaceted process in which many biotic and abiotic factors are implicated. The recent accumulation of knowledge about the biochemistry and genetics of the biodegradation process, and its categorization and formalization in structured databases, has recently opened the door to systems biology approaches, where the interactions of the involved parts are the main subject of study, and the system is analysed as a whole. The global analysis of the biodegradation metabolic network is beginning to produce knowledge about its structure, behaviour and evolution, such as its free-scale structure or its intrinsic robustness. Moreover, these approaches are also developing into useful tools such as predictors for compounds' degradability or the assisted design of artificial pathways. However, it is the environmental application of high-throughput technologies from the genomics, metagenomics, proteomics and metabolomics that harbours the most promising opportunities to understand the biodegradation process, and at the same time poses tremendous challenges from the data management and data mining point of view.

Marburg Virus Reverse Genetics Systems

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Kristina Maria Schmidt

2016-06-01

Full Text Available The highly pathogenic Marburg virus (MARV is a member of the Filoviridae family and belongs to the group of nonsegmented negative-strand RNA viruses. Reverse genetics systems established for MARV have been used to study various aspects of the viral replication cycle, analyze host responses, image viral infection, and screen for antivirals. This article provides an overview of the currently established MARV reverse genetic systems based on minigenomes, infectious virus-like particles and full-length clones, and the research that has been conducted using these systems.

Application of genetic algorithm for optimization the safety system of the nuclear reactor

International Nuclear Information System (INIS)

El-Sayed Wahed, M.; Ibrahim, W.Z.; Effat, A.M.

2009-01-01

The purpose of this paper is to present an approach to optimization in which every target is considered as a separate objective to be optimized. Multi-objective optimization is a powerful tool for resolving conflicting objectives in engineering design and numerous other fields. One approach to solve multi-objective optimization problems is the non-dominated sorting genetic algorithm (NSGA). Genetic algorithm (GA) was applied in regarding the choice of the time intervals for the periodic testing of the components of the chimney water injection system (CWIS) of the 22 MW open pool multipurpose reactor (MPR), ETRR-2, at the Egyptian Atomic Energy Authority, has been used as a case study. (authors)

Identifying genetic signatures of selection in a non-model species, alpine gentian (Gentiana nivalis L.), using a landscape genetic approach

DEFF Research Database (Denmark)

Bothwell, H.; Bisbing, S.; Therkildsen, Nina Overgaard

2013-01-01

It is generally accepted that most plant populations are locally adapted. Yet, understanding how environmental forces give rise to adaptive genetic variation is a challenge in conservation genetics and crucial to the preservation of species under rapidly changing climatic conditions. Environmental...... loci, we compared outlier locus detection methods with a recently-developed landscape genetic approach. We analyzed 157 loci from samples of the alpine herb Gentiana nivalis collected across the European Alps. Principle coordinates of neighbor matrices (PCNM), eigenvectors that quantify multi...... variables identified eight more potentially adaptive loci than models run without spatial variables. 3) When compared to outlier detection methods, the landscape genetic approach detected four of the same loci plus 11 additional loci. 4) Temperature, precipitation, and solar radiation were the three major...

Systems Genetics Analysis to Identify the Genetic Modulation of a Glaucoma-Associated Gene.

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Chintalapudi, Sumana R; Jablonski, Monica M

2017-01-01

Loss of retinal ganglion cells (RGCs) is one of the hallmarks of retinal neurodegenerative diseases, glaucoma being one of the most common. Recently, γ-synuclein (SNCG) was shown to be highly expressed in the somas and axons of RGCs. In various mouse models of glaucoma, downregulation of Sncg gene expression correlates with RGC loss. To investigate the regulation of Sncg in RGCs, we used a systems genetics approach to identify a gene that modulates the expression of Sncg, followed by confirmatory studies in both healthy and diseased retinas. We found that chromosome 1 harbors an eQTL that modulates the expression of Sncg in the mouse retina and identified Pfdn2 as the candidate upstream modulator of Sncg expression. Downregulation of Pfdn2 in enriched RGCs causes a concomitant reduction in Sncg. In this chapter, we describe our strategy and methods for identifying and confirming a genetic modulation of a glaucoma-associated gene. A similar method can be applied to other genes expressed in other tissues.

A genetic ensemble approach for gene-gene interaction identification

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Ho Joshua WK

2010-10-01

Full Text Available Abstract Background It has now become clear that gene-gene interactions and gene-environment interactions are ubiquitous and fundamental mechanisms for the development of complex diseases. Though a considerable effort has been put into developing statistical models and algorithmic strategies for identifying such interactions, the accurate identification of those genetic interactions has been proven to be very challenging. Methods In this paper, we propose a new approach for identifying such gene-gene and gene-environment interactions underlying complex diseases. This is a hybrid algorithm and it combines genetic algorithm (GA and an ensemble of classifiers (called genetic ensemble. Using this approach, the original problem of SNP interaction identification is converted into a data mining problem of combinatorial feature selection. By collecting various single nucleotide polymorphisms (SNP subsets as well as environmental factors generated in multiple GA runs, patterns of gene-gene and gene-environment interactions can be extracted using a simple combinatorial ranking method. Also considered in this study is the idea of combining identification results obtained from multiple algorithms. A novel formula based on pairwise double fault is designed to quantify the degree of complementarity. Conclusions Our simulation study demonstrates that the proposed genetic ensemble algorithm has comparable identification power to Multifactor Dimensionality Reduction (MDR and is slightly better than Polymorphism Interaction Analysis (PIA, which are the two most popular methods for gene-gene interaction identification. More importantly, the identification results generated by using our genetic ensemble algorithm are highly complementary to those obtained by PIA and MDR. Experimental results from our simulation studies and real world data application also confirm the effectiveness of the proposed genetic ensemble algorithm, as well as the potential benefits of

A propensity score approach to correction for bias due to population stratification using genetic and non-genetic factors.

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Zhao, Huaqing; Rebbeck, Timothy R; Mitra, Nandita

2009-12-01

Confounding due to population stratification (PS) arises when differences in both allele and disease frequencies exist in a population of mixed racial/ethnic subpopulations. Genomic control, structured association, principal components analysis (PCA), and multidimensional scaling (MDS) approaches have been proposed to address this bias using genetic markers. However, confounding due to PS can also be due to non-genetic factors. Propensity scores are widely used to address confounding in observational studies but have not been adapted to deal with PS in genetic association studies. We propose a genomic propensity score (GPS) approach to correct for bias due to PS that considers both genetic and non-genetic factors. We compare the GPS method with PCA and MDS using simulation studies. Our results show that GPS can adequately adjust and consistently correct for bias due to PS. Under no/mild, moderate, and severe PS, GPS yielded estimated with bias close to 0 (mean=-0.0044, standard error=0.0087). Under moderate or severe PS, the GPS method consistently outperforms the PCA method in terms of bias, coverage probability (CP), and type I error. Under moderate PS, the GPS method consistently outperforms the MDS method in terms of CP. PCA maintains relatively high power compared to both MDS and GPS methods under the simulated situations. GPS and MDS are comparable in terms of statistical properties such as bias, type I error, and power. The GPS method provides a novel and robust tool for obtaining less-biased estimates of genetic associations that can consider both genetic and non-genetic factors. 2009 Wiley-Liss, Inc.

Comparing targeted exome and whole exome approaches for genetic diagnosis of neuromuscular disorders

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Svetlana Gorokhova

2015-12-01

Full Text Available Massively parallel sequencing is rapidly becoming a widely used method in genetic diagnostics. However, there is still no clear consensus as to which approach can most efficiently identify the pathogenic mutations carried by a given patient, while avoiding false negative and false positive results. We developed a targeted exome approach (MyoPanel2 in order to optimize genetic diagnosis of neuromuscular disorders. Using this approach, we were able to analyse 306 genes known to be mutated in myopathies as well as in related disorders, obtaining 98.8% target sequence coverage at 20×. Moreover, MyoPanel2 was able to detect 99.7% of 11,467 known mutations responsible for neuromuscular disorders. We have then used several quality control parameters to compare performance of the targeted exome approach with that of whole exome sequencing. The results of this pilot study of 140 DNA samples suggest that targeted exome sequencing approach is an efficient genetic diagnostic test for most neuromuscular diseases.

Integrative Functional Genomics for Systems Genetics in GeneWeaver.org.

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Bubier, Jason A; Langston, Michael A; Baker, Erich J; Chesler, Elissa J

2017-01-01

The abundance of existing functional genomics studies permits an integrative approach to interpreting and resolving the results of diverse systems genetics studies. However, a major challenge lies in assembling and harmonizing heterogeneous data sets across species for facile comparison to the positional candidate genes and coexpression networks that come from systems genetic studies. GeneWeaver is an online database and suite of tools at www.geneweaver.org that allows for fast aggregation and analysis of gene set-centric data. GeneWeaver contains curated experimental data together with resource-level data such as GO annotations, MP annotations, and KEGG pathways, along with persistent stores of user entered data sets. These can be entered directly into GeneWeaver or transferred from widely used resources such as GeneNetwork.org. Data are analyzed using statistical tools and advanced graph algorithms to discover new relations, prioritize candidate genes, and generate function hypotheses. Here we use GeneWeaver to find genes common to multiple gene sets, prioritize candidate genes from a quantitative trait locus, and characterize a set of differentially expressed genes. Coupling a large multispecies repository curated and empirical functional genomics data to fast computational tools allows for the rapid integrative analysis of heterogeneous data for interpreting and extrapolating systems genetics results.

Reverse genetics with animal viruses. NSV reverse genetics

International Nuclear Information System (INIS)

Mebatsion, T.

2005-01-01

New strategies to genetically manipulate the genomes of several important animal pathogens have been established in recent years. This article focuses on the reverse genetics techniques, which enables genetic manipulation of the genomes of non-segmented negative-sense RNA viruses. Recovery of a negative-sense RNA virus entirely from cDNA was first achieved for rabies virus in 1994. Since then, reverse genetic systems have been established for several pathogens of medical and veterinary importance. Based on the reverse genetics technique, it is now possible to design safe and more effective live attenuated vaccines against important viral agents. In addition, genetically tagged recombinant viruses can be designed to facilitate serological differentiation of vaccinated animals from infected animals. The approach of delivering protective immunogens of different pathogens using a single vector was made possible with the introduction of the reverse genetics system, and these novel broad-spectrum vaccine vectors have potential applications in improving animal health in developing countries. (author)

Molecular genetics and livestock selection. Approaches, opportunities and risks

International Nuclear Information System (INIS)

Williams, J.L.

2005-01-01

Following domestication, livestock were selected both naturally through adaptation to their environments and by man so that they would fulfil a particular use. As selection methods have become more sophisticated, rapid progress has been made in improving those traits that are easily measured. However, selection has also resulted in decreased diversity. In some cases, improved breeds have replaced local breeds, risking the loss of important survival traits. The advent of molecular genetics provides the opportunity to identify the genes that control particular traits by a gene mapping approach. However, as with selection, the early mapping studies focused on traits that are easy to measure. Where molecular genetics can play a valuable role in livestock production is by providing the means to select effectively for traits that are difficult to measure. Identifying the genes underpinning particular traits requires a population in which these traits are segregating. Fortunately, several experimental populations have been created that have allowed a wide range of traits to be studied. Gene mapping work in these populations has shown that the role of particular genes in controlling variation in a given trait can depend on the genetic background. A second finding is that the most favourable alleles for a trait may in fact. be present in animals that perform poorly for the trait. In the long term, knowledge of -the genes controlling particular traits, and the way they interact with the genetic background, will allow introgression between breeds and the assembly of genotypes that are best suited to particular environments, producing animals with the desired characteristics. If used wisely, this approach will maintain genetic diversity while improving performance over a wide range of desired traits. (author)

Sensitivity analysis approaches applied to systems biology models.

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Zi, Z

2011-11-01

With the rising application of systems biology, sensitivity analysis methods have been widely applied to study the biological systems, including metabolic networks, signalling pathways and genetic circuits. Sensitivity analysis can provide valuable insights about how robust the biological responses are with respect to the changes of biological parameters and which model inputs are the key factors that affect the model outputs. In addition, sensitivity analysis is valuable for guiding experimental analysis, model reduction and parameter estimation. Local and global sensitivity analysis approaches are the two types of sensitivity analysis that are commonly applied in systems biology. Local sensitivity analysis is a classic method that studies the impact of small perturbations on the model outputs. On the other hand, global sensitivity analysis approaches have been applied to understand how the model outputs are affected by large variations of the model input parameters. In this review, the author introduces the basic concepts of sensitivity analysis approaches applied to systems biology models. Moreover, the author discusses the advantages and disadvantages of different sensitivity analysis methods, how to choose a proper sensitivity analysis approach, the available sensitivity analysis tools for systems biology models and the caveats in the interpretation of sensitivity analysis results.

Landscape genetic approaches to guide native plant restoration in the Mojave Desert

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Shryock, Daniel F.; Havrilla, Caroline A.; DeFalco, Lesley; Esque, Todd C.; Custer, Nathan; Wood, Troy E.

2016-01-01

Restoring dryland ecosystems is a global challenge due to synergistic drivers of disturbance coupled with unpredictable environmental conditions. Dryland plant species have evolved complex life-history strategies to cope with fluctuating resources and climatic extremes. Although rarely quantified, local adaptation is likely widespread among these species and potentially influences restoration outcomes. The common practice of reintroducing propagules to restore dryland ecosystems, often across large spatial scales, compels evaluation of adaptive divergence within these species. Such evaluations are critical to understanding the consequences of large-scale manipulation of gene flow and to predicting success of restoration efforts. However, genetic information for species of interest can be difficult and expensive to obtain through traditional common garden experiments. Recent advances in landscape genetics offer marker-based approaches for identifying environmental drivers of adaptive genetic variability in non-model species, but tools are still needed to link these approaches with practical aspects of ecological restoration. Here, we combine spatially-explicit landscape genetics models with flexible visualization tools to demonstrate how cost-effective evaluations of adaptive genetic divergence can facilitate implementation of different seed sourcing strategies in ecological restoration. We apply these methods to Amplified Fragment Length Polymorphism (AFLP) markers genotyped in two Mojave Desert shrub species of high restoration importance: the long-lived, wind-pollinated gymnosperm Ephedra nevadensis, and the short-lived, insect-pollinated angiosperm Sphaeralcea ambigua. Mean annual temperature was identified as an important driver of adaptive genetic divergence for both species. Ephedra showed stronger adaptive divergence with respect to precipitation variability, while temperature variability and precipitation averages explained a larger fraction of adaptive

Forward Genetic Approaches for Elucidation of Novel Regulators of Lyme Arthritis Severity

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Kenneth K.C. Bramwell

2014-06-01

Full Text Available Patients experiencing natural infection with Borrelia burgdorferi display a spectrum of associated symptoms and severity, strongly implicating the impact of genetically determined host factors in the pathogenesis of Lyme disease. Herein, we provide a summary of the host genetic factors that have been demonstrated to influence the severity and chronicity of Lyme arthritis symptoms, and a review of the resources available, current progress, and added value of a forward genetic approach for identification of novel genetic regulators.

The underlying mechanisms of genetic innovation and speciation in the family Corynebacteriaceae: A phylogenomics approach.

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Zhi, Xiao-Yang; Jiang, Zhao; Yang, Ling-Ling; Huang, Ying

2017-02-01

The pangenome of a bacterial species population is formed by genetic reduction and genetic expansion over the long course of evolution. Gene loss is a pervasive source of genetic reduction, and (exogenous and endogenous) gene gain is the main driver of genetic expansion. To understand the genetic innovation and speciation of the family Corynebacteriaceae, which cause a wide range of serious infections in humans and animals, we analyzed the pangenome of this family, and reconstructed its phylogeny using a phylogenomics approach. Genetic variations have occurred throughout the whole evolutionary history of the Corynebacteriaceae. Gene loss has been the primary force causing genetic changes, not only in terms of the number of protein families affected, but also because of its continuity on the time series. The variation in metabolism caused by these genetic changes mainly occurred for membrane transporters, two-component systems, and metabolism related to amino acids and carbohydrates. Interestingly, horizontal gene transfer (HGT) not only caused changes related to pathogenicity, but also triggered the acquisition of antimicrobial resistance. The Darwinian theory of evolution did not adequately explain the effects of dispersive HGT and/or gene loss in the evolution of the Corynebacteriaceae. These findings provide new insight into the evolution and speciation of Corynebacteriaceae and advance our understanding of the genetic innovation in microbial populations. Copyright © 2016 Elsevier Inc. All rights reserved.

Approach to estimation of level of information security at enterprise based on genetic algorithm

Science.gov (United States)

V, Stepanov L.; V, Parinov A.; P, Korotkikh L.; S, Koltsov A.

2018-05-01

In the article, the way of formalization of different types of threats of information security and vulnerabilities of an information system of the enterprise and establishment is considered. In a type of complexity of ensuring information security of application of any new organized system, the concept and decisions in the sphere of information security are expedient. One of such approaches is the method of a genetic algorithm. For the enterprises of any fields of activity, the question of complex estimation of the level of security of information systems taking into account the quantitative and qualitative factors characterizing components of information security is relevant.

Earthquake—explosion discrimination using genetic algorithm-based boosting approach

Science.gov (United States)

Orlic, Niksa; Loncaric, Sven

2010-02-01

An important and challenging problem in seismic data processing is to discriminate between natural seismic events such as earthquakes and artificial seismic events such as explosions. Many automatic techniques for seismogram classification have been proposed in the literature. Most of these methods have a similar approach to seismogram classification: a predefined set of features based on ad-hoc feature selection criteria is extracted from the seismogram waveform or spectral data and these features are used for signal classification. In this paper we propose a novel approach for seismogram classification. A specially formulated genetic algorithm has been employed to automatically search for a near-optimal seismogram feature set, instead of using ad-hoc feature selection criteria. A boosting method is added to the genetic algorithm when searching for multiple features in order to improve classification performance. A learning set of seismogram data is used by the genetic algorithm to discover a near-optimal feature set. The feature set identified by the genetic algorithm is then used for seismogram classification. The described method is developed to classify seismograms in two groups, whereas a brief overview of method extension for multiple group classification is given. For method verification, a learning set consisting of 40 local earthquake seismograms and 40 explosion seismograms was used. The method was validated on seismogram set consisting of 60 local earthquake seismograms and 60 explosion seismograms, with correct classification of 85%.

Symmetries in Genetic Systems and the Concept of Geno-Logical Coding

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Sergey V. Petoukhov

2016-12-01

Full Text Available The genetic code of amino acid sequences in proteins does not allow understanding and modeling of inherited processes such as inborn coordinated motions of living bodies, innate principles of sensory information processing, quasi-holographic properties, etc. To be able to model these phenomena, the concept of geno-logical coding, which is connected with logical functions and Boolean algebra, is put forward. The article describes basic pieces of evidence in favor of the existence of the geno-logical code, which exists in p­arallel with the known genetic code of amino acid sequences but which serves for transferring inherited processes along chains of generations. These pieces of evidence have been received due to the analysis of symmetries in structures of molecular-genetic systems. The analysis has revealed a close connection of the genetic system with dyadic groups of binary numbers and with other mathematical objects, which are related with dyadic groups: Walsh functions (which are algebraic characters of dyadic groups, bit-reversal permutations, logical holography, etc. These results provide a new approach for mathematical modeling of genetic structures, which uses known mathematical formalisms from technological fields of noise-immunity coding of information, binary analysis, logical holography, and digital devices of artificial intellect. Some opportunities for a development of algebraic-logical biology are opened.

Recent insights into the genetic basis of systemic lupus erythematosus.

Science.gov (United States)

Moser, K L; Kelly, J A; Lessard, C J; Harley, J B

2009-07-01

Genetic variation was first shown to be important in systemic lupus erythematosus (SLE or lupus) in the 1970s with associations in the human leukocyte antigen region. Almost four decades later, and with the help of increasingly powerful genetic approaches, more than 25 genes are now known to contribute to the mechanisms that predispose individuals to lupus. Over half of these loci have been discovered in the past 2 years, underscoring the extraordinary success of genome-wide association approaches in SLE. Well-established risk factors include alleles in the major histocompatibility complex region (multiple genes), IRF5, ITGAM, STAT4, BLK, BANK1, PDCD1, PTPN22, TNFSF4, TNFAIP3, SPP1, some of the Fcgamma receptors, and deficiencies in several complement components, including C1q, C4 and C2. As reviewed here, many susceptibility genes fall into key pathways that are consistent with previous studies implicating immune complexes, host immune signal transduction and interferon pathways in the pathogenesis of SLE. Other loci have no known function or apparent immunological role and have the potential to reveal novel disease mechanisms. Certainly, as our understanding of the genetic etiology of SLE continues to mature, important new opportunities will emerge for developing more effective diagnostic and clinical management tools for this complex autoimmune disease.

Metaheuristic Approaches for Hydropower System Scheduling

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Ieda G. Hidalgo

2015-01-01

Full Text Available This paper deals with the short-term scheduling problem of hydropower systems. The objective is to meet the daily energy demand in an economic and safe way. The individuality of the generating units and the nonlinearity of their efficiency curves are taken into account. The mathematical model is formulated as a dynamic, mixed integer, nonlinear, nonconvex, combinatorial, and multiobjective optimization problem. We propose two solution methods using metaheuristic approaches. They combine Genetic Algorithm with Strength Pareto Evolutionary Algorithm and Ant Colony Optimization. Both approaches are divided into two phases. In the first one, to maximize the plant’s net generation, the problem is solved for each hour of the day (static dispatch. In the second phase, to minimize the units’ switching on-off, the day is considered as a whole (dynamic dispatch. The proposed methodology is applied to two Brazilian hydroelectric plants, in cascade, that belong to the national interconnected system. The nondominated solutions from both approaches are presented. All of them meet demand respecting the physical, electrical, and hydraulic constraints.

WONOEP appraisal: new genetic approaches to study epilepsy

Science.gov (United States)

Rossignol, Elsa; Kobow, Katja; Simonato, Michele; Loeb, Jeffrey A.; Grisar, Thierry; Gilby, Krista L.; Vinet, Jonathan; Kadam, Shilpa D.; Becker, Albert J.

2014-01-01

Objective New genetic investigation techniques, including next-generation sequencing, epigenetic profiling, cell lineage mapping, targeted genetic manipulation of specific neuronal cell types, stem cell reprogramming and optogenetic manipulations within epileptic networks are progressively unravelling the mysteries of epileptogenesis and ictogenesis. These techniques have opened new avenues to discover the molecular basis of epileptogenesis and to study the physiological impacts of mutations in epilepsy-associated genes on a multilayer level, from cells to circuits. Methods This manuscript reviews recently published applications of these new genetic technologies in the study of epilepsy, as well as work presented by the authors at the genetic session of the XII Workshop on the Neurobiology of Epilepsy in Quebec, Canada. Results Next-generation sequencing is providing investigators with an unbiased means to assess the molecular causes of sporadic forms of epilepsy and have revealed the complexity and genetic heterogeneity of sporadic epilepsy disorders. To assess the functional impact of mutations in these newly identified genes on specific neuronal cell-types during brain development, new modeling strategies in animals, including conditional genetics in mice and in utero knockdown approaches, are enabling functional validation with exquisite cell-type and temporal specificity. In addition, optogenetics, using cell-type specific Cre recombinase driver lines, is enabling investigators to dissect networks involved in epilepsy. Genetically-encoded cell-type labeling is also providing new means to assess the role of the non-neuronal components of epileptic networks such as glial cells. Furthermore, beyond its role in revealing coding variants involved in epileptogenesis, next-generation sequencing can be used to assess the epigenetic modifications that lead to sustained network hyperexcitability in epilepsy, including methylation changes in gene promoters and non

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.

[Genetics factors in pathogenesis and clinical genetics of binge eating disorder].

Science.gov (United States)

Kibitov, А О; Мazo, G E

2016-01-01

Genetic studies have shown that binge eating disorder (ВЕD) aggregates in families, heritability was estimated as about 60% and additive genetic influences on BED up to 50%. Using a genetic approach has proved useful for verifying the diagnostic categories of BED using DSM-IV criteria and supporting the validity of considering this pathology as a separate nosological category. The results confirmed the genetic and pathogenic originality of BED as a separate psychopathological phenomenon, but not a subtype of obesity. It seems fruitful to considerate BED as a disease with hereditary predisposition with significant genetic influence and a complex psychopathological syndrome, including not only eating disorders, but also depressive and addictive component. A possible mechanism of pathogenesis of BED may be the interaction of the neuroendocrine and neurotransmitters systems including the active involvement of the reward system in response to a variety of chronic stress influences with the important modulatory role of specific personality traits. The high level of genetic influence on the certain clinical manifestations of BED confirms the ability to identify the subphenotypes of BED on genetic basis involving clinical criteria. It can not only contribute to further genetic studies, taking into account more homogeneous samples, but also help in finding differentiated therapeutic approaches.

Using Genetic Algorithms for Building Metrics of Collaborative Systems

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Cristian CIUREA

2011-01-01

Full Text Available he paper objective is to reveal the importance of genetic algorithms in building robust metrics of collaborative systems. The main types of collaborative systems in economy are presented and some characteristics of genetic algorithms are described. A genetic algorithm was implemented in order to determine the local maximum and minimum points of the relative complexity function associated to a collaborative banking system. The intelligent collaborative systems based on genetic algorithms, representing the new generation of collaborative systems, are analyzed and the implementation of auto-adaptive interfaces in a banking application is described.

Nuclear power plant maintenance scheduling dilemma: a genetic algorithm approach

International Nuclear Information System (INIS)

Mahdavi, M.H.; Modarres, M.

2004-01-01

There are huge numbers of components scheduled for maintenance when a nuclear power plant is shut down. Among these components, a number of them are safety related which their operability as well as reliability when plant becomes up is main concerns. Not performing proper maintenance on this class of components/system would impose substantial risk on operating the NPP. In this paper a new approach based on genetic algorithms is presented to optimize the NPP maintenance schedule during shutdown. following this approach the cost incurred by maintenance activities for each schedule is balanced with the risk imposed by the maintenance scheduling plan to the plant operation status when it is up. The risk model implemented in the GA scheduler as its evaluation function is developed on the basis of the probabilistic risk assessment methodology. the Ga optimizers itself is shown to be superior compared to other optimization methods such as the monte carlo technique

Environmental Contamination Genetic Consequences Monitoring on the Former Semipalatinsk Test Site: General Approach

International Nuclear Information System (INIS)

Seisebaev, A.T.; Bakhtin, M.M.; Zhapbasov, R.Zh.

1998-01-01

For an objective assessment of nuclear test consequences for the environment it is necessary, together with the investigation of radiation situation, to study live biological systems, particularly the genetic effects of chronic ionizing radiation. The long staying of plants and animals on the territories with the elevated radiation background level can lead to the change of organism genetic system. In this connection the monitoring of chronically exposed natural populations is of particular interest and can serve as the objective indicator of the scale of natural biota genetic damage. Basing on the results obtained during plant and animal studies one can indirectly assess the hazard of people genetic damage. Besides, studying the mutational process on natural populations exposed to the chronic ionizing radiation one can reveal new regularities, which are impossible to be detected in the laboratory conditions, and new aspects of radiation genetics. The issue of radiation adaptation of organisms affected by the various doses of ionizing radiation is very acute. The prerequisite of organism adaptation to the certain radiation background is genetic heterogeneity of individuals comprising the population and selection of radiation-induced individuals, which are the carriers of the mutation of high radioresistance. The uniqueness of the Semipalatinsk Test site and the necessity of long-term investigations of the nuclear test consequences for the environment demand the elaboration of principles for organization and utilization of natural population genetic monitoring. Radiation-genetic monitoring is the long-term observation of palpitation gene pool conditions, assessment and forecast of their spatial and time alteration, determination of limits of changes admitted under the condition of environmental radioactive contamination. It includes a series of the main research directions and has quite certain methodological peculiarities. In this paper we discuss the tasks of

Markov chains and entropy tests in genetic-based lithofacies analysis of deep-water clastic depositional systems

Directory of Open Access Journals (Sweden)

Borka Szabolcs

2016-01-01

Full Text Available The aim of this study was to examine the relationship between structural elements and the so-called genetic lithofacies in a clastic deep-water depositional system. Process-sedimentology has recently been gaining importance in the characterization of these systems. This way the recognized facies attributes can be associated with the depositional processes establishing the genetic lithofacies. In this paper this approach was presented through a case study of a Tertiary deep-water sequence of the Pannonian-basin.

Food control and a citizen science approach for improving teaching of Genetics in universities.

Science.gov (United States)

Borrell, Y J; Muñoz-Colmenero, A M; Dopico, E; Miralles, L; Garcia-Vazquez, E

2016-09-10

A Citizen Science approach was implemented in the laboratory practices of Genetics at the University of Oviedo, related with the engaging topic of Food Control. Real samples of food products consumed by students at home (students as samplers) were employed as teaching material in three different courses of Genetics during the academic year 2014-2015: Experimental Methods in Food Production (MBTA) (Master level), and Applied Molecular Biology (BMA) and Conservation Genetics and Breeding (COMGE) (Bachelor/Degree level). Molecular genetics based on PCR amplification of DNA markers was employed for species identification of 22 seafood products in COMGE and MBTA, and for detection of genetically modified (GM) maize from nine products in BMA. In total six seafood products incorrectly labeled (27%), and two undeclared GM maize (22%) were found. A post-Laboratory survey was applied for assessing the efficacy of the approach for improving motivation in the Laboratory Practices of Genetics. Results confirmed that students that worked on their own samples from local markets were significantly more motivated and better evaluated their Genetic laboratory practices than control students (χ(2)  = 12.11 p = 0.033). Our results suggest that citizen science approaches could not be only useful for improving teaching of Genetics in universities but also to incorporate students and citizens as active agents in food control. © 2016 by The International Union of Biochemistry and Molecular Biology, 44(5):450-462, 2016. © 2016 The International Union of Biochemistry and Molecular Biology.

Forecasting systems reliability based on support vector regression with genetic algorithms

International Nuclear Information System (INIS)

Chen, K.-Y.

2007-01-01

This study applies a novel neural-network technique, support vector regression (SVR), to forecast reliability in engine systems. The aim of this study is to examine the feasibility of SVR in systems reliability prediction by comparing it with the existing neural-network approaches and the autoregressive integrated moving average (ARIMA) model. To build an effective SVR model, SVR's parameters must be set carefully. This study proposes a novel approach, known as GA-SVR, which searches for SVR's optimal parameters using real-value genetic algorithms, and then adopts the optimal parameters to construct the SVR models. A real reliability data for 40 suits of turbochargers were employed as the data set. The experimental results demonstrate that SVR outperforms the existing neural-network approaches and the traditional ARIMA models based on the normalized root mean square error and mean absolute percentage error

Systems medicine: a new approach to clinical practice.

Science.gov (United States)

Cardinal-Fernández, Pablo; Nin, Nicolás; Ruíz-Cabello, Jesús; Lorente, José A

2014-10-01

Most respiratory diseases are considered complex diseases as their susceptibility and outcomes are determined by the interaction between host-dependent factors (genetic factors, comorbidities, etc.) and environmental factors (exposure to microorganisms or allergens, treatments received, etc.) The reductionist approach in the study of diseases has been of fundamental importance for the understanding of the different components of a system. Systems biology or systems medicine is a complementary approach aimed at analyzing the interactions between the different components within one organizational level (genome, transcriptome, proteome), and then between the different levels. Systems medicine is currently used for the interpretation and understanding of the pathogenesis and pathophysiology of different diseases, biomarker discovery, design of innovative therapeutic targets, and the drawing up of computational models for different biological processes. In this review we discuss the most relevant concepts of the theory underlying systems medicine, as well as its applications in the various biological processes in humans. Copyright © 2013 SEPAR. Published by Elsevier Espana. All rights reserved.

A genetic algorithm approach to recognition and data mining

Energy Technology Data Exchange (ETDEWEB)

Punch, W.F.; Goodman, E.D.; Min, Pei [Michigan State Univ., East Lansing, MI (United States)] [and others

1996-12-31

We review here our use of genetic algorithm (GA) and genetic programming (GP) techniques to perform {open_quotes}data mining,{close_quotes} the discovery of particular/important data within large datasets, by finding optimal data classifications using known examples. Our first experiments concentrated on the use of a K-nearest neighbor algorithm in combination with a GA. The GA selected weights for each feature so as to optimize knn classification based on a linear combination of features. This combined GA-knn approach was successfully applied to both generated and real-world data. We later extended this work by substituting a GP for the GA. The GP-knn could not only optimize data classification via linear combinations of features but also determine functional relationships among the features. This allowed for improved performance and new information on important relationships among features. We review the effectiveness of the overall approach on examples from biology and compare the effectiveness of the GA and GP.

Genetically caused congenital anomalies of reproductive system

Directory of Open Access Journals (Sweden)

L. F. Kurilo

2013-01-01

Full Text Available Classification of congenital disorders, their frequency of occurrence in populations, and some terminology questions discussed in the review. Genetically caused congenital anomalies of reproductive system are outlined. Full information about genetic syndromes is stated in the book: Kozlova S.I., Demikova N.S. Hereditary syndromes and genetic counseling. M., 2007.

Systems approaches to study root architecture dynamics

Directory of Open Access Journals (Sweden)

Candela eCuesta

2013-12-01

Full Text Available The plant root system is essential for providing anchorage to the soil, supplying minerals and water, and synthesizing metabolites. It is a dynamic organ modulated by external cues such as environmental signals, water and nutrients availability, salinity and others. Lateral roots are initiated from the primary root post-embryonically, after which they progress through discrete developmental stages which can be independently controlled, providing a high level of plasticity during root system formation.Within this review, main contributions are presented, from the classical forward genetic screens to the more recent high-throughput approaches, combined with computer model predictions, dissecting how lateral roots and thereby root system architecture is established and developed.

Genetic Approaches to Develop Salt Tolerant Germplasm

KAUST Repository

Tester, Mark A.

2015-08-19

Forty percent of the world\\'s food is produced under irrigation, and this is directly threatened by over-exploitation and changes in the global environment. One way to address this threat is to develop systems for increasing our ability to use lower quality water, in particular saline water. Low cost partial desalination of brackish water, use of saline water for cooling and increases in the salinity tolerance of crops can all contribute to the development of this new agricultural system. In this talk, the focus will be on the use of forward genetic approaches for discovery of genes related to salinity tolerance in barley and tomatoes. Rather than studying salinity tolerance as a trait in itself, we dissect salinity tolerance into a series of components that are hypothesised to contribute to overall salinity tolerance (following the paradigm of Munns & Tester, 2008). For example, one significant component of tolerance of most crop plants to moderate soil salinity is due to the ability to maintain low concentrations of Na+ in the leaves, and much analysis of this aspect has been done (e.g. Roy et al., 2013, 2014). A major site for the control of shoot Na+ accumulation is at the plasma membrane of the mature stele of the root. Alleles of HKT, a major gene underlying this transport process have been characterized and, in work led by Dr Rana Munns (CSIRO), have now been introgressed into commercial durum wheat and led to significantly increased yields in saline field conditions (Munns et al., 2012). The genotyping of mapping populations is now highly efficient. However, the ability to quantitatively phenotype these populations is now commonly limiting forward progress in plant science. The increasing power of digital imaging and computational technologies offers the opportunity to relieve this phenotyping bottleneck. The Plant Accelerator is a 4500m2 growth facility that provides non-destructive phenotyping of large populations of plants (http

Understanding mammalian genetic systems: the challenge of phenotyping in the mouse.

Directory of Open Access Journals (Sweden)

Steve D M Brown

2006-08-01

Full Text Available Understanding mammalian genetic systems is predicated on the determination of the relationship between genetic variation and phenotype. Several international programmes are under way to deliver mutations in every gene in the mouse genome. The challenge for mouse geneticists is to develop approaches that will provide comprehensive phenotype datasets for these mouse mutant libraries. Several factors are critical to success in this endeavour. It will be important to catalogue assay and environment and where possible to adopt standardised procedures for phenotyping tests along with common environmental conditions to ensure comparable datasets of phenotypes. Moreover, the scale of the task underlines the need to invest in technological development improving both the speed and cost of phenotyping platforms. In addition, it will be necessary to develop new informatics standards that capture the phenotype assay as well as other factors, genetic and environmental, that impinge upon phenotype outcome.

Yeast Augmented Network Analysis (YANA: a new systems approach to identify therapeutic targets for human genetic diseases [v1; ref status: indexed, http://f1000r.es/3gk

Directory of Open Access Journals (Sweden)

David J. Wiley

2014-06-01

Full Text Available Genetic interaction networks that underlie most human diseases are highly complex and poorly defined. Better-defined networks will allow identification of a greater number of therapeutic targets. Here we introduce our Yeast Augmented Network Analysis (YANA approach and test it with the X-linked spinal muscular atrophy (SMA disease gene UBA1. First, we express UBA1 and a mutant variant in fission yeast and use high-throughput methods to identify fission yeast genetic modifiers of UBA1. Second, we analyze available protein-protein interaction network databases in both fission yeast and human to construct UBA1 genetic networks. Third, from these networks we identified potential therapeutic targets for SMA. Finally, we validate one of these targets in a vertebrate (zebrafish SMA model. This study demonstrates the power of combining synthetic and chemical genetics with a simple model system to identify human disease gene networks that can be exploited for treating human diseases.

The challenges and promises of genetic approaches for ballast water management

Science.gov (United States)

Rey, Anaïs; Basurko, Oihane C.; Rodríguez-Ezpeleta, Naiara

2018-03-01

Ballast water is a main vector of introduction of Harmful Aquatic Organisms and Pathogens, which includes Non-Indigenous Species. Numerous and diversified organisms are transferred daily from a donor to a recipient port. Developed to prevent these introduction events, the International Convention for the Control and Management of Ships' Ballast Water and Sediments will enter into force in 2017. This international convention is asking for the monitoring of Harmful Aquatic Organisms and Pathogens. In this review, we highlight the urgent need to develop cost-effective methods to: (1) perform the biological analyses required by the convention; and (2) assess the effectiveness of two main ballast water management strategies, i.e. the ballast water exchange and the use of ballast water treatment systems. We have compiled the biological analyses required by the convention, and performed a comprehensive evaluation of the potential and challenges of the use of genetic tools in this context. Following an overview of the studies applying genetic tools to ballast water related research, we present metabarcoding as a relevant approach for early detection of Harmful Aquatic Organisms and Pathogens in general and for ballast water monitoring and port risk assessment in particular. Nonetheless, before implementation of genetic tools in the context of the ballast water management convention, benchmarked tests against traditional methods should be performed, and standard, reproducible and easy to apply protocols should be developed.

Network-assisted crop systems genetics: network inference and integrative analysis.

Science.gov (United States)

Lee, Tak; Kim, Hyojin; Lee, Insuk

2015-04-01

Although next-generation sequencing (NGS) technology has enabled the decoding of many crop species genomes, most of the underlying genetic components for economically important crop traits remain to be determined. Network approaches have proven useful for the study of the reference plant, Arabidopsis thaliana, and the success of network-based crop genetics will also require the availability of a genome-scale functional networks for crop species. In this review, we discuss how to construct functional networks and elucidate the holistic view of a crop system. The crop gene network then can be used for gene prioritization and the analysis of resequencing-based genome-wide association study (GWAS) data, the amount of which will rapidly grow in the field of crop science in the coming years. Copyright © 2015 Elsevier Ltd. All rights reserved.

Understanding the Science-Learning Environment: A Genetically Sensitive Approach

Science.gov (United States)

Haworth, Claire M. A.; Davis, Oliver S. P.; Hanscombe, Ken B.; Kovas, Yulia; Dale, Philip S.; Plomin, Robert

2013-01-01

Previous studies have shown that environmental influences on school science performance increase in importance from primary to secondary school. Here we assess for the first time the relationship between the science-learning environment and science performance using a genetically sensitive approach to investigate the aetiology of this link. 3000…

Safety of genetically engineered foods: approaches to assessing unintended health effects

National Research Council Canada - National Science Library

Committee on Identifying and Assessing Unintended Effects of Genetically Engineered Foods on Human Health, National Research Council

2004-01-01

.... It identifies and recommends several pre- and post-market approaches to guide the assessment of unintended compositional changes that could result from genetically modified foods and research avenues...

Rationale for an integrated approach to genetic epidemiology.

Science.gov (United States)

Laberge, Claude M; Knoppers, Bartha Maria

1992-10-01

Genetic knowledge is now in the public domain and its interpretation by the media and the citizens brings the issues into the public forum of discussion for the necessary ethical, legal and socio-cultural evaluation of its application. Science is being perceived by some as dangerous and as requiring international regulation. Others feel that genetic knowledge will be the breakthrough that will permit medical progress and individual autonomy with regards to personal health and lifestyle choices. The mapping of the human genome has already yielded valuable information on an increasing number of diseases and their variants. Prevailing popular and journalistic archetypes ("imaginaires") used in the media are perceived by the producers as slowing down the possible application of genetic knowledge. The answers to these dilemmas are not readily apparent nor are they prescribed by classical philosophy of medicine. Since genetic knowledge eventually resides with the individual who carries the genes of disease and/or susceptibility, a logical approach to integration of this knowledge at a societal level would seem to reside with individual education and decision-making. The politics of the ensuing social debate could transform the current social contract since an individual's interests need to be balanced against those of his or her immediate family in the sharing of information. The ethical foundations of such a contract requires the genetic education of "Everyone" as a matter of urgent priority. Genetic education should not serve ideological power struggles between the medical establishment and the ethical-legal alliance. Instead, it should ensure the transfer of knowledge to physicians, to patients, to users, to planners, to social science and humanities researchers and to politicians, so that they may make "informed" and free decisions....

An integrated system for genetic analysis

Directory of Open Access Journals (Sweden)

Duan Xiao

2006-04-01

Full Text Available Abstract Background Large-scale genetic mapping projects require data management systems that can handle complex phenotypes and detect and correct high-throughput genotyping errors, yet are easy to use. Description We have developed an Integrated Genotyping System (IGS to meet this need. IGS securely stores, edits and analyses genotype and phenotype data. It stores information about DNA samples, plates, primers, markers and genotypes generated by a genotyping laboratory. Data are structured so that statistical genetic analysis of both case-control and pedigree data is straightforward. Conclusion IGS can model complex phenotypes and contain genotypes from whole genome association studies. The database makes it possible to integrate genetic analysis with data curation. The IGS web site http://bioinformatics.well.ox.ac.uk/project-igs.shtml contains further information.

Time-Delay System Identification Using Genetic Algorithm

DEFF Research Database (Denmark)

Yang, Zhenyu; Seested, Glen Thane

2013-01-01

Due to the unknown dead-time coefficient, the time-delay system identification turns to be a non-convex optimization problem. This paper investigates the identification of a simple time-delay system, named First-Order-Plus-Dead-Time (FOPDT), by using the Genetic Algorithm (GA) technique. The qual......Due to the unknown dead-time coefficient, the time-delay system identification turns to be a non-convex optimization problem. This paper investigates the identification of a simple time-delay system, named First-Order-Plus-Dead-Time (FOPDT), by using the Genetic Algorithm (GA) technique...

Optimal support arrangement of piping systems using genetic algorithm

International Nuclear Information System (INIS)

Chiba, T.; Okado, S.; Fujii, I.; Itami, K.

1996-01-01

The support arrangement is one of the important factors in the design of piping systems. Much time is required to decide the arrangement of the supports. The authors applied a genetic algorithm to find the optimum support arrangement for piping systems. Examples are provided to illustrate the effectiveness of the genetic algorithm. Good results are obtained when applying the genetic algorithm to the actual designing of the piping system

Molecular, Genetic and Agronomic Approaches to Utilizing Pulses as Cover Crops and Green Manure into Cropping Systems.

Science.gov (United States)

Tani, Eleni; Abraham, Eleni; Chachalis, Demosthenis; Travlos, Ilias

2017-06-05

Cover crops constitute one of the most promising agronomic practices towards a more sustainable agriculture. Their beneficial effects on main crops, soil and environment are many and various, while risks and disadvantages may also appear. Several legumes show a high potential but further research is required in order to suggest the optimal legume cover crops for each case in terms of their productivity and ability to suppress weeds. The additional cost associated with cover crops should also be addressed and in this context the use of grain legumes such as cowpea, faba bean and pea could be of high interest. Some of the aspects of these grain legumes as far as their use as cover crops, their genetic diversity and their breeding using conventional and molecular approaches are discussed in the present review. The specific species seem to have a high potential for use as cover crops, especially if their noticeable genetic diversity is exploited and their breeding focuses on several desirable traits.

Molecular, Genetic and Agronomic Approaches to Utilizing Pulses as Cover Crops and Green Manure into Cropping Systems

Science.gov (United States)

Tani, Eleni; Abraham, Eleni; Chachalis, Demosthenis; Travlos, Ilias

2017-01-01

Cover crops constitute one of the most promising agronomic practices towards a more sustainable agriculture. Their beneficial effects on main crops, soil and environment are many and various, while risks and disadvantages may also appear. Several legumes show a high potential but further research is required in order to suggest the optimal legume cover crops for each case in terms of their productivity and ability to suppress weeds. The additional cost associated with cover crops should also be addressed and in this context the use of grain legumes such as cowpea, faba bean and pea could be of high interest. Some of the aspects of these grain legumes as far as their use as cover crops, their genetic diversity and their breeding using conventional and molecular approaches are discussed in the present review. The specific species seem to have a high potential for use as cover crops, especially if their noticeable genetic diversity is exploited and their breeding focuses on several desirable traits. PMID:28587254

A Genetic Algorithms-based Approach for Optimized Self-protection in a Pervasive Service Middleware

DEFF Research Database (Denmark)

Zhang, Weishan; Ingstrup, Mads; Hansen, Klaus Marius

2009-01-01

With increasingly complex and heterogeneous systems in pervasive service computing, it becomes more and more important to provide self-protected services to end users. In order to achieve self-protection, the corresponding security should be provided in an optimized manner considering...... the constraints of heterogeneous devices and networks. In this paper, we present a Genetic Algorithms-based approach for obtaining optimized security configurations at run time, supported by a set of security OWL ontologies and an event-driven framework. This approach has been realized as a prototype for self-protection...... in the Hydra middleware, and is integrated with a framework for enforcing the computed solution at run time using security obligations. The experiments with the prototype on configuring security strategies for a pervasive service middleware show that this approach has acceptable performance, and could be used...

Virus fitness differences observed between two naturally occurring isolates of Ebola virus Makona variant using a reverse genetics approach.

Science.gov (United States)

Albariño, César G; Guerrero, Lisa Wiggleton; Chakrabarti, Ayan K; Kainulainen, Markus H; Whitmer, Shannon L M; Welch, Stephen R; Nichol, Stuart T

2016-09-01

During the large outbreak of Ebola virus disease that occurred in Western Africa from late 2013 to early 2016, several hundred Ebola virus (EBOV) genomes have been sequenced and the virus genetic drift analyzed. In a previous report, we described an efficient reverse genetics system designed to generate recombinant EBOV based on a Makona variant isolate obtained in 2014. Using this system, we characterized the replication and fitness of 2 isolates of the Makona variant. These virus isolates are nearly identical at the genetic level, but have single amino acid differences in the VP30 and L proteins. The potential effects of these differences were tested using minigenomes and recombinant viruses. The results obtained with this approach are consistent with the role of VP30 and L as components of the EBOV RNA replication machinery. Moreover, the 2 isolates exhibited clear fitness differences in competitive growth assays. Published by Elsevier Inc.

Generalizing genetical genomics: getting added value from environmental perturbation.

Science.gov (United States)

Li, Yang; Breitling, Rainer; Jansen, Ritsert C

2008-10-01

Genetical genomics is a useful approach for studying the effect of genetic perturbations on biological systems at the molecular level. However, molecular networks depend on the environmental conditions and, thus, a comprehensive understanding of biological systems requires studying them across multiple environments. We propose a generalization of genetical genomics, which combines genetic and sensibly chosen environmental perturbations, to study the plasticity of molecular networks. This strategy forms a crucial step toward understanding why individuals respond differently to drugs, toxins, pathogens, nutrients and other environmental influences. Here we outline a strategy for selecting and allocating individuals to particular treatments, and we discuss the promises and pitfalls of the generalized genetical genomics approach.

Contributions of dopamine-related genes and environmental factors to highly sensitive personality: a multi-step neuronal system-level approach.

Directory of Open Access Journals (Sweden)

Chunhui Chen

Full Text Available Traditional behavioral genetic studies (e.g., twin, adoption studies have shown that human personality has moderate to high heritability, but recent molecular behavioral genetic studies have failed to identify quantitative trait loci (QTL with consistent effects. The current study adopted a multi-step approach (ANOVA followed by multiple regression and permutation to assess the cumulative effects of multiple QTLs. Using a system-level (dopamine system genetic approach, we investigated a personality trait deeply rooted in the nervous system (the Highly Sensitive Personality, HSP. 480 healthy Chinese college students were given the HSP scale and genotyped for 98 representative polymorphisms in all major dopamine neurotransmitter genes. In addition, two environment factors (stressful life events and parental warmth that have been implicated for their contributions to personality development were included to investigate their relative contributions as compared to genetic factors. In Step 1, using ANOVA, we identified 10 polymorphisms that made statistically significant contributions to HSP. In Step 2, these polymorphism's main effects and interactions were assessed using multiple regression. This model accounted for 15% of the variance of HSP (p<0.001. Recent stressful life events accounted for an additional 2% of the variance. Finally, permutation analyses ascertained the probability of obtaining these findings by chance to be very low, p ranging from 0.001 to 0.006. Dividing these loci by the subsystems of dopamine synthesis, degradation/transport, receptor and modulation, we found that the modulation and receptor subsystems made the most significant contribution to HSP. The results of this study demonstrate the utility of a multi-step neuronal system-level approach in assessing genetic contributions to individual differences in human behavior. It can potentially bridge the gap between the high heritability estimates based on traditional

Evolution of genetic systems in filamentous ascomycetes

NARCIS (Netherlands)

Nauta, M.J.

1994-01-01

A great variety of genetic systems exist in filamentous ascomycetes. The transmission of genetic material does not only occur by (sexual or asexual) reproduction, but it can also follow vegetative fusion of different strains. In this thesis the evolution of this variability is studied,

Mouse forward genetics in the study of the peripheral nervous system and human peripheral neuropathy

Science.gov (United States)

Douglas, Darlene S.; Popko, Brian

2009-01-01

Forward genetics, the phenotype-driven approach to investigating gene identity and function, has a long history in mouse genetics. Random mutations in the mouse transcend bias about gene function and provide avenues towards unique discoveries. The study of the peripheral nervous system is no exception; from historical strains such as the trembler mouse, which led to the identification of PMP22 as a human disease gene causing multiple forms of peripheral neuropathy, to the more recent identification of the claw paw and sprawling mutations, forward genetics has long been a tool for probing the physiology, pathogenesis, and genetics of the PNS. Even as spontaneous and mutagenized mice continue to enable the identification of novel genes, provide allelic series for detailed functional studies, and generate models useful for clinical research, new methods, such as the piggyBac transposon, are being developed to further harness the power of forward genetics. PMID:18481175

Human Metabolic Enzymes Deficiency: A Genetic Mutation Based Approach

Directory of Open Access Journals (Sweden)

Swati Chaturvedi

2016-01-01

Full Text Available One of the extreme challenges in biology is to ameliorate the understanding of the mechanisms which emphasize metabolic enzyme deficiency (MED and how these pretend to have influence on human health. However, it has been manifested that MED could be either inherited as inborn error of metabolism (IEM or acquired, which carries a high risk of interrupted biochemical reactions. Enzyme deficiency results in accumulation of toxic compounds that may disrupt normal organ functions and cause failure in producing crucial biological compounds and other intermediates. The MED related disorders cover widespread clinical presentations and can involve almost any organ system. To sum up the causal factors of almost all the MED-associated disorders, we decided to embark on a less traveled but nonetheless relevant direction, by focusing our attention on associated gene family products, regulation of their expression, genetic mutation, and mutation types. In addition, the review also outlines the clinical presentations as well as diagnostic and therapeutic approaches.

An Interval-Valued Approach to Business Process Simulation Based on Genetic Algorithms and the BPMN

Directory of Open Access Journals (Sweden)

Mario G.C.A. Cimino

2014-05-01

Full Text Available Simulating organizational processes characterized by interacting human activities, resources, business rules and constraints, is a challenging task, because of the inherent uncertainty, inaccuracy, variability and dynamicity. With regard to this problem, currently available business process simulation (BPS methods and tools are unable to efficiently capture the process behavior along its lifecycle. In this paper, a novel approach of BPS is presented. To build and manage simulation models according to the proposed approach, a simulation system is designed, developed and tested on pilot scenarios, as well as on real-world processes. The proposed approach exploits interval-valued data to represent model parameters, in place of conventional single-valued or probability-valued parameters. Indeed, an interval-valued parameter is comprehensive; it is the easiest to understand and express and the simplest to process, among multi-valued representations. In order to compute the interval-valued output of the system, a genetic algorithm is used. The resulting process model allows forming mappings at different levels of detail and, therefore, at different model resolutions. The system has been developed as an extension of a publicly available simulation engine, based on the Business Process Model and Notation (BPMN standard.

Using probability modelling and genetic parentage assignment to test the role of local mate availability in mating system variation.

Science.gov (United States)

Blyton, Michaela D J; Banks, Sam C; Peakall, Rod; Lindenmayer, David B

2012-02-01

The formal testing of mating system theories with empirical data is important for evaluating the relative importance of different processes in shaping mating systems in wild populations. Here, we present a generally applicable probability modelling framework to test the role of local mate availability in determining a population's level of genetic monogamy. We provide a significance test for detecting departures in observed mating patterns from model expectations based on mate availability alone, allowing the presence and direction of behavioural effects to be inferred. The assessment of mate availability can be flexible and in this study it was based on population density, sex ratio and spatial arrangement. This approach provides a useful tool for (1) isolating the effect of mate availability in variable mating systems and (2) in combination with genetic parentage analyses, gaining insights into the nature of mating behaviours in elusive species. To illustrate this modelling approach, we have applied it to investigate the variable mating system of the mountain brushtail possum (Trichosurus cunninghami) and compared the model expectations with the outcomes of genetic parentage analysis over an 18-year study. The observed level of monogamy was higher than predicted under the model. Thus, behavioural traits, such as mate guarding or selective mate choice, may increase the population level of monogamy. We show that combining genetic parentage data with probability modelling can facilitate an improved understanding of the complex interactions between behavioural adaptations and demographic dynamics in driving mating system variation. © 2011 Blackwell Publishing Ltd.

Phage Genetic Engineering Using CRISPR–Cas Systems

Directory of Open Access Journals (Sweden)

Asma Hatoum-Aslan

2018-06-01

Full Text Available Since their discovery over a decade ago, the class of prokaryotic immune systems known as CRISPR–Cas have afforded a suite of genetic tools that have revolutionized research in model organisms spanning all domains of life. CRISPR-mediated tools have also emerged for the natural targets of CRISPR–Cas immunity, the viruses that specifically infect bacteria, or phages. Despite their status as the most abundant biological entities on the planet, the majority of phage genes have unassigned functions. This reality underscores the need for robust genetic tools to study them. Recent reports have demonstrated that CRISPR–Cas systems, specifically the three major types (I, II, and III, can be harnessed to genetically engineer phages that infect diverse hosts. Here, the mechanisms of each of these systems, specific strategies used, and phage editing efficacies will be reviewed. Due to the relatively wide distribution of CRISPR–Cas systems across bacteria and archaea, it is anticipated that these immune systems will provide generally applicable tools that will advance the mechanistic understanding of prokaryotic viruses and accelerate the development of novel technologies based on these ubiquitous organisms.

The genetic architecture of the human immune system: a bioresource for autoimmunity and disease pathogenesis.

Science.gov (United States)

Roederer, Mario; Quaye, Lydia; Mangino, Massimo; Beddall, Margaret H; Mahnke, Yolanda; Chattopadhyay, Pratip; Tosi, Isabella; Napolitano, Luca; Terranova Barberio, Manuela; Menni, Cristina; Villanova, Federica; Di Meglio, Paola; Spector, Tim D; Nestle, Frank O

2015-04-09

Despite recent discoveries of genetic variants associated with autoimmunity and infection, genetic control of the human immune system during homeostasis is poorly understood. We undertook a comprehensive immunophenotyping approach, analyzing 78,000 immune traits in 669 female twins. From the top 151 heritable traits (up to 96% heritable), we used replicated GWAS to obtain 297 SNP associations at 11 genetic loci, explaining up to 36% of the variation of 19 traits. We found multiple associations with canonical traits of all major immune cell subsets and uncovered insights into genetic control for regulatory T cells. This data set also revealed traits associated with loci known to confer autoimmune susceptibility, providing mechanistic hypotheses linking immune traits with the etiology of disease. Our data establish a bioresource that links genetic control elements associated with normal immune traits to common autoimmune and infectious diseases, providing a shortcut to identifying potential mechanisms of immune-related diseases. Copyright © 2015 Elsevier Inc. All rights reserved.

Preservice Science Teachers' Efficacy Regarding a Socioscientific Issue: A Belief System Approach

Science.gov (United States)

Kilinç, Ahmet; Kartal, Tezcan; Eroglu, Baris; Demiral, Ümit; Afacan, Özlem; Polat, Dilber; Demirci Guler, Mutlu P.; Görgülü, Özkan

2013-01-01

The aim of the present study was to understand the nature of teaching efficacy beliefs related to a socioscientific issue (SSI). We investigated Turkish preservice science teachers' teaching efficacy beliefs about genetically modified (GM) foods using a belief system approach. We assumed that preservice teachers' beliefs about GM foods (content…

Genetic optimization of steam multi-turbines system

International Nuclear Information System (INIS)

Olszewski, Pawel

2014-01-01

Optimization analysis of partially loaded cogeneration, multiple-stages steam turbines system was numerically investigated by using own-developed code (C++). The system can be controlled by following variables: fresh steam temperature, pressure, and flow rates through all stages in steam turbines. Five various strategies, four thermodynamics and one economical, which quantify system operation, were defined and discussed as an optimization functions. Mathematical model of steam turbines calculates steam properties according to the formulation proposed by the International Association for the Properties of Water and Steam. Genetic algorithm GENOCOP was implemented as a solving engine for non–linear problem with handling constrains. Using formulated methodology, example solution for partially loaded system, composed of five steam turbines (30 input variables) with different characteristics, was obtained for five strategies. The genetic algorithm found multiple solutions (various input parameters sets) giving similar overall results. In real application it allows for appropriate scheduling of machine operation that would affect equable time load of every system compounds. Also based on these results three strategies where chosen as the most complex: the first thermodynamic law energy and exergy efficiency maximization and total equivalent energy minimization. These strategies can be successfully used in optimization of real cogeneration applications. - Highlights: • Genetic optimization model for a set of five various steam turbines was presented. • Four various thermodynamic optimization strategies were proposed and discussed. • Operational parameters (steam pressure, temperature, flow) influence was examined. • Genetic algorithm generated optimal solutions giving the best estimators values. • It has been found that similar energy effect can be obtained for various inputs

A yeast screening system for simultaneously monitoring multiple genetic endpoints

International Nuclear Information System (INIS)

Dixon, M.L.; Mortimer, R.K.

1986-01-01

Mutation, recombination, and mitochondrial deficiencies have been proposed to have roles in the carcinogenic process. The authors describe a diploid strain of the yeast Saccharomyces cerevisiae capable of detecting this wide spectrum of genetic changes. The markers used for monitoring these events have been especially well characterized genetically. Ultraviolet light was chosen as a model carcinogenic agent to test this system. In addition to highly significant increases in the frequencies of each genetic change, increases in the absolute numbers of each change indicated induction and not selective survival. The relative amounts of each type of genetic change varied with dose. The wide spectrum of endpoints monitored in the XD83 yeast system may allow the detection of certain carcinogens and other genetically toxic agents which have escaped detection in more limited systems. Since only one strain is required to simultaneously monitor these genetic changes, this assay system should facilitate comparisons of the induced changes and be more efficient than using multiple strains to monitor the same endpoints. (Auth.)

CRISPR-Cas9: a promising genetic engineering approach in cancer research

Science.gov (United States)

Ratan, Zubair Ahmed; Son, Young-Jin; Uddin, Bhuiyan Mohammad Mahtab; Yusuf, Md. Abdullah; Zaman, Sojib Bin; Kim, Jong-Hoon; Banu, Laila Anjuman

2018-01-01

Bacteria and archaea possess adaptive immunity against foreign genetic materials through clustered regularly interspaced short palindromic repeat (CRISPR) systems. The discovery of this intriguing bacterial system heralded a revolutionary change in the field of medical science. The CRISPR and CRISPR-associated protein 9 (Cas9) based molecular mechanism has been applied to genome editing. This CRISPR-Cas9 technique is now able to mediate precise genetic corrections or disruptions in in vitro and in vivo environments. The accuracy and versatility of CRISPR-Cas have been capitalized upon in biological and medical research and bring new hope to cancer research. Cancer involves complex alterations and multiple mutations, translocations and chromosomal losses and gains. The ability to identify and correct such mutations is an important goal in cancer treatment. In the context of this complex cancer genomic landscape, there is a need for a simple and flexible genetic tool that can easily identify functional cancer driver genes within a comparatively short time. The CRISPR-Cas system shows promising potential for modeling, repairing and correcting genetic events in different types of cancer. This article reviews the concept of CRISPR-Cas, its application and related advantages in oncology. PMID:29434679

Systematic documentation and analysis of human genetic variation using the microattribution approach

Science.gov (United States)

Giardine, Belinda; Borg, Joseph; Higgs, Douglas R.; Peterson, Kenneth R.; Maglott, Donna; Basak, A. Nazli; Clark, Barnaby; Faustino, Paula; Felice, Alex E.; Francina, Alain; Gallivan, Monica V. E.; Georgitsi, Marianthi; Gibbons, Richard J.; Giordano, Piero C.; Harteveld, Cornelis L.; Joly, Philippe; Kanavakis, Emmanuel; Kollia, Panagoula; Menzel, Stephan; Miller, Webb; Moradkhani, Kamran; Old, John; Papachatzopoulou, Adamantia; Papadakis, Manoussos N.; Papadopoulos, Petros; Pavlovic, Sonja; Philipsen, Sjaak; Radmilovic, Milena; Riemer, Cathy; Schrijver, Iris; Stojiljkovic, Maja; Thein, Swee Lay; Traeger-Synodinos, Jan; Tully, Ray; Wada, Takahito; Waye, John; Wiemann, Claudia; Zukic, Branka; Chui, David H. K.; Wajcman, Henri; Hardison, Ross C.; Patrinos, George P.

2013-01-01

We developed a series of interrelated locus-specific databases to store all published and unpublished genetic variation related to these disorders, and then implemented microattribution to encourage submission of unpublished observations of genetic variation to these public repositories 1. A total of 1,941 unique genetic variants in 37 genes, encoding globins (HBA2, HBA1, HBG2, HBG1, HBD, HBB) and other erythroid proteins (ALOX5AP, AQP9, ARG2, ASS1, ATRX, BCL11A, CNTNAP2, CSNK2A1, EPAS1, ERCC2, FLT1, GATA1, GPM6B, HAO2, HBS1L, KDR, KL, KLF1, MAP2K1, MAP3K5, MAP3K7, MYB, NOS1, NOS2, NOS3, NOX3, NUP133, PDE7B, SMAD3, SMAD6, and TOX) are currently documented in these databases with reciprocal attribution of microcitations to data contributors. Our project provides the first example of implementing microattribution to incentivise submission of all known genetic variation in a defined system. It has demonstrably increased the reporting of human variants and now provides a comprehensive online resource for systematically describing human genetic variation in the globin genes and other genes contributing to hemoglobinopathies and thalassemias. The large repository of previously reported data, together with more recent data, acquired by microattribution, demonstrates how the comprehensive documentation of human variation will provide key insights into normal biological processes and how these are perturbed in human genetic disease. Using the microattribution process set out here, datasets which took decades to accumulate for the globin genes could be assembled rapidly for other genes and disease systems. The principles established here for the globin gene system will serve as a model for other systems and the analysis of other common and/or complex human genetic diseases. PMID:21423179

Food Control and a Citizen Science Approach for Improving Teaching of Genetics in Universities

Science.gov (United States)

Borrell, Y. J.; Muñoz-Colmenero, A. M.; Dopico, E.; Miralles, L.; Garcia-Vazquez, E.

2016-01-01

A Citizen Science approach was implemented in the laboratory practices of Genetics at the University of Oviedo, related with the engaging topic of Food Control. Real samples of food products consumed by students at home ("students as samplers") were employed as teaching material in three different courses of Genetics during the academic…

Toward a generalized and high-throughput enzyme screening system based on artificial genetic circuits.

Science.gov (United States)

Choi, Su-Lim; Rha, Eugene; Lee, Sang Jun; Kim, Haseong; Kwon, Kilkoang; Jeong, Young-Su; Rhee, Young Ha; Song, Jae Jun; Kim, Hak-Sung; Lee, Seung-Goo

2014-03-21

Large-scale screening of enzyme libraries is essential for the development of cost-effective biological processes, which will be indispensable for the production of sustainable biobased chemicals. Here, we introduce a genetic circuit termed the Genetic Enzyme Screening System that is highly useful for high-throughput enzyme screening from diverse microbial metagenomes. The circuit consists of two AND logics. The first AND logic, the two inputs of which are the target enzyme and its substrate, is responsible for the accumulation of a phenol compound in cell. Then, the phenol compound and its inducible transcription factor, whose activation turns on the expression of a reporter gene, interact in the other logic gate. We confirmed that an individual cell harboring this genetic circuit can present approximately a 100-fold higher cellular fluorescence than the negative control and can be easily quantified by flow cytometry depending on the amounts of phenolic derivatives. The high sensitivity of the genetic circuit enables the rapid discovery of novel enzymes from metagenomic libraries, even for genes that show marginal activities in a host system. The crucial feature of this approach is that this single system can be used to screen a variety of enzymes that produce a phenol compound from respective synthetic phenyl-substrates, including cellulase, lipase, alkaline phosphatase, tyrosine phenol-lyase, and methyl parathion hydrolase. Consequently, the highly sensitive and quantitative nature of this genetic circuit along with flow cytometry techniques could provide a widely applicable toolkit for discovering and engineering novel enzymes at a single cell level.

Systems Biology Genetic Approach Identifies Serotonin Pathway as a Possible Target for Obstructive Sleep Apnea: Results from a Literature Search Review

Directory of Open Access Journals (Sweden)

Ram Jagannathan

2017-01-01

Full Text Available Rationale. Overall validity of existing genetic biomarkers in the diagnosis of obstructive sleep apnea (OSA remains unclear. The objective of this systematic genetic study is to identify “novel” biomarkers for OSA using systems biology approach. Methods. Candidate genes for OSA were extracted from PubMed, MEDLINE, and Embase search engines and DisGeNET database. The gene ontology (GO analyses and candidate genes prioritization were performed using Enrichr tool. Genes pertaining to the top 10 pathways were extracted and used for Ingenuity Pathway Analysis. Results. In total, we have identified 153 genes. The top 10 pathways associated with OSA include (i serotonin receptor interaction, (ii pathways in cancer, (iii AGE-RAGE signaling in diabetes, (iv infectious diseases, (v serotonergic synapse, (vi inflammatory bowel disease, (vii HIF-1 signaling pathway, (viii PI3-AKT signaling pathway, (ix regulation lipolysis in adipocytes, and (x rheumatoid arthritis. After removing the overlapping genes, we have identified 23 candidate genes, out of which >30% of the genes were related to the genes involved in the serotonin pathway. Among these 4 serotonin receptors SLC6A4, HTR2C, HTR2A, and HTR1B were strongly associated with OSA. Conclusions. This preliminary report identifies several potential candidate genes associated with OSA and also describes the possible regulatory mechanisms.

Genetic Algorithm Based Economic Dispatch with Valve Point Effect

Energy Technology Data Exchange (ETDEWEB)

Park, Jong Nam; Park, Kyung Won; Kim, Ji Hong; Kim, Jin O [Hanyang University (Korea, Republic of)

1999-03-01

This paper presents a new approach on genetic algorithm to economic dispatch problem for valve point discontinuities. Proposed approach in this paper on genetic algorithms improves the performance to solve economic dispatch problem for valve point discontinuities through improved death penalty method, generation-apart elitism, atavism and sexual selection with sexual distinction. Numerical results on a test system consisting of 13 thermal units show that the proposed approach is faster, more robust and powerful than conventional genetic algorithms. (author). 8 refs., 10 figs.

Genetic Complexity of Episodic Memory: A Twin Approach to Studies of Aging

Science.gov (United States)

Kremen, William S.; Spoon, Kelly M.; Jacobson, Kristen C.; Vasilopoulos, Terrie; McCaffery, Jeanne M.; Panizzon, Matthew S.; Franz, Carol E.; Vuoksimaa, Eero; Xian, Hong; Rana, Brinda K.; Toomey, Rosemary; McKenzie, Ruth; Lyons, Michael J.

2016-01-01

Episodic memory change is a central issue in cognitive aging, and understanding that process will require elucidation of its genetic underpinnings. A key limiting factor in genetically informed research on memory has been lack of attention to genetic and phenotypic complexity, as if “memory is memory” and all well-validated assessments are essentially equivalent. Here we applied multivariate twin models to data from late-middle-aged participants in the Vietnam Era Twin Study of Aging to examine the genetic architecture of 6 measures from 3 standard neuropsychological tests: the California Verbal Learning Test-2, and Wechsler Memory Scale-III Logical Memory (LM) and Visual Reproductions (VR). An advantage of the twin method is that it can estimate the extent to which latent genetic influences are shared or independent across different measures before knowing which specific genes are involved. The best-fitting model was a higher order common pathways model with a heritable higher order general episodic memory factor and three test-specific subfactors. More importantly, substantial genetic variance was accounted for by genetic influences that were specific to the latent LM and VR subfactors (28% and 30%, respectively) and independent of the general factor. Such unique genetic influences could partially account for replication failures. Moreover, if different genes influence different memory phenotypes, they could well have different age-related trajectories. This approach represents an important step toward providing critical information for all types of genetically informative studies of aging and memory. PMID:24956007

An Airborne Conflict Resolution Approach Using a Genetic Algorithm

Science.gov (United States)

Mondoloni, Stephane; Conway, Sheila

2001-01-01

An airborne conflict resolution approach is presented that is capable of providing flight plans forecast to be conflict-free with both area and traffic hazards. This approach is capable of meeting constraints on the flight plan such as required times of arrival (RTA) at a fix. The conflict resolution algorithm is based upon a genetic algorithm, and can thus seek conflict-free flight plans meeting broader flight planning objectives such as minimum time, fuel or total cost. The method has been applied to conflicts occurring 6 to 25 minutes in the future in climb, cruise and descent phases of flight. The conflict resolution approach separates the detection, trajectory generation and flight rules function from the resolution algorithm. The method is capable of supporting pilot-constructed resolutions, cooperative and non-cooperative maneuvers, and also providing conflict resolution on trajectories forecast by an onboard FMC.

Genetic Learning of Fuzzy Expert Systems for Decision Support in the Automated Process of Wooden Boards Cutting

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Yaroslav MATSYSHYN

2014-03-01

Full Text Available Sawing solid wood (lumber, wooden boards into blanks is an important technological operation, which has significant influence on the efficiency of the woodworking industry as a whole. Selecting a rational variant of lumber cutting is a complex multicriteria problem with many stochastic factors, characterized by incomplete information and fuzzy attributes. About this property by currently used automatic optimizing cross-cut saw is not always rational use of wood raw material. And since the optimization algorithms of these saw functions as a “black box”, their improvement is not possible. Therefore topical the task of developing a new approach to the optimal cross-cutting that takes into account stochastic properties of wood as a material from biological origin. Here we propose a new approach to the problem of lumber optimal cutting in the conditions of uncertainty of lumber quantity and fuzziness lengths of defect-free areas. To account for these conditions, we applied the methods of fuzzy sets theory and used a genetic algorithm to simulate the process of human learning in the implementation the technological operation. Thus, the rules of behavior with yet another defect-free area is defined in fuzzy expert system that can be configured to perform specific production tasks using genetic algorithm. The author's implementation of the genetic algorithm is used to set up the parameters of fuzzy expert system. Working capacity of the developed system verified on simulated and real-world data. Implementation of this approach will make it suitable for the control of automated or fully automatic optimizing cross cutting of solid wood.

Generalizing genetical genomics : getting added value from environmental perturbation

NARCIS (Netherlands)

Li, Yang; Breitling, Rainer; Jansen, Ritsert C.

2008-01-01

Genetical genomics is a useful approach for studying the effect of genetic perturbations on biological systems at the molecular level. However, molecular networks depend on the environmental conditions and, thus, a comprehensive understanding of biological systems requires studying them across

Analysis of stock investment selection based on CAPM using covariance and genetic algorithm approach

Science.gov (United States)

Sukono; Susanti, D.; Najmia, M.; Lesmana, E.; Napitupulu, H.; Supian, S.; Putra, A. S.

2018-03-01

Investment is one of the economic growth factors of countries, especially in Indonesia. Stocks is a form of investment, which is liquid. In determining the stock investment decisions which need to be considered by investors is to choose stocks that can generate maximum returns with a minimum risk level. Therefore, we need to know how to allocate the capital which may give the optimal benefit. This study discusses the issue of stock investment based on CAPM which is estimated using covariance and Genetic Algorithm approach. It is assumed that the stocks analyzed follow the CAPM model. To do the estimation of beta parameter on CAPM equation is done by two approach, first is to be represented by covariance approach, and second with genetic algorithm optimization. As a numerical illustration, in this paper analyzed ten stocks traded on the capital market in Indonesia. The results of the analysis show that estimation of beta parameters using covariance and genetic algorithm approach, give the same decision, that is, six underpriced stocks with buying decision, and four overpriced stocks with a sales decision. Based on the analysis, it can be concluded that the results can be used as a consideration for investors buying six under-priced stocks, and selling four overpriced stocks.

Introduction to focus issue: quantitative approaches to genetic networks.

Science.gov (United States)

Albert, Réka; Collins, James J; Glass, Leon

2013-06-01

All cells of living organisms contain similar genetic instructions encoded in the organism's DNA. In any particular cell, the control of the expression of each different gene is regulated, in part, by binding of molecular complexes to specific regions of the DNA. The molecular complexes are composed of protein molecules, called transcription factors, combined with various other molecules such as hormones and drugs. Since transcription factors are coded by genes, cellular function is partially determined by genetic networks. Recent research is making large strides to understand both the structure and the function of these networks. Further, the emerging discipline of synthetic biology is engineering novel gene circuits with specific dynamic properties to advance both basic science and potential practical applications. Although there is not yet a universally accepted mathematical framework for studying the properties of genetic networks, the strong analogies between the activation and inhibition of gene expression and electric circuits suggest frameworks based on logical switching circuits. This focus issue provides a selection of papers reflecting current research directions in the quantitative analysis of genetic networks. The work extends from molecular models for the binding of proteins, to realistic detailed models of cellular metabolism. Between these extremes are simplified models in which genetic dynamics are modeled using classical methods of systems engineering, Boolean switching networks, differential equations that are continuous analogues of Boolean switching networks, and differential equations in which control is based on power law functions. The mathematical techniques are applied to study: (i) naturally occurring gene networks in living organisms including: cyanobacteria, Mycoplasma genitalium, fruit flies, immune cells in mammals; (ii) synthetic gene circuits in Escherichia coli and yeast; and (iii) electronic circuits modeling genetic networks

An Adaptive Agent-Based Model of Homing Pigeons: A Genetic Algorithm Approach

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Francis Oloo

2017-01-01

Full Text Available Conventionally, agent-based modelling approaches start from a conceptual model capturing the theoretical understanding of the systems of interest. Simulation outcomes are then used “at the end” to validate the conceptual understanding. In today’s data rich era, there are suggestions that models should be data-driven. Data-driven workflows are common in mathematical models. However, their application to agent-based models is still in its infancy. Integration of real-time sensor data into modelling workflows opens up the possibility of comparing simulations against real data during the model run. Calibration and validation procedures thus become automated processes that are iteratively executed during the simulation. We hypothesize that incorporation of real-time sensor data into agent-based models improves the predictive ability of such models. In particular, that such integration results in increasingly well calibrated model parameters and rule sets. In this contribution, we explore this question by implementing a flocking model that evolves in real-time. Specifically, we use genetic algorithms approach to simulate representative parameters to describe flight routes of homing pigeons. The navigation parameters of pigeons are simulated and dynamically evaluated against emulated GPS sensor data streams and optimised based on the fitness of candidate parameters. As a result, the model was able to accurately simulate the relative-turn angles and step-distance of homing pigeons. Further, the optimised parameters could replicate loops, which are common patterns in flight tracks of homing pigeons. Finally, the use of genetic algorithms in this study allowed for a simultaneous data-driven optimization and sensitivity analysis.

Zebrafish Functional Genetics Approach to the Pathogenesis of Well-Differentiated Liposarcoma

Science.gov (United States)

2015-12-01

Roderick JE, LaBelle JL, Bird G, Mathieu R, Bodaar K, Colon D, Pyati U, Stevenson KE, Qi J, Harris M, Silverman LB, Sallan SE, Bradner JL, Neuberg DS...pathogenesis of high-risk T-cell acute lymphoblastic leukemia. Our approach combines human cancer genomics with functional genetics, biochemistry and

Application of Smart Infrastructure Systems approach to precision medicine

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Diddahally R. Govindaraju

2015-12-01

Full Text Available All biological variation is hierarchically organized dynamic network system of genomic components, organelles, cells, tissues, organs, individuals, families, populations and metapopulations. Individuals are axial in this hierarchy, as they represent antecedent, attendant and anticipated aspects of health, disease, evolution and medical care. Humans show individual specific genetic and clinical features such as complexity, cooperation, resilience, robustness, vulnerability, self-organization, latent and emergent behavior during their development, growth and senescence. Accurate collection, measurement, organization and analyses of individual specific data, embedded at all stratified levels of biological, demographic and cultural diversity – the big data – is necessary to make informed decisions on health, disease and longevity; which is a central theme of precision medicine initiative (PMI. This initiative also calls for the development of novel analytical approaches to handle complex multidimensional data. Here we suggest the application of Smart Infrastructure Systems (SIS approach to accomplish some of the goals set forth by the PMI on the premise that biological systems and the SIS share many common features. The latter has been successfully employed in managing complex networks of non-linear adaptive controls, commonly encountered in smart engineering systems. We highlight their concordance and discuss the utility of the SIS approach in precision medicine programs.

Non-Genetic Engineering Approaches for Isolating and Generating Novel Yeasts for Industrial Applications

Science.gov (United States)

Chambers, P. J.; Bellon, J. R.; Schmidt, S. A.; Varela, C.; Pretorius, I. S.

Generating novel yeast strains for industrial applications should be quite straightforward; after all, research into the genetics, biochemistry and physiology of Baker's Yeast, Saccharomyces cerevisiae, has paved the way for many advances in the modern biological sciences. We probably know more about this humble eukaryote than any other, and it is the most tractable of organisms for manipulation using modern genetic engineering approaches. In many countries, however, there are restrictions on the use of genetically-modified organisms (GMOs), particularly in foods and beverages, and the level of consumer acceptance of GMOs is, at best, variable. Thus, many researchers working with industrial yeasts use genetic engineering techniques primarily as research tools, and strain development continues to rely on non-GM technologies. This chapter explores the non-GM tools and strategies available to such researchers.

Basic Genetics: A Human Approach.

Science.gov (United States)

Biological Sciences Curriculum Study, Colorado Springs, CO. Center for Education in Human and Medical Genetics.

This document (which has the form of a magazine) provides a variety of articles, stories, editorials, letters, interviews, and other types of magazine features (such as book reviews) which focus on human genetics. In addition to providing information about the principles of genetics, nearly all of the sections in the "magazine" address moral,…

Multiobjective genetic algorithm approaches to project scheduling under risk

OpenAIRE

Kılıç, Murat; Kilic, Murat

2003-01-01

In this thesis, project scheduling under risk is chosen as the topic of research. Project scheduling under risk is defined as a biobjective decision problem and is formulated as a 0-1 integer mathematical programming model. In this biobjective formulation, one of the objectives is taken as the expected makespan minimization and the other is taken as the expected cost minimization. As the solution approach to this biobjective formulation genetic algorithm (GA) is chosen. After carefully invest...

Cryptic Genetic Variation in Evolutionary Developmental Genetics

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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.

Application of genetic algorithms to tuning fuzzy control systems

Science.gov (United States)

Espy, Todd; Vombrack, Endre; Aldridge, Jack

1993-01-01

Real number genetic algorithms (GA) were applied for tuning fuzzy membership functions of three controller applications. The first application is our 'Fuzzy Pong' demonstration, a controller that controls a very responsive system. The performance of the automatically tuned membership functions exceeded that of manually tuned membership functions both when the algorithm started with randomly generated functions and with the best manually-tuned functions. The second GA tunes input membership functions to achieve a specified control surface. The third application is a practical one, a motor controller for a printed circuit manufacturing system. The GA alters the positions and overlaps of the membership functions to accomplish the tuning. The applications, the real number GA approach, the fitness function and population parameters, and the performance improvements achieved are discussed. Directions for further research in tuning input and output membership functions and in tuning fuzzy rules are described.

Mouse genetic approaches applied to the normal tissue radiation response

International Nuclear Information System (INIS)

Haston, Christina K.

2012-01-01

The varying responses of inbred mouse models to radiation exposure present a unique opportunity to dissect the genetic basis of radiation sensitivity and tissue injury. Such studies are complementary to human association studies as they permit both the analysis of clinical features of disease, and of specific variants associated with its presentation, in a controlled environment. Herein I review how animal models are studied to identify specific genetic variants influencing predisposition to radiation-induced traits. Among these radiation-induced responses are documented strain differences in repair of DNA damage and in extent of tissue injury (in the lung, skin, and intestine) which form the base for genetic investigations. For example, radiation-induced DNA damage is consistently greater in tissues from BALB/cJ mice, than the levels in C57BL/6J mice, suggesting there may be an inherent DNA damage level per strain. Regarding tissue injury, strain specific inflammatory and fibrotic phenotypes have been documented for principally, C57BL/6 C3H and A/J mice but a correlation among responses such that knowledge of the radiation injury in one tissue informs of the response in another is not evident. Strategies to identify genetic differences contributing to a trait based on inbred strain differences, which include linkage analysis and the evaluation of recombinant congenic (RC) strains, are presented, with a focus on the lung response to irradiation which is the only radiation-induced tissue injury mapped to date. Such approaches are needed to reveal genetic differences in susceptibility to radiation injury, and also to provide a context for the effects of specific genetic variation uncovered in anticipated clinical association studies. In summary, mouse models can be studied to uncover heritable variation predisposing to specific radiation responses, and such variations may point to pathways of importance to phenotype development in the clinic.

Systems genetics analysis of pharmacogenomics variation during antidepressant treatment

DEFF Research Database (Denmark)

Madsen, Majbritt Busk; Kogelman, L J A; Kadarmideen, H N

2016-01-01

Selective serotonin reuptake inhibitors (SSRIs) are the most widely used antidepressants, but the efficacy of the treatment varies significantly among individuals. It is believed that complex genetic mechanisms play a part in this variation. We have used a network based approach to unravel the in...... genes involved in calcium homeostasis. In conclusion, we suggest a difference in genetic interaction networks between initial and subsequent SSRI response.The Pharmacogenomics Journal advance online publication, 18 October 2016; doi:10.1038/tpj.2016.68....

Branch-pipe-routing approach for ships using improved genetic algorithm

Science.gov (United States)

Sui, Haiteng; Niu, Wentie

2016-09-01

Branch-pipe routing plays fundamental and critical roles in ship-pipe design. The branch-pipe-routing problem is a complex combinatorial optimization problem and is thus difficult to solve when depending only on human experts. A modified genetic-algorithm-based approach is proposed in this paper to solve this problem. The simplified layout space is first divided into threedimensional (3D) grids to build its mathematical model. Branch pipes in layout space are regarded as a combination of several two-point pipes, and the pipe route between two connection points is generated using an improved maze algorithm. The coding of branch pipes is then defined, and the genetic operators are devised, especially the complete crossover strategy that greatly accelerates the convergence speed. Finally, simulation tests demonstrate the performance of proposed method.

Unraveling the genetic landscape of autosomal recessive Charcot-Marie-Tooth neuropathies using a homozygosity mapping approach

Science.gov (United States)

Zimoń, Magdalena; Battaloǧlu, Esra; Parman, Yesim; Erdem, Sevim; Baets, Jonathan; De Vriendt, Els; Atkinson, Derek; Almeida-Souza, Leonardo; Deconinck, Tine; Ozes, Burcak; Goossens, Dirk; Cirak, Sebahattin; Van Damme, Philip; Shboul, Mohammad; Voit, Thomas; Van Maldergem, Lionel; Dan, Bernard; El-Khateeb, Mohammed S.; Guergueltcheva, Velina; Lopez-Laso, Eduardo; Goemans, Nathalie; Masri, Amira; Züchner, Stephan; Timmerman, Vincent; Topaloǧlu, Haluk; De Jonghe, Peter

2016-01-01

Autosomal recessive forms of Charcot-Marie-Tooth disease (ARCMT) are rare but severe disorders of the peripheral nervous system. Their molecular basis is poorly understood due to the extensive genetic and clinical heterogeneity, posing considerable challenges for patients, physicians, and researchers. We report on the genetic findings from a systematic study of a large collection of 174 independent ARCMT families. Initial sequencing of the three most common ARCMT genes (ganglioside-induced differentiation protein 1—GDAP1, SH3 domain and tetratricopeptide repeats-containing protein 2—SH3TC2, histidine-triad nucleotide binding protein 1—HINT1) identified pathogenic mutations in 41 patients. Subsequently, 87 selected nuclear families underwent single nucleotide polymorphism (SNP) genotyping and homozygosity mapping, followed by targeted screening of known ARCMT genes. This strategy provided molecular diagnosis to 22 % of the families. Altogether, our unbiased genetic approach identified pathogenic mutations in ten ARCMT genes in a total of 41.3 % patients. Apart from a newly described founder mutation in GDAP1, the majority of variants constitute private molecular defects. Since the gene testing was independent of the clinical phenotype of the patients, we identified mutations in patients with unusual or additional clinical features, extending the phenotypic spectrum of the SH3TC2 gene. Our study provides an overview of the ARCMT genetic landscape and proposes guidelines for tackling the genetic heterogeneity of this group of hereditary neuropathies. PMID:25231362

Efficacy of a web-based intelligent tutoring system for communicating genetic risk of breast cancer: a fuzzy-trace theory approach.

Science.gov (United States)

Wolfe, Christopher R; Reyna, Valerie F; Widmer, Colin L; Cedillos, Elizabeth M; Fisher, Christopher R; Brust-Renck, Priscila G; Weil, Audrey M

2015-01-01

. Many healthy women consider genetic testing for breast cancer risk, yet BRCA testing issues are complex. . To determine whether an intelligent tutor, BRCA Gist, grounded in fuzzy-trace theory (FTT), increases gist comprehension and knowledge about genetic testing for breast cancer risk, improving decision making. . In 2 experiments, 410 healthy undergraduate women were randomly assigned to 1 of 3 groups: an online module using a Web-based tutoring system (BRCA Gist) that uses artificial intelligence technology, a second group read highly similar content from the National Cancer Institute (NCI) Web site, and a third that completed an unrelated tutorial. . BRCA Gist applied FTT and was designed to help participants develop gist comprehension of topics relevant to decisions about BRCA genetic testing, including how breast cancer spreads, inherited genetic mutations, and base rates. . We measured content knowledge, gist comprehension of decision-relevant information, interest in testing, and genetic risk and testing judgments. . Control knowledge scores ranged from 54% to 56%, NCI improved significantly to 65% and 70%, and BRCA Gist improved significantly more to 75% and 77%, P tutors, such as BRCA Gist, are scalable, cost-effective ways of helping people understand complex issues, improving decision making. © The Author(s) 2014.

A proteomic network approach across the ALS-FTD disease spectrum resolves clinical phenotypes and genetic vulnerability in human brain.

Science.gov (United States)

Umoh, Mfon E; Dammer, Eric B; Dai, Jingting; Duong, Duc M; Lah, James J; Levey, Allan I; Gearing, Marla; Glass, Jonathan D; Seyfried, Nicholas T

2018-01-01

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are neurodegenerative diseases with overlap in clinical presentation, neuropathology, and genetic underpinnings. The molecular basis for the overlap of these disorders is not well established. We performed a comparative unbiased mass spectrometry-based proteomic analysis of frontal cortical tissues from postmortem cases clinically defined as ALS, FTD, ALS and FTD (ALS/FTD), and controls. We also included a subset of patients with the C9orf72 expansion mutation, the most common genetic cause of both ALS and FTD Our systems-level analysis of the brain proteome integrated both differential expression and co-expression approaches to assess the relationship of these differences to clinical and pathological phenotypes. Weighted co-expression network analysis revealed 15 modules of co-expressed proteins, eight of which were significantly different across the ALS-FTD disease spectrum. These included modules associated with RNA binding proteins, synaptic transmission, and inflammation with cell-type specificity that showed correlation with TDP-43 pathology and cognitive dysfunction. Modules were also examined for their overlap with TDP-43 protein-protein interactions, revealing one module enriched with RNA-binding proteins and other causal ALS genes that increased in FTD/ALS and FTD cases. A module enriched with astrocyte and microglia proteins was significantly increased in ALS cases carrying the C9orf72 mutation compared to sporadic ALS cases, suggesting that the genetic expansion is associated with inflammation in the brain even without clinical evidence of dementia. Together, these findings highlight the utility of integrative systems-level proteomic approaches to resolve clinical phenotypes and genetic mechanisms underlying the ALS-FTD disease spectrum in human brain. © 2017 The Authors. Published under the terms of the CC BY 4.0 license.

Genetic and epigenetic control of gene expression by CRISPR–Cas systems

Science.gov (United States)

Lo, Albert; Qi, Lei

2017-01-01

The discovery and adaption of bacterial clustered regularly interspaced short palindromic repeats (CRISPR)–CRISPR-associated (Cas) systems has revolutionized the way researchers edit genomes. Engineering of catalytically inactivated Cas variants (nuclease-deficient or nuclease-deactivated [dCas]) combined with transcriptional repressors, activators, or epigenetic modifiers enable sequence-specific regulation of gene expression and chromatin state. These CRISPR–Cas-based technologies have contributed to the rapid development of disease models and functional genomics screening approaches, which can facilitate genetic target identification and drug discovery. In this short review, we will cover recent advances of CRISPR–dCas9 systems and their use for transcriptional repression and activation, epigenome editing, and engineered synthetic circuits for complex control of the mammalian genome. PMID:28649363

Introducing Systems Approaches

Science.gov (United States)

Reynolds, Martin; Holwell, Sue

Systems Approaches to Managing Change brings together five systems approaches to managing complex issues, each having a proven track record of over 25 years. The five approaches are: System Dynamics (SD) developed originally in the late 1950s by Jay Forrester Viable Systems Model (VSM) developed originally in the late 1960s by Stafford Beer Strategic Options Development and Analysis (SODA: with cognitive mapping) developed originally in the 1970s by Colin Eden Soft Systems Methodology (SSM) developed originally in the 1970s by Peter Checkland Critical Systems Heuristics (CSH) developed originally in the late 1970s by Werner Ulrich

A systems genetics approach identifies CXCL14, ITGAX, and LPCAT2 as novel aggressive prostate cancer susceptibility genes.

Directory of Open Access Journals (Sweden)

Kendra A Williams

2014-11-01

Full Text Available Although prostate cancer typically runs an indolent course, a subset of men develop aggressive, fatal forms of this disease. We hypothesize that germline variation modulates susceptibility to aggressive prostate cancer. The goal of this work is to identify susceptibility genes using the C57BL/6-Tg(TRAMP8247Ng/J (TRAMP mouse model of neuroendocrine prostate cancer. Quantitative trait locus (QTL mapping was performed in transgene-positive (TRAMPxNOD/ShiLtJ F2 intercross males (n = 228, which facilitated identification of 11 loci associated with aggressive disease development. Microarray data derived from 126 (TRAMPxNOD/ShiLtJ F2 primary tumors were used to prioritize candidate genes within QTLs, with candidate genes deemed as being high priority when possessing both high levels of expression-trait correlation and a proximal expression QTL. This process enabled the identification of 35 aggressive prostate tumorigenesis candidate genes. The role of these genes in aggressive forms of human prostate cancer was investigated using two concurrent approaches. First, logistic regression analysis in two human prostate gene expression datasets revealed that expression levels of five genes (CXCL14, ITGAX, LPCAT2, RNASEH2A, and ZNF322 were positively correlated with aggressive prostate cancer and two genes (CCL19 and HIST1H1A were protective for aggressive prostate cancer. Higher than average levels of expression of the five genes that were positively correlated with aggressive disease were consistently associated with patient outcome in both human prostate cancer tumor gene expression datasets. Second, three of these five genes (CXCL14, ITGAX, and LPCAT2 harbored polymorphisms associated with aggressive disease development in a human GWAS cohort consisting of 1,172 prostate cancer patients. This study is the first example of using a systems genetics approach to successfully identify novel susceptibility genes for aggressive prostate cancer. Such

Arbitrariness is not enough: towards a functional approach to the genetic code.

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Lacková, Ľudmila; Matlach, Vladimír; Faltýnek, Dan

2017-12-01

Arbitrariness in the genetic code is one of the main reasons for a linguistic approach to molecular biology: the genetic code is usually understood as an arbitrary relation between amino acids and nucleobases. However, from a semiotic point of view, arbitrariness should not be the only condition for definition of a code, consequently it is not completely correct to talk about "code" in this case. Yet we suppose that there exist a code in the process of protein synthesis, but on a higher level than the nucleic bases chains. Semiotically, a code should be always associated with a function and we propose to define the genetic code not only relationally (in basis of relation between nucleobases and amino acids) but also in terms of function (function of a protein as meaning of the code). Even if the functional definition of meaning in the genetic code has been discussed in the field of biosemiotics, its further implications have not been considered. In fact, if the function of a protein represents the meaning of the genetic code (the sign's object), then it is crucial to reconsider the notion of its expression (the sign) as well. In our contribution, we will show that the actual model of the genetic code is not the only possible and we will propose a more appropriate model from a semiotic point of view.

DNA enrichment approaches to identify unauthorized genetically modified organisms (GMOs).

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Arulandhu, Alfred J; van Dijk, Jeroen P; Dobnik, David; Holst-Jensen, Arne; Shi, Jianxin; Zel, Jana; Kok, Esther J

2016-07-01

With the increased global production of different genetically modified (GM) plant varieties, chances increase that unauthorized GM organisms (UGMOs) may enter the food chain. At the same time, the detection of UGMOs is a challenging task because of the limited sequence information that will generally be available. PCR-based methods are available to detect and quantify known UGMOs in specific cases. If this approach is not feasible, DNA enrichment of the unknown adjacent sequences of known GMO elements is one way to detect the presence of UGMOs in a food or feed product. These enrichment approaches are also known as chromosome walking or gene walking (GW). In recent years, enrichment approaches have been coupled with next generation sequencing (NGS) analysis and implemented in, amongst others, the medical and microbiological fields. The present review will provide an overview of these approaches and an evaluation of their applicability in the identification of UGMOs in complex food or feed samples.

Developmental psychopathology in an era of molecular genetics and neuroimaging: A developmental neurogenetics approach.

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Hyde, Luke W

2015-05-01

The emerging field of neurogenetics seeks to model the complex pathways from gene to brain to behavior. This field has focused on imaging genetics techniques that examine how variability in common genetic polymorphisms predict differences in brain structure and function. These studies are informed by other complimentary techniques (e.g., animal models and multimodal imaging) and have recently begun to incorporate the environment through examination of Imaging Gene × Environment interactions. Though neurogenetics has the potential to inform our understanding of the development of psychopathology, there has been little integration between principles of neurogenetics and developmental psychopathology. The paper describes a neurogenetics and Imaging Gene × Environment approach and how these approaches have been usefully applied to the study of psychopathology. Six tenets of developmental psychopathology (the structure of phenotypes, the importance of exploring mechanisms, the conditional nature of risk, the complexity of multilevel pathways, the role of development, and the importance of who is studied) are identified, and how these principles can further neurogenetics applications to understanding the development of psychopathology is discussed. A major issue of this piece is how neurogenetics and current imaging and molecular genetics approaches can be incorporated into developmental psychopathology perspectives with a goal of providing models for better understanding pathways from among genes, environments, the brain, and behavior.

Integrating a Genetic Algorithm Into a Knowledge-Based System for Ordering Complex Design Processes

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Rogers, James L.; McCulley, Collin M.; Bloebaum, Christina L.

1996-01-01

The design cycle associated with large engineering systems requires an initial decomposition of the complex system into design processes which are coupled through the transference of output data. Some of these design processes may be grouped into iterative subcycles. In analyzing or optimizing such a coupled system, it is essential to be able to determine the best ordering of the processes within these subcycles to reduce design cycle time and cost. Many decomposition approaches assume the capability is available to determine what design processes and couplings exist and what order of execution will be imposed during the design cycle. Unfortunately, this is often a complex problem and beyond the capabilities of a human design manager. A new feature, a genetic algorithm, has been added to DeMAID (Design Manager's Aid for Intelligent Decomposition) to allow the design manager to rapidly examine many different combinations of ordering processes in an iterative subcycle and to optimize the ordering based on cost, time, and iteration requirements. Two sample test cases are presented to show the effects of optimizing the ordering with a genetic algorithm.

Next-generation mammalian genetics toward organism-level systems biology.

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Susaki, Etsuo A; Ukai, Hideki; Ueda, Hiroki R

2017-01-01

Organism-level systems biology in mammals aims to identify, analyze, control, and design molecular and cellular networks executing various biological functions in mammals. In particular, system-level identification and analysis of molecular and cellular networks can be accelerated by next-generation mammalian genetics. Mammalian genetics without crossing, where all production and phenotyping studies of genome-edited animals are completed within a single generation drastically reduce the time, space, and effort of conducting the systems research. Next-generation mammalian genetics is based on recent technological advancements in genome editing and developmental engineering. The process begins with introduction of double-strand breaks into genomic DNA by using site-specific endonucleases, which results in highly efficient genome editing in mammalian zygotes or embryonic stem cells. By using nuclease-mediated genome editing in zygotes, or ~100% embryonic stem cell-derived mouse technology, whole-body knock-out and knock-in mice can be produced within a single generation. These emerging technologies allow us to produce multiple knock-out or knock-in strains in high-throughput manner. In this review, we discuss the basic concepts and related technologies as well as current challenges and future opportunities for next-generation mammalian genetics in organism-level systems biology.

Comparison between genetic fuzzy system and neuro fuzzy system to select oil wells for hydraulic fracturing; Comparacao entre genetic fuzzy system e neuro fuzzy system para selecao de pocos de petroleo para fraturamento hidraulico

Energy Technology Data Exchange (ETDEWEB)

Castro, Antonio Orestes de Salvo [PETROBRAS, Rio de Janeiro, RJ (Brazil); Ferreira Filho, Virgilio Jose Martins [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil)

2004-07-01

The hydraulic fracture operation is wide used to increase the oil wells production and to reduce formation damage. Reservoir studies and engineer analysis are made to select the wells for this kind of operation. As the reservoir parameters have some diffuses characteristics, Fuzzy Inference Systems (SIF) have been tested for this selection processes in the last few years. This paper compares the performance of a neuro fuzzy system and a genetic fuzzy system used for hydraulic Fracture well selection, with knowledge acquisition from an operational data base to set the SIF membership functions. The training data and the validation data used were the same for both systems. We concluded that, in despite of the genetic fuzzy system would be a younger process, it got better results than the neuro fuzzy system. Another conclusion was that, as the genetic fuzzy system can work with constraints, the membership functions setting kept the consistency of variables linguistic values. (author)

A reverse genetics approach to study feline infectious peritonitis.

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Tekes, Gergely; Spies, Danica; Bank-Wolf, Barbara; Thiel, Volker; Thiel, Heinz-Jürgen

2012-06-01

Feline infectious peritonitis (FIP) is a lethal immunopathological disease caused by feline coronaviruses (FCoVs). Here, we describe a reverse genetics approach to study FIP by assessing the pathogenicity of recombinant type I and type II and chimeric type I/type II FCoVs. All recombinant FCoVs established productive infection in cats, and recombinant type II FCoV (strain 79-1146) induced FIP. Virus sequence analyses from FIP-diseased cats revealed that the 3c gene stop codon of strain 79-1146 has changed to restore a full-length open reading frame (ORF).

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

Population genetics of Setaria viridis, a new model system.

Science.gov (United States)

Huang, Pu; Feldman, Maximilian; Schroder, Stephan; Bahri, Bochra A; Diao, Xianmin; Zhi, Hui; Estep, Matt; Baxter, Ivan; Devos, Katrien M; Kellogg, Elizabeth A

2014-10-01

An extensive survey of the standing genetic variation in natural populations is among the priority steps in developing a species into a model system. In recent years, green foxtail (Setaria viridis), along with its domesticated form foxtail millet (S. italica), has rapidly become a promising new model system for C4 grasses and bioenergy crops, due to its rapid life cycle, large amount of seed production and small diploid genome, among other characters. However, remarkably little is known about the genetic diversity in natural populations of this species. In this study, we survey the genetic diversity of a worldwide sample of more than 200 S. viridis accessions, using the genotyping-by-sequencing technique. Two distinct genetic groups in S. viridis and a third group resembling S. italica were identified, with considerable admixture among the three groups. We find the genetic variation of North American S. viridis correlates with both geography and climate and is representative of the total genetic diversity in this species. This pattern may reflect several introduction/dispersal events of S. viridis into North America. We also modelled demographic history and show signal of recent population decline in one subgroup. Finally, we show linkage disequilibrium decay is rapid (<45 kb) in our total sample and slow in genetic subgroups. These results together provide an in-depth understanding of the pattern of genetic diversity of this new model species on a broad geographic scale. They also provide key guidelines for on-going and future work including germplasm preservation, local adaptation, crossing designs and genomewide association studies. © 2014 John Wiley & Sons Ltd.

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

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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

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%.

Stabilization of Electromagnetic Suspension System Behavior by Genetic Algorithm

Directory of Open Access Journals (Sweden)

Abbas Najar Khoda Bakhsh

2012-07-01

Full Text Available Electromagnetic suspension system with a nonlinear and unstable behavior, is used in maglev trains. In this paper a linear mathematical model of system is achieved and the state feedback method is used to improve the system stability. The control coefficients are tuned by two different methods, Riccati and a new method based on Genetic algorithm. In this new proposed method, we use Genetic algorithm to achieve the optimum values of control coefficients. The results of the system simulation by Matlab indicate the effectiveness of new proposed system. When a new reference of air gap is needed or a new external force is added, the proposed system could omit the vibration and shake of the train coupe and so, passengers feel more comfortable.

Chapter 7. Management strategies for dwarf mistletoes: Biological, chemical, and genetic approaches

Science.gov (United States)

S. F. Shamoun; L. E. DeWald

2002-01-01

The opportunity and need for management of mistletoe populations with biological, chemical, and genetic approaches are greatest for application to the dwarf mistletoes. Although much information is available on these management strategies (see reviews by Hawksworth 1972, Knutson 1978), significant research and development are still required for these to become...

Interspecific sex in grass smuts and the genetic diversity of their pheromone-receptor system.

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Ronny Kellner

2011-12-01

Full Text Available The grass smuts comprise a speciose group of biotrophic plant parasites, so-called Ustilaginaceae, which are specifically adapted to hosts of sweet grasses, the Poaceae family. Mating takes a central role in their life cycle, as it initiates parasitism by a morphological and physiological transition from saprobic yeast cells to pathogenic filaments. As in other fungi, sexual identity is determined by specific genomic regions encoding allelic variants of a pheromone-receptor (PR system and heterodimerising transcription factors. Both operate in a biphasic mating process that starts with PR-triggered recognition, directed growth of conjugation hyphae, and plasmogamy of compatible mating partners. So far, studies on the PR system of grass smuts revealed diverse interspecific compatibility and mating type determination. However, many questions concerning the specificity and evolutionary origin of the PR system remain unanswered. Combining comparative genetics and biological approaches, we report on the specificity of the PR system and its genetic diversity in 10 species spanning about 100 million years of mating type evolution. We show that three highly syntenic PR alleles are prevalent among members of the Ustilaginaceae, favouring a triallelic determination as the plesiomorphic characteristic of this group. Furthermore, the analysis of PR loci revealed increased genetic diversity of single PR locus genes compared to genes of flanking regions. Performing interspecies sex tests, we detected a high potential for hybridisation that is directly linked to pheromone signalling as known from intraspecies sex. Although the PR system seems to be optimised for intraspecific compatibility, the observed functional plasticity of the PR system increases the potential for interspecific sex, which might allow the hybrid-based genesis of newly combined host specificities.

A multi-objective genetic approach to domestic load scheduling in an energy management system

International Nuclear Information System (INIS)

Soares, Ana; Antunes, Carlos Henggeler; Oliveira, Carlos; Gomes, Álvaro

2014-01-01

In this paper a multi-objective genetic algorithm is used to solve a multi-objective model to optimize the time allocation of domestic loads within a planning period of 36 h, in a smart grid context. The management of controllable domestic loads is aimed at minimizing the electricity bill and the end-user’s dissatisfaction concerning two different aspects: the preferred time slots for load operation and the risk of interruption of the energy supply. The genetic algorithm is similar to the Elitist NSGA-II (Nondominated Sorting Genetic Algorithm II), in which some changes have been introduced to adapt it to the physical characteristics of the load scheduling problem and improve usability of results. The mathematical model explicitly considers economical, technical, quality of service and comfort aspects. Illustrative results are presented and the characteristics of different solutions are analyzed. - Highlights: • A genetic algorithm similar to the NSGA-II is used to solve a multi-objective model. • The optimized time allocation of domestic loads in a smart grid context is achieved. • A variable preference profile for the operation of the managed loads is included. • A safety margin is used to account for the quality of the energy services provided. • A non-dominated front with the solutions in the two-objective space is obtained

Dynamic modeling of genetic networks using genetic algorithm and S-system.

Science.gov (United States)

Kikuchi, Shinichi; Tominaga, Daisuke; Arita, Masanori; Takahashi, Katsutoshi; Tomita, Masaru

2003-03-22

The modeling of system dynamics of genetic networks, metabolic networks or signal transduction cascades from time-course data is formulated as a reverse-problem. Previous studies focused on the estimation of only network structures, and they were ineffective in inferring a network structure with feedback loops. We previously proposed a method to predict not only the network structure but also its dynamics using a Genetic Algorithm (GA) and an S-system formalism. However, it could predict only a small number of parameters and could rarely obtain essential structures. In this work, we propose a unified extension of the basic method. Notable improvements are as follows: (1) an additional term in its evaluation function that aims at eliminating futile parameters; (2) a crossover method called Simplex Crossover (SPX) to improve its optimization ability; and (3) a gradual optimization strategy to increase the number of predictable parameters. The proposed method is implemented as a C program called PEACE1 (Predictor by Evolutionary Algorithms and Canonical Equations 1). Its performance was compared with the basic method. The comparison showed that: (1) the convergence rate increased about 5-fold; (2) the optimization speed was raised about 1.5-fold; and (3) the number of predictable parameters was increased about 5-fold. Moreover, we successfully inferred the dynamics of a small genetic network constructed with 60 parameters for 5 network variables and feedback loops using only time-course data of gene expression.

[Genetic diagnostics of pathogenic splicing abnormalities in the clinical laboratory--pitfalls and screening approaches].

Science.gov (United States)

Niimi, Hideki; Ogawa, Tomomi; Note, Rhougou; Hayashi, Shirou; Ueno, Tomohiro; Harada, Kenu; Uji, Yoshinori; Kitajima, Isao

2010-12-01

In recent years, genetic diagnostics of pathogenic splicing abnormalities are increasingly recognized as critically important in the clinical genetic diagnostics. It is reported that approximately 10% of pathogenic mutations causing human inherited diseases are splicing mutations. Nonetheless, it is still difficult to identify splicing abnormalities in routine genetic diagnostic settings. Here, we studied two different kinds of cases with splicing abnormalities. The first case is a protein S deficiency. Nucleotide analyses revealed that the proband had a previously reported G to C substitution in the invariant AG dinucleotide at the splicing acceptor site of intronl/exon2, which produces multiple splicing abnormalities resulting in protein S deficiency. The second case is an antithrombin (AT) deficiency. This proband had a previously reported G to A substitution, at nucleotide position 9788 in intron 4, 14 bp in front of exon 5, which created a de novo exon 5 splice site and resulted in AT deficiency. From a practical standpoint, we discussed the pitfalls, attentions, and screening approaches in genetic diagnostics of pathogenic splicing abnormalities. Due to the difficulty with full-length sequence analysis of introns, and the lack of RNA samples, splicing mutations may escape identification. Although current genetic testing remains to be improved, to screen for splicing abnormalities more efficiently, it is significant to use an appropriate combination of various approaches such as DNA and/or RNA samples, splicing mutation databases, bioinformatic tools to detect splice sites and cis-regulatory elements, and in vitro and/or in vivo experimentally methods as needed.

Genetic Approaches to Study Meiosis and Meiosis-Specific Gene Expression in Saccharomyces cerevisiae.

Science.gov (United States)

Kassir, Yona; Stuart, David T

2017-01-01

The budding yeast Saccharomyces cerevisiae has a long history as a model organism for studies of meiosis and the cell cycle. The popularity of this yeast as a model is in large part due to the variety of genetic and cytological approaches that can be effectively performed with the cells. Cultures of the cells can be induced to synchronously progress through meiosis and sporulation allowing large-scale gene expression and biochemical studies to be performed. Additionally, the spore tetrads resulting from meiosis make it possible to characterize the haploid products of meiosis allowing investigation of meiotic recombination and chromosome segregation. Here we describe genetic methods for analysis progression of S. cerevisiae through meiosis and sporulation with an emphasis on strategies for the genetic analysis of regulators of meiosis-specific genes.

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.

Dating Antarctic ice sheet collapse: Proposing a molecular genetic approach

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Strugnell, Jan M.; Pedro, Joel B.; Wilson, Nerida G.

2018-01-01

Sea levels at the end of this century are projected to be 0.26-0.98 m higher than today. The upper end of this range, and even higher estimates, cannot be ruled out because of major uncertainties in the dynamic response of polar ice sheets to a warming climate. Here, we propose an ecological genetics approach that can provide insight into the past stability and configuration of the West Antarctic Ice Sheet (WAIS). We propose independent testing of the hypothesis that a trans-Antarctic seaway occurred at the last interglacial. Examination of the genomic signatures of bottom-dwelling marine species using the latest methods can provide an independent window into the integrity of the WAIS more than 100,000 years ago. Periods of connectivity facilitated by trans-Antarctic seaways could be revealed by dating coalescent events recorded in DNA. These methods allow alternative scenarios to be tested against a fit to genomic data. Ideal candidate taxa for this work would need to possess a circumpolar distribution, a benthic habitat, and some level of genetic structure indicated by phylogeographical investigation. The purpose of this perspective piece is to set out an ecological genetics method to help resolve when the West Antarctic Ice Shelf last collapsed.

Identification of novel genetic loci for osteoporosis and/or rheumatoid arthritis using cFDR approach.

Directory of Open Access Journals (Sweden)

Rou Zhou

Full Text Available There are co-morbidity between osteoporosis (OP and rheumatoid arthritis (RA. Some genetic risk factors have been identified for these two phenotypes respectively in previous research; however, they accounted for only a small portion of the underlying total genetic variances. Here, we sought to identify additional common genetic loci associated with OP and/or RA. The conditional false discovery rate (cFDR approach allows detection of additional genetic factors (those respective ones as well as common pleiotropic ones for the two associated phenotypes. We collected and analyzed summary statistics provided by large, multi-center GWAS studies of FNK (femoral neck BMD (a major risk factor for osteoporosis (n = 53,236 and RA (n = 80,799. The conditional quantile-quantile (Q-Q plots can assess the enrichment of SNPs related to FNK BMD and RA, respectively. Furthermore, we identified shared loci between FNK BMD and RA using conjunction cFDR (ccFDR. We found strong enrichment of p-values in FNK BMD when conditional Q-Q was done on RA and vice versa. We identified 30 novel OP-RA associated pleiotropic loci that have not been reported in previous OP or RA GWAS, 18 of which located in the MHC (major histocompatibility complex region previously reported to play an important role in immune system and bone health. We identified some specific novel polygenic factors for OP and RA respectively, and identified 30 novel OP-RA associated pleiotropic loci. These discovery findings may offer novel pathobiological insights, and suggest new targets and pathways for drug development in OP and RA patients.

A genetic epidemiology approach to cyber-security.

Science.gov (United States)

Gil, Santiago; Kott, Alexander; Barabási, Albert-László

2014-07-16

While much attention has been paid to the vulnerability of computer networks to node and link failure, there is limited systematic understanding of the factors that determine the likelihood that a node (computer) is compromised. We therefore collect threat log data in a university network to study the patterns of threat activity for individual hosts. We relate this information to the properties of each host as observed through network-wide scans, establishing associations between the network services a host is running and the kinds of threats to which it is susceptible. We propose a methodology to associate services to threats inspired by the tools used in genetics to identify statistical associations between mutations and diseases. The proposed approach allows us to determine probabilities of infection directly from observation, offering an automated high-throughput strategy to develop comprehensive metrics for cyber-security.

Developmental Systems Theory and the Person-Oriented Approach. Commentary on: "An Interpretation of Part of Gilbert Gottlieb's Legacy: Developmental Systems Theory Contra Developmental Behavior Genetics"

Science.gov (United States)

Bergman, Lars R.

2015-01-01

Molenaar's (2015) article concerns Developmental Systems Theory (DST) in relation to behavior genetics and he presents implications of DST for empirical research, especially the need for subject-specific studies. In this commentary, the article is discussed from a broader developmental science perspective, particularly regarded through the lens of…

Maximizing lifetime of wireless sensor networks using genetic approach

DEFF Research Database (Denmark)

Wagh, Sanjeev; Prasad, Ramjee

2014-01-01

The wireless sensor networks are designed to install the smart network applications or network for emergency solutions, where human interaction is not possible. The nodes in wireless sensor networks have to self organize as per the users requirements through monitoring environments. As the sensor......-objective parameters are considered to solve the problem using genetic algorithm of evolutionary approach.......The wireless sensor networks are designed to install the smart network applications or network for emergency solutions, where human interaction is not possible. The nodes in wireless sensor networks have to self organize as per the users requirements through monitoring environments. As the sensor...

Plant Genetic Resources: Selected Issues from Genetic Erosion to Genetic Engineering

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Karl Hammer

2008-04-01

Full Text Available Plant Genetic Resources (PGR continue to play an important role in the development of agriculture. The following aspects receive a special consideration:1. Definition. The term was coined in 1970. The genepool concept served as an important tool in the further development. Different approaches are discussed.2. Values of Genetic Resources. A short introduction is highlighting this problem and stressing the economic usfulness of PGR.3. Genetic Erosion. Already observed by E. Baur in 1914, this is now a key issue within PGR. The case studies cited include Ethiopia, Italy, China, S Korea, Greece and S. Africa. Modern approaches concentrate on allelic changes in varieties over time but neglect the landraces. The causes and consequences of genetic erosion are discussed.4. Genetic Resources Conservation. Because of genetic erosion there is a need for conservation. PGR should be consigned to the appropriate method of conservation (ex situ, in situ, on-farm according to the scientific basis of biodiversity (genetic diversity, species diversity, ecosystem diversity and the evolutionary status of plants (cultivated plants, weeds, related wild plants (crop wild relatives.5. GMO. The impact of genetically engineered plants on genetic diversity is discussed.6. The Conclusions and Recommendations stress the importance of PGR. Their conservation and use are urgent necessities for the present development and future survival of mankind.

New approaches to evaluating the genetic effects of the atomic bombs

International Nuclear Information System (INIS)

Neel, J.V.

1995-01-01

In the aftermath of the atomic bombings of Hiroshima and Nagasaki fifty years ago, one of the compelling biomedical questions that arose concerned the genetic effects of this exposure. More recently, revelations of the extent of industrial or accidental exposures in the former Soviet Union and charges that employment in the Sellafield Nuclear Reprocessing Plant in West Cumbria, England has resulted in a gene-mediated increase in children of plant employees have served to keep in the public mind the issue of the genetic risks of exposure to ionizing radiation. The study of the genetic effects of the atomic bombs has moved from the gross morphological level of congenital malformations to the examination of DNA. However, were the need for such genetic studies to arise in the foreseeable future, despite this impressive progress in DNA-oriented systems, the documentation of congenital defect, genetic disease and child survival would still be an essential component of any future study. Whatever the geneticists may think, the phenotypic well-being and survival of children are still the primary indicators on which the public, who ultimately supports these studies, will base its judgement of risk. 28 refs

Maternal Smoking During Pregnancy and Offspring Birth Weight: A Genetically-Informed Approach Comparing Multiple Raters

Science.gov (United States)

Knopik, Valerie S.; Marceau, Kristine; Palmer, Rohan H. C.; Smith, Taylor F.; Heath, Andrew C.

2016-01-01

Maternal smoking during pregnancy (SDP) is a significant public health concern with adverse consequences to the health and well-being of the fetus. There is considerable debate about the best method of assessing SDP, including birth/medical records, timeline follow-back approaches, multiple reporters, and biological verification (e.g., cotinine). This is particularly salient for genetically-informed approaches where it is not always possible or practical to do a prospective study starting during the prenatal period when concurrent biological specimen samples can be collected with ease. In a sample of families (N = 173) specifically selected for sibling pairs discordant for prenatal smoking exposure, we: (1) compare rates of agreement across different types of report—maternal report of SDP, paternal report of maternal SDP, and SDP contained on birth records from the Department of Vital Statistics; (2) examine whether SDP is predictive of birth weight outcomes using our best SDP report as identified via step (1); and (3) use a sibling-comparison approach that controls for genetic and familial influences that siblings share in order to assess the effects of SDP on birth weight. Results show high agreement between reporters and support the utility of retrospective report of SDP. Further, we replicate a causal association between SDP and birth weight, wherein SDP results in reduced birth weight even when accounting for genetic and familial confounding factors via a sibling comparison approach. PMID:26494459

Application of genetic algorithms to the maintenance scheduling optimization in a nuclear system basing on reliability

International Nuclear Information System (INIS)

Lapa, Celso M. Franklin; Pereira, Claudio M.N.A.; Mol, Antonio C. de Abreu

1999-01-01

This paper presents a solution based on genetic algorithm and probabilistic safety analysis that can be applied in the optimization of the preventive maintenance politic of nuclear power plant safety systems. The goal of this approach is to improve the average availability of the system through the optimization of the preventive maintenance scheduling politic. The auxiliary feed water system of a two loops pressurized water reactor is used as a sample case, in order to demonstrate the effectiveness of the proposed method. The results, when compared to those obtained by some standard maintenance politics, reveal quantitative gains and operational safety levels. (author)

Feature Selection using Multi-objective Genetic Algorith m: A Hybrid Approach

OpenAIRE

Ahuja, Jyoti; GJUST - Guru Jambheshwar University of Sciecne and Technology; Ratnoo, Saroj Dahiya; GJUST - Guru Jambheshwar University of Sciecne and Technology

2015-01-01

Feature selection is an important pre-processing task for building accurate and comprehensible classification models. Several researchers have applied filter, wrapper or hybrid approaches using genetic algorithms which are good candidates for optimization problems that involve large search spaces like in the case of feature selection. Moreover, feature selection is an inherently multi-objective problem with many competing objectives involving size, predictive power and redundancy of the featu...

Genetic counseling and the ethical issues around direct to consumer genetic testing.

Science.gov (United States)

Hawkins, Alice K; Ho, Anita

2012-06-01

Over the last several years, direct to consumer(DTC) genetic testing has received increasing attention in the public, healthcare and academic realms. DTC genetic testing companies face considerable criticism and scepticism,particularly from the medical and genetic counseling community. This raises the question of what specific aspects of DTC genetic testing provoke concerns, and conversely,promises, for genetic counselors. This paper addresses this question by exploring DTC genetic testing through an ethic allens. By considering the fundamental ethical approaches influencing genetic counseling (the ethic of care and principle-based ethics) we highlight the specific ethical concerns raised by DTC genetic testing companies. Ultimately,when considering the ethics of DTC testing in a genetic counseling context, we should think of it as a balancing act. We need careful and detailed consideration of the risks and troubling aspects of such testing, as well as the potentially beneficial direct and indirect impacts of the increased availability of DTC genetic testing. As a result it is essential that genetic counselors stay informed and involved in the ongoing debate about DTC genetic testing and DTC companies. Doing so will ensure that the ethical theories and principles fundamental to the profession of genetic counseling are promoted not just in traditional counseling sessions,but also on a broader level. Ultimately this will help ensure that the public enjoys the benefits of an increasingly genetic based healthcare system.

Inverse problem studies of biochemical systems with structure identification of S-systems by embedding training functions in a genetic algorithm.

Science.gov (United States)

Sarode, Ketan Dinkar; Kumar, V Ravi; Kulkarni, B D

2016-05-01

An efficient inverse problem approach for parameter estimation, state and structure identification from dynamic data by embedding training functions in a genetic algorithm methodology (ETFGA) is proposed for nonlinear dynamical biosystems using S-system canonical models. Use of multiple shooting and decomposition approach as training functions has been shown for handling of noisy datasets and computational efficiency in studying the inverse problem. The advantages of the methodology are brought out systematically by studying it for three biochemical model systems of interest. By studying a small-scale gene regulatory system described by a S-system model, the first example demonstrates the use of ETFGA for the multifold aims of the inverse problem. The estimation of a large number of parameters with simultaneous state and network identification is shown by training a generalized S-system canonical model with noisy datasets. The results of this study bring out the superior performance of ETFGA on comparison with other metaheuristic approaches. The second example studies the regulation of cAMP oscillations in Dictyostelium cells now assuming limited availability of noisy data. Here, flexibility of the approach to incorporate partial system information in the identification process is shown and its effect on accuracy and predictive ability of the estimated model are studied. The third example studies the phenomenological toy model of the regulation of circadian oscillations in Drosophila that follows rate laws different from S-system power-law. For the limited noisy data, using a priori information about properties of the system, we could estimate an alternate S-system model that showed robust oscillatory behavior with predictive abilities. Copyright © 2016 Elsevier Inc. All rights reserved.

The Collaborative Cross Resource for Systems Genetics Research of Infectious Diseases.

Science.gov (United States)

Maurizio, Paul L; Ferris, Martin T

2017-01-01

An increasing body of evidence highlights the role of host genetic variation in driving susceptibility to severe disease following pathogen infection. In order to fully appreciate the importance of host genetics on infection susceptibility and resulting disease, genetically variable experimental model systems should be employed. These systems allow for the identification, characterization, and mechanistic dissection of genetic variants that cause differential disease responses. Herein we discuss application of the Collaborative Cross (CC) panel of recombinant inbred strains to study viral pathogenesis, focusing on practical considerations for experimental design, assessment and analysis of disease responses within the CC, as well as some of the resources developed for the CC. Although the focus of this chapter is on viral pathogenesis, many of the methods presented within are applicable to studies of other pathogens, as well as to case-control designs in genetically diverse populations.

A reliability model of the Angra 1 power system by the device of stages optimized by genetic algorithms

International Nuclear Information System (INIS)

Crossetti, Patricia Guimaraes

2006-01-01

This thesis proposes a probabilistic model to perform the reliability analysis of nuclear power plant systems under aging. This work analyses the Angra 1 power system. Systems subject to aging consist of components whose failure rates are not all constant, thus generating Non-Markovian models. Genetic algorithms were used for optimizing the application of the device of stages. Two approaches were used in the optimization, MCEF and MCEV. The results obtained for the Angra 1 power system show that the probability of a station blackout is negligible. (author)

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…

A Heuristics Approach for Classroom Scheduling Using Genetic Algorithm Technique

Science.gov (United States)

Ahmad, Izah R.; Sufahani, Suliadi; Ali, Maselan; Razali, Siti N. A. M.

2018-04-01

Reshuffling and arranging classroom based on the capacity of the audience, complete facilities, lecturing time and many more may lead to a complexity of classroom scheduling. While trying to enhance the productivity in classroom planning, this paper proposes a heuristic approach for timetabling optimization. A new algorithm was produced to take care of the timetabling problem in a university. The proposed of heuristics approach will prompt a superior utilization of the accessible classroom space for a given time table of courses at the university. Genetic Algorithm through Java programming languages were used in this study and aims at reducing the conflicts and optimizes the fitness. The algorithm considered the quantity of students in each class, class time, class size, time accessibility in each class and lecturer who in charge of the classes.

A Parallel Approach To Optimum Actuator Selection With a Genetic Algorithm

Science.gov (United States)

Rogers, James L.

2000-01-01

Recent discoveries in smart technologies have created a variety of aerodynamic actuators which have great potential to enable entirely new approaches to aerospace vehicle flight control. For a revolutionary concept such as a seamless aircraft with no moving control surfaces, there is a large set of candidate locations for placing actuators, resulting in a substantially larger number of combinations to examine in order to find an optimum placement satisfying the mission requirements. The placement of actuators on a wing determines the control effectiveness of the airplane. One approach to placement Maximizes the moments about the pitch, roll, and yaw axes, while minimizing the coupling. Genetic algorithms have been instrumental in achieving good solutions to discrete optimization problems, such as the actuator placement problem. As a proof of concept, a genetic has been developed to find the minimum number of actuators required to provide uncoupled pitch, roll, and yaw control for a simplified, untapered, unswept wing model. To find the optimum placement by searching all possible combinations would require 1,100 hours. Formulating the problem and as a multi-objective problem and modifying it to take advantage of the parallel processing capabilities of a multi-processor computer, reduces the optimization time to 22 hours.

A systematic approach to assessing the clinical significance of genetic variants.

Science.gov (United States)

Duzkale, H; Shen, J; McLaughlin, H; Alfares, A; Kelly, M A; Pugh, T J; Funke, B H; Rehm, H L; Lebo, M S

2013-11-01

Molecular genetic testing informs diagnosis, prognosis, and risk assessment for patients and their family members. Recent advances in low-cost, high-throughput DNA sequencing and computing technologies have enabled the rapid expansion of genetic test content, resulting in dramatically increased numbers of DNA variants identified per test. To address this challenge, our laboratory has developed a systematic approach to thorough and efficient assessments of variants for pathogenicity determination. We first search for existing data in publications and databases including internal, collaborative and public resources. We then perform full evidence-based assessments through statistical analyses of observations in the general population and disease cohorts, evaluation of experimental data from in vivo or in vitro studies, and computational predictions of potential impacts of each variant. Finally, we weigh all evidence to reach an overall conclusion on the potential for each variant to be disease causing. In this report, we highlight the principles of variant assessment, address the caveats and pitfalls, and provide examples to illustrate the process. By sharing our experience and providing a framework for variant assessment, including access to a freely available customizable tool, we hope to help move towards standardized and consistent approaches to variant assessment. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Approaches in Characterizing Genetic Structure and Mapping in a Rice Multiparental Population.

Science.gov (United States)

Raghavan, Chitra; Mauleon, Ramil; Lacorte, Vanica; Jubay, Monalisa; Zaw, Hein; Bonifacio, Justine; Singh, Rakesh Kumar; Huang, B Emma; Leung, Hei

2017-06-07

Multi-parent Advanced Generation Intercross (MAGIC) populations are fast becoming mainstream tools for research and breeding, along with the technology and tools for analysis. This paper demonstrates the analysis of a rice MAGIC population from data filtering to imputation and processing of genetic data to characterizing genomic structure, and finally quantitative trait loci (QTL) mapping. In this study, 1316 S6:8 indica MAGIC (MI) lines and the eight founders were sequenced using Genotyping by Sequencing (GBS). As the GBS approach often includes missing data, the first step was to impute the missing SNPs. The observable number of recombinations in the population was then explored. Based on this case study, a general outline of procedures for a MAGIC analysis workflow is provided, as well as for QTL mapping of agronomic traits and biotic and abiotic stress, using the results from both association and interval mapping approaches. QTL for agronomic traits (yield, flowering time, and plant height), physical (grain length and grain width) and cooking properties (amylose content) of the rice grain, abiotic stress (submergence tolerance), and biotic stress (brown spot disease) were mapped. Through presenting this extensive analysis in the MI population in rice, we highlight important considerations when choosing analytical approaches. The methods and results reported in this paper will provide a guide to future genetic analysis methods applied to multi-parent populations. Copyright © 2017 Raghavan et al.

Approaches in Characterizing Genetic Structure and Mapping in a Rice Multiparental Population

Directory of Open Access Journals (Sweden)

Chitra Raghavan

2017-06-01

Full Text Available Multi-parent Advanced Generation Intercross (MAGIC populations are fast becoming mainstream tools for research and breeding, along with the technology and tools for analysis. This paper demonstrates the analysis of a rice MAGIC population from data filtering to imputation and processing of genetic data to characterizing genomic structure, and finally quantitative trait loci (QTL mapping. In this study, 1316 S6:8 indica MAGIC (MI lines and the eight founders were sequenced using Genotyping by Sequencing (GBS. As the GBS approach often includes missing data, the first step was to impute the missing SNPs. The observable number of recombinations in the population was then explored. Based on this case study, a general outline of procedures for a MAGIC analysis workflow is provided, as well as for QTL mapping of agronomic traits and biotic and abiotic stress, using the results from both association and interval mapping approaches. QTL for agronomic traits (yield, flowering time, and plant height, physical (grain length and grain width and cooking properties (amylose content of the rice grain, abiotic stress (submergence tolerance, and biotic stress (brown spot disease were mapped. Through presenting this extensive analysis in the MI population in rice, we highlight important considerations when choosing analytical approaches. The methods and results reported in this paper will provide a guide to future genetic analysis methods applied to multi-parent populations.

Genetic and Computational Approaches for Studying Plant Development and Abiotic Stress Responses Using Image-Based Phenotyping

Science.gov (United States)

Campbell, M. T.; Walia, H.; Grondin, A.; Knecht, A.

2017-12-01

The development of abiotic stress tolerant crops (i.e. drought, salinity, or heat stress) requires the discovery of DNA sequence variants associated with stress tolerance-related traits. However, many traits underlying adaptation to abiotic stress involve a suite of physiological pathways that may be induced at different times throughout the duration of stress. Conventional single-point phenotyping approaches fail to fully capture these temporal responses, and thus downstream genetic analysis may only identify a subset of the genetic variants that are important for adaptation to sub-optimal environments. Although genomic resources for crops have advanced tremendously, the collection of phenotypic data for morphological and physiological traits is laborious and remains a significant bottleneck in bridging the phenotype-genotype gap. In recent years, the availability of automated, image-based phenotyping platforms has provided researchers with an opportunity to collect morphological and physiological traits non-destructively in a highly controlled environment. Moreover, these platforms allow abiotic stress responses to be recorded throughout the duration of the experiment, and have facilitated the use of function-valued traits for genetic analyses in major crops. We will present our approaches for addressing abiotic stress tolerance in cereals. This talk will focus on novel open-source software to process and extract biological meaningful data from images generated from these phenomics platforms. In addition, we will discuss the statistical approaches to model longitudinal phenotypes and dissect the genetic basis of dynamic responses to these abiotic stresses throughout development.

Noise in Genetic Toggle Switch Models

Directory of Open Access Journals (Sweden)

Andrecut M.

2006-06-01

Full Text Available In this paper we study the intrinsic noise effect on the switching behavior of a simple genetic circuit corresponding to the genetic toggle switch model. The numerical results obtained from a noisy mean-field model are compared to those obtained from the stochastic Gillespie simulation of the corresponding system of chemical reactions. Our results show that by using a two step reaction approach for modeling the transcription and translation processes one can make the system to lock in one of the steady states for exponentially long times.

A Genetic Algorithms Based Approach for Identification of Escherichia coli Fed-batch Fermentation

Directory of Open Access Journals (Sweden)

Olympia Roeva

2004-10-01

Full Text Available This paper presents the use of genetic algorithms for identification of Escherichia coli fed-batch fermentation process. Genetic algorithms are a directed random search technique, based on the mechanics of natural selection and natural genetics, which can find the global optimal solution in complex multidimensional search space. The dynamic behavior of considered process has known nonlinear structure, described with a system of deterministic nonlinear differential equations according to the mass balance. The parameters of the model are estimated using genetic algorithms. Simulation examples for demonstration of the effectiveness and robustness of the proposed identification scheme are included. As a result, the model accurately predicts the process of cultivation of E. coli.

A probabilistic multi objective CLSC model with Genetic algorithm-ε_Constraint approach

Directory of Open Access Journals (Sweden)

Alireza TaheriMoghadam

2014-05-01

Full Text Available In this paper an uncertain multi objective closed-loop supply chain is developed. The first objective function is maximizing the total profit. The second objective function is minimizing the use of row materials. In the other word, the second objective function is maximizing the amount of remanufacturing and recycling. Genetic algorithm is used for optimization and for finding the pareto optimal line, Epsilon-constraint method is used. Finally a numerical example is solved with proposed approach and performance of the model is evaluated in different sizes. The results show that this approach is effective and useful for managerial decisions.

Systems genetics identifies a role for Cacna2d1 regulation in elevated intraocular pressure and glaucoma susceptibility.

Science.gov (United States)

Chintalapudi, Sumana R; Maria, Doaa; Di Wang, Xiang; Bailey, Jessica N Cooke; Hysi, Pirro G; Wiggs, Janey L; Williams, Robert W; Jablonski, Monica M

2017-11-24

Glaucoma is a multi-factorial blinding disease in which genetic factors play an important role. Elevated intraocular pressure is a highly heritable risk factor for primary open angle glaucoma and currently the only target for glaucoma therapy. Our study helps to better understand underlying genetic and molecular mechanisms that regulate intraocular pressure, and identifies a new candidate gene, Cacna2d1, that modulates intraocular pressure and a promising therapeutic, pregabalin, which binds to CACNA2D1 protein and lowers intraocular pressure significantly. Because our study utilizes a genetically diverse population of mice with known sequence variants, we are able to determine that the intraocular pressure-lowering effect of pregabalin is dependent on the Cacna2d1 haplotype. Using human genome-wide association study (GWAS) data, evidence for association of a CACNA2D1 single-nucleotide polymorphism and primary open angle glaucoma is found. Importantly, these results demonstrate that our systems genetics approach represents an efficient method to identify genetic variation that can guide the selection of therapeutic targets.

Combined Simulated Annealing and Genetic Algorithm Approach to Bus Network Design

Science.gov (United States)

Liu, Li; Olszewski, Piotr; Goh, Pong-Chai

A new method - combined simulated annealing (SA) and genetic algorithm (GA) approach is proposed to solve the problem of bus route design and frequency setting for a given road network with fixed bus stop locations and fixed travel demand. The method involves two steps: a set of candidate routes is generated first and then the best subset of these routes is selected by the combined SA and GA procedure. SA is the main process to search for a better solution to minimize the total system cost, comprising user and operator costs. GA is used as a sub-process to generate new solutions. Bus demand assignment on two alternative paths is performed at the solution evaluation stage. The method was implemented on four theoretical grid networks of different size and a benchmark network. Several GA operators (crossover and mutation) were utilized and tested for their effectiveness. The results show that the proposed method can efficiently converge to the optimal solution on a small network but computation time increases significantly with network size. The method can also be used for other transport operation management problems.

Systems Theory and Systems Approach to Leadership

Directory of Open Access Journals (Sweden)

Dr.Sc. Berim Ramosaj

2014-06-01

Full Text Available Systems theory is product of the efforts of many researchers to create an intermediate field of coexistence of all sciences. If not for anything else, because of the magnitude that the use of systemic thinking and systemic approach has taken, it has become undisputed among the theories. Systems theory not only provides a glossary of terms with which researchers from different fields can be understood, but provides a framework for the presentation and interpretation of phenomena and realities. This paper addresses a systematic approach to leadership, as an attempt to dredge leadership and systems theory literature to find the meeting point. Systems approach is not an approach to leadership in terms of a manner of leader’s work, but it’s the leader's determination to factorize in his leadership the external environment and relationships with and among elements. Leader without followers is unable to exercise his leadership and to ensure their conviction he should provide a system, a structure, a purpose, despite the alternative chaos. Systems approach clarifies the thought on the complexity and dynamism of the environment and provides a framework for building ideas. If the general system theory is the skeleton of science (Boulding: 1956, this article aims to replenish it with leadership muscles by prominent authors who have written on systems theory and leadership, as well as through original ideas. In this work analytical methods were used (by analyzing approaches individually as well as synthetic methods (by assaying individual approaches in context of entirety. The work is a critical review of literature as well as a deductive analysis mingled with models proposed by authors through inductive analysis. Meta-analysis has been used to dissect the interaction and interdependence between leadership approaches.

A practical approach to screen for authorised and unauthorised genetically modified plants.

Science.gov (United States)

Waiblinger, Hans-Ulrich; Grohmann, Lutz; Mankertz, Joachim; Engelbert, Dirk; Pietsch, Klaus

2010-03-01

In routine analysis, screening methods based on real-time PCR are most commonly used for the detection of genetically modified (GM) plant material in food and feed. In this paper, it is shown that the combination of five DNA target sequences can be used as a universal screening approach for at least 81 GM plant events authorised or unauthorised for placing on the market and described in publicly available databases. Except for maize event LY038, soybean events DP-305423 and BPS-CV127-9 and cotton event 281-24-236 x 3006-210-23, at least one of the five genetic elements has been inserted in these GM plants and is targeted by this screening approach. For the detection of these sequences, fully validated real-time PCR methods have been selected. A screening table is presented that describes the presence or absence of the target sequences for most of the listed GM plants. These data have been verified either theoretically according to available databases or experimentally using available reference materials. The screening table will be updated regularly by a network of German enforcement laboratories.

Smart Integrated Renewable Energy Systems (SIRES: A Novel Approach for Sustainable Development

Directory of Open Access Journals (Sweden)

Zeel Maheshwari

2017-08-01

Full Text Available Technical and economic aspects of the viability of SIRES (Smart Integrated Renewable Energy Systems for sustainable development of remote and rural areas of the world are discussed. The hallmark of the proposed SIRES is the smart utilization of several renewable resources in an integrated fashion and matching of resources and needs a priori with the ultimate goal of “energization”, not just “electrification”. Historical background leading to this approach is succinctly presented along with a comprehensive schematic diagram. Modeling of various components and their collective use in optimizing SIRES with the aid of genetic algorithm are presented using a typical hypothetical example. SIRES is also compared with various approaches for rural development based on Annualized Cost of System (ACS and installation costs. Implementation of SIRES will lead to overall sustainable development of rural communities.

Felling-system and regeneration of pine forests on ecological-genetic-geographical basis

Directory of Open Access Journals (Sweden)

S. N. Sannikov

2015-12-01

Full Text Available A conception of the adaptation of Scots pine populations to the natural regeneration on open sites with the mosaic retained stand and mineralized soil surface on the basis of the ecological-genetic-geographical investigations in the forests of the Russia and the theory of petropsammofitness-pyrofitness (Sannikov S. N., 1983 has been substantiated. The methods of clear cuts with the seeding from surrounding forest, seed curtains and sufficiently extent of the substrate preparation for the pine selfsown have been selected and elaborated as a main organization principle of the system «felling-regeneration» in the plains pine forests of the forest zone. High regeneration efficiency of this system with the application of original aggregate for the optimal mineralization of the soil substrate (with its synchronous loosing has been shown on the example of dominating pine forest types in the subzone for-forest-steppe of the Western Siberia. The silvicultural-ecological and reproductive-genetic advantages of retaining seed curtains instead of separate seed trees have been substantiated. The basic parameters of the system «felling-regeneration», which guarantee a sufficient success of the following pine regeneration in the for-forest-steppe subzone, have been determined with the help of the methods of the mathematical imitation modeling of the pine selfsown density depending on the area and localization of seed curtains, surrounding forest and the extent of the substrate mineralization. The zonal differentiated system of the fellings and measures for the regeneration optimization in the climatically substituting pine forest types in the Western Siberia has been elaborated according to the parameters, studied earlier, on the ecological-genetic-geographical basis. The principles of this system in forest zone come to the clear strip-fellings with insemination of cuts from the seed curtains and forest walls, and to the hollow-fellings with the

A computational intelligent approach to multi-factor analysis of violent crime information system

Science.gov (United States)

Liu, Hongbo; Yang, Chao; Zhang, Meng; McLoone, Seán; Sun, Yeqing

2017-02-01

Various scientific studies have explored the causes of violent behaviour from different perspectives, with psychological tests, in particular, applied to the analysis of crime factors. The relationship between bi-factors has also been extensively studied including the link between age and crime. In reality, many factors interact to contribute to criminal behaviour and as such there is a need to have a greater level of insight into its complex nature. In this article we analyse violent crime information systems containing data on psychological, environmental and genetic factors. Our approach combines elements of rough set theory with fuzzy logic and particle swarm optimisation to yield an algorithm and methodology that can effectively extract multi-knowledge from information systems. The experimental results show that our approach outperforms alternative genetic algorithm and dynamic reduct-based techniques for reduct identification and has the added advantage of identifying multiple reducts and hence multi-knowledge (rules). Identified rules are consistent with classical statistical analysis of violent crime data and also reveal new insights into the interaction between several factors. As such, the results are helpful in improving our understanding of the factors contributing to violent crime and in highlighting the existence of hidden and intangible relationships between crime factors.

Genetic fuzzy system modeling and simulation of vascular behaviour

DEFF Research Database (Denmark)

Tang, Jiaowei; Boonen, Harrie C.M.

Background: The purpose of our project is to identify the rule sets and their interaction within the framework of cardiovascular function. By an iterative process of computational simulation and experimental work, we strive to mimic the physiological basis for cardiovascular adaptive changes in c...... the pressure change of different blood vessels. Conclusion: Genetic fuzzy system is one of potential modeling methods in modeling and simulation of vascular behavior.......Background: The purpose of our project is to identify the rule sets and their interaction within the framework of cardiovascular function. By an iterative process of computational simulation and experimental work, we strive to mimic the physiological basis for cardiovascular adaptive changes...... in cardiovascular disease and ultimately improve pharmacotherapy. For this purpose, novel computational approaches incorporating adaptive properties, auto-regulatory control and rule sets will be assessed, properties that are commonly lacking in deterministic models based on differential equations. We hypothesize...

Forensic Science in Support of Wildlife Conservation Efforts - Genetic Approaches (Global Trends).

Science.gov (United States)

Linacre, A

2011-01-01

Wildlife forensic science is a relatively recent development to meet the increasing need of the criminal justice system where there are investigations in alleged transgressions of either international or national legislation. This application of science draws on conservation genetics and forensic geneticists from mainstream forensic science. This review is a broad overview of the history of forensic wildlife science and some of the recent developments in forensic wildlife genetics with the application of DNA developments to nonhuman samples encountered in a forensic science investigation. The review will move from methods to look at the entire genome, when there is no previous knowledge of the species studied, through methods of species identification, using DNA to determine a possible geographic origin, through to assigning samples to a particular individual or a close genetic relative of this individual. The transfer of research methods into the criminal justice system for the investigation of wildlife crimes has been largely successful as is illustrated in the review. The review concludes with comments on the need for standardization and regulation in wildlife forensic science. Copyright © 2011 Central Police University.

Construction of the first compendium of chemical-genetic profiles in the fission yeast Schizosaccharomyces pombe and comparative compendium approach

Energy Technology Data Exchange (ETDEWEB)

Han, Sangjo [Bioinformatics Lab, Healthcare Group, SK Telecom, 9-1, Sunae-dong, Pundang-gu, Sungnam-si, Kyunggi-do 463-784 (Korea, Republic of); Lee, Minho [Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701 (Korea, Republic of); Chang, Hyeshik [Department of Biological Science, Seoul National University, 599 Gwanakro, Gwanak-gu, Seoul 151-747 (Korea, Republic of); Nam, Miyoung [Department of New Drug Discovery and Development, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon, 305-764 (Korea, Republic of); Park, Han-Oh [Bioneer Corp., 8-11 Munpyeongseo-ro, Daedeok-gu, Daejeon 306-220 (Korea, Republic of); Kwak, Youn-Sig [Department of Applied Biology, Gyeongsang National University, 501 Jinju-daero, Jinju, Gyeongnam 660-701 (Korea, Republic of); Ha, Hye-jeong [Aging Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), 125 Gwahak-ro, Yuseong-Gu, Daejeon 305-806 (Korea, Republic of); Kim, Dongsup [Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701 (Korea, Republic of); Hwang, Sung-Ook [Department of Obstetrics and Gynecology, Inha University Hospital, 7-206 Sinheung-dong, Jung-gu, Incheon 400-711 (Korea, Republic of); Hoe, Kwang-Lae [Department of New Drug Discovery and Development, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon, 305-764 (Korea, Republic of); Kim, Dong-Uk [Aging Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), 125 Gwahak-ro, Yuseong-Gu, Daejeon 305-806 (Korea, Republic of)

2013-07-12

Highlights: •The first compendium of chemical-genetic profiles form fission yeast was generated. •The first HTS of drug mode-of-action in fission yeast was performed. •The first comparative chemical genetic analysis between two yeasts was conducted. -- Abstract: Genome-wide chemical genetic profiles in Saccharomyces cerevisiae since the budding yeast deletion library construction have been successfully used to reveal unknown mode-of-actions of drugs. Here, we introduce comparative approach to infer drug target proteins more accurately using two compendiums of chemical-genetic profiles from the budding yeast S. cerevisiae and the fission yeast Schizosaccharomyces pombe. For the first time, we established DNA-chip based growth defect measurement of genome-wide deletion strains of S. pombe, and then applied 47 drugs to the pooled heterozygous deletion strains to generate chemical-genetic profiles in S. pombe. In our approach, putative drug targets were inferred from strains hypersensitive to given drugs by analyzing S. pombe and S. cerevisiae compendiums. Notably, many evidences in the literature revealed that the inferred target genes of fungicide and bactericide identified by such comparative approach are in fact the direct targets. Furthermore, by filtering out the genes with no essentiality, the multi-drug sensitivity genes, and the genes with less eukaryotic conservation, we created a set of drug target gene candidates that are expected to be directly affected by a given drug in human cells. Our study demonstrated that it is highly beneficial to construct the multiple compendiums of chemical genetic profiles using many different species. The fission yeast chemical-genetic compendium is available at (http://pombe.kaist.ac.kr/compendium)

Genetics, systems, and alcohol.

Science.gov (United States)

McClearn, G E

1993-03-01

Under a variety of rubrics (e.g., complexity, self-constructing systems, dissipative structures), interest has recently burgeoned in applying principles of complex systems to a wide variety of scientific issues. A major concern is with emergent properties of systems not derivable from the properties of components of the systems. In this paper, some elementary aspects of "systems" considerations are applied to phenomena of alcohol pharmacogenetics. It is likely that whole new families of informative phenotypes can be generated by this approach.

A simulation-powered approach to ventilation, lighting and shading systems control

Energy Technology Data Exchange (ETDEWEB)

Schuss, Matthias; Proeglhoef, Claus; Orehounig, Kristina; Mahdavi, Ardeshir [Department of Building Physics and Building Ecology, Vienna University of Technology (Austria)

2010-12-15

This paper reports on ongoing work toward implementing a predictive control approach for buildings systems for ventilation, lighting, and shading. The main objective of this method is the optimized control of multiple devices toward usage of passive cooling and natural lighting. In this way, control options (various opening positions of windows, shades, etc.) are generated and computationally assessed using a combination of option space navigation via genetic algorithms and numeric simulation. (Copyright copyright 2010 Ernst and Sohn Verlag fuer Architektur und technische Wissenschaften GmbH and Co. KG, Berlin)

Epilogue: Systems Approaches and Systems Practice

Science.gov (United States)

Reynolds, Martin; Holwell, Sue

Each of the five systems approaches discussed in this volume: system dynamics (SD), the viable systems model (VSM), strategic options development and analysis (SODA), soft systems methodology (SSM) and critical systems heuristics (CSH) has a pedigree. Not in the sense of the sometimes absurd spectacle of animals paraded at dog shows. Rather, their pedigree derives from their systems foundations, their capacity to evolve and their flexibility in use. None of the five approaches has developed out of use in restricted and controlled contexts of either low or high levels of complicatedness. Neither has any one of them evolved as a consequence of being applied only to situations with either presumed stakeholder agreement on purpose, or courteous disagreement amongst stakeholders, or stakeholder coercion. The compilation is not a celebration of abstract ‘methodologies', but of theoretically robust approaches that have a genuine pedigree in practice.

A practical approach to ichthyoses with systemic manifestations.

Science.gov (United States)

Saral, S; Vural, A; Wollenberg, A; Ruzicka, T

2017-06-01

Inherited ichthyoses are rare disorders in terms of patient numbers, but abundant in terms of clinical-genetic subtypes. These disorders are often associated with severe systemic manifestations, in addition to significant medical, cosmetic and social problems. There are 17 subtypes of syndromic ichthyosis identified so far and most patients with these syndromes are living in countries with high consanguinity rates. Frequently, clinicians cannot make a definitive diagnosis and patients are not managed properly owing to the rarity and complexity of these disorders. These difficulties make this group of ichthyosis and the patients living with them 'orphan'. After skin and skin appendages, nervous system is the most frequently involved system in ichthyosis syndromes. Thus, association of ichthyosis with neurological symptoms provides an important clue for diagnosis. In this article, we aim to increase clinicians' comprehension of ichthyosis syndromes by providing a symptomatology-based approach based on this observation. Additionally, we provide a review of ichthyosis syndromes, with special emphasis on neurological symptoms, hoping to attract interest to this complicated field. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties of functional gene network

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Han Kyungsook

2010-06-01

Full Text Available Abstract Background Genetic interaction profiles are highly informative and helpful for understanding the functional linkages between genes, and therefore have been extensively exploited for annotating gene functions and dissecting specific pathway structures. However, our understanding is rather limited to the relationship between double concurrent perturbation and various higher level phenotypic changes, e.g. those in cells, tissues or organs. Modifier screens, such as synthetic genetic arrays (SGA can help us to understand the phenotype caused by combined gene mutations. Unfortunately, exhaustive tests on all possible combined mutations in any genome are vulnerable to combinatorial explosion and are infeasible either technically or financially. Therefore, an accurate computational approach to predict genetic interaction is highly desirable, and such methods have the potential of alleviating the bottleneck on experiment design. Results In this work, we introduce a computational systems biology approach for the accurate prediction of pairwise synthetic genetic interactions (SGI. First, a high-coverage and high-precision functional gene network (FGN is constructed by integrating protein-protein interaction (PPI, protein complex and gene expression data; then, a graph-based semi-supervised learning (SSL classifier is utilized to identify SGI, where the topological properties of protein pairs in weighted FGN is used as input features of the classifier. We compare the proposed SSL method with the state-of-the-art supervised classifier, the support vector machines (SVM, on a benchmark dataset in S. cerevisiae to validate our method's ability to distinguish synthetic genetic interactions from non-interaction gene pairs. Experimental results show that the proposed method can accurately predict genetic interactions in S. cerevisiae (with a sensitivity of 92% and specificity of 91%. Noticeably, the SSL method is more efficient than SVM, especially for

Systems Biology-an interdisciplinary approach.

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Friboulet, Alain; Thomas, Daniel

2005-06-15

System-level approaches in biology are not new but foundations of "Systems Biology" are achieved only now at the beginning of the 21st century [Kitano, H., 2001. Foundations of Systems Biology. MIT Press, Cambridge, MA]. The renewed interest for a system-level approach is linked to the progress in collecting experimental data and to the limits of the "reductionist" approach. System-level understanding of native biological and pathological systems is needed to provide potential therapeutic targets. Examples of interdisciplinary approach in Systems Biology are described in U.S., Japan and Europe. Robustness in biology, metabolic engineering and idiotypic networks are discussed in the framework of Systems Biology.

Genetic-neuro-fuzzy system for grading depression

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Kumar Ashish

2018-01-01

Full Text Available Main aim of this study is to develop a software prototype tool for grading and diagnosing depression that will help general physicians for first hand applications. Identification of key symptoms responsible for depression is also another important issue considered in this study. It involves collection of data taken from patients through doctors. Due to several reasons, collection of data in Indian scenario is extremely difficult and thus this tool will be very handy and useful for general physicians working at remote locations. Also, it is possible to collect a data pool through this software model. An intelligent Neuro-Fuzzy model is developed for this purpose. Performance of the said model has been optimized through two approaches. In Approach 1, where a back-propagation algorithm has been considered and in Approach 2, Genetic Algorithm has been used. The model is trained with 78 data and validated with 10 data. Approach 2 superseded Approach 1 in terms of diagnostic accuracy. Therefore, it can be said that the soft computing-based diagnostic models could assist the doctors to make informed decisions. Data for training and validation for this purpose has been collected during 2004–2005 from a Government mental hospital in India.

AGROBACTERIUM-MEDIATED GENETIC TRANSFORMATION OF SORGHUM USING TISSUE CULTURE-BASED AND POLLEN-MEDIATED APPROACHES

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Elkonin L.A.

2012-08-01

Full Text Available Genetic transformation is a powerful tool for genetic improvement of arable crops. Genetic engineering approaches are especially important for modification of starch and protein contents, vitamin and micronutrient concentration, improvement of nutritive value of protein fractions, and increase tolerance to environmental stresses. Application of transgenic technologies for genetic improvement of sorghum, a highly productive heat tolerant and drought resistant crop, is extremely important since climate aridization in many regions all over the globe hampers sustainable production of traditional cereals, such as wheat, maize and barley. However, sorghum, in spite of great number of investigations, is one of the most recalcitrant crop species to genetic modification. The most frequently reported problems are a low frequency of transformation and silencing of transgenes. Using the A. tumefaciens strain AGL0/p35SGIB with the bar and gus-intron genes under the nos and CaMV35S promoters, respectively, we studied different methods of Agrobacterium-mediated genetic transformation of the grain sorghum: in vitro culture-based techniques, by inoculation of immature embryos or embryo-derived calli, and pollen-mediated approach, by inoculation of flowering panicles. Four lines of grain sorghum – Milo-10, [9E] Milo-10 (CMS-line, KVV-114, and KVV-45 – were used. In both approaches, for activation of vir-genes agrobacterial cell suspension was grown in the AB or modified AB media with acetosyringone at room temperature. In vitro culture approach was effective for obtaining transgenic plants in the lines Milo-10 and KVV-45, which were able to produce embryogenic callus from immature embryos after their co-cultivation with agrobacterial cell suspension. Callus cultures tolerant to glufosinate ammonium (GA and capable to plant regeneration were obtained. The frequency of immature embryos producing PCR-positive transgenic plants varied in different experiments

Optimal Design of Gravity Pipeline Systems Using Genetic Algorithm and Mathematical Optimization

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maryam rohani

2015-03-01

Full Text Available In recent years, the optimal design of pipeline systems has become increasingly important in the water industry. In this study, the two methods of genetic algorithm and mathematical optimization were employed for the optimal design of pipeline systems with the objective of avoiding the water hammer effect caused by valve closure. The problem of optimal design of a pipeline system is a constrained one which should be converted to an unconstrained optimization problem using an external penalty function approach in the mathematical programming method. The quality of the optimal solution greatly depends on the value of the penalty factor that is calculated by the iterative method during the optimization procedure such that the computational effort is simultaneously minimized. The results obtained were used to compare the GA and mathematical optimization methods employed to determine their efficiency and capabilities for the problem under consideration. It was found that the mathematical optimization method exhibited a slightly better performance compared to the GA method.

Genetic variations in the serotoninergic system contribute to amygdala volume in humans

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Jin eLi

2015-10-01

Full Text Available The amygdala plays a critical role in emotion processing and psychiatric disorders associated with emotion dysfunction. Accumulating evidence suggests that amygdala structure is modulated by serotonin-related genes. However, there is a gap between the small contributions of single loci (less than 1% and the reported 63-65% heritability of amygdala structure. To understand the missing heritability, we systematically explored the contribution of serotonin genes on amygdala structure at the gene set level. The present study of 417 healthy Chinese volunteers examined 129 representative polymorphisms in genes from multiple biological mechanisms in the regulation of serotonin neurotransmission. A system-level approach using multiple regression analyses identified that nine SNPs collectively accounted for approximately 8% of the variance in amygdala volume. Permutation analyses showed that the probability of obtaining these findings by chance was low (p=0.043, permuted for 1000 times. Findings showed that serotonin genes contribute moderately to individual differences in amygdala volume in a healthy Chinese sample. These results indicate that the system-level approach can help us to understand the genetic basis of a complex trait such as amygdala structure.

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

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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…

Mapping genetic influences on the corticospinal motor system in humans

DEFF Research Database (Denmark)

Cheeran, B J; Ritter, C; Rothwell, J C

2009-01-01

of the contribution of single nucleotide polymorphisms (SNP) and variable number tandem repeats. In humans, the corticospinal motor system is essential to the acquisition of fine manual motor skills which require a finely tuned coordination of activity in distal forelimb muscles. Here we review recent brain mapping......It is becoming increasingly clear that genetic variations account for a certain amount of variance in the acquisition and maintenance of different skills. Until now, several levels of genetic influences were examined, ranging from global heritability estimates down to the analysis...... studies that have begun to explore the influence of functional genetic variation as well as mutations on function and structure of the human corticospinal motor system, and also the clinical implications of these studies. Transcranial magnetic stimulation of the primary motor hand area revealed...

The Genetics of Obsessive-Compulsive Disorder and Tourette Syndrome: An Epidemiological and Pathway-Based Approach for Gene Discovery

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Grados, Marco A.

2010-01-01

Objective: To provide a contemporary perspective on genetic discovery methods applied to obsessive-compulsive disorder (OCD) and Tourette syndrome (TS). Method: A review of research trends in genetics research in OCD and TS is conducted, with emphasis on novel approaches. Results: Genome-wide association studies (GWAS) are now in progress in OCD…

Hybrid Type II fuzzy system & data mining approach for surface finish

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Tzu-Liang (Bill Tseng

2015-07-01

Full Text Available In this study, a new methodology in predicting a system output has been investigated by applying a data mining technique and a hybrid type II fuzzy system in CNC turning operations. The purpose was to generate a supplemental control function under the dynamic machining environment, where unforeseeable changes may occur frequently. Two different types of membership functions were developed for the fuzzy logic systems and also by combining the two types, a hybrid system was generated. Genetic algorithm was used for fuzzy adaptation in the control system. Fuzzy rules are automatically modified in the process of genetic algorithm training. The computational results showed that the hybrid system with a genetic adaptation generated a far better accuracy. The hybrid fuzzy system with genetic algorithm training demonstrated more effective prediction capability and a strong potential for the implementation into existing control functions.

Hybrid Genetic Algorithm Optimization for Case Based Reasoning Systems

International Nuclear Information System (INIS)

Mohamed, A.H.

2008-01-01

The success of a CBR system largely depen ds on an effective retrieval of useful prior case for the problem. Nearest neighbor and induction are the main CBR retrieval algorithms. Each of them can be more suitable in different situations. Integrated the two retrieval algorithms can catch the advantages of both of them. But, they still have some limitations facing the induction retrieval algorithm when dealing with a noisy data, a large number of irrelevant features, and different types of data. This research utilizes a hybrid approach using genetic algorithms (GAs) to case-based induction retrieval of the integrated nearest neighbor - induction algorithm in an attempt to overcome these limitations and increase the overall classification accuracy. GAs can be used to optimize the search space of all the possible subsets of the features set. It can deal with the irrelevant and noisy features while still achieving a significant improvement of the retrieval accuracy. Therefore, the proposed CBR-GA introduces an effective general purpose retrieval algorithm that can improve the performance of CBR systems. It can be applied in many application areas. CBR-GA has proven its success when applied for different problems in real-life

Global Optimization of a Periodic System using a Genetic Algorithm

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Stucke, David; Crespi, Vincent

2001-03-01

We use a novel application of a genetic algorithm global optimizatin technique to find the lowest energy structures for periodic systems. We apply this technique to colloidal crystals for several different stoichiometries of binary and trinary colloidal crystals. This application of a genetic algorithm is decribed and results of likely candidate structures are presented.

Buffering mechanisms in aging: a systems approach toward uncovering the genetic component of aging.

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Aviv Bergman

2007-08-01

Full Text Available An unrealized potential to understand the genetic basis of aging in humans, is to consider the immense survival advantage of the rare individuals who live 100 years or more. The Longevity Gene Study was initiated in 1998 at the Albert Einstein College of Medicine to investigate longevity genes in a selected population: the "oldest old" Ashkenazi Jews, 95 years of age and older, and their children. The study proved the principle that some of these subjects are endowed with longevity-promoting genotypes. Here we reason that some of the favorable genotypes act as mechanisms that buffer the deleterious effect of age-related disease genes. As a result, the frequency of deleterious genotypes may increase among individuals with extreme lifespan because their protective genotype allows disease-related genes to accumulate. Thus, studies of genotypic frequencies among different age groups can elucidate the genetic determinants and pathways responsible for longevity. Borrowing from evolutionary theory, we present arguments regarding the differential survival via buffering mechanisms and their target age-related disease genes in searching for aging and longevity genes. Using more than 1,200 subjects between the sixth and eleventh decades of life (at least 140 subjects in each group, we corroborate our hypotheses experimentally. We study 66 common allelic site polymorphism in 36 candidate genes on the basis of their phenotype. Among them we have identified a candidate-buffering mechanism and its candidate age-related disease gene target. Previously, the beneficial effect of an advantageous cholesteryl ester transfer protein (CETP-VV genotype on lipoprotein particle size in association with decreased metabolic and cardiovascular diseases, as well as with better cognitive function, have been demonstrated. We report an additional advantageous effect of the CETP-VV (favorable genotype in neutralizing the deleterious effects of the lipoprotein(a (LPA gene

Molecular genetic approach to human meningioma: loss of genes on chromosome 22

International Nuclear Information System (INIS)

Seizinger, B.R.; De La Monte, S.; Atkins, L.; Gusella, J.F.; Martuza, R.L.

1987-01-01

A molecular genetic approach employing polymorphic DNA markers has been used to investigate the role of chromosomal aberrations in meningioma, one of the most common tumors of the human nervous system. Comparison of the alleles detected by DNA markers in tumor DNA versus DNA from normal tissue revealed chromosomal alterations present in primary surgical specimens. In agreement with cytogenetic studies of cultured meningiomas, the most frequent alteration detected was loss of heterozygosity on chromosome 22. Forty of 51 patients were constitutionally heterozygous for at least one chromosome 22 DNA marker. Seventeen of the 40 constitutionally heterozygotic patients (43%) displayed hemizygosity for the corresponding marker in their meningioma tumor tissues. Loss of heterozygosity was also detected at a significantly lower frequency for markers on several other autosomes. In view of the striking association between acoustic neuroma and meningioma in bilateral acoustic neurofibromatosis and the discovery that acoustic neuromas display specific loss of genes on chromosome 22, the authors propose that a common mechanism involving chromosome 22 is operative in the development of both tumor types. Fine-structure mapping to reveal partial deletions in meningiomas may provide the means to clone and characterize a gene (or genes) of importance for tumorigenesis in this and possibly other clinically associated tumors of the human nervous system

An approach for multi-objective optimization of vehicle suspension system

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Koulocheris, D.; Papaioannou, G.; Christodoulou, D.

2017-10-01

In this paper, a half car model of with nonlinear suspension systems is selected in order to study the vertical vibrations and optimize its suspension system with respect to ride comfort and road holding. A road bump was used as road profile. At first, the optimization problem is solved with the use of Genetic Algorithms with respect to 6 optimization targets. Then the k - ɛ optimization method was implemented to locate one optimum solution. Furthermore, an alternative approach is presented in this work: the previous optimization targets are separated in main and supplementary ones, depending on their importance in the analysis. The supplementary targets are not crucial to the optimization but they could enhance the main objectives. Thus, the problem was solved again using Genetic Algorithms with respect to the 3 main targets of the optimization. Having obtained the Pareto set of solutions, the k - ɛ optimality method was implemented for the 3 main targets and the supplementary ones, evaluated by the simulation of the vehicle model. The results of both cases are presented and discussed in terms of convergence of the optimization and computational time. The optimum solutions acquired from both cases are compared based on performance metrics as well.

Novel therapeutic strategy in the management of COPD: a systems medicine approach.

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Lococo, Filippo; Cesario, Alfredo; Del Bufalo, Alessandra; Ciarrocchi, Alessia; Prinzi, Giulia; Mina, Marco; Bonassi, Stefano; Russo, Patrizia

2015-01-01

Respiratory diseases including chronic-obstructive-pulmonary-disease (COPD) are globally increasing, with COPD predicted to become the third leading cause of global mortality by 2020. COPD is a heterogeneous disease with COPD-patients displaying different phenotypes as a result of a complex interaction between various genetic, environmental and life-style factors. In recent years, several investigations have been performed to better define such interactions, but the identification of the resulting phenotypes is still somewhat difficult, and may lead to inadequate assessment and management of COPD (usually based solely on the severity of airflow limitation parameter FEV1). In this new scenario, the management of COPD has been driven towards an integrative and holistic approach. The degree of complexity requires analyses based on large datasets (also including advanced functional genomic assays) and novel computational biology approaches (essential to extract information relevant for the clinical decision process and for the development of new drugs). Therefore, according to the emerging "systems/network medicine", COPD should be re.-evaluated considering multiple network(s) perturbations such as genetic and environmental changes. Systems Medicine (SM) platforms, in which patients are extensively characterized, offer a basis for a more targeted clinical approach, which is predictive, preventive, personalized and participatory ("P4-medicine"). It clearly emerges that in the next future, new opportunities will become available for clinical research on rare COPD patterns and for the identification of new biomarkers of comorbidity, severity, and progression. Herein, we overview the literature discussing the opportunity coming from the adoption of SMapproaches in COPD management, focusing on proteomics and metabolomics, and emphasizing the identification of disease sub-clusters, to improve the development of more effective therapies.

Perceptron Genetic to Recognize Openning Strategy Ruy Lopez

Science.gov (United States)

Azmi, Zulfian; Mawengkang, Herman

2018-01-01

The application of Perceptron method is not effective for coding on hardware based systems because it is not real time learning. With Genetic algorithm approach in calculating and searching the best weight (fitness value) system will do learning only one iteration. And the results of this analysis were tested in the case of the introduction of the opening pattern of chess Ruy Lopez. The Analysis with Perceptron Model with Algorithm Approach Genetics from group Artificial Neural Network for open Ruy Lopez. The data is processed with base open chess, with step eight a position white Pion from end open chess. Using perceptron method have many input and one output process many weight and refraction until output equal goal. Data trained and test with software Matlab and system can recognize the chess opening Ruy Lopez or Not open Ruy Lopez with Real time.

Nuclear power control system design using genetic algorithm

International Nuclear Information System (INIS)

Lee, Yoon Joon; Cho, Kyung Ho

1996-01-01

The genetic algorithm(GA) is applied to the design of the nuclear power control system. The reactor control system model is described in the LQR configuration. The LQR system order is increased to make the tracking system. The key parameters of the design are weighting matrices, and these are usually determined through numerous simulations in the conventional design. To determine the more objective and optimal weightings, the improved GA is applied. The results show that the weightings determined by the GA yield the better system responses than those obtained by the conventional design method

US system of oversight for genetic testing: a report from the Secretary's Advisory Committee on Genetics, Health and Society.

Science.gov (United States)

Ferreira-Gonzalez, Andrea; Teutsch, Steven; Williams, Marc S; Au, Sylvia M; Fitzgerald, Kevin T; Miller, Paul Steven; Fomous, Cathy

2008-09-01

As genetic testing technology is integrated into healthcare, increasingly detailed information about individual and population genetic variation is available to patients and providers. Health professionals use genetic testing to diagnose or assess the risk of disease in individuals, families and populations and to guide healthcare decisions. Consumers are beginning to explore personalized genomic services in an effort to learn more about their risk for common diseases. Scientific and technological advances in genetic testing, as with any newly introduced medical technology, present certain challenges to existing frameworks of oversight. In addition, the growing use of genetic testing will require a significant investment in evidence-based assessments to understand the validity and utility of these tests in clinical and personal decisionmaking. To optimize the use of genetic testing in healthcare, all sectors of the oversight system need to be strengthened and yet remain flexible in order to adapt to advances that will inevitably increase the range of genetic tests and methodologies.

Control of bovine spongiform encephalopathy by genetic engineering: possible approaches and regulatory considerations

International Nuclear Information System (INIS)

Gavora, J.S.; Kochhar, H.P.S.; Gifford, G.A.

2005-01-01

Transmissible spongiform encephalopathies (TSE) include bovine spongiform encephalopathy (BSE), scrapie in sheep and Creutzfeldt-Jakob disease (CJD) in humans. A new CJD variant (nvCJD) is believed to be related to consumption of meat from BSE cattle. In TSE individuals, prion proteins (PrP) with approximately 250 amino acids convert to the pathogenic prion PrP Sc , leading to a dysfunction of the central neural system. Research elsewhere with mice has indicated a possible genetic engineering approach to the introduction of BSE resistance: individuals with amino acid substitutions at positions 167 or 218, inoculated with a pathogenic prion protein, did not support PrP Sc replication. This raises the possibility of producing prion-resistant cattle with a single PrP amino acid substitution. Since prion-resistant animals might still harbour acquired prion infectivity, regulatory assessment of the engineered animals would need to ascertain that such possible 'carriers' do not result in a threat to animal and human health. (author)

View-Invariant Gait Recognition Through Genetic Template Segmentation

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Isaac, Ebenezer R. H. P.; Elias, Susan; Rajagopalan, Srinivasan; Easwarakumar, K. S.

2017-08-01

Template-based model-free approach provides by far the most successful solution to the gait recognition problem in literature. Recent work discusses how isolating the head and leg portion of the template increase the performance of a gait recognition system making it robust against covariates like clothing and carrying conditions. However, most involve a manual definition of the boundaries. The method we propose, the genetic template segmentation (GTS), employs the genetic algorithm to automate the boundary selection process. This method was tested on the GEI, GEnI and AEI templates. GEI seems to exhibit the best result when segmented with our approach. Experimental results depict that our approach significantly outperforms the existing implementations of view-invariant gait recognition.

A novel genetic score approach using instruments to investigate interactions between pathways and environment: application to air pollution.

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Marie-Abele Bind

Full Text Available Air pollution has been associated with increased systemic inflammation markers. We developed a new pathway analysis approach to investigate whether gene variants within relevant pathways (oxidative stress, endothelial function, and metal processing modified the association between particulate air pollution and fibrinogen, C-reactive protein (CRP, intercellular adhesion molecule-1 (ICAM-1, and vascular cell adhesion molecule-1 (VCAM-1. Our study population consisted of 822 elderly participants of the Normative Aging Study (1999-2011. To investigate the role of biological mechanisms and to reduce the number of comparisons in the analysis, we created pathway-specific scores using gene variants related to each pathway. To select the most appropriate gene variants, we used the least absolute shrinkage and selection operator (Lasso to relate independent outcomes representative of each pathway (8-hydroxydeoxyguanosine for oxidative stress, augmentation index for endothelial function, and patella lead for metal processing to gene variants. A high genetic score corresponds to a higher allelic risk profile. We fit mixed-effects models to examine modification by the genetic score of the weekly air pollution association with the outcome. Among participants with higher genetic scores within the oxidative stress pathway, we observed significant associations between particle number and fibrinogen, while we did not find any association among participants with lower scores (p(interaction = 0.04. Compared to individuals with low genetic scores of metal processing gene variants, participants with higher scores had greater effects of particle number on fibrinogen (p(interaction = 0.12, CRP (p(interaction = 0.02, and ICAM-1 (pinteraction = 0.08. This two-stage penalization method is easy to implement and can be used for large-scale genetic applications.

Mob/oriT, a mobilizable site-specific recombination system for unmarked genetic manipulation in Bacillus thuringiensis and Bacillus cereus.

Science.gov (United States)

Wang, Pengxia; Zhu, Yiguang; Zhang, Yuyang; Zhang, Chunyi; Xu, Jianyi; Deng, Yun; Peng, Donghai; Ruan, Lifang; Sun, Ming

2016-06-10

Bacillus thuringiensis and Bacillus cereus are two important species in B. cereus group. The intensive study of these strains at the molecular level and construction of genetically modified bacteria requires the development of efficient genetic tools. To insert genes into or delete genes from bacterial chromosomes, marker-less manipulation methods were employed. We present a novel genetic manipulation method for B. thuringiensis and B. cereus strains that does not leave selection markers. Our approach takes advantage of the relaxase Mob02281 encoded by plasmid pBMB0228 from Bacillus thuringiensis. In addition to its mobilization function, this Mob protein can mediate recombination between oriT sites. The Mob02281 mobilization module was associated with a spectinomycin-resistance gene to form a Mob-Spc cassette, which was flanked by the core 24-bp oriT sequences from pBMB0228. A strain in which the wild-type chromosome was replaced with the modified copy containing the Mob-Spc cassette at the target locus was obtained via homologous recombination. Thus, the spectinomycin-resistance gene can be used to screen for Mob-Spc cassette integration mutants. Recombination between the two oriT sequences mediated by Mob02281, encoded by the Mob-Spc cassette, resulted in the excision of the Mob-Spc cassette, producing the desired chromosomal alteration without introducing unwanted selection markers. We used this system to generate an in-frame deletion of a target gene in B. thuringiensis as well as a gene located in an operon of B. cereus. Moreover, we demonstrated that this system can be used to introduce a single gene or an expression cassette of interest in B. thuringiensis. The Mob/oriT recombination system provides an efficient method for unmarked genetic manipulation and for constructing genetically modified bacteria of B. thuringiensis and B. cereus. Our method extends the available genetic tools for B. thuringiensis and B. cereus strains.

A systems approach to obesity

Science.gov (United States)

Bartsch, Sarah M.; Mui, Yeeli; Haidari, Leila A.; Spiker, Marie L.; Gittelsohn, Joel

2017-01-01

Obesity has become a truly global epidemic, affecting all age groups, all populations, and countries of all income levels. To date, existing policies and interventions have not reversed these trends, suggesting that innovative approaches are needed to transform obesity prevention and control. There are a number of indications that the obesity epidemic is a systems problem, as opposed to a simple problem with a linear cause-and-effect relationship. What may be needed to successfully address obesity is an approach that considers the entire system when making any important decision, observation, or change. A systems approach to obesity prevention and control has many benefits, including the potential to further understand indirect effects or to test policies virtually before implementing them in the real world. Discussed here are 5 key efforts to implement a systems approach for obesity prevention: 1) utilize more global approaches; 2) bring new experts from disciplines that do not traditionally work with obesity to share experiences and ideas with obesity experts; 3) utilize systems methods, such as systems mapping and modeling; 4) modify and combine traditional approaches to achieve a stronger systems orientation; and 5) bridge existing gaps between research, education, policy, and action. This article also provides an example of how a systems approach has been used to convene a multidisciplinary team and conduct systems mapping and modeling as part of an obesity prevention program in Baltimore, Maryland. PMID:28049754

On Gene Concepts and Teaching Genetics: Episodes from Classical Genetics

Science.gov (United States)

Burian, Richard M.

2013-01-01

This paper addresses the teaching of advanced high school courses or undergraduate courses for non-biology majors about genetics or history of genetics. It will probably be difficult to take the approach described here in a high school science course, although the general approach could help improve such courses. It would be ideal for a college…

On Gene Concepts and Teaching Genetics: Episodes from Classical Genetics

Science.gov (United States)

Burian, Richard M.

2013-02-01

This paper addresses the teaching of advanced high school courses or undergraduate courses for non-biology majors about genetics or history of genetics. It will probably be difficult to take the approach described here in a high school science course, although the general approach could help improve such courses. It would be ideal for a college course in history of genetics or a course designed to teach non-science majors how science works or the rudiments of the genetics in a way that will help them as citizens. The approach aims to teach the processes of discovery, correction, and validation by utilizing illustrative episodes from the history of genetics. The episodes are treated in way that should foster understanding of basic questions about genes, the sorts of techniques used to answer questions about the constitution and structure of genes, how they function, and what they determine, and some of the major biological disagreements that arose in dealing with these questions. The material covered here could be connected to social and political issues raised by genetics, but these connections are not surveyed here. As it is, to cover this much territory, the article is limited to four major episodes from Mendel's paper to the beginning of World War II. A sequel will deal with the molecularization of genetics and with molecular gene concepts through the Human Genome Project.

Evaluating oversight systems for emerging technologies: a case study of genetically engineered organisms.

Science.gov (United States)

Kuzma, Jennifer; Najmaie, Pouya; Larson, Joel

2009-01-01

The U.S. oversight system for genetically engineered organisms (GEOs) was evaluated to develop hypotheses and derive lessons for oversight of other emerging technologies, such as nanotechnology. Evaluation was based upon quantitative expert elicitation, semi-standardized interviews, and historical literature analysis. Through an interdisciplinary policy analysis approach, blending legal, ethical, risk analysis, and policy sciences viewpoints, criteria were used to identify strengths and weaknesses of GEOs oversight and explore correlations among its attributes and outcomes. From the three sources of data, hypotheses and broader conclusions for oversight were developed. Our analysis suggests several lessons for oversight of emerging technologies: the importance of reducing complexity and uncertainty in oversight for minimizing financial burdens on small product developers; consolidating multi-agency jurisdictions to avoid gaps and redundancies in safety reviews; consumer benefits for advancing acceptance of GEO products; rigorous and independent pre- and post-market assessment for environmental safety; early public input and transparency for ensuring public confidence; and the positive role of public input in system development, informed consent, capacity, compliance, incentives, and data requirements and stringency in promoting health and environmental safety outcomes, as well as the equitable distribution of health impacts. Our integrated approach is instructive for more comprehensive analyses of oversight systems, developing hypotheses for how features of oversight systems affect outcomes, and formulating policy options for oversight of future technological products, especially nanotechnology products.

Beyond dual systems: A genetically-informed, latent factor model of behavioral and self-report measures related to adolescent risk-taking

Directory of Open Access Journals (Sweden)

K. Paige Harden

2017-06-01

Full Text Available The dual systems model posits that adolescent risk-taking results from an imbalance between a cognitive control system and an incentive processing system. Researchers interested in understanding the development of adolescent risk-taking use a diverse array of behavioral and self-report measures to index cognitive control and incentive processing. It is currently unclear whether different measures commonly interpreted as indicators of the same psychological construct do, in fact, tap the same underlying dimension of individual differences. In a diverse sample of 810 adolescent twins and triplets (M age = 15.9 years, SD = 1.4 years from the Texas Twin Project, we investigated the factor structure of fifteen self-report and task-based measures relevant to adolescent risk-taking. These measures can be organized into four factors, which we labeled premeditation, fearlessness, cognitive dyscontrol, and reward seeking. Most behavioral measures contained large amounts of task-specific variance; however, most genetic variance in each measure was shared with other measures of the corresponding factor. Behavior genetic analyses further indicated that genetic influences on cognitive dyscontrol overlapped nearly perfectly with genetic influences on IQ (rA = −0.91. These findings underscore the limitations of using single laboratory tasks in isolation, and indicate that the study of adolescent risk taking will benefit from applying multimethod approaches.

Chemical Genetics — A Versatile Method to Combine Science and Higher Level Teaching in Molecular Genetics

Directory of Open Access Journals (Sweden)

Björn Sandrock

2012-10-01

Full Text Available Phosphorylation is a key event in many cellular processes like cell cycle, transformation of environmental signals to transcriptional activation or polar growth. The chemical genetics approach can be used to analyse the effect of highly specific inhibition in vivo and is a promising method to screen for kinase targets. We have used this approach to study the role of the germinal centre kinase Don3 during the cell division in the phytopathogenic fungus Ustilago maydis. Due to the easy determination of the don3 phenotype we have chosen this approach for a genetic course for M.Sc. students and for IMPRS (International Max-Planck research school students. According to the principle of “problem-based learning” the aim of this two-week course is to transfer knowledge about the broad spectrum of kinases to the students and that the students acquire the ability to design their own analog-sensitive kinase of interest. In addition to these training goals, we benefit from these annual courses the synthesis of basic constructs for genetic modification of several kinases in our model system U. maydis.

Application of Genetic Algorithm and Particle Swarm Optimization techniques for improved image steganography systems

Directory of Open Access Journals (Sweden)

Jude Hemanth Duraisamy

2016-01-01

Full Text Available Image steganography is one of the ever growing computational approaches which has found its application in many fields. The frequency domain techniques are highly preferred for image steganography applications. However, there are significant drawbacks associated with these techniques. In transform based approaches, the secret data is embedded in random manner in the transform coefficients of the cover image. These transform coefficients may not be optimal in terms of the stego image quality and embedding capacity. In this work, the application of Genetic Algorithm (GA and Particle Swarm Optimization (PSO have been explored in the context of determining the optimal coefficients in these transforms. Frequency domain transforms such as Bandelet Transform (BT and Finite Ridgelet Transform (FRIT are used in combination with GA and PSO to improve the efficiency of the image steganography system.

Molecular and Chemical Genetic Approaches to Developmental Origins of Aging and Disease in Zebrafish

Science.gov (United States)

Sasaki, Tomoyuki; Kishi, Shuji

2013-01-01

The incidence of diseases increases rapidly with age, accompanied by progressive deteriorations of physiological functions in organisms. Aging-associated diseases are sporadic but mostly inevitable complications arising from senescence. Senescence is often considered the antithesis of early development, but yet there may be factors and mechanisms in common between these two phenomena over the dynamic process of aging. The association between early development and late-onset disease with advancing age is thought to come from a consequence of developmental plasticity, the phenomenon by which one genotype can give rise to a range of physiologically and/or morphologically adaptive states in response to different environmental or genetic perturbations. On the one hand, we hypothesized that the future aging process can be predictive based on adaptivity during the early developmental period. Modulating the thresholds of adaptive plasticity by chemical genetic approaches, we have been investigating whether any relationship exists between the regulatory mechanisms that function in early development and in senescence using the zebrafish (Danio rerio), a small freshwater fish and a useful model animal for genetic studies. We have successfully conducted experiments to isolate zebrafish mutants expressing apparently altered senescence phenotypes during embryogenesis (“embryonic senescence”), subsequently showing shortened lifespan in adulthoods. We anticipate that previously uncharacterized developmental genes may mediate the aging process and play a pivotal role in senescence. On the other hand, unexpected senescence-related genes might also be involved in the early developmental process and regulation. The ease of manipulation using the zebrafish system allows us to conduct an exhaustive exploration of novel genes and small molecular compounds that can be linked to the senescence phenotype, and thereby facilitates searching for the evolutionary and developmental origins

A High-Level Petri Net Framework for Genetic Regulatory Networks

Directory of Open Access Journals (Sweden)

Banks Richard

2007-12-01

Full Text Available To understand the function of genetic regulatory networks in the development of cellular systems, we must not only realise the individual network entities, but also the manner by which they interact. Multi-valued networks are a promising qualitative approach for modelling such genetic regulatory networks, however, at present they have limited formal analysis techniques and tools. We present a flexible formal framework for modelling and analysing multi-valued genetic regulatory networks using high-level Petri nets and logic minimization techniques. We demonstrate our approach with a detailed case study in which part of the genetic regulatory network responsible for the carbon starvation stress response in Escherichia coli is modelled and analysed. We then compare and contrast this multivalued model to a corresponding Boolean model and consider their formal relationship.

Translation and genetic criticism : genetic and editorial approaches to the 'untranslatable' in Joyce and Beckett

OpenAIRE

Hulle, Van, Dirk

2015-01-01

Abstract: Genetics of translation may suggest a unidirectional link between two fields of research (genetic criticism applied to translation), but there are many ways in which translation and genetic criticism interact. This article's research hypothesis is that an exchange of ideas between translation studies and genetic criticism can be mutually beneficial in more than one way. The main function of this exchange is to enhance a form of textual awareness, and to realize this enhanced textual...

[Reverse genetics system of rotaviruses: development and application for analysis of VP4 spike protein].

Science.gov (United States)

Komoto, Satoshi

2013-01-01

The rotavirus genome is composed of 11 gene segments of double-stranded (ds)RNA. Reverse genetics is the powerful and ideal methodology for the molecular analysis of virus biology, which enables the virus genome to be artificially manipulated. Although reverse genetics systems exist for nearly all major groups of RNA viruses, development of such a system for rotaviruses is more challenging owing in part to the technical complexity of manipulation of their multi-segmented genome. A breakthrough in the field of rotavirus reverse genetics came in 2006, when we established the first reverse genetics system for rotaviruses, which is a partially plasmid-based system that permits replacement of a viral gene segment with the aid of a helper virus. Although this helper virus-driven system is technically limited and gives low levels of recombinant viruses, it allows alteration of the rotavirus genome, thus contributing to our understanding of these medically important viruses. In this review, I describe the development and application of our rotavirus reverse genetics system, and its future perspectives.

Method of transient identification based on a possibilistic approach, optimized by genetic algorithm

International Nuclear Information System (INIS)

Almeida, Jose Carlos Soares de

2001-02-01

This work develops a method for transient identification based on a possible approach, optimized by Genetic Algorithm to optimize the number of the centroids of the classes that represent the transients. The basic idea of the proposed method is to optimize the partition of the search space, generating subsets in the classes within a partition, defined as subclasses, whose centroids are able to distinguish the classes with the maximum correct classifications. The interpretation of the subclasses as fuzzy sets and the possible approach provided a heuristic to establish influence zones of the centroids, allowing to achieve the 'don't know' answer for unknown transients, that is, outside the training set. (author)

Designing of a Decision Support System (DSS for resource allocation with genetic algorithm approach (Case Study: Central Library of Tarbiat Modares University

Directory of Open Access Journals (Sweden)

Alireza Hasanzadeh

2014-09-01

Full Text Available The allocation of information is one of the main responsibilities of a manager. In case there is a limitation in the available resources, the issue of resources allocation is raised. Universities and post graduate centers have faced limitations in accessing resources such as budget, human resources, physical space, etc. This problem results in inappropriate use of the approved budget in buying and sharing the different types of information resources, lack of easy access to information resources by users, and users’ dissatisfaction. This paper is intended to see whether the model of genetic algorithm can be used in helping library heads of university to develop a support system for the proper allocation of resources. The data of the central library of a university as the main core of DSS through using genetic algorithm in MATLAB was used in order to come up with a better distribution of effective resources. Research methodology used in this paper was field study and survey. The findings indicated that genetic algorithm was successful in achieving this end.

The perceived impact of the European registration system for genetic counsellors and nurses.

Science.gov (United States)

Paneque, Milena; Moldovan, Ramona; Cordier, Christophe; Serra-Juhé, Clara; Feroce, Irene; Pasalodos, Sara; Haquet, Emmanuelle; Lambert, Debby; Bjørnevoll, Inga; Skirton, Heather

2017-09-01

The aim of the European Board of Medical Genetics has been to develop and promote academic and professional standards necessary in order to provide competent genetic counselling services. The aim of this study was to explore the impact of the European registration system for genetic nurses and counsellors from the perspectives of those professionals who have registered. Registration system was launched in 2013. A cross-sectional, online survey was used to explore the motivations and experiences of those applying for, and the effect of registration on their career. Fifty-five Genetic Nurses and Counsellors are registered till now, from them, thirty-three agreed to participate on this study. The main motivations for registering were for recognition of their work value and competence (30.3%); due to the absence of a registration system in their own country (15.2%) and the possibility of obtaining a European/international certification (27.3%), while 27.3% of respondents registered to support recognition of the genetic counselling profession. Some participants valued the registration process as an educational activity in its own right, while the majority indicated the greatest impact of the registration process was on their clinical practice. The results confirm that registrants value the opportunity to both confirm their own competence and advance the genetic counselling profession in Europe.

Endogenous Molecular-Cellular Network Cancer Theory: A Systems Biology Approach.

Science.gov (United States)

Wang, Gaowei; Yuan, Ruoshi; Zhu, Xiaomei; Ao, Ping

2018-01-01

In light of ever apparent limitation of the current dominant cancer mutation theory, a quantitative hypothesis for cancer genesis and progression, endogenous molecular-cellular network hypothesis has been proposed from the systems biology perspective, now for more than 10 years. It was intended to include both the genetic and epigenetic causes to understand cancer. Its development enters the stage of meaningful interaction with experimental and clinical data and the limitation of the traditional cancer mutation theory becomes more evident. Under this endogenous network hypothesis, we established a core working network of hepatocellular carcinoma (HCC) according to the hypothesis and quantified the working network by a nonlinear dynamical system. We showed that the two stable states of the working network reproduce the main known features of normal liver and HCC at both the modular and molecular levels. Using endogenous network hypothesis and validated working network, we explored genetic mutation pattern in cancer and potential strategies to cure or relieve HCC from a totally new perspective. Patterns of genetic mutations have been traditionally analyzed by posteriori statistical association approaches in light of traditional cancer mutation theory. One may wonder the possibility of a priori determination of any mutation regularity. Here, we found that based on the endogenous network theory the features of genetic mutations in cancers may be predicted without any prior knowledge of mutation propensities. Normal hepatocyte and cancerous hepatocyte stable states, specified by distinct patterns of expressions or activities of proteins in the network, provide means to directly identify a set of most probable genetic mutations and their effects in HCC. As the key proteins and main interactions in the network are conserved through cell types in an organism, similar mutational features may also be found in other cancers. This analysis yielded straightforward and testable

Optimization of linear consecutive-k-out-of-n system with a Birnbaum importance-based genetic algorithm

International Nuclear Information System (INIS)

Cai, Zhiqiang; Si, Shubin; Sun, Shudong; Li, Caitao

2016-01-01

The optimization of linear consecutive-k-out-of-n (Lin/Con/k/n) is to find an optimal component arrangement where n components are assigned to n positions to maximize the system reliability. With the interchangeability of components in practical systems, the optimization of Lin/Con/k/n systems is becoming widely applied in engineering practice, which is also a typical component assignment problem concerned by many researchers. This paper proposes a Birnbaum importance-based genetic algorithm (BIGA) to search the near global optimal solution for Lin/Con/k/n systems. First, the operation procedures and corresponding execution methods of BIGA are described in detail. Then, comprehensive simulation experiments are implemented on both small and large systems to evaluate the performance of the BIGA by comparing with the Birnbaum importance-based two-stage approach and Birnbaum importance-based genetic local search algorithm. Thirdly, further experiments are provided to discuss the applicability of BIGA for Lin/Con/k/n system with different k and n. Finally, the case study on oil transportation system is implemented to demonstrate the application of BIGA in the optimization of Lin/Con/k/n system. - Highlights: • BIGA integrates BI and GA to solve the Lin/Con/k/n systems optimization problems. • The experiment results show that the BIGA performs well in most conditions. • Suggestions are given for the application of BIGA and BITA with different k and n. • The application procedure of BIGA is demonstrated by the oil transportation system.

Activity System Theory Approach to Healthcare Information System

OpenAIRE

Bai, Guohua

2004-01-01

Healthcare information system is a very complex system and has to be approached from systematic perspectives. This paper presents an Activity System Theory (ATS) approach by integrating system thinking and social psychology. First part of the paper, the activity system theory is presented, especially a recursive model of human activity system is introduced. A project ‘Integrated Mobile Information System for Diabetic Healthcare (IMIS)’ is then used to demonstrate a practical application of th...

The calculus a genetic approach

CERN Document Server

Toeplitz, Otto

2007-01-01

When first published posthumously in 1963, this book presented a radically different approach to the teaching of calculus.  In sharp contrast to the methods of his time, Otto Toeplitz did not teach calculus as a static system of techniques and facts to be memorized. Instead, he drew on his knowledge of the history of mathematics and presented calculus as an organic evolution of ideas beginning with the discoveries of Greek scholars, such as Archimedes, Pythagoras, and Euclid, and developing through the centuries in the work of Kepler, Galileo, Fermat, Newton, and Leibniz. Through this unique a

A genetic replacement system for selection-based engineering of essential proteins

Science.gov (United States)

2012-01-01

Background Essential genes represent the core of biological functions required for viability. Molecular understanding of essentiality as well as design of synthetic cellular systems includes the engineering of essential proteins. An impediment to this effort is the lack of growth-based selection systems suitable for directed evolution approaches. Results We established a simple strategy for genetic replacement of an essential gene by a (library of) variant(s) during a transformation. The system was validated using three different essential genes and plasmid combinations and it reproducibly shows transformation efficiencies on the order of 107 transformants per microgram of DNA without any identifiable false positives. This allowed for reliable recovery of functional variants out of at least a 105-fold excess of non-functional variants. This outperformed selection in conventional bleach-out strains by at least two orders of magnitude, where recombination between functional and non-functional variants interfered with reliable recovery even in recA negative strains. Conclusions We propose that this selection system is extremely suitable for evaluating large libraries of engineered essential proteins resulting in the reliable isolation of functional variants in a clean strain background which can readily be used for in vivo applications as well as expression and purification for use in in vitro studies. PMID:22898007

A group approach to genetic counselling of cardiomyopathy patients: satisfaction and psychological outcomes sufficient for further implementation.

Science.gov (United States)

Otten, Ellen; Birnie, Erwin; Ranchor, Adelita V; van Tintelen, J Peter; van Langen, Irene M

2015-11-01

The introduction of next-generation sequencing in everyday clinical genetics practise is increasing the number of genetic disorders that can be confirmed at DNA-level, and consequently increases the possibilities for cascade screening. This leads to a greater need for genetic counselling, whereas the number of professionals available to provide this is limited. We therefore piloted group genetic counselling for symptomatic cardiomyopathy patients at regional hospitals, to assess whether this could be an acceptable alternative to individual counselling. We performed a cohort study with pre- and post-counselling patient measurements using questionnaires, supplemented with evaluations of the group counselling format by the professionals involved. Patients from eight regional hospitals in the northern part of the Netherlands were included. Questionnaires comprised patient characteristics, psychological measures (personal perceived control (PPC), state and trait anxiety inventory (STAI)), and satisfaction with counsellors, counselling content and design. In total, 82 patients (mean age 57.5 year) attended one of 13 group sessions. Median PPC and STAI scores showed significantly higher control and lower anxiety after the counselling. Patients reported they were satisfied with the counsellors, and almost 75% of patients were satisfied with the group counselling. Regional professionals were also, overall, satisfied with the group sessions. The genetics professionals were less satisfied, mainly because of their perceived large time investment and less-than-expected group interaction. Hence, a group approach to cardiogenetic counselling is feasible, accessible, and psychologically effective, and could be one possible approach to counselling the increasing patient numbers in cardiogenetics.

A Robust Computational Technique for Model Order Reduction of Two-Time-Scale Discrete Systems via Genetic Algorithms

Directory of Open Access Journals (Sweden)

Othman M. K. Alsmadi

2015-01-01

Full Text Available A robust computational technique for model order reduction (MOR of multi-time-scale discrete systems (single input single output (SISO and multi-input multioutput (MIMO is presented in this paper. This work is motivated by the singular perturbation of multi-time-scale systems where some specific dynamics may not have significant influence on the overall system behavior. The new approach is proposed using genetic algorithms (GA with the advantage of obtaining a reduced order model, maintaining the exact dominant dynamics in the reduced order, and minimizing the steady state error. The reduction process is performed by obtaining an upper triangular transformed matrix of the system state matrix defined in state space representation along with the elements of B, C, and D matrices. The GA computational procedure is based on maximizing the fitness function corresponding to the response deviation between the full and reduced order models. The proposed computational intelligence MOR method is compared to recently published work on MOR techniques where simulation results show the potential and advantages of the new approach.

Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: Comparing meta and megaanalytical approaches for data pooling.

Science.gov (United States)

Kochunov, Peter; Jahanshad, Neda; Sprooten, Emma; Nichols, Thomas E; Mandl, René C; Almasy, Laura; Booth, Tom; Brouwer, Rachel M; Curran, Joanne E; de Zubicaray, Greig I; Dimitrova, Rali; Duggirala, Ravi; Fox, Peter T; Hong, L Elliot; Landman, Bennett A; Lemaitre, Hervé; Lopez, Lorna M; Martin, Nicholas G; McMahon, Katie L; Mitchell, Braxton D; Olvera, Rene L; Peterson, Charles P; Starr, John M; Sussmann, Jessika E; Toga, Arthur W; Wardlaw, Joanna M; Wright, Margaret J; Wright, Susan N; Bastin, Mark E; McIntosh, Andrew M; Boomsma, Dorret I; Kahn, René S; den Braber, Anouk; de Geus, Eco J C; Deary, Ian J; Hulshoff Pol, Hilleke E; Williamson, Douglas E; Blangero, John; van 't Ent, Dennis; Thompson, Paul M; Glahn, David C

2014-07-15

Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability. Copyright © 2014 Elsevier Inc. All rights reserved.

Maximum volume cuboids for arbitrarily shaped in-situ rock blocks as determined by discontinuity analysis—A genetic algorithm approach

Science.gov (United States)

Ülker, Erkan; Turanboy, Alparslan

2009-07-01

The block stone industry is one of the main commercial use of rock. The economic potential of any block quarry depends on the recovery rate, which is defined as the total volume of useful rough blocks extractable from a fixed rock volume in relation to the total volume of moved material. The natural fracture system, the rock type(s) and the extraction method used directly influence the recovery rate. The major aims of this study are to establish a theoretical framework for optimising the extraction process in marble quarries for a given fracture system, and for predicting the recovery rate of the excavated blocks. We have developed a new approach by taking into consideration only the fracture structure for maximum block recovery in block quarries. The complete model uses a linear approach based on basic geometric features of discontinuities for 3D models, a tree structure (TS) for individual investigation and finally a genetic algorithm (GA) for the obtained cuboid volume(s). We tested our new model in a selected marble quarry in the town of İscehisar (AFYONKARAHİSAR—TURKEY).

A Genetic Based Neuro-Fuzzy Controller System

International Nuclear Information System (INIS)

Mohamed, A.H.

2014-01-01

Recently, the mobile robots have great importance in the manufacturing processes. They are widely used for assembling processes, handling the dangerous components, moving the weighted things, etc. Designing the controller of the mobile robot is a very complex task. Many simple control systems used the neuro-fuzzy controller in the mobile robots. But, they faced with great complexity when moving in unstructured and dynamic environments. The proposed system introduces the uses of the genetic algorithm for optimizing the parameters of the neuro-fuzzy controller. So, the proposed system can improve the performance of the mobile robots. It has applied for a mobile robot used for moving the dangerous and critical materials in unstructured environment. Its results are compared with other traditional controller systems. The suggested system has proved its success for the real-time applications

An Evolutionary Approach for Optimizing Hierarchical Multi-Agent System Organization

OpenAIRE

Shen, Zhiqi; Yu, Ling; Yu, Han

2014-01-01

It has been widely recognized that the performance of a multi-agent system is highly affected by its organization. A large scale system may have billions of possible ways of organization, which makes it impractical to find an optimal choice of organization using exhaustive search methods. In this paper, we propose a genetic algorithm aided optimization scheme for designing hierarchical structures of multi-agent systems. We introduce a novel algorithm, called the hierarchical genetic algorithm...

Genetic testing in congenital heart disease:A clinical approach

Institute of Scientific and Technical Information of China (English)

Marie A Chaix; Gregor Andelfinger; Paul Khairy

2016-01-01

Congenital heart disease(CHD) is the most common type of birth defect. Traditionally, a polygenic model defined by the interaction of multiple genes and environmental factors was hypothesized to account for different forms of CHD. It is now understood that the contribution of genetics to CHD extends beyond a single unified paradigm. For example, monogenic models and chromosomal abnormalities have been associated with various syndromic and non-syndromic forms of CHD. In such instances, genetic investigation and testing may potentially play an important role in clinical care. A family tree with a detailed phenotypic description serves as the initial screening tool to identify potentially inherited defects and to guide further genetic investigation. The selection of a genetic test is contingent upon the particular diagnostic hypothesis generated by clinical examination. Genetic investigation in CHD may carry the potential to improve prognosis by yielding valuable information with regards to personalized medical care, confidence in the clinical diagnosis, and/or targeted patient followup. Moreover, genetic assessment may serve as a tool to predict recurrence risk, define the pattern of inheritance within a family, and evaluate the need for further family screening. In some circumstances, prenatal or preimplantation genetic screening could identify fetuses or embryos at high risk for CHD. Although genetics may appear to constitute a highly specialized sector of cardiology, basic knowledge regarding inheritance patterns, recurrence risks, and available screening and diagnostic tools, including their strengths and limitations, could assist the treating physician in providing sound counsel.

Unfolding neutron spectra obtained from BS–TLD system using genetic algorithm

International Nuclear Information System (INIS)

Santos, J.A.L.; Silva, E.R.; Ferreira, T.A.E; Vilela, E.C.

2012-01-01

Due to the variability of neutron spectrum within the same environment, it is essential that the spectral distribution as a function of energy should be characterized. The precise information allows radiological quantities establishment related to that spectrum, but it is necessary that a spectrometric system covers a large interval of energy and an unfolding process is appropriate. This paper proposes use of a technique of Artificial Intelligence (AI) called genetic algorithm (GA), which uses bio-inspired mathematical models with the implementation of a specific matrix to unfolding data obtained from a combination of TLDs embedded in a BS system to characterize the neutron spectrum as a function of energy. The results obtained with this method were in accordance with reference spectra, thus enabling this technique to unfold neutron spectra with the BS–TLD system. - Highlights: ► The unfolding code used the artificial intelligence technique called genetic algorithms. ► A response matrix specific to the unfolding data obtained with the BS–TLD system is used by the AGLN. ► The observed results demonstrate the potential use of genetic algorithms in solving complex nuclear problems.

Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: comparing meta and mega analytical approaches for data pooling

Science.gov (United States)

Kochunov, Peter; Jahanshad, Neda; Sprooten, Emma; Nichols, Thomas E.; Mandl, René C.; Almasy, Laura; Booth, Tom; Brouwer, Rachel M.; Curran, Joanne E.; de Zubicaray, Greig I.; Dimitrova, Rali; Duggirala, Ravi; Fox, Peter T.; Hong, L. Elliot; Landman, Bennett A.; Lemaitre, Hervé; Lopez, Lorna; Martin, Nicholas G.; McMahon, Katie L.; Mitchell, Braxton D.; Olvera, Rene L.; Peterson, Charles P.; Starr, John M.; Sussmann, Jessika E.; Toga, Arthur W.; Wardlaw, Joanna M.; Wright, Margaret J.; Wright, Susan N.; Bastin, Mark E.; McIntosh, Andrew M.; Boomsma, Dorret I.; Kahn, René S.; den Braber, Anouk; de Geus, Eco JC; Deary, Ian J.; Hulshoff Pol, Hilleke E.; Williamson, Douglas E.; Blangero, John; van ’t Ent, Dennis; Thompson, Paul M.; Glahn, David C.

2014-01-01

Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9–85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large “mega-family”. We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability. PMID:24657781

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)

Generation of genetically modified mice using CRISPR/Cas9 and haploid embryonic stem cell systems

Directory of Open Access Journals (Sweden)

Li-Fang JIN

2016-07-01

Full Text Available With the development of high-throughput sequencing technology in the post-genomic era, researchers have concentrated their efforts on elucidating the relationships between genes and their corresponding functions. Recently, important progress has been achieved in the generation of genetically modified mice based on CRISPR/Cas9 and haploid embryonic stem cell (haESC approaches, which provide new platforms for gene function analysis, human disease modeling, and gene therapy. Here, we review the CRISPR/Cas9 and haESC technology for the generation of genetically modified mice and discuss the key challenges in the application of these approaches.

[The role of the genetics history in genetics teaching].

Science.gov (United States)

Li, Ming-Hui

2006-08-01

The research of the scientific history and development status reflect the science and technology level of a nation. The genetic history is one of the branches of the life science and the 21st century is life science century. The genetics history in the teaching of genetics not only can help students get familiar with the birth and development of genetics, but also enhance their thinking ability and scientific qualities. The roles and approaches of teaching are discussed in this paper.

Genetic testing in congenital heart disease: A clinical approach

Science.gov (United States)

Chaix, Marie A; Andelfinger, Gregor; Khairy, Paul

2016-01-01

Congenital heart disease (CHD) is the most common type of birth defect. Traditionally, a polygenic model defined by the interaction of multiple genes and environmental factors was hypothesized to account for different forms of CHD. It is now understood that the contribution of genetics to CHD extends beyond a single unified paradigm. For example, monogenic models and chromosomal abnormalities have been associated with various syndromic and non-syndromic forms of CHD. In such instances, genetic investigation and testing may potentially play an important role in clinical care. A family tree with a detailed phenotypic description serves as the initial screening tool to identify potentially inherited defects and to guide further genetic investigation. The selection of a genetic test is contingent upon the particular diagnostic hypothesis generated by clinical examination. Genetic investigation in CHD may carry the potential to improve prognosis by yielding valuable information with regards to personalized medical care, confidence in the clinical diagnosis, and/or targeted patient follow-up. Moreover, genetic assessment may serve as a tool to predict recurrence risk, define the pattern of inheritance within a family, and evaluate the need for further family screening. In some circumstances, prenatal or preimplantation genetic screening could identify fetuses or embryos at high risk for CHD. Although genetics may appear to constitute a highly specialized sector of cardiology, basic knowledge regarding inheritance patterns, recurrence risks, and available screening and diagnostic tools, including their strengths and limitations, could assist the treating physician in providing sound counsel. PMID:26981213

Insulated transcriptional elements enable precise design of genetic circuits.

Science.gov (United States)

Zong, Yeqing; Zhang, Haoqian M; Lyu, Cheng; Ji, Xiangyu; Hou, Junran; Guo, Xian; Ouyang, Qi; Lou, Chunbo

2017-07-03

Rational engineering of biological systems is often complicated by the complex but unwanted interactions between cellular components at multiple levels. Here we address this issue at the level of prokaryotic transcription by insulating minimal promoters and operators to prevent their interaction and enable the biophysical modeling of synthetic transcription without free parameters. This approach allows genetic circuit design with extraordinary precision and diversity, and consequently simplifies the design-build-test-learn cycle of circuit engineering to a mix-and-match workflow. As a demonstration, combinatorial promoters encoding NOT-gate functions were designed from scratch with mean errors of 96% using our insulated transcription elements. Furthermore, four-node transcriptional networks with incoherent feed-forward loops that execute stripe-forming functions were obtained without any trial-and-error work. This insulation-based engineering strategy improves the resolution of genetic circuit technology and provides a simple approach for designing genetic circuits for systems and synthetic biology.Unwanted interactions between cellular components can complicate rational engineering of biological systems. Here the authors design insulated minimal promoters and operators that enable biophysical modeling of bacterial transcription without free parameters for precise circuit design.

A combined genetic and multi medium approach revels new secondary metabolites in Aspergillus nidulans

DEFF Research Database (Denmark)

Klejnstrup, Marie Louise; Nielsen, Morten Thrane; Frisvad, Jens Christian

Secondary metabolites are a diverse group of metabolites which serve as important natural sources of drugs for treating diseases. The availability of full genome sequences of several filamentous fungi has revealed a large genetic potential for production of secondary metabolites that are not obse......Secondary metabolites are a diverse group of metabolites which serve as important natural sources of drugs for treating diseases. The availability of full genome sequences of several filamentous fungi has revealed a large genetic potential for production of secondary metabolites...... that are not observed under standard laboratory conditions. Genetic approaches have proven a fruitfull strategy towards the production and identification of these unknown metabolites. Examples include deletion of the cclA1 and laeA2 genes in A. nidulans which affects the expression of secondary metabolites including...... monodictyphenone and terrequinone A respectively. We have deleted the cclA gene in A. nidulans and grown the mutants on several complex media to provoke the production of secondary metabolites. This resulted in the production of several metabolites not previously reported from A. nidulans. Some of these have been...

A genetic approach to shape reconstruction in limited data tomography

International Nuclear Information System (INIS)

Turcanu, C.; Craciunescu, T.

2001-01-01

The paper proposes a new method for shape reconstruction in computerized tomography. Unlike nuclear medicine applications, in physical science problems we are often confronted with limited data sets: constraints in the number of projections or limited view angles . The problem of image reconstruction from projection may be considered as a problem of finding an image (solution) having projections that match the experimental ones. In our approach, we choose a statistical correlation coefficient to evaluate the fitness of any potential solution. The optimization process is carried out by a genetic algorithm. The algorithm has some features common to all genetic algorithms but also some problem-oriented characteristics. One of them is that a chromosome, representing a potential solution, is not linear but coded as a matrix of pixels corresponding to a two-dimensional image. This kind of internal representation reflects the genuine manifestation and slight differences between two points situated in the original problem space give rise to similar differences once they become coded. Another particular feature is a newly built crossover operator: the grid-based crossover, suitable for high dimension two-dimensional chromosomes. Except for the population size and the dimension of the cutting grid for the grid-based crossover, all the other parameters of the algorithm are independent of the geometry of the tomographic reconstruction. The performances of the method are evaluated on a phantom typical for an application with limited data sets: the determination of the neutron energy spectra with time resolution in case of short-pulsed neutron emission. A genetic reconstruction is presented. The qualitative judgement and also the quantitative one, based on some figures of merit, point out that the proposed method ensures an improved reconstruction of shapes, sizes and resolution in the image, even in the presence of noise. (authors)

A New Selectable Marker System for Genetic Studies of Bacteria: Final Report

Energy Technology Data Exchange (ETDEWEB)

Parsons, D; Tolmasky, M; Chain, P; Segelke, B W

2011-03-18

Genetic manipulations in bacteria currently rely on the introduction of antibiotic resistance genes into a bacterial strain; for those organisms that will be used for commercial or industrial applications, the genetic cassette encoding the antibiotic resistance is sometimes removed after selection. it is clear that if alternative technologies could obviate the need to introduce antibiotic resistance into bacteria, they would most certainly become a standard tool in molecular micriobiology for commercial, industrial as well as research applications. Here, they present the development of a novel genetic engineering technology based on toxin-antitoxin systems to modify bacterial genomes without the use of antibiotic resistance in the mutagenesis process. The primary goal is to develop antibiotic-free selection for genetically altered select agent pathogens. They are adapting the toxinc-antitoxin system to enable gene replacement in select agent pathogens since the NIH restrictions introducing antibiotic resistance into select agent pathogens have hindered research with select agent pathogens.

eHealth provides a novel opportunity to exploit the advantages of the Nordic countries in psychiatric genetic research, building on the public health care system, biobanks, and registries.

Science.gov (United States)

Andreassen, Ole A

2017-07-07

Nordic countries have played an important role in the recent progress in psychiatric genetics, both with large well-characterized samples and expertise. The Nordic countries have research advantages due to the organization of their societies, including system of personal identifiers, national health registries with information about diseases, treatment and prescriptions, and a public health system with geographical catchment areas. For psychiatric genetic research, the large biobanks and population surveys are a unique added value. Further, the population is motivated to participate in research, and there is a trust in the institutions of the society. These factors have been important for Nordic contributions to biomedical research, and particularly psychiatric genetics. In the era of eHealth, the situation seems even more advantageous for Nordic countries. The system with public health care makes it easy to implement national measures, and most of the Nordic health care sector is already based on electronic information. The potential advantages regarding informed consent, large scale recruitment and follow-up, and longitudinal cohort studies are tremendous. New precision medicine approaches can be tested within the health care system, with an integrated approach, using large hospitals or regions of the country as a test beds. However, data protection and legal framework have to be clarified. In order to succeed, it is important to keep the people's trust, and maintain the high ethical standards and systems for secure data management. Then the full potential of the Nordic countries can be leveraged in the new era of precision medicine including psychiatric genetics. © 2017 Wiley Periodicals, Inc.

Genetic & epigenetic approach to human obesity

Directory of Open Access Journals (Sweden)

K Rajender Rao

2014-01-01

Full Text Available Obesity is an important clinical and public health challenge, epitomized by excess adipose tissue accumulation resulting from an imbalance in energy intake and energy expenditure. It is a forerunner for a variety of other diseases such as type-2-diabetes (T2D, cardiovascular diseases, some types of cancer, stroke, hyperlipidaemia and can be fatal leading to premature death. Obesity is highly heritable and arises from the interplay of multiple genes and environmental factors. Recent advancements in Genome-wide association studies (GWAS have shown important steps towards identifying genetic risks and identification of genetic markers for lifestyle diseases, especially for a metabolic disorder like obesity. According to the 12 th u0 pdate of Human Obesity Gene Map there are 253 quantity trait loci (QTL for obesity related phenotypes from 61 genome wide scan studies. Contribution of genetic propensity of individual ethnic and racial variations in obesity is an active area of research. Further, understanding its complexity as to how these variations could influence ones susceptibility to become or remain obese will lead us to a greater understanding of how obesity occurs and hopefully, how to prevent and treat this condition. In this review, various strategies adapted for such an analysis based on the recent advances in genome wide and functional variations in human obesity are discussed.

Genetic coding and united-hypercomplex systems in the models of algebraic biology.

Science.gov (United States)

Petoukhov, Sergey V

2017-08-01

Structured alphabets of DNA and RNA in their matrix form of representations are connected with Walsh functions and a new type of systems of multidimensional numbers. This type generalizes systems of complex numbers and hypercomplex numbers, which serve as the basis of mathematical natural sciences and many technologies. The new systems of multi-dimensional numbers have interesting mathematical properties and are called in a general case as "systems of united-hypercomplex numbers" (or briefly "U-hypercomplex numbers"). They can be widely used in models of multi-parametrical systems in the field of algebraic biology, artificial life, devices of biological inspired artificial intelligence, etc. In particular, an application of U-hypercomplex numbers reveals hidden properties of genetic alphabets under cyclic permutations in their doublets and triplets. A special attention is devoted to the author's hypothesis about a multi-linguistic in DNA-sequences in a relation with an ensemble of U-numerical sub-alphabets. Genetic multi-linguistic is considered as an important factor to provide noise-immunity properties of the multi-channel genetic coding. Our results attest to the conformity of the algebraic properties of the U-numerical systems with phenomenological properties of the DNA-alphabets and with the complementary device of the double DNA-helix. It seems that in the modeling field of algebraic biology the genetic-informational organization of living bodies can be considered as a set of united-hypercomplex numbers in some association with the famous slogan of Pythagoras "the numbers rule the world". Copyright © 2017 Elsevier B.V. All rights reserved.

Tracing Technological Development Trajectories: A Genetic Knowledge Persistence-Based Main Path Approach.

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Hyunseok Park

Full Text Available The aim of this paper is to propose a new method to identify main paths in a technological domain using patent citations. Previous approaches for using main path analysis have greatly improved our understanding of actual technological trajectories but nonetheless have some limitations. They have high potential to miss some dominant patents from the identified main paths; nonetheless, the high network complexity of their main paths makes qualitative tracing of trajectories problematic. The proposed method searches backward and forward paths from the high-persistence patents which are identified based on a standard genetic knowledge persistence algorithm. We tested the new method by applying it to the desalination and the solar photovoltaic domains and compared the results to output from the same domains using a prior method. The empirical results show that the proposed method can dramatically reduce network complexity without missing any dominantly important patents. The main paths identified by our approach for two test cases are almost 10x less complex than the main paths identified by the existing approach. The proposed approach identifies all dominantly important patents on the main paths, but the main paths identified by the existing approach miss about 20% of dominantly important patents.

Nonlinear inversion of potential-field data using a hybrid-encoding genetic algorithm

Science.gov (United States)

Chen, C.; Xia, J.; Liu, J.; Feng, G.

2006-01-01

Using a genetic algorithm to solve an inverse problem of complex nonlinear geophysical equations is advantageous because it does not require computer gradients of models or "good" initial models. The multi-point search of a genetic algorithm makes it easier to find the globally optimal solution while avoiding falling into a local extremum. As is the case in other optimization approaches, the search efficiency for a genetic algorithm is vital in finding desired solutions successfully in a multi-dimensional model space. A binary-encoding genetic algorithm is hardly ever used to resolve an optimization problem such as a simple geophysical inversion with only three unknowns. The encoding mechanism, genetic operators, and population size of the genetic algorithm greatly affect search processes in the evolution. It is clear that improved operators and proper population size promote the convergence. Nevertheless, not all genetic operations perform perfectly while searching under either a uniform binary or a decimal encoding system. With the binary encoding mechanism, the crossover scheme may produce more new individuals than with the decimal encoding. On the other hand, the mutation scheme in a decimal encoding system will create new genes larger in scope than those in the binary encoding. This paper discusses approaches of exploiting the search potential of genetic operations in the two encoding systems and presents an approach with a hybrid-encoding mechanism, multi-point crossover, and dynamic population size for geophysical inversion. We present a method that is based on the routine in which the mutation operation is conducted in the decimal code and multi-point crossover operation in the binary code. The mix-encoding algorithm is called the hybrid-encoding genetic algorithm (HEGA). HEGA provides better genes with a higher probability by a mutation operator and improves genetic algorithms in resolving complicated geophysical inverse problems. Another significant

Optimal planning approaches with multiple impulses for rendezvous based on hybrid genetic algorithm and control method

Directory of Open Access Journals (Sweden)

JingRui Zhang

2015-03-01

Full Text Available In this article, we focus on safe and effective completion of a rendezvous and docking task by looking at planning approaches and control with fuel-optimal rendezvous for a target spacecraft running on a near-circular reference orbit. A variety of existent practical path constraints are considered, including the constraints of field of view, impulses, and passive safety. A rendezvous approach is calculated by using a hybrid genetic algorithm with those constraints. Furthermore, a control method of trajectory tracking is adopted to overcome the external disturbances. Based on Clohessy–Wiltshire equations, we first construct the mathematical model of optimal planning approaches of multiple impulses with path constraints. Second, we introduce the principle of hybrid genetic algorithm with both stronger global searching ability and local searching ability. We additionally explain the application of this algorithm in the problem of trajectory planning. Then, we give three-impulse simulation examples to acquire an optimal rendezvous trajectory with the path constraints presented in this article. The effectiveness and applicability of the tracking control method are verified with the optimal trajectory above as control objective through the numerical simulation.

A Mission Planning Approach for Precision Farming Systems Based on Multi-Objective Optimization

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Zhaoyu Zhai

2018-06-01

Full Text Available As the demand for food grows continuously, intelligent agriculture has drawn much attention due to its capability of producing great quantities of food efficiently. The main purpose of intelligent agriculture is to plan agricultural missions properly and use limited resources reasonably with minor human intervention. This paper proposes a Precision Farming System (PFS as a Multi-Agent System (MAS. Components of PFS are treated as agents with different functionalities. These agents could form several coalitions to complete the complex agricultural missions cooperatively. In PFS, mission planning should consider several criteria, like expected benefit, energy consumption or equipment loss. Hence, mission planning could be treated as a Multi-objective Optimization Problem (MOP. In order to solve MOP, an improved algorithm, MP-PSOGA, is proposed, taking advantages of the Genetic Algorithms and Particle Swarm Optimization. A simulation, called precise pesticide spraying mission, is performed to verify the feasibility of the proposed approach. Simulation results illustrate that the proposed approach works properly. This approach enables the PFS to plan missions and allocate scarce resources efficiently. The theoretical analysis and simulation is a good foundation for the future study. Once the proposed approach is applied to a real scenario, it is expected to bring significant economic improvement.

A systems medicine research approach for studying alcohol addiction.

Science.gov (United States)

Spanagel, Rainer; Durstewitz, Daniel; Hansson, Anita; Heinz, Andreas; Kiefer, Falk; Köhr, Georg; Matthäus, Franziska; Nöthen, Markus M; Noori, Hamid R; Obermayer, Klaus; Rietschel, Marcella; Schloss, Patrick; Scholz, Henrike; Schumann, Gunter; Smolka, Michael; Sommer, Wolfgang; Vengeliene, Valentina; Walter, Henrik; Wurst, Wolfgang; Zimmermann, Uli S; Stringer, Sven; Smits, Yannick; Derks, Eske M

2013-11-01

According to the World Health Organization, about 2 billion people drink alcohol. Excessive alcohol consumption can result in alcohol addiction, which is one of the most prevalent neuropsychiatric diseases afflicting our society today. Prevention and intervention of alcohol binging in adolescents and treatment of alcoholism are major unmet challenges affecting our health-care system and society alike. Our newly formed German SysMedAlcoholism consortium is using a new systems medicine approach and intends (1) to define individual neurobehavioral risk profiles in adolescents that are predictive of alcohol use disorders later in life and (2) to identify new pharmacological targets and molecules for the treatment of alcoholism. To achieve these goals, we will use omics-information from epigenomics, genetics transcriptomics, neurodynamics, global neurochemical connectomes and neuroimaging (IMAGEN; Schumann et al. ) to feed mathematical prediction modules provided by two Bernstein Centers for Computational Neurosciences (Berlin and Heidelberg/Mannheim), the results of which will subsequently be functionally validated in independent clinical samples and appropriate animal models. This approach will lead to new early intervention strategies and identify innovative molecules for relapse prevention that will be tested in experimental human studies. This research program will ultimately help in consolidating addiction research clusters in Germany that can effectively conduct large clinical trials, implement early intervention strategies and impact political and healthcare decision makers. © 2013 Society for the Study of Addiction.

Genetic algorithm based reactive power dispatch for voltage stability improvement

Energy Technology Data Exchange (ETDEWEB)

Devaraj, D. [Department of Electrical and Electronics, Kalasalingam University, Krishnankoil 626 190 (India); Roselyn, J. Preetha [Department of Electrical and Electronics, SRM University, Kattankulathur 603 203, Chennai (India)

2010-12-15

Voltage stability assessment and control form the core function in a modern energy control centre. This paper presents an improved Genetic algorithm (GA) approach for voltage stability enhancement. The proposed technique is based on the minimization of the maximum of L-indices of load buses. Generator voltages, switchable VAR sources and transformer tap changers are used as optimization variables of this problem. The proposed approach permits the optimization variables to be represented in their natural form in the genetic population. For effective genetic processing, the crossover and mutation operators which can directly deal with the floating point numbers and integers are used. The proposed algorithm has been tested on IEEE 30-bus and IEEE 57-bus test systems and successful results have been obtained. (author)

Optimal design of link systems using successive zooming genetic algorithm

Science.gov (United States)

Kwon, Young-Doo; Sohn, Chang-hyun; Kwon, Soon-Bum; Lim, Jae-gyoo

2009-07-01

Link-systems have been around for a long time and are still used to control motion in diverse applications such as automobiles, robots and industrial machinery. This study presents a procedure involving the use of a genetic algorithm for the optimal design of single four-bar link systems and a double four-bar link system used in diesel engine. We adopted the Successive Zooming Genetic Algorithm (SZGA), which has one of the most rapid convergence rates among global search algorithms. The results are verified by experiment and the Recurdyn dynamic motion analysis package. During the optimal design of single four-bar link systems, we found in the case of identical input/output (IO) angles that the initial and final configurations show certain symmetry. For the double link system, we introduced weighting factors for the multi-objective functions, which minimize the difference between output angles, providing balanced engine performance, as well as the difference between final output angle and the desired magnitudes of final output angle. We adopted a graphical method to select a proper ratio between the weighting factors.

Genetic learning in rule-based and neural systems

Science.gov (United States)

Smith, Robert E.

1993-01-01

The design of neural networks and fuzzy systems can involve complex, nonlinear, and ill-conditioned optimization problems. Often, traditional optimization schemes are inadequate or inapplicable for such tasks. Genetic Algorithms (GA's) are a class of optimization procedures whose mechanics are based on those of natural genetics. Mathematical arguments show how GAs bring substantial computational leverage to search problems, without requiring the mathematical characteristics often necessary for traditional optimization schemes (e.g., modality, continuity, availability of derivative information, etc.). GA's have proven effective in a variety of search tasks that arise in neural networks and fuzzy systems. This presentation begins by introducing the mechanism and theoretical underpinnings of GA's. GA's are then related to a class of rule-based machine learning systems called learning classifier systems (LCS's). An LCS implements a low-level production-system that uses a GA as its primary rule discovery mechanism. This presentation illustrates how, despite its rule-based framework, an LCS can be thought of as a competitive neural network. Neural network simulator code for an LCS is presented. In this context, the GA is doing more than optimizing and objective function. It is searching for an ecology of hidden nodes with limited connectivity. The GA attempts to evolve this ecology such that effective neural network performance results. The GA is particularly well adapted to this task, given its naturally-inspired basis. The LCS/neural network analogy extends itself to other, more traditional neural networks. Conclusions to the presentation discuss the implications of using GA's in ecological search problems that arise in neural and fuzzy systems.

Genome-Wide Approaches to Drosophila Heart Development

Directory of Open Access Journals (Sweden)

Manfred Frasch

2016-05-01

Full Text Available The development of the dorsal vessel in Drosophila is one of the first systems in which key mechanisms regulating cardiogenesis have been defined in great detail at the genetic and molecular level. Due to evolutionary conservation, these findings have also provided major inputs into studies of cardiogenesis in vertebrates. Many of the major components that control Drosophila cardiogenesis were discovered based on candidate gene approaches and their functions were defined by employing the outstanding genetic tools and molecular techniques available in this system. More recently, approaches have been taken that aim to interrogate the entire genome in order to identify novel components and describe genomic features that are pertinent to the regulation of heart development. Apart from classical forward genetic screens, the availability of the thoroughly annotated Drosophila genome sequence made new genome-wide approaches possible, which include the generation of massive numbers of RNA interference (RNAi reagents that were used in forward genetic screens, as well as studies of the transcriptomes and proteomes of the developing heart under normal and experimentally manipulated conditions. Moreover, genome-wide chromatin immunoprecipitation experiments have been performed with the aim to define the full set of genomic binding sites of the major cardiogenic transcription factors, their relevant target genes, and a more complete picture of the regulatory network that drives cardiogenesis. This review will give an overview on these genome-wide approaches to Drosophila heart development and on computational analyses of the obtained information that ultimately aim to provide a description of this process at the systems level.

Genetic engineering of industrial Saccharomyces cerevisiae strains using a selection/counter-selection approach.

Science.gov (United States)

Kutyna, Dariusz R; Cordente, Antonio G; Varela, Cristian

2014-01-01

Gene modification of laboratory yeast strains is currently a very straightforward task thanks to the availability of the entire yeast genome sequence and the high frequency with which yeast can incorporate exogenous DNA into its genome. Unfortunately, laboratory strains do not perform well in industrial settings, indicating the need for strategies to modify industrial strains to enable strain development for industrial applications. Here we describe approaches we have used to genetically modify industrial strains used in winemaking.

Genetic Algorithm-Based Model Order Reduction of Aeroservoelastic Systems with Consistant States

Science.gov (United States)

Zhu, Jin; Wang, Yi; Pant, Kapil; Suh, Peter M.; Brenner, Martin J.

2017-01-01

This paper presents a model order reduction framework to construct linear parameter-varying reduced-order models of flexible aircraft for aeroservoelasticity analysis and control synthesis in broad two-dimensional flight parameter space. Genetic algorithms are used to automatically determine physical states for reduction and to generate reduced-order models at grid points within parameter space while minimizing the trial-and-error process. In addition, balanced truncation for unstable systems is used in conjunction with the congruence transformation technique to achieve locally optimal realization and weak fulfillment of state consistency across the entire parameter space. Therefore, aeroservoelasticity reduced-order models at any flight condition can be obtained simply through model interpolation. The methodology is applied to the pitch-plant model of the X-56A Multi-Use Technology Testbed currently being tested at NASA Armstrong Flight Research Center for flutter suppression and gust load alleviation. The present studies indicate that the reduced-order model with more than 12× reduction in the number of states relative to the original model is able to accurately predict system response among all input-output channels. The genetic-algorithm-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The interpolated aeroservoelasticity reduced order models exhibit smooth pole transition and continuously varying gains along a set of prescribed flight conditions, which verifies consistent state representation obtained by congruence transformation. The present model order reduction framework can be used by control engineers for robust aeroservoelasticity controller synthesis and novel vehicle design.

Selection of security system design via games of imperfect information and multi-objective genetic algorithm

International Nuclear Information System (INIS)

Lins, Isis Didier; Rêgo, Leandro Chaves; Moura, Márcio das Chagas

2013-01-01

This work analyzes the strategic interaction between a defender and an intelligent attacker by means of a game and reliability framework involving a multi-objective approach and imperfect information so as to support decision-makers in choosing efficiently designed security systems. A multi-objective genetic algorithm is used to determine the optimal security system's configurations representing the tradeoff between the probability of a successful defense and the acquisition and operational costs. Games with imperfect information are considered, in which the attacker has limited knowledge about the actual security system. The types of security alternatives are readily observable, but the number of redundancies actually implemented in each security subsystem is not known. The proposed methodology is applied to an illustrative example considering power transmission lines in the Northeast of Brazil, which are often targets for attackers who aims at selling the aluminum conductors. The empirical results show that the framework succeeds in handling this sort of strategic interaction. -- Highlights: ► Security components must have feasible costs and must be reliable. ► The optimal design of security systems considers a multi-objective approach. ► Games of imperfect information enable the choice of non-dominated configurations. ► MOGA, reliability and games support the entire defender's decision process. ► The selection of effective security systems may discourage attacker's actions

A non-genetic approach to labelling acute myeloid leukemia and bone marrow cells with quantum dots.

Science.gov (United States)

Zheng, Yanwen; Tan, Dongming; Chen, Zheng; Hu, Chenxi; Mao, Zhengwei J; Singleton, Timothy P; Zeng, Yan; Shao, Xuejun; Yin, Bin

2014-06-01

The difficulty in manipulation of leukemia cells has long hindered the dissection of leukemia pathogenesis. We have introduced a non-genetic approach of marking blood cells, using quantum dots. We compared quantum dots complexed with different vehicles, including a peptide Tat, cationic polymer Turbofect and liposome. Quantum dots-Tat showed the highest efficiency of marking hematopoietic cells among the three vehicles. Quantum dots-Tat could also label a panel of leukemia cell lines at varied efficiencies. More uniform intracellular distributions of quantum dots in mouse bone marrow and leukemia cells were obtained with quantum dots-Tat, compared with the granule-like formation obtained with quantum dots-liposome. Our results suggest that quantum dots have provided a photostable and non-genetic approach that labels normal and malignant hematopoietic cells, in a cell type-, vehicle-, and quantum dot concentration-dependent manner. We expect for potential applications of quantum dots as an easy and fast marking tool assisting investigations of various types of blood cells in the future.

A Neuro-genetic Based Short-term Forecasting Framework for Network Intrusion Prediction System

Institute of Scientific and Technical Information of China (English)

Siva S. Sivatha Sindhu; S. Geetha; M. Marikannan; A. Kannan

2009-01-01

Information systems are one of the most rapidly changing and vulnerable systems, where security is a major issue. The number of security-breaking attempts originating inside organizations is increasing steadily. Attacks made in this way, usually done by "authorized" users of the system, cannot be immediately traced. Because the idea of filtering the traffic at the entrance door, by using firewalls and the like, is not completely successful, the use of intrusion detection systems should be considered to increase the defense capacity of an information system. An intrusion detection system (IDS) is usually working in a dynamically changing environment, which forces continuous tuning of the intrusion detection model, in order to maintain sufficient performance. The manual tuning process required by current IDS depends on the system operators in working out the tuning solution and in integrating it into the detection model. Furthermore, an extensive effort is required to tackle the newly evolving attacks and a deep study is necessary to categorize it into the respective classes. To reduce this dependence, an automatically evolving anomaly IDS using neuro-genetic algorithm is presented. The proposed system automatically tunes the detection model on the fly according to the feedback provided by the system operator when false predictions are encountered. The system has been evaluated using the Knowledge Discovery in Databases Conference (KDD 2009) intrusion detection dataset. Genetic paradigm is employed to choose the predominant features, which reveal the occurrence of intrusions. The neuro-genetic IDS (NGIDS) involves calculation of weightage value for each of the categorical attributes so that data of uniform representation can be processed by the neuro-genetic algorithm. In this system unauthorized invasion of a user are identified and newer types of attacks are sensed and classified respectively by the neuro-genetic algorithm. The experimental results obtained in this

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

Global structural optimizations of surface systems with a genetic algorithm

International Nuclear Information System (INIS)

Chuang, Feng-Chuan

2005-01-01

Global structural optimizations with a genetic algorithm were performed for atomic cluster and surface systems including aluminum atomic clusters, Si magic clusters on the Si(111) 7 x 7 surface, silicon high-index surfaces, and Ag-induced Si(111) reconstructions. First, the global structural optimizations of neutral aluminum clusters Al n (n up to 23) were performed using a genetic algorithm coupled with a tight-binding potential. Second, a genetic algorithm in combination with tight-binding and first-principles calculations were performed to study the structures of magic clusters on the Si(111) 7 x 7 surface. Extensive calculations show that the magic cluster observed in scanning tunneling microscopy (STM) experiments consist of eight Si atoms. Simulated STM images of the Si magic cluster exhibit a ring-like feature similar to STM experiments. Third, a genetic algorithm coupled with a highly optimized empirical potential were used to determine the lowest energy structure of high-index semiconductor surfaces. The lowest energy structures of Si(105) and Si(114) were determined successfully. The results of Si(105) and Si(114) are reported within the framework of highly optimized empirical potential and first-principles calculations. Finally, a genetic algorithm coupled with Si and Ag tight-binding potentials were used to search for Ag-induced Si(111) reconstructions at various Ag and Si coverages. The optimized structural models of √3 x √3, 3 x 1, and 5 x 2 phases were reported using first-principles calculations. A novel model is found to have lower surface energy than the proposed double-honeycomb chained (DHC) model both for Au/Si(111) 5 x 2 and Ag/Si(111) 5 x 2 systems

Setaria viridis as a model system to advance millet genetics and genomics

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Pu Huang

2016-11-01

Full Text Available Millet is a common name for a group of polyphyletic, small-seeded cereal crops that include pearl, finger and foxtail millet. Millet species are an important source of calories for many societies, often in developing countries. Compared to major cereal crops such as rice and maize, millets are generally better adapted to dry and hot environments. Despite their food security value, the genetic architecture of agronomically important traits in millets, including both morphological traits and climate resilience remains poorly studied. These complex traits have been challenging to dissect in large part because of the lack of sufficient genetic tools and resources. In this article, we review the phylogenetic relationship among various millet species and discuss the value of a genetic model system for millet research. We propose that a broader adoption of green foxtail (Setaria viridis as a model system for millets could greatly accelerate the pace of gene discovery in the millets, and summarize available and emerging resources in S. viridis and its domesticated relative S. italica. These resources have value in forward genetics, reverse genetics and high throughput phenotyping. We describe methods and strategies to best utilize these resources to facilitate the genetic dissection of complex traits. We envision that coupling cutting-edge technologies and the use of S. viridis for gene discovery will accelerate genetic research in millets in general. This will enable strategies and provide opportunities to increase productivity, especially in the semi-arid tropics of Asia and Africa where millets are staple food crop.

Setaria viridis as a Model System to Advance Millet Genetics and Genomics.

Science.gov (United States)

Huang, Pu; Shyu, Christine; Coelho, Carla P; Cao, Yingying; Brutnell, Thomas P

2016-01-01

Millet is a common name for a group of polyphyletic, small-seeded cereal crops that include pearl, finger and foxtail millet. Millet species are an important source of calories for many societies, often in developing countries. Compared to major cereal crops such as rice and maize, millets are generally better adapted to dry and hot environments. Despite their food security value, the genetic architecture of agronomically important traits in millets, including both morphological traits and climate resilience remains poorly studied. These complex traits have been challenging to dissect in large part because of the lack of sufficient genetic tools and resources. In this article, we review the phylogenetic relationship among various millet species and discuss the value of a genetic model system for millet research. We propose that a broader adoption of green foxtail ( Setaria viridis ) as a model system for millets could greatly accelerate the pace of gene discovery in the millets, and summarize available and emerging resources in S. viridis and its domesticated relative S. italica . These resources have value in forward genetics, reverse genetics and high throughput phenotyping. We describe methods and strategies to best utilize these resources to facilitate the genetic dissection of complex traits. We envision that coupling cutting-edge technologies and the use of S. viridis for gene discovery will accelerate genetic research in millets in general. This will enable strategies and provide opportunities to increase productivity, especially in the semi-arid tropics of Asia and Africa where millets are staple food crops.

Setaria viridis as a Model System to Advance Millet Genetics and Genomics

Science.gov (United States)

Huang, Pu; Shyu, Christine; Coelho, Carla P.; Cao, Yingying; Brutnell, Thomas P.

2016-01-01

Millet is a common name for a group of polyphyletic, small-seeded cereal crops that include pearl, finger and foxtail millet. Millet species are an important source of calories for many societies, often in developing countries. Compared to major cereal crops such as rice and maize, millets are generally better adapted to dry and hot environments. Despite their food security value, the genetic architecture of agronomically important traits in millets, including both morphological traits and climate resilience remains poorly studied. These complex traits have been challenging to dissect in large part because of the lack of sufficient genetic tools and resources. In this article, we review the phylogenetic relationship among various millet species and discuss the value of a genetic model system for millet research. We propose that a broader adoption of green foxtail (Setaria viridis) as a model system for millets could greatly accelerate the pace of gene discovery in the millets, and summarize available and emerging resources in S. viridis and its domesticated relative S. italica. These resources have value in forward genetics, reverse genetics and high throughput phenotyping. We describe methods and strategies to best utilize these resources to facilitate the genetic dissection of complex traits. We envision that coupling cutting-edge technologies and the use of S. viridis for gene discovery will accelerate genetic research in millets in general. This will enable strategies and provide opportunities to increase productivity, especially in the semi-arid tropics of Asia and Africa where millets are staple food crops. PMID:27965689

Modeling solar radiation of Mediterranean region in Turkey by using fuzzy genetic approach

International Nuclear Information System (INIS)

Kisi, Ozgur

2014-01-01

The study investigates the ability of FG (fuzzy genetic) approach in modeling solar radiation of seven cities from Mediterranean region of Anatolia, Turkey. Latitude, longitude, altitude and month of the year data from the Adana, K. Maras, Mersin, Antalya, Isparta, Burdur and Antakya cities are used as inputs to the FG model to estimate one month ahead solar radiation. FG model is compared with ANNs (artificial neural networks) and ANFIS (adaptive neruro fuzzzy inference system) models with respect to RMSE (root mean square errors), MAE (mean absolute errors) and determination coefficient (R 2 ) statistics. Comparison results indicate that the FG model performs better than the ANN and ANFIS models. It is found that the FG model can be successfully used for estimating solar radiation by using latitude, longitude, altitude and month of the year information. FG model with RMSE = 6.29 MJ/m 2 , MAE = 4.69 MJ/m 2 and R 2 = 0.905 in the test stage was found to be superior to the optimal ANN model with RMSE = 7.17 MJ/m 2 , MAE = 5.29 MJ/m 2 and R 2 = 0.876 and ANFIS model with RMSE = 6.75 MJ/m 2 , MAE = 5.10 MJ/m 2 and R 2 = 0.892 in estimating solar radiation. - Highlights: • SR (Solar radiation) of seven cities from Mediterranean region of Turkey is predicted. • FG (Fuzzy genetic) models are developed for accurately estimation of SR. • The ability of the FG models used in the study is found to be satisfactory. • FG models are compared with commonly used ANNs (artificial neural networks). • FG models are found to perform better than the ANNs models

A New Spectral Shape-Based Record Selection Approach Using Np and Genetic Algorithms

Directory of Open Access Journals (Sweden)

Edén Bojórquez

2013-01-01

Full Text Available With the aim to improve code-based real records selection criteria, an approach inspired in a parameter proxy of spectral shape, named Np, is analyzed. The procedure is based on several objectives aimed to minimize the record-to-record variability of the ground motions selected for seismic structural assessment. In order to select the best ground motion set of records to be used as an input for nonlinear dynamic analysis, an optimization approach is applied using genetic algorithms focuse on finding the set of records more compatible with a target spectrum and target Np values. The results of the new Np-based approach suggest that the real accelerograms obtained with this procedure, reduce the scatter of the response spectra as compared with the traditional approach; furthermore, the mean spectrum of the set of records is very similar to the target seismic design spectrum in the range of interest periods, and at the same time, similar Np values are obtained for the selected records and the target spectrum.

Multi-objective optimization of an underwater compressed air energy storage system using genetic algorithm

International Nuclear Information System (INIS)

Cheung, Brian C.; Carriveau, Rupp; Ting, David S.K.

2014-01-01

This paper presents the findings from a multi-objective genetic algorithm optimization study on the design parameters of an underwater compressed air energy storage system (UWCAES). A 4 MWh UWCAES system was numerically simulated and its energy, exergy, and exergoeconomics were analysed. Optimal system configurations were determined that maximized the UWCAES system round-trip efficiency and operating profit, and minimized the cost rate of exergy destruction and capital expenditures. The optimal solutions obtained from the multi-objective optimization model formed a Pareto-optimal front, and a single preferred solution was selected using the pseudo-weight vector multi-criteria decision making approach. A sensitivity analysis was performed on interest rates to gauge its impact on preferred system designs. Results showed similar preferred system designs for all interest rates in the studied range. The round-trip efficiency and operating profit of the preferred system designs were approximately 68.5% and $53.5/cycle, respectively. The cost rate of the system increased with interest rates. - Highlights: • UWCAES system configurations were developed using multi-objective optimization. • System was optimized for energy efficiency, exergy, and exergoeconomics • Pareto-optimal solution surfaces were developed at different interest rates. • Similar preferred system configurations were found at all interest rates studied

Usher syndrome: an effective sequencing approach to establish a genetic and clinical diagnosis.

Science.gov (United States)

Lenarduzzi, S; Vozzi, D; Morgan, A; Rubinato, E; D'Eustacchio, A; Osland, T M; Rossi, C; Graziano, C; Castorina, P; Ambrosetti, U; Morgutti, M; Girotto, G

2015-02-01

Usher syndrome is an autosomal recessive disorder characterized by retinitis pigmentosa, sensorineural hearing loss and, in some cases, vestibular dysfunction. The disorder is clinically and genetically heterogeneous and, to date, mutations in 11 genes have been described. This finding makes difficult to get a precise molecular diagnosis and offer patients accurate genetic counselling. To overcome this problem and to increase our knowledge of the molecular basis of Usher syndrome, we designed a targeted resequencing custom panel. In a first validation step a series of 16 Italian patients with known molecular diagnosis were analysed and 31 out of 32 alleles were detected (97% of accuracy). After this step, 31 patients without a molecular diagnosis were enrolled in the study. Three out of them with an uncertain Usher diagnosis were excluded. One causative allele was detected in 24 out 28 patients (86%) while the presence of both causative alleles characterized 19 patients out 28 (68%). Sixteen novel and 27 known alleles were found in the following genes: USH2A (50%), MYO7A (7%), CDH23 (11%), PCDH15 (7%) and USH1G (2%). Overall, on the 44 patients the protocol was able to characterize 74 alleles out of 88 (84%). These results suggest that our panel is an effective approach for the genetic diagnosis of Usher syndrome leading to: 1) an accurate molecular diagnosis, 2) better genetic counselling, 3) more precise molecular epidemiology data fundamental for future interventional plans. Copyright © 2014 Elsevier B.V. All rights reserved.

Application of medical cases in general genetics teaching in universities.

Science.gov (United States)

He, Zhumei; Bie, Linsai; Li, Wei

2018-01-20

General genetics is a core course in life sciences, medicine, agriculture and other related fields. As one of the most fast-developing disciplines of life sciences in the 21th century, the influence of the genetics knowledge on daily life is expanding, especially on human health and reproduction. In order to make it easier for students to understand the profound principles of genetics and to better apply the theories to daily life, we have introduced appropriate medical cases in general genetics teaching and further extended them combined with theoretical basis of genetics. This approach will be beneficial to enhance students' abilities of genetic analysis and promote their enthusiasm to learn and master practical skills. In this paper, we enumerate medical cases related to the modern genetics teaching system to provide a reference for genetics teaching in general and normal universities.

Inferring genetic interactions from comparative fitness data.

Science.gov (United States)

Crona, Kristina; Gavryushkin, Alex; Greene, Devin; Beerenwinkel, Niko

2017-12-20

Darwinian fitness is a central concept in evolutionary biology. In practice, however, it is hardly possible to measure fitness for all genotypes in a natural population. Here, we present quantitative tools to make inferences about epistatic gene interactions when the fitness landscape is only incompletely determined due to imprecise measurements or missing observations. We demonstrate that genetic interactions can often be inferred from fitness rank orders, where all genotypes are ordered according to fitness, and even from partial fitness orders. We provide a complete characterization of rank orders that imply higher order epistasis. Our theory applies to all common types of gene interactions and facilitates comprehensive investigations of diverse genetic interactions. We analyzed various genetic systems comprising HIV-1, the malaria-causing parasite Plasmodium vivax , the fungus Aspergillus niger , and the TEM-family of β-lactamase associated with antibiotic resistance. For all systems, our approach revealed higher order interactions among mutations.

Unmanned Maritime Systems Incremental Acquisition Approach

Science.gov (United States)

2016-12-01

REPORT TYPE AND DATES COVERED MBA professional report 4. TITLE AND SUBTITLE UNMANNED MARITIME SYSTEMS INCREMENTAL ACQUISITION APPROACH 5. FUNDING...Approved for public release. Distribution is unlimited. UNMANNED MARITIME SYSTEMS INCREMENTAL ACQUISITION APPROACH Thomas Driscoll, Lieutenant...UNMANNED MARITIME SYSTEMS INCREMENTAL ACQUISITION APPROACH ABSTRACT The purpose of this MBA report is to explore and understand the issues

Genetic architecture of the Delis-Kaplan Executive Function System Trail Making Test: evidence for distinct genetic influences on executive function.

Science.gov (United States)

Vasilopoulos, Terrie; Franz, Carol E; Panizzon, Matthew S; Xian, Hong; Grant, Michael D; Lyons, Michael J; Toomey, Rosemary; Jacobson, Kristen C; Kremen, William S

2012-03-01

To examine how genes and environments contribute to relationships among Trail Making Test (TMT) conditions and the extent to which these conditions have unique genetic and environmental influences. Participants included 1,237 middle-aged male twins from the Vietnam Era Twin Study of Aging. The Delis-Kaplan Executive Function System TMT included visual searching, number and letter sequencing, and set-shifting components. Phenotypic correlations among TMT conditions ranged from 0.29 to 0.60, and genes accounted for the majority (58-84%) of each correlation. Overall heritability ranged from 0.34 to 0.62 across conditions. Phenotypic factor analysis suggested a single factor. In contrast, genetic models revealed a single common genetic factor but also unique genetic influences separate from the common factor. Genetic variance (i.e., heritability) of number and letter sequencing was completely explained by the common genetic factor while unique genetic influences separate from the common factor accounted for 57% and 21% of the heritabilities of visual search and set shifting, respectively. After accounting for general cognitive ability, unique genetic influences accounted for 64% and 31% of those heritabilities. A common genetic factor, most likely representing a combination of speed and sequencing, accounted for most of the correlation among TMT 1-4. Distinct genetic factors, however, accounted for a portion of variance in visual scanning and set shifting. Thus, although traditional phenotypic shared variance analysis techniques suggest only one general factor underlying different neuropsychological functions in nonpatient populations, examining the genetic underpinnings of cognitive processes with twin analysis can uncover more complex etiological processes.

Timing of gene expression from different genetic systems in shaping ...

Indian Academy of Sciences (India)

2011-12-16

Dec 16, 2011 ... different genetic systems, nutrition quality traits were mainly controlled by the accumulative or net ... pable of providing valuable information on the expression of ...... protein, carbohydrates, and dietary fiber components.

Genetic algorithms optimized fuzzy logic control for the maximum power point tracking in photovoltaic system

Energy Technology Data Exchange (ETDEWEB)

Larbes, C.; Ait Cheikh, S.M.; Obeidi, T.; Zerguerras, A. [Laboratoire des Dispositifs de Communication et de Conversion Photovoltaique, Departement d' Electronique, Ecole Nationale Polytechnique, 10, Avenue Hassen Badi, El Harrach, Alger 16200 (Algeria)

2009-10-15

This paper presents an intelligent control method for the maximum power point tracking (MPPT) of a photovoltaic system under variable temperature and irradiance conditions. First, for the purpose of comparison and because of its proven and good performances, the perturbation and observation (P and O) technique is briefly introduced. A fuzzy logic controller based MPPT (FLC) is then proposed which has shown better performances compared to the P and O MPPT based approach. The proposed FLC has been also improved using genetic algorithms (GA) for optimisation. Different development stages are presented and the optimized fuzzy logic MPPT controller (OFLC) is then simulated and evaluated, which has shown better performances. (author)

Isolation and genetic analysis of pure cells from forensic biological mixtures: The precision of a digital approach.

Science.gov (United States)

Fontana, F; Rapone, C; Bregola, G; Aversa, R; de Meo, A; Signorini, G; Sergio, M; Ferrarini, A; Lanzellotto, R; Medoro, G; Giorgini, G; Manaresi, N; Berti, A

2017-07-01

Latest genotyping technologies allow to achieve a reliable genetic profile for the offender identification even from extremely minute biological evidence. The ultimate challenge occurs when genetic profiles need to be retrieved from a mixture, which is composed of biological material from two or more individuals. In this case, DNA profiling will often result in a complex genetic profile, which is then subject matter for statistical analysis. In principle, when more individuals contribute to a mixture with different biological fluids, their single genetic profiles can be obtained by separating the distinct cell types (e.g. epithelial cells, blood cells, sperm), prior to genotyping. Different approaches have been investigated for this purpose, such as fluorescent-activated cell sorting (FACS) or laser capture microdissection (LCM), but currently none of these methods can guarantee the complete separation of different type of cells present in a mixture. In other fields of application, such as oncology, DEPArray™ technology, an image-based, microfluidic digital sorter, has been widely proven to enable the separation of pure cells, with single-cell precision. This study investigates the applicability of DEPArray™ technology to forensic samples analysis, focusing on the resolution of the forensic mixture problem. For the first time, we report here the development of an application-specific DEPArray™ workflow enabling the detection and recovery of pure homogeneous cell pools from simulated blood/saliva and semen/saliva mixtures, providing full genetic match with genetic profiles of corresponding donors. In addition, we assess the performance of standard forensic methods for DNA quantitation and genotyping on low-count, DEPArray™-isolated cells, showing that pure, almost complete profiles can be obtained from as few as ten haploid cells. Finally, we explore the applicability in real casework samples, demonstrating that the described approach provides complete

A clinical approach to the diagnosis of patients with leukodystrophies and genetic leukoencephelopathies

NARCIS (Netherlands)

Parikh, Sumit; Bernard, Geneviève; Leventer, Richard J.; van der Knaap, Marjo S.; van Hove, Johan; Pizzino, Amy; McNeill, Nathan H.; Helman, Guy; Simons, Cas; Schmidt, Johanna L.; Rizzo, William B.; Patterson, Marc C.; Taft, Ryan J.; Vanderver, Adeline

2015-01-01

Leukodystrophies (LD) and genetic leukoencephalopathies (gLE) are disorders that result in white matter abnormalities in the central nervous system (CNS). Magnetic resonance (MR) imaging (MRI) has dramatically improved and systematized the diagnosis of LDs and gLEs, and in combination with specific

An efficient Bayesian meta-analysis approach for studying cross-phenotype genetic associations.

Directory of Open Access Journals (Sweden)

Arunabha Majumdar

2018-02-01

Full Text Available Simultaneous analysis of genetic associations with multiple phenotypes may reveal shared genetic susceptibility across traits (pleiotropy. For a locus exhibiting overall pleiotropy, it is important to identify which specific traits underlie this association. We propose a Bayesian meta-analysis approach (termed CPBayes that uses summary-level data across multiple phenotypes to simultaneously measure the evidence of aggregate-level pleiotropic association and estimate an optimal subset of traits associated with the risk locus. This method uses a unified Bayesian statistical framework based on a spike and slab prior. CPBayes performs a fully Bayesian analysis by employing the Markov Chain Monte Carlo (MCMC technique Gibbs sampling. It takes into account heterogeneity in the size and direction of the genetic effects across traits. It can be applied to both cohort data and separate studies of multiple traits having overlapping or non-overlapping subjects. Simulations show that CPBayes can produce higher accuracy in the selection of associated traits underlying a pleiotropic signal than the subset-based meta-analysis ASSET. We used CPBayes to undertake a genome-wide pleiotropic association study of 22 traits in the large Kaiser GERA cohort and detected six independent pleiotropic loci associated with at least two phenotypes. This includes a locus at chromosomal region 1q24.2 which exhibits an association simultaneously with the risk of five different diseases: Dermatophytosis, Hemorrhoids, Iron Deficiency, Osteoporosis and Peripheral Vascular Disease. We provide an R-package 'CPBayes' implementing the proposed method.

Going forward with genetics: recent technological advances and forward genetics in mice.

Science.gov (United States)

Moresco, Eva Marie Y; Li, Xiaohong; Beutler, Bruce

2013-05-01

Forward genetic analysis is an unbiased approach for identifying genes essential to defined biological phenomena. When applied to mice, it is one of the most powerful methods to facilitate understanding of the genetic basis of human biology and disease. The speed at which disease-causing mutations can be identified in mutagenized mice has been markedly increased by recent advances in DNA sequencing technology. Creating and analyzing mutant phenotypes may therefore become rate-limiting in forward genetic experimentation. We review the forward genetic approach and its future in the context of recent technological advances, in particular massively parallel DNA sequencing, induced pluripotent stem cells, and haploid embryonic stem cells. Copyright © 2013 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Supply of genetic information--amount, format, and frequency.

Science.gov (United States)

Misztal, I; Lawlor, T J

1999-05-01

The volume and complexity of genetic information is increasing because of new traits and better models. New traits may include reproduction, health, and carcass. More comprehensive models include the test day model in dairy cattle or a growth model in beef cattle. More complex models, which may include nonadditive effects such as inbreeding and dominance, also provide additional information. The amount of information per animal may increase drastically if DNA marker typing becomes routine and quantitative trait loci information is utilized. In many industries, evaluations are run more frequently. They result in faster genetic progress and improved management and marketing opportunities but also in extra costs and information overload. Adopting new technology and making some organizational changes can help realize all the added benefits of the improvements to the genetic evaluation systems at an acceptable cost. Continuous genetic evaluation, in which new records are accepted and breeding values are updated continuously, will relieve time pressures. An online mating system with access to both genetic and marketing information can result in mating recommendations customized for each user. Such a system could utilize inbreeding and dominance information that cannot efficiently be accommodated in the current sire summaries or off-line mating programs. The new systems will require a new organizational approach in which the task of scientists and technicians will not be simply running the evaluations but also providing the research, design, supervision, and maintenance required in the entire system of evaluation, decision making, and distribution.

Hereditary breast and ovarian cancer: successful systematic implementation of a group approach to genetic counselling.

Science.gov (United States)

Benusiglio, Patrick R; Di Maria, Marina; Dorling, Leila; Jouinot, Anne; Poli, Antoine; Villebasse, Sophie; Le Mentec, Marine; Claret, Béatrice; Boinon, Diane; Caron, Olivier

2017-01-01

The increase in referrals to cancer genetics clinics, partially associated with the "Angelina Jolie effect", presents a challenge to existing services, many are already running at full capacity. More efficient ways to deliver genetic counselling are therefore urgently needed. We now systematically offer group instead of standard individual counselling to patients with suspected Hereditary Breast and Ovarian Cancer. Group sessions last 30 min. The first twenty consist of a presentation by the genetic counsellor, the next ten of a discussion involving a cancer geneticist and a psychologist. A short individual consultation ensues, where personal and family issues are addressed and consent obtained. Blood is drawn afterwards. Satisfaction and knowledge are evaluated. We report data for the Oct-2014-Aug-2015 period. 210 patients attended group counselling, up to eight simultaneously. We always fitted them within a 4-h time frame. Mean satisfaction score was 41/43. Knowledge scores increased from 3.1/6 to 4.9/6 post-counselling (p value group counselling, we have withstood increases in referrals without compromising care. The "Angelina Jolie effect" and rapid developments in personalized medicine threaten to overwhelm cancer genetics clinics. In this context, our innovative approach should ensure that all patients have access to approved services.

Genetic Evaluation of Children with Global Developmental Delay—Current Status of Network Systems in Taiwan

Directory of Open Access Journals (Sweden)

Yong-Lin Foo

2015-08-01

Full Text Available This review article aims to introduce the screening and referral network of genetic evaluation for children with developmental delay in Taiwan. For these children, integrated systems provide services from the medical, educational, and social welfare sectors. All cities and counties in Taiwan have established a network for screening, detection, referral, evaluation, and intervention services. Increased awareness improves early detection and intervention. There remains a gap between supply and demand, especially with regard to financial resources and professional manpower. Genetic etiology has a major role in prenatal causes of developmental delay. A summary of reports on some related genetic disorders in the Taiwanese population is included in this review. Genetic diagnosis allows counseling with regard to recurrence risk and prevention. Networking with neonatal screening, laboratory diagnosis, genetic counseling, and orphan drugs logistics systems can provide effective treatment for patients. In Taiwan, several laboratories provide genetic tests for clinical diagnosis. Accessibility to advanced expensive tests such as gene chips or whole exome sequencing is limited because of funding problems; however, the service system in Taiwan can still operate in a relatively cost-effective manner. This experience in Taiwan may serve as a reference for other countries.

Genetic bases of the nutritional approach to migraine.

Science.gov (United States)

De Marchis, Maria Laura; Guadagni, Fiorella; Silvestris, Erica; Lovero, Domenica; Della-Morte, David; Ferroni, Patrizia; Barbanti, Piero; Palmirotta, Raffaele

2018-03-08

Migraine is a common multifactorial and polygenic neurological disabling disorder characterized by a genetic background and associated to environmental, hormonal and food stimulations. A large series of evidence suggest a strong correlation between nutrition and migraine and indicates several commonly foods, food additives and beverages that may be involved in the mechanisms triggering the headache attack in migraine-susceptible persons. There are foods and drinks, or ingredients of the same, that can trigger the migraine crisis as well as some foods play a protective function depending on the specific genetic sensitivity of the subject. The recent biotechnological advances have enhanced the identification of some genetic factors involved in onset diseases and the identification of sequence variants of genes responsible for the individual sensitivity to migraine trigger-foods. Therefore many studies are aimed at the analysis of polymorphisms of genes coding for the enzymes involved in the metabolism of food factors in order to clarify the different ways in which people respond to foods based on their genetic constitution. This review discusses the latest knowledge and scientific evidence of the role of gene variants and nutrients, food additives and nutraceuticals interactions in migraine.

Bounding approaches to system identification

CERN Document Server

Norton, John; Piet-Lahanier, Hélène; Walter, Éric

1996-01-01

In response to the growing interest in bounding error approaches, the editors of this volume offer the first collection of papers to describe advances in techniques and applications of bounding of the parameters, or state variables, of uncertain dynamical systems. Contributors explore the application of the bounding approach as an alternative to the probabilistic analysis of such systems, relating its importance to robust control-system design.

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.

Phenotype prediction using regularized regression on genetic data in the DREAM5 Systems Genetics B Challenge.

Directory of Open Access Journals (Sweden)

Po-Ru Loh

Full Text Available A major goal of large-scale genomics projects is to enable the use of data from high-throughput experimental methods to predict complex phenotypes such as disease susceptibility. The DREAM5 Systems Genetics B Challenge solicited algorithms to predict soybean plant resistance to the pathogen Phytophthora sojae from training sets including phenotype, genotype, and gene expression data. The challenge test set was divided into three subcategories, one requiring prediction based on only genotype data, another on only gene expression data, and the third on both genotype and gene expression data. Here we present our approach, primarily using regularized regression, which received the best-performer award for subchallenge B2 (gene expression only. We found that despite the availability of 941 genotype markers and 28,395 gene expression features, optimal models determined by cross-validation experiments typically used fewer than ten predictors, underscoring the importance of strong regularization in noisy datasets with far more features than samples. We also present substantial analysis of the training and test setup of the challenge, identifying high variance in performance on the gold standard test sets.

Subthreshold pharmacological and genetic approaches to analyzing CaV2.1-mediated NMDA receptor signaling in short-term memory.

Science.gov (United States)

Takahashi, Eiki; Niimi, Kimie; Itakura, Chitoshi

2010-10-25

Ca(V)2.1 is highly expressed in the nervous system and plays an essential role in the presynaptic modulation of neurotransmitter release machinery. Recently, the antiepileptic drug levetiracetam was reported to inhibit presynaptic Ca(V)2.1 functions, reducing glutamate release in the hippocampus, although the precise physiological role of Ca(V)2.1-regulated synaptic functions in cognitive performance at the system level remains unknown. This study examined whether Ca(V)2.1 mediates hippocampus-dependent spatial short-term memory using the object location and Y-maze tests, and perirhinal cortex-dependent nonspatial short-term memory using the object recognition test, via a combined pharmacological and genetic approach. Heterozygous rolling Nagoya (rol/+) mice carrying the Ca(V)2.1alpha(1) mutation had normal spatial and nonspatial short-term memory. A 100mg/kg dose of levetiracetam, which is ineffective in wild-type controls, blocked spatial short-term memory in rol/+ mice. At 5mg/kg, the N-methyl-D-aspartate (NMDA) receptor blocker (+/-)-3-(2-carboxypiperazin-4-yl)-propyl-1-phosphonic acid (CPP), which is ineffective in wild-type controls, also blocked the spatial short-term memory in rol/+ mice. Furthermore, a combination of subthreshold doses of levetiracetam (25 mg/kg) and CPP (2.5mg/kg) triggered a spatial short-term memory deficit in rol/+ mice, but not in wild-type controls. Similar patterns of nonspatial short-term memory were observed in wild-type and rol/+ mice when injected with levetiracetam (0-300 mg/kg). These results indicate that Ca(V)2.1-mediated NMDA receptor signaling is critical in hippocampus-dependent spatial short-term memory and differs in various regions. The combination subthreshold pharmacological and genetic approach presented here is easily performed and can be used to study functional signaling pathways in neuronal circuits. Copyright © 2010 Elsevier B.V. All rights reserved.

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 ...

Periodontal disease associated to systemic genetic disorders.

Science.gov (United States)

Nualart Grollmus, Zacy Carola; Morales Chávez, Mariana Carolina; Silvestre Donat, Francisco Javier

2007-05-01

A number of systemic disorders increase patient susceptibility to periodontal disease, which moreover evolves more rapidly and more aggressively. The underlying factors are mainly related to alterations in immune, endocrine and connective tissue status. These alterations are associated with different pathologies and syndromes that generate periodontal disease either as a primary manifestation or by aggravating a pre-existing condition attributable to local factors. This is where the role of bacterial plaque is subject to debate. In the presence of qualitative or quantitative cellular immune alterations, periodontal disease may manifest early on a severe localized or generalized basis--in some cases related to the presence of plaque and/or specific bacteria (severe congenital neutropenia or infantile genetic agranulocytosis, Chediak-Higiashi syndrome, Down syndrome and Papillon-Lefévre syndrome). In the presence of humoral immune alterations, periodontal damage may result indirectly as a consequence of alterations in other systems. In connective tissue disorders, bacterial plaque and alterations of the periodontal tissues increase patient susceptibility to gingival inflammation and alveolar resorption (Marfan syndrome and Ehler-Danlos syndrome). The management of periodontal disease focuses on the control of infection and bacterial plaque by means of mechanical and chemical methods. Periodontal surgery and even extraction of the most seriously affected teeth have also been suggested. There are variable degrees of consensus regarding the background systemic disorder, as in the case of Chediak-Higiashi syndrome, where antibiotic treatment proves ineffective; in severe congenital neutropenia or infantile genetic agranulocytosis, where antibiotic prophylaxis is suggested; and in Papillon-Lefévre syndrome, where an established treatment protocol is available.

Efficient Feedforward Linearization Technique Using Genetic Algorithms for OFDM Systems

Directory of Open Access Journals (Sweden)

García Paloma

2010-01-01

Full Text Available Feedforward is a linearization method that simultaneously offers wide bandwidth and good intermodulation distortion suppression; so it is a good choice for Orthogonal Frequency Division Multiplexing (OFDM systems. Feedforward structure consists of two loops, being necessary an accurate adjustment between them along the time, and when temperature, environmental, or operating changes are produced. Amplitude and phase imbalances of the circuit elements in both loops produce mismatched effects that lead to degrade its performance. A method is proposed to compensate these mismatches, introducing two complex coefficients calculated by means of a genetic algorithm. A full study is carried out to choose the optimal parameters of the genetic algorithm applied to wideband systems based on OFDM technologies, which are very sensitive to nonlinear distortions. The method functionality has been verified by means of simulation.

Latent spatial models and sampling design for landscape genetics

Science.gov (United States)

Hanks, Ephraim M.; Hooten, Mevin B.; Knick, Steven T.; Oyler-McCance, Sara J.; Fike, Jennifer A.; Cross, Todd B.; Schwartz, Michael K.

2016-01-01

We propose a spatially-explicit approach for modeling genetic variation across space and illustrate how this approach can be used to optimize spatial prediction and sampling design for landscape genetic data. We propose a multinomial data model for categorical microsatellite allele data commonly used in landscape genetic studies, and introduce a latent spatial random effect to allow for spatial correlation between genetic observations. We illustrate how modern dimension reduction approaches to spatial statistics can allow for efficient computation in landscape genetic statistical models covering large spatial domains. We apply our approach to propose a retrospective spatial sampling design for greater sage-grouse (Centrocercus urophasianus) population genetics in the western United States.

An analysis of the genetic diversity and genetic structure of ...

African Journals Online (AJOL)

Scientific approaches to conservation of threatened species depend on a good understanding of the genetic information of wild and artificial population. The genetic diversity and structure analysis of 10 Eucommia ulmoides population was analyzed using inter-simple sequence repeat (ISSR) markers in this paper.

Plant traits correlated with generation time directly affect inbreeding depression and mating system and indirectly genetic structure

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Hardy Olivier J

2009-07-01

Full Text Available Abstract Background Understanding the mechanisms that control species genetic structure has always been a major objective in evolutionary studies. The association between genetic structure and species attributes has received special attention. As species attributes are highly taxonomically constrained, phylogenetically controlled methods are necessary to infer causal relationships. In plants, a previous study controlling for phylogenetic signal has demonstrated that Wright's FST, a measure of genetic differentiation among populations, is best predicted by the mating system (outcrossing, mixed-mating or selfing and that plant traits such as perenniality and growth form have only an indirect influence on FST via their association with the mating system. The objective of this study is to further outline the determinants of plant genetic structure by distinguishing the effects of mating system on gene flow and on genetic drift. The association of biparental inbreeding and inbreeding depression with population genetic structure, mating system and plant traits are also investigated. Results Based on data from 263 plant species for which estimates of FST, inbreeding (FIS and outcrossing rate (tm are available, we confirm that mating system is the main influencing factor of FST. Moreover, using an alternative measure of FST unaffected by the impact of inbreeding on effective population size, we show that the influence of tm on FST is due to its impact on gene flow (reduced pollen flow under selfing and on genetic drift (higher drift under selfing due to inbreeding. Plant traits, in particular perenniality, influence FST mostly via their effect on the mating system but also via their association with the magnitude of selection against inbred individuals: the mean inbreeding depression increases from short-lived herbaceous to long-lived herbaceous and then to woody species. The influence of perenniality on mating system does not seem to be related to

Type VI secretion systems of human gut Bacteroidales segregate into three genetic architectures, two of which are contained on mobile genetic elements.

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Coyne, Michael J; Roelofs, Kevin G; Comstock, Laurie E

2016-01-15

Type VI secretion systems (T6SSs) are contact-dependent antagonistic systems employed by Gram negative bacteria to intoxicate other bacteria or eukaryotic cells. T6SSs were recently discovered in a few Bacteroidetes strains, thereby extending the presence of these systems beyond Proteobacteria. The present study was designed to analyze in a global nature the diversity, abundance, and properties of T6SSs in the Bacteroidales, the most predominant Gram negative bacterial order of the human gut. By performing extensive bioinformatics analyses and creating hidden Markov models for Bacteroidales Tss proteins, we identified 130 T6SS loci in 205 human gut Bacteroidales genomes. Of the 13 core T6SS proteins of Proteobacteria, human gut Bacteroidales T6SS loci encode orthologs of nine, and an additional five other core proteins not present in Proteobacterial T6SSs. The Bacteroidales T6SS loci segregate into three distinct genetic architectures with extensive DNA identity between loci of a given genetic architecture. We found that divergent DNA regions of a genetic architecture encode numerous types of effector and immunity proteins and likely include new classes of these proteins. TheT6SS loci of genetic architecture 1 are contained on highly similar integrative conjugative elements (ICEs), as are the T6SS loci of genetic architecture 2, whereas the T6SS loci of genetic architecture 3 are not and are confined to Bacteroides fragilis. Using collections of co-resident Bacteroidales strains from human subjects, we provide evidence for the transfer of genetic architecture 1 T6SS loci among co-resident Bacteroidales species in the human gut. However, we also found that established ecosystems can harbor strains with distinct T6SS of all genetic architectures. This is the first study to comprehensively analyze of the presence and diversity of T6SS loci within an order of bacteria and to analyze T6SSs of bacteria from a natural community. These studies demonstrate that more than

PAX6 aniridia syndrome: clinics, genetics, and therapeutics.

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Lim, Hyun Taek; Kim, Dae Hee; Kim, Hyuna

2017-09-01

Aniridia is a rare and panocular disorder affecting most of the ocular structures which may have significant impact on vision. The purpose of this review is to describe the clinical features, genetics, and therapeutic options for this disease and to provide an update of current knowledge and latest research findings. Aside from the ocular features, a variety of associated systemic abnormalities, including hormonal, metabolic, gastrointestinal, genitourinary, and neurologic pathologies have been reported in children with aniridia. Although mutations in PAX6 are a major cause of aniridia, genetic defects in nearby genes, such as TRIM44 or ELP4, have also been reported to cause aniridia. Recent improvement in genetic testing technique will help more rapid and precise diagnosis for aniridia. A promising therapeutic approach called nonsense suppression therapy has been introduced and successfully used in an animal model. Aniridia is a challenging disease. The progressive nature of this condition and its potential complications require continuous and life-long ophthalmologic care. Genetic diagnosis for aniridia is important for establishing definitive molecular characterization as well as identifying individuals at high risk for Wilms tumor. Recent advancement in understanding the genetic pathogenesis of this disease offers promise for the approaches to treatment.

Performance improvement of VAV air conditioning system through feedforward compensation decoupling and genetic algorithm

International Nuclear Information System (INIS)

Wang Jun; Wang Yan

2008-01-01

VAV (variable air volume) control system has the feature of multi-control loops. While all the control loops are working together, they interfere and influence each other. This paper designs the decoupling compensation unit in VAV system in the method of feedforward compensation. This paper also designs the controller parameters of VAV system by means of inverse deducing and the genetic algorithm. Experimental results demonstrate that the combination of the feedforward compensation decoupling and the controller optimization by genetic algorithm can improve the performance of the VAV control system

Non-genetic engineering of cells for drug delivery and cell-based therapy.

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Wang, Qun; Cheng, Hao; Peng, Haisheng; Zhou, Hao; Li, Peter Y; Langer, Robert

2015-08-30

Cell-based therapy is a promising modality to address many unmet medical needs. In addition to genetic engineering, material-based, biochemical, and physical science-based approaches have emerged as novel approaches to modify cells. Non-genetic engineering of cells has been applied in delivering therapeutics to tissues, homing of cells to the bone marrow or inflammatory tissues, cancer imaging, immunotherapy, and remotely controlling cellular functions. This new strategy has unique advantages in disease therapy and is complementary to existing gene-based cell engineering approaches. A better understanding of cellular systems and different engineering methods will allow us to better exploit engineered cells in biomedicine. Here, we review non-genetic cell engineering techniques and applications of engineered cells, discuss the pros and cons of different methods, and provide our perspectives on future research directions. Copyright © 2014 Elsevier B.V. All rights reserved.

Reactor controller design using genetic algorithms with simulated annealing

International Nuclear Information System (INIS)

Erkan, K.; Buetuen, E.

2000-01-01

This chapter presents a digital control system for ITU TRIGA Mark-II reactor using genetic algorithms with simulated annealing. The basic principles of genetic algorithms for problem solving are inspired by the mechanism of natural selection. Natural selection is a biological process in which stronger individuals are likely to be winners in a competing environment. Genetic algorithms use a direct analogy of natural evolution. Genetic algorithms are global search techniques for optimisation but they are poor at hill-climbing. Simulated annealing has the ability of probabilistic hill-climbing. Thus, the two techniques are combined here to get a fine-tuned algorithm that yields a faster convergence and a more accurate search by introducing a new mutation operator like simulated annealing or an adaptive cooling schedule. In control system design, there are currently no systematic approaches to choose the controller parameters to obtain the desired performance. The controller parameters are usually determined by test and error with simulation and experimental analysis. Genetic algorithm is used automatically and efficiently searching for a set of controller parameters for better performance. (orig.)

Stroke genetics: prospects for personalized medicine

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Markus Hugh S

2012-09-01

Full Text Available Abstract Epidemiologic evidence supports a genetic predisposition to stroke. Recent advances, primarily using the genome-wide association study approach, are transforming what we know about the genetics of multifactorial stroke, and are identifying novel stroke genes. The current findings are consistent with different stroke subtypes having different genetic architecture. These discoveries may identify novel pathways involved in stroke pathogenesis, and suggest new treatment approaches. However, the already identified genetic variants explain only a small proportion of overall stroke risk, and therefore are not currently useful in predicting risk for the individual patient. Such risk prediction may become a reality as identification of a greater number of stroke risk variants that explain the majority of genetic risk proceeds, and perhaps when information on rare variants, identified by whole-genome sequencing, is also incorporated into risk algorithms. Pharmacogenomics may offer the potential for earlier implementation of 'personalized genetic' medicine. Genetic variants affecting clopidogrel and warfarin metabolism may identify non-responders and reduce side-effects, but these approaches have not yet been widely adopted in clinical practice.

Genes, Culture and Conservatism-A Psychometric-Genetic Approach.

Science.gov (United States)

Schwabe, Inga; Jonker, Wilfried; van den Berg, Stéphanie M

2016-07-01

The Wilson-Patterson conservatism scale was psychometrically evaluated using homogeneity analysis and item response theory models. Results showed that this scale actually measures two different aspects in people: on the one hand people vary in their agreement with either conservative or liberal catch-phrases and on the other hand people vary in their use of the "?" response category of the scale. A 9-item subscale was constructed, consisting of items that seemed to measure liberalism, and this subscale was subsequently used in a biometric analysis including genotype-environment interaction, correcting for non-homogeneous measurement error. Biometric results showed significant genetic and shared environmental influences, and significant genotype-environment interaction effects, suggesting that individuals with a genetic predisposition for conservatism show more non-shared variance but less shared variance than individuals with a genetic predisposition for liberalism.

Biotechnological approaches for the genetic improvement of Jatropha curcas L.: A biodiesel plant

KAUST Repository

Kumar, Nitish

2015-08-14

Ever increasing demand for energy sources and reduction of non-renewable fossil fuel reserves have lead to exploration of alternative and renewable energy sources. Due to wide distribution, agronomic suitability, and desirable oil properties, J. curcas has been identified as a renewable and alternative energy source of biodiesel. Large scale commercial cultivation of this crop would not only be environmentally friendly and be worthwhile in carbon sequestration but also in decreasing the energy supply pressures. Wide adaptation across geographic regions, short gestation period compared to most tree species, rapid growth, hardiness, optimum plant size, and easy propagation in combination make this species suitable for large scale cultivation on barren lands. The limited information of the genetics and inheritance of desirable traits, unpredictable and low yields, the limited diversity and susceptibility to diseases and insects are however, key limitations in fruitful farming of J. curcas. In this review, an effort is made to project the current biotechnology and molecular biology tools employed in the direction of, evaluating the genetic diversity and phylogeny revelation of Jatropha spp., identification of genetic markers for desirable traits, development of efficient micropropagation and regeneration system, and genetic transformation methods for J. curcas. © 2015 Elsevier B.V.

Genetic Evaluation of Children with Global Developmental Delay--Current Status of Network Systems in Taiwan.

Science.gov (United States)

Foo, Yong-Lin; Chow, Julie Chi; Lai, Ming-Chi; Tsai, Wen-Hui; Tung, Li-Chen; Kuo, Mei-Chin; Lin, Shio-Jean

2015-08-01

This review article aims to introduce the screening and referral network of genetic evaluation for children with developmental delay in Taiwan. For these children, integrated systems provide services from the medical, educational, and social welfare sectors. All cities and counties in Taiwan have established a network for screening, detection, referral, evaluation, and intervention services. Increased awareness improves early detection and intervention. There remains a gap between supply and demand, especially with regard to financial resources and professional manpower. Genetic etiology has a major role in prenatal causes of developmental delay. A summary of reports on some related genetic disorders in the Taiwanese population is included in this review. Genetic diagnosis allows counseling with regard to recurrence risk and prevention. Networking with neonatal screening, laboratory diagnosis, genetic counseling, and orphan drugs logistics systems can provide effective treatment for patients. In Taiwan, several laboratories provide genetic tests for clinical diagnosis. Accessibility to advanced expensive tests such as gene chips or whole exome sequencing is limited because of funding problems; however, the service system in Taiwan can still operate in a relatively cost-effective manner. This experience in Taiwan may serve as a reference for other countries. Copyright © 2014. Published by Elsevier B.V.

Evolution of branched regulatory genetic pathways: directional selection on pleiotropic loci accelerates developmental system drift.

Science.gov (United States)

Johnson, Norman A; Porter, Adam H

2007-01-01

Developmental systems are regulated by a web of interacting loci. One common and useful approach in studying the evolution of development is to focus on classes of interacting elements within these systems. Here, we use individual-based simulations to study the evolution of traits controlled by branched developmental pathways involving three loci, where one locus regulates two different traits. We examined the system under a variety of selective regimes. In the case where one branch was under stabilizing selection and the other under directional selection, we observed "developmental system drift": the trait under stabilizing selection showed little phenotypic change even though the loci underlying that trait showed considerable evolutionary divergence. This occurs because the pleiotropic locus responds to directional selection and compensatory mutants are then favored in the pathway under stabilizing selection. Though developmental system drift may be caused by other mechanisms, it seems likely that it is accelerated by the same underlying genetic mechanism as that producing the Dobzhansky-Muller incompatibilities that lead to speciation in both linear and branched pathways. We also discuss predictions of our model for developmental system drift and how different selective regimes affect probabilities of speciation in the branched pathway system.

Apparatus, System and Method for Fast Detection of Genetic Information by PCR in an Interchangeable Chip

KAUST Repository

Wen, Weijia

2011-03-03

A polymerase chain reaction (PCR) device for fast amplification and detection of DNA includes an interchangeable PCR chamber, a temperature control component, and an optical detection system. The DNA amplification is performed on an interchangeable chip with volumes as small as 1.25 µl, while the heating and cooling rate may be as fast as 12.7 °C/second ensuring that the total time needed of only 25 minutes to complete the 35 cycle PCR amplification. The PCR may be performed according to a two-temperature approach for denaturing and annealing (Td and Ta) of DNA with the PCR chip, with which the amplification of male-specific SRY gene marker by utilizing raw saliva may be achieved. The genetic identification may be in-situ detected after PCR by the optical detection system.

Management of Uncertainty by Statistical Process Control and a Genetic Tuned Fuzzy System

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Stephan Birle

2016-01-01

Full Text Available In food industry, bioprocesses like fermentation often are a crucial part of the manufacturing process and decisive for the final product quality. In general, they are characterized by highly nonlinear dynamics and uncertainties that make it difficult to control these processes by the use of traditional control techniques. In this context, fuzzy logic controllers offer quite a straightforward way to control processes that are affected by nonlinear behavior and uncertain process knowledge. However, in order to maintain process safety and product quality it is necessary to specify the controller performance and to tune the controller parameters. In this work, an approach is presented to establish an intelligent control system for oxidoreductive yeast propagation as a representative process biased by the aforementioned uncertainties. The presented approach is based on statistical process control and fuzzy logic feedback control. As the cognitive uncertainty among different experts about the limits that define the control performance as still acceptable may differ a lot, a data-driven design method is performed. Based upon a historic data pool statistical process corridors are derived for the controller inputs control error and change in control error. This approach follows the hypothesis that if the control performance criteria stay within predefined statistical boundaries, the final process state meets the required quality definition. In order to keep the process on its optimal growth trajectory (model based reference trajectory a fuzzy logic controller is used that alternates the process temperature. Additionally, in order to stay within the process corridors, a genetic algorithm was applied to tune the input and output fuzzy sets of a preliminarily parameterized fuzzy controller. The presented experimental results show that the genetic tuned fuzzy controller is able to keep the process within its allowed limits. The average absolute error to the

Dynamical System Approaches to Combinatorial Optimization

DEFF Research Database (Denmark)

Starke, Jens

2013-01-01

of large times as an asymptotically stable point of the dynamics. The obtained solutions are often not globally optimal but good approximations of it. Dynamical system and neural network approaches are appropriate methods for distributed and parallel processing. Because of the parallelization......Several dynamical system approaches to combinatorial optimization problems are described and compared. These include dynamical systems derived from penalty methods; the approach of Hopfield and Tank; self-organizing maps, that is, Kohonen networks; coupled selection equations; and hybrid methods...... thereof can be used as models for many industrial problems like manufacturing planning and optimization of flexible manufacturing systems. This is illustrated for an example in distributed robotic systems....

A Hybrid Fuzzy Genetic Algorithm for an Adaptive Traffic Signal System

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S. M. Odeh

2015-01-01

Full Text Available This paper presents a hybrid algorithm that combines Fuzzy Logic Controller (FLC and Genetic Algorithms (GAs and its application on a traffic signal system. FLCs have been widely used in many applications in diverse areas, such as control system, pattern recognition, signal processing, and forecasting. They are, essentially, rule-based systems, in which the definition of these rules and fuzzy membership functions is generally based on verbally formulated rules that overlap through the parameter space. They have a great influence over the performance of the system. On the other hand, the Genetic Algorithm is a metaheuristic that provides a robust search in complex spaces. In this work, it has been used to adapt the decision rules of FLCs that define an intelligent traffic signal system, obtaining a higher performance than a classical FLC-based control. The simulation results yielded by the hybrid algorithm show an improvement of up to 34% in the performance with respect to a standard traffic signal controller, Conventional Traffic Signal Controller (CTC, and up to 31% in the comparison with a traditional logic controller, FLC.

A systems genetics approach identifies genes and pathways for type 2 diabetes in human islets

DEFF Research Database (Denmark)

Taneera, Jalal; Lang, Stefan; Sharma, Amitabh

2012-01-01

Close to 50 genetic loci have been associated with type 2 diabetes (T2D), but they explain only 15% of the heritability. In an attempt to identify additional T2D genes, we analyzed global gene expression in human islets from 63 donors. Using 48 genes located near T2D risk variants, we identified ...

Modelling Autistic Features in Mice Using Quantitative Genetic Approaches

NARCIS (Netherlands)

Molenhuis, Remco T; Bruining, Hilgo; Kas, Martien J

2017-01-01

Animal studies provide a unique opportunity to study the consequences of genetic variants at the behavioural level. Human studies have identified hundreds of risk genes for autism spectrum disorder (ASD) that can lead to understanding on how genetic variation contributes to individual differences in

Genetic Investigations Using Immuno-biochemical Markers in a Maramureş Brown Cattle Population

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Nicoleta Isfan

2011-05-01

Full Text Available The study of the genetic markers and identifying new markers involves an increasing number of research projects in the fields of genetics of immunology, biochemical genetics, molecular genetics, quantity genetics and the genetic improvement of animals. Some studies on genes frequency determining the red cells specificity and for whey hemoglobin are approached in the present report. In this way, some blood factors, most of them belonging to B system (the most complex system in cattle have been evidenced. The lowest gene frequency was present in K factor (7%, and highest one in, O1, G’ , W and F1 (100%. In addition to basic importance on knowledge and determination of cattle population genetic structure for studied protein loci, another theme proposed to correlate hemoglobin type with some traits of economical importance: milk yield, fat and protein content, fat and protein yield. Higher performance was recorded by HbA/HbA individuals.

Ethical genetic research in Indigenous communities: challenges and successful approaches.

Science.gov (United States)

McWhirter, Rebekah E; Mununggirritj, Djapirri; Marika, Dipililnga; Dickinson, Joanne L; Condon, John R

2012-12-01

Indigenous populations, in common with all populations, stand to benefit from the potential of genetic research to lead to improvements in diagnostic and therapeutic tools for a wide range of complex diseases. However, many Indigenous communities, especially ones that are isolated, are not included in genetic research efforts. This situation is largely a consequence of the challenges of ethically conducting genetic research in Indigenous communities and compounded by Indigenous peoples' negative past experiences with genetic issues. To examine ways of addressing these challenges, we review one investigation of a cancer cluster in remote Aboriginal communities in Arnhem Land, Australia. Our experiences demonstrate that genetic research can be both ethically and successfully conducted with Indigenous communities by respecting the authority of the community, involving community members, and including regular community review throughout the research process. Copyright © 2012 Elsevier Ltd. All rights reserved.

Fault Diagnosis of Power System Based on Improved Genetic Optimized BP-NN

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Yuan Pu

2015-01-01

Full Text Available BP neural network (Back-Propagation Neural Network, BP-NN is one of the most widely neural network models and is applied to fault diagnosis of power system currently. BP neural network has good self-learning and adaptive ability and generalization ability, but the operation process is easy to fall into local minima. Genetic algorithm has global optimization features, and crossover is the most important operation of the Genetic Algorithm. In this paper, we can modify the crossover of traditional Genetic Algorithm, using improved genetic algorithm optimized BP neural network training initial weights and thresholds, to avoid the problem of BP neural network fall into local minima. The results of analysis by an example, the method can efficiently diagnose network fault location, and improve fault-tolerance and grid fault diagnosis effect.

Genetic modification of hematopoietic stem cells with nonviral systems: past progress and future prospects.

Science.gov (United States)

Papapetrou, E P; Zoumbos, N C; Athanassiadou, A

2005-10-01

Serious unwanted complications provoked by retroviral gene transfer into hematopoietic stem cells (HSCs) have recently raised the need for the development and assessment of alternative gene transfer vectors. Within this context, nonviral gene transfer systems are attracting increasing interest. Their main advantages include low cost, ease of handling and large-scale production, large packaging capacity and, most importantly, biosafety. While nonviral gene transfer into HSCs has been restricted in the past by poor transfection efficiency and transient maintenance, in recent years, biotechnological developments are converting nonviral transfer into a realistic approach for genetic modification of cells of hematopoietic origin. Herein we provide an overview of past accomplishments in the field of nonviral gene transfer into hematopoietic progenitor/stem cells and we point at future challenges. We argue that episomally maintained self-replicating vectors combined with physical methods of delivery show the greatest promise among nonviral gene transfer strategies for the treatment of disorders of the hematopoietic system.

Electromagnetic energy as a bridge between atomic and cellular levels in the genetics approach to cancer treatment.

Science.gov (United States)

Tofani, Santi

2015-01-01

Literature on magnetic fields (MF) and gene expression, as well as on DNA damage, supports the hypothesis that electromagnetic energy may act at atomic level influencing genetic stability. According to quantum physics, MF act on the interconversion of singlet and triplet spin states, and therefore on genetic instability, activating oxidative processes connected to biological free radicals formation, particularly ROS. In the above frame, the results of in vitro and in vivo laboratory trials have been analyzed. The use of a static MF amplitude modulated by 50 Hz MF, with a time average total intensity of 5.5 mT, has been shown to influence tumor cell functions such as cell proliferation, apoptosis, p53 expression, inhibition of tumor growth and prolongation of survival in animals, evidence that MF can be more effective than chemotherapy (cyclophosphamide) in inhibiting metastatic spread and growth, having synergistic activity with chemotherapy (Cis-platin), and no observable side effects or toxicity in animals or in humans. The beneficial biological/clinical effects observed, without any adverse effects, have been confirmed by various authors and augur well for the potentiality of this new approach to treat genetically based diseases like cancer. Further studies are needed to develop a quantum physics approach to biology, allowing a stable bridge to be built between atomic and cellular levels, therefore developing quantum biology.

Management of genetic resources in the nursery system of wild cherry (Prunus avium L.

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Proietti R

2006-01-01

Full Text Available Knowledge of genetic and adaptive traits of reproductive materials used in the nursery system of wild cherry, could be an useful instrument to improve ecological and economic sustainability of plantation ecosystems. This work reports results from a research which the objectives were: 1 to study the genetic variation of a Prunus avium L. Population, used for seed harvesting, through its multi-locus genotypes detected by starch gel electrophoresis; 2 to analyze the level of genetic variation within and among different steps in a commercial nursery system (basic population and sub-populations, seedlings aged S1T1 and S1T2, plantation. Results showed low genetic variation levels of the basic population, similar to a reference system of other 12 wild cherry Italian populations and to other French and Caucasian materials. The genetic distances among Monte Baldo and some closer Lombardy provenances (Area Garda, Bosco Fontana, Valtellina were smaller than the Venice Region populations (Monti Lessini and Asiago. Number of alleles and percentage of polymorphic loci within the complex of Monte Baldo provenance and multiplication materials were similar, whilst a variable value of Fis was noted. Indeed, along with the nursery system until the plantation, heterozygosis initially (S1T1 increased, then decreased proceeding to the plantation. This fluctuation of FIS values could be determined by seed lots characterized initially by higher levels of variation, due to self-incompatibility. In the following steps, a possible selection pressure can affect randomly the genotypic structure of wild cherry by increasing the homozygosity. There is not among population a well defined geographic characterization, as suggested by genetic distances, therefore homogeneous seed harvest could be established an area larger than geographic and administrative borders. On this way we could have reproductive material with a wide genetic base and environmental adaptability. To

Genetic View To Stroke Occurrence

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Sadegh Yoosefee

2017-02-01

Full Text Available Stroke is the third leading cause of death. The role of genetics in the etiology and development of this disease is undeniable. As a result of inadequate previous research, more and more studies in the field of genetics are necessary to identify pathways involved in the pathogenesis of stroke, which in turn, may lead to new therapeutic approaches. However, due to the multifactorial nature of stroke and the few studies conducted in this field, genetic diversity is able to predict only a small fraction of the risk of disease. On the other hand, studies have shown genetically different architecture for different types of stroke, and finally pharmacogenomics as an important part of personalized medicine approach, is influenced by genetic studies, all of which confirm the need of addressing the topic by researchers.

Is it acceptable to approach colorectal cancer patients at diagnosis to discuss genetic testing? A pilot study

OpenAIRE

Porteous, M; Dunckley, M; Appleton, S; Catt, S; Dunlop, M; Campbell, H; Cull, A

2003-01-01

In this pilot study, the acceptability of approaching 111 newly diagnosed colorectal cancer patients with the offer of genetic testing for hereditary nonpolyposis colorectal cancer (HNPCC) was assessed. A total of 78% of participants found it highly acceptable to have the information about HNPCC brought to their attention at that time.

A Novel Approach to Managing Invasive Termite Species Using Genetically Engineered Bacteria

Science.gov (United States)

2008-08-01

Coptotcnnes fonnosanus; lytic peptide; defaunation; tennite gut bacteria ; yeast 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF 18. NUMBER 19a. NAME OF...genetically modified bacteria in a termite colony ; no detrimental gene products were expressed for termite control. Preliminary data suggested that lytic...defaunated within 4 weeks. The yeast -based prototype paratransgenesis system provided proof of concept that a symbiotic microorganism can act as a “Trojan

A Multi-Model Approach for System Diagnosis

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Poulsen, Niels Kjølstad; Bækgaard, Mikkel Ask Buur

2007-01-01

A multi-model approach for system diagnosis is presented in this paper. The relation with fault diagnosis as well as performance validation is considered. The approach is based on testing a number of pre-described models and find which one is the best. It is based on an active approach......,i.e. an auxiliary input to the system is applied. The multi-model approach is applied on a wind turbine system....

Computational Genetic Regulatory Networks Evolvable, Self-organizing Systems

CERN Document Server

Knabe, Johannes F

2013-01-01

Genetic Regulatory Networks (GRNs) in biological organisms are primary engines for cells to enact their engagements with environments, via incessant, continually active coupling. In differentiated multicellular organisms, tremendous complexity has arisen in the course of evolution of life on earth. Engineering and science have so far achieved no working system that can compare with this complexity, depth and scope of organization. Abstracting the dynamics of genetic regulatory control to a computational framework in which artificial GRNs in artificial simulated cells differentiate while connected in a changing topology, it is possible to apply Darwinian evolution in silico to study the capacity of such developmental/differentiated GRNs to evolve. In this volume an evolutionary GRN paradigm is investigated for its evolvability and robustness in models of biological clocks, in simple differentiated multicellularity, and in evolving artificial developing 'organisms' which grow and express an ontogeny starting fr...

PID-Controller Tuning Optimization with Genetic Algorithms in Servo Systems

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Arturo Y. Jaen-Cuellar

2013-09-01

Full Text Available Performance improvement is the main goal of the study of PID control and much research has been conducted for this purpose. The PID filter is implemented in almost all industrial processes because of its well-known beneficial features. In general, the whole system's performance strongly depends on the controller's efficiency and hence the tuning process plays a key role in the system's behaviour. In this work, the servo systems will be analysed, specifically the positioning control systems. Among the existent tuning methods, the Gain-Phase Margin method based on Frequency Response analysis is the most adequate for controller tuning in positioning control systems. Nevertheless, this method can be improved by integrating an optimization technique. The novelty of this work is the development of a new methodology for PID control tuning by coupling the Gain-Phase Margin method with the Genetic Algorithms in which the micro-population concept and adaptive mutation probability are applied. Simulations using a positioning system model in MATLAB and experimental tests in two CNC machines and an industrial robot are carried out in order to show the effectiveness of the proposal. The obtained results are compared with both the classical Gain-Phase Margin tuning and with a recent PID controller optimization using Genetic Algorithms based on real codification. The three methodologies are implemented using software.

Chaotic logic gate: A new approach in set and design by genetic algorithm

International Nuclear Information System (INIS)

Beyki, Mahmood; Yaghoobi, Mahdi

2015-01-01

How to reconfigure a logic gate is an attractive subject for different applications. Chaotic systems can yield a wide variety of patterns and here we use this feature to produce a logic gate. This feature forms the basis for designing a dynamical computing device that can be rapidly reconfigured to become any wanted logical operator. This logic gate that can reconfigure to any logical operator when placed in its chaotic state is called chaotic logic gate. The reconfiguration realize by setting the parameter values of chaotic logic gate. In this paper we present mechanisms about how to produce a logic gate based on the logistic map in its chaotic state and genetic algorithm is used to set the parameter values. We use three well-known selection methods used in genetic algorithm: tournament selection, Roulette wheel selection and random selection. The results show the tournament selection method is the best method for set the parameter values. Further, genetic algorithm is a powerful tool to set the parameter values of chaotic logic gate

Multi-objective hierarchical genetic algorithms for multilevel redundancy allocation optimization

Energy Technology Data Exchange (ETDEWEB)

Kumar, Ranjan [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: ranjan.k@ks3.ecs.kyoto-u.ac.jp; Izui, Kazuhiro [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: izui@prec.kyoto-u.ac.jp; Yoshimura, Masataka [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: yoshimura@prec.kyoto-u.ac.jp; Nishiwaki, Shinji [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: shinji@prec.kyoto-u.ac.jp

2009-04-15

Multilevel redundancy allocation optimization problems (MRAOPs) occur frequently when attempting to maximize the system reliability of a hierarchical system, and almost all complex engineering systems are hierarchical. Despite their practical significance, limited research has been done concerning the solving of simple MRAOPs. These problems are not only NP hard but also involve hierarchical design variables. Genetic algorithms (GAs) have been applied in solving MRAOPs, since they are computationally efficient in solving such problems, unlike exact methods, but their applications has been confined to single-objective formulation of MRAOPs. This paper proposes a multi-objective formulation of MRAOPs and a methodology for solving such problems. In this methodology, a hierarchical GA framework for multi-objective optimization is proposed by introducing hierarchical genotype encoding for design variables. In addition, we implement the proposed approach by integrating the hierarchical genotype encoding scheme with two popular multi-objective genetic algorithms (MOGAs)-the strength Pareto evolutionary genetic algorithm (SPEA2) and the non-dominated sorting genetic algorithm (NSGA-II). In the provided numerical examples, the proposed multi-objective hierarchical approach is applied to solve two hierarchical MRAOPs, a 4- and a 3-level problems. The proposed method is compared with a single-objective optimization method that uses a hierarchical genetic algorithm (HGA), also applied to solve the 3- and 4-level problems. The results show that a multi-objective hierarchical GA (MOHGA) that includes elitism and mechanism for diversity preserving performed better than a single-objective GA that only uses elitism, when solving large-scale MRAOPs. Additionally, the experimental results show that the proposed method with NSGA-II outperformed the proposed method with SPEA2 in finding useful Pareto optimal solution sets.

Multi-objective hierarchical genetic algorithms for multilevel redundancy allocation optimization

International Nuclear Information System (INIS)

Kumar, Ranjan; Izui, Kazuhiro; Yoshimura, Masataka; Nishiwaki, Shinji

2009-01-01

Multilevel redundancy allocation optimization problems (MRAOPs) occur frequently when attempting to maximize the system reliability of a hierarchical system, and almost all complex engineering systems are hierarchical. Despite their practical significance, limited research has been done concerning the solving of simple MRAOPs. These problems are not only NP hard but also involve hierarchical design variables. Genetic algorithms (GAs) have been applied in solving MRAOPs, since they are computationally efficient in solving such problems, unlike exact methods, but their applications has been confined to single-objective formulation of MRAOPs. This paper proposes a multi-objective formulation of MRAOPs and a methodology for solving such problems. In this methodology, a hierarchical GA framework for multi-objective optimization is proposed by introducing hierarchical genotype encoding for design variables. In addition, we implement the proposed approach by integrating the hierarchical genotype encoding scheme with two popular multi-objective genetic algorithms (MOGAs)-the strength Pareto evolutionary genetic algorithm (SPEA2) and the non-dominated sorting genetic algorithm (NSGA-II). In the provided numerical examples, the proposed multi-objective hierarchical approach is applied to solve two hierarchical MRAOPs, a 4- and a 3-level problems. The proposed method is compared with a single-objective optimization method that uses a hierarchical genetic algorithm (HGA), also applied to solve the 3- and 4-level problems. The results show that a multi-objective hierarchical GA (MOHGA) that includes elitism and mechanism for diversity preserving performed better than a single-objective GA that only uses elitism, when solving large-scale MRAOPs. Additionally, the experimental results show that the proposed method with NSGA-II outperformed the proposed method with SPEA2 in finding useful Pareto optimal solution sets

A Systems Thinking Approach to Engineering Challenges of Military Systems-of-Systems

Science.gov (United States)

2016-09-01

as part of organizational thinking , processes and practice; and 2) an adequate SoSE practice supporting environment created and used to enable SoS...UNCLASSIFIED UNCLLASIFIED A Systems Thinking Approach to Engineering Challenges of Military Systems-of-Systems Pin Chen and Mark...their products and outcomes. This report introduces a systems thinking -based approach, SoS thinking , which offers a language and a thoughtful process

Assessing Date Palm Genetic Diversity Using Different Molecular Markers.

Science.gov (United States)

Atia, Mohamed A M; Sakr, Mahmoud M; Adawy, Sami S

2017-01-01

Molecular marker technologies which rely on DNA analysis provide powerful tools to assess biodiversity at different levels, i.e., among and within species. A range of different molecular marker techniques have been developed and extensively applied for detecting variability in date palm at the DNA level. Recently, the employment of gene-targeting molecular marker approaches to study biodiversity and genetic variations in many plant species has increased the attention of researchers interested in date palm to carry out phylogenetic studies using these novel marker systems. Molecular markers are good indicators of genetic distances among accessions, because DNA-based markers are neutral in the face of selection. Here we describe the employment of multidisciplinary molecular marker approaches: amplified fragment length polymorphism (AFLP), start codon targeted (SCoT) polymorphism, conserved DNA-derived polymorphism (CDDP), intron-targeted amplified polymorphism (ITAP), simple sequence repeats (SSR), and random amplified polymorphic DNA (RAPD) to assess genetic diversity in date palm.

A Systems Approach to Nitrogen Delivery

Energy Technology Data Exchange (ETDEWEB)

Goins, Bobby [Y-12 National Security Complex, Oak Ridge, TN (United States)

2017-10-23

A systems based approach will be used to evaluate the nitrogen delivery process. This approach involves principles found in Lean, Reliability, Systems Thinking, and Requirements. This unique combination of principles and thought process yields a very in depth look into the system to which it is applied. By applying a systems based approach to the nitrogen delivery process there should be improvements in cycle time, efficiency, and a reduction in the required number of personnel needed to sustain the delivery process. This will in turn reduce the amount of demurrage charges that the site incurs. In addition there should be less frustration associated with the delivery process.

A Systems Approach to Nitrogen Delivery

Energy Technology Data Exchange (ETDEWEB)

Goins, Bobby [Y-12 National Security Complex, Oak Ridge, TN (United States); Univ. of Tennessee, Knoxville, TN (United States)

2017-10-17

A systems based approach will be used to evaluate the nitrogen delivery process. This approach involves principles found in Lean, Reliability, Systems Thinking, and Requirements. This unique combination of principles and thought process yields a very in depth look into the system to which it is applied. By applying a systems based approach to the nitrogen delivery process there should be improvements in cycle time, efficiency, and a reduction in the required number of personnel needed to sustain the delivery process. This will in turn reduce the amount of demurrage charges that the site incurs. In addition there should be less frustration associated with the delivery process.

Genetic algorithms applied to the nuclear power plant operation

International Nuclear Information System (INIS)

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

2000-01-01

Nuclear power plant operation often involves very important human decisions, such as actions to be taken after a nuclear accident/transient, or finding the best core reload pattern, a complex combinatorial optimization problem which requires expert knowledge. Due to the complexity involved in the decisions to be taken, computerized systems have been intensely explored in order to aid the operator. Following hardware advances, soft computing has been improved and, nowadays, intelligent technologies, such as genetic algorithms, neural networks and fuzzy systems, are being used to support operator decisions. In this chapter two main problems are explored: transient diagnosis and nuclear core refueling. Here, solutions to such kind of problems, based on genetic algorithms, are described. A genetic algorithm was designed to optimize the nuclear fuel reload of Angra-1 nuclear power plant. Results compared to those obtained by an expert reveal a gain in the burn-up cycle. Two other genetic algorithm approaches were used to optimize real time diagnosis systems. The first one learns partitions in the time series that represents the transients, generating a set of classification centroids. The other one involves the optimization of an adaptive vector quantization neural network. Results are shown and commented. (orig.)

Sex separation strategies: past experience and new approaches

Directory of Open Access Journals (Sweden)

Malcolm Colin A

2009-11-01

Full Text Available Abstract The success of the sterile insect technique (SIT and other genetic strategies designed to eliminate large populations of insects relies on the efficient inundative releases of competitive, sterile males into the natural habitat of the target species. As released sterile females do not contribute to the sterility in the field population, systems for the efficient mass production and separation of males from females are needed. For vector species like mosquitoes, in which only females bite and transmit diseases, the thorough removal of females before release while leaving males competent to mate is a stringent prerequisite. Biological, genetic and transgenic approaches have been developed that permit efficient male-female separation for some species considered for SIT. However, most sex separation methods have drawbacks and many of these methods are not directly transferable to mosquitoes. Unlike genetic and transgenic systems, biological methods that rely on sexually dimorphic characters, such as size or development rate, are subject to natural variation, requiring regular adjustment and re-calibration of the sorting systems used. The yield can be improved with the optimization of rearing, but the scale of mass production places practical limits on what is achievable, resulting in a poor rearing to output ratio. High throughput separation is best achieved with scalable genetic or transgenic approaches.

Endocannabinoid system and drug addiction: new insights from mutant mice approaches.

Science.gov (United States)

Maldonado, Rafael; Robledo, Patricia; Berrendero, Fernando

2013-08-01

The involvement of the endocannabinoid system in drug addiction was initially studied by the use of compounds with different affinities for each cannabinoid receptor or for the proteins involved in endocannabinoids inactivation. The generation of genetically modified mice with selective mutations in these endocannabinoid system components has now provided important advances in establishing their specific contribution to drug addiction. These genetic tools have identified the particular interest of CB1 cannabinoid receptor and endogenous anandamide as potential targets for drug addiction treatment. Novel genetic tools will allow determining if the modulation of CB2 cannabinoid receptor activity and 2-arachidonoylglycerol tone can also have an important therapeutic relevance for drug addiction. Copyright © 2013 Elsevier Ltd. All rights reserved.

Optimum energy re-establishment in distribution systems: a comparison between the search performance using fuzzy heuristics and genetic algorithms; Restabelecimento otimo de energia em sistemas de distribuicao: uma comparacao entre o desempenho de busca com heuristica fuzzy e algoritmos geneticos

Energy Technology Data Exchange (ETDEWEB)

Delbem, Alexandre C.B.; Bretas, Newton G. [Sao Paulo Univ., Sao Carlos, SP (Brazil). Dept. de Engenharia Eletrica; Carvalho, Andre C.P.L.F. [Sao Paulo Univ., Sao Carlos, SP (Brazil). Dept. de Ciencias de Computacao e Estatistica

1996-11-01

A search approach using fuzzy heuristics and a neural network parameter was developed for service restoration of a distribution system. The goal was to restore energy for an un-faulted zone after a fault had been identified and isolated. The restoration plan must be carried out in a very short period. However, the combinatorial feature of the problem constrained the application of automatic energy restoration planners. To overcome this problem, an heuristic search approach using fuzzy heuristics was proposed. As a result, a genetic algorithm approach was developed to achieve the optimal energy restoration plan. The effectiveness of these approaches were tested in a simplified distribution system based on the complex distribution system of Sao Carlos city, Sao Paulo State - southeast Brazil. It was noticed that the genetic algorithm provided better performance than the fuzzy heuristic search in this problem. 11 refs., 10 figs.

Genetic Disruption of the Core Circadian Clock Impairs Hippocampus-Dependent Memory

Science.gov (United States)

Wardlaw, Sarah M.; Phan, Trongha X.; Saraf, Amit; Chen, Xuanmao; Storm, Daniel R.

2014-01-01

Perturbing the circadian system by electrolytically lesioning the suprachiasmatic nucleus (SCN) or varying the environmental light:dark schedule impairs memory, suggesting that memory depends on the circadian system. We used a genetic approach to evaluate the role of the molecular clock in memory. Bmal1[superscript -/-] mice, which are arrhythmic…

Soft systems methodology as a systemic approach to nuclear safety management

International Nuclear Information System (INIS)

Vieira Neto, Antonio S.; Guilhen, Sabine N.; Rubin, Gerson A.; Caldeira Filho, Jose S.; Camargo, Iara M.C.

2017-01-01

Safety approach currently adopted by nuclear installations is built almost exclusively upon analytical methodologies based, mainly, on the belief that the properties of a system, such as its safety, are given by its constituent parts. This approach, however, does not properly address the complex dynamic interactions between technical, human and organizational factors occurring within and outside the organization. After the accident at Fukushima Daiichi nuclear power plant in March 2011, experts of the International Atomic Energy Agency (IAEA) recommended a systemic approach as a complementary perspective to nuclear safety. The aim of this paper is to present an overview of the systems thinking approach and its potential use for structuring socio technical problems involved in the safety of nuclear installations, highlighting the methodologies related to the soft systems thinking, in particular the Soft Systems Methodology (SSM). The implementation of a systemic approach may thus result in a more holistic picture of the system by the complex dynamic interactions between technical, human and organizational factors. (author)

Soft systems methodology as a systemic approach to nuclear safety management

Energy Technology Data Exchange (ETDEWEB)

Vieira Neto, Antonio S.; Guilhen, Sabine N.; Rubin, Gerson A.; Caldeira Filho, Jose S.; Camargo, Iara M.C., E-mail: asvneto@ipen.br, E-mail: snguilhen@ipen.br, E-mail: garubin@ipen.br, E-mail: jscaldeira@ipen.br, E-mail: icamargo@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNE-SP), Sao Paulo, SP (Brazil)

2017-07-01

Safety approach currently adopted by nuclear installations is built almost exclusively upon analytical methodologies based, mainly, on the belief that the properties of a system, such as its safety, are given by its constituent parts. This approach, however, does not properly address the complex dynamic interactions between technical, human and organizational factors occurring within and outside the organization. After the accident at Fukushima Daiichi nuclear power plant in March 2011, experts of the International Atomic Energy Agency (IAEA) recommended a systemic approach as a complementary perspective to nuclear safety. The aim of this paper is to present an overview of the systems thinking approach and its potential use for structuring socio technical problems involved in the safety of nuclear installations, highlighting the methodologies related to the soft systems thinking, in particular the Soft Systems Methodology (SSM). The implementation of a systemic approach may thus result in a more holistic picture of the system by the complex dynamic interactions between technical, human and organizational factors. (author)

High-precision approach to localization scheme of visible light communication based on artificial neural networks and modified genetic algorithms

Science.gov (United States)

Guan, Weipeng; Wu, Yuxiang; Xie, Canyu; Chen, Hao; Cai, Ye; Chen, Yingcong

2017-10-01

An indoor positioning algorithm based on visible light communication (VLC) is presented. This algorithm is used to calculate a three-dimensional (3-D) coordinate of an indoor optical wireless environment, which includes sufficient orders of multipath reflections from reflecting surfaces of the room. Leveraging the global optimization ability of the genetic algorithm (GA), an innovative framework for 3-D position estimation based on a modified genetic algorithm is proposed. Unlike other techniques using VLC for positioning, the proposed system can achieve indoor 3-D localization without making assumptions about the height or acquiring the orientation angle of the mobile terminal. Simulation results show that an average localization error of less than 1.02 cm can be achieved. In addition, in most VLC-positioning systems, the effect of reflection is always neglected and its performance is limited by reflection, which makes the results not so accurate for a real scenario and the positioning errors at the corners are relatively larger than other places. So, we take the first-order reflection into consideration and use artificial neural network to match the model of a nonlinear channel. The studies show that under the nonlinear matching of direct and reflected channels the average positioning errors of four corners decrease from 11.94 to 0.95 cm. The employed algorithm is emerged as an effective and practical method for indoor localization and outperform other existing indoor wireless localization approaches.

Using Genetic Algorithm and MODFLOW to Characterize Aquifer System of Northwest Florida

Science.gov (United States)

By integrating Genetic Algorithm and MODFLOW2005, an optimizing tool is developed to characterize the aquifer system of Region II, Northwest Florida. The history and the newest available observation data of the aquifer system is fitted automatically by using the numerical model c...

Multi-objective approach in thermoenvironomic optimization of a benchmark cogeneration system

International Nuclear Information System (INIS)

Sayyaadi, Hoseyn

2009-01-01

Multi-objective optimization for designing of a benchmark cogeneration system known as CGAM cogeneration system has been performed. In optimization approach, the exergetic, economic and environmental aspects have been considered, simultaneously. The thermodynamic modeling has been implemented comprehensively while economic analysis conducted in accordance with the total revenue requirement (TRR) method. The results for the single objective thermoeconomic optimization have been compared with the previous studies in optimization of CGAM problem. In multi-objective optimization of the CGAM problem, the three objective functions including the exergetic efficiency, total levelized cost rate of the system product and the cost rate of environmental impact have been considered. The environmental impact objective function has been defined and expressed in cost terms. This objective has been integrated with the thermoeconomic objective to form a new unique objective function known as a thermoenvironomic objective function. The thermoenvironomic objective has been minimized while the exergetic objective has been maximized. One of the most suitable optimization techniques developed using a particular class of search algorithms known as multi-objective evolutionary algorithms (MOEAs) has been considered here. This approach which is developed based on the genetic algorithm has been applied to find the set of Pareto optimal solutions with respect to the aforementioned objective functions. An example of decision-making has been presented and a final optimal solution has been introduced. The sensitivity of the solutions to the interest rate and the fuel cost has been studied

A contemporary view of systems engineering. [definition of system and discussion of systems approach

Science.gov (United States)

Miles, R. F., Jr.

1974-01-01

The concept of a 'system' is defined, and the 'systems approach' is discussed. Four contemporary examples of the systems approach are presented: an operations research project, the planning-programming-budgeting system, an information processing system, and aerospace programs.

Genetic databases and consent for use of medical records

NARCIS (Netherlands)

Gevers, J. K. M.

2004-01-01

The legislation on the Icelandic genetic database provides for an opting-out system for the collection of encoded medical information from individual medical records. From the beginning this has raised criticism, in Iceland itself and abroad. The Supreme Court has now decided that this approach of

Dynamic Load Balanced Clustering using Elitism based Random Immigrant Genetic Approach for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

K. Mohaideen Pitchai

2017-07-01

Full Text Available Wireless Sensor Network (WSN consists of a large number of small sensors with restricted energy. Prolonged network lifespan, scalability, node mobility and load balancing are important needs for several WSN applications. Clustering the sensor nodes is an efficient technique to reach these goals. WSN have the characteristics of topology dynamics because of factors like energy conservation and node movement that leads to Dynamic Load Balanced Clustering Problem (DLBCP. In this paper, Elitism based Random Immigrant Genetic Approach (ERIGA is proposed to solve DLBCP which adapts to topology dynamics. ERIGA uses the dynamic Genetic Algorithm (GA components for solving the DLBCP. The performance of load balanced clustering process is enhanced with the help of this dynamic GA. As a result, the ERIGA achieves to elect suitable cluster heads which balances the network load and increases the lifespan of the network.

Genetic algorithm approach to thin film optical parameters determination

International Nuclear Information System (INIS)

Jurecka, S.; Jureckova, M.; Muellerova, J.

2003-01-01

Optical parameters of thin film are important for several optical and optoelectronic applications. In this work the genetic algorithm proposed to solve optical parameters of thin film values. The experimental reflectance is modelled by the Forouhi - Bloomer dispersion relations. The refractive index, the extinction coefficient and the film thickness are the unknown parameters in this model. Genetic algorithm use probabilistic examination of promissing areas of the parameter space. It creates a population of solutions based on the reflectance model and then operates on the population to evolve the best solution by using selection, crossover and mutation operators on the population individuals. The implementation of genetic algorithm method and the experimental results are described too (Authors)

A Comprehensive Quality Evaluation System for Complex Herbal Medicine Using PacBio Sequencing, PCR-Denaturing Gradient Gel Electrophoresis, and Several Chemical Approaches

Directory of Open Access Journals (Sweden)

Xiasheng Zheng

2017-09-01

Full Text Available Herbal medicine is a major component of complementary and alternative medicine, contributing significantly to the health of many people and communities. Quality control of herbal medicine is crucial to ensure that it is safe and sound for use. Here, we investigated a comprehensive quality evaluation system for a classic herbal medicine, Danggui Buxue Formula, by applying genetic-based and analytical chemistry approaches to authenticate and evaluate the quality of its samples. For authenticity, we successfully applied two novel technologies, third-generation sequencing and PCR-DGGE (denaturing gradient gel electrophoresis, to analyze the ingredient composition of the tested samples. For quality evaluation, we used high performance liquid chromatography assays to determine the content of chemical markers to help estimate the dosage relationship between its two raw materials, plant roots of Huangqi and Danggui. A series of surveys were then conducted against several exogenous contaminations, aiming to further access the efficacy and safety of the samples. In conclusion, the quality evaluation system demonstrated here can potentially address the authenticity, quality, and safety of herbal medicines, thus providing novel insight for enhancing their overall quality control.Highlight: We established a comprehensive quality evaluation system for herbal medicine, by combining two genetic-based approaches third-generation sequencing and DGGE (denaturing gradient gel electrophoresis with analytical chemistry approaches to achieve the authentication and quality connotation of the samples.

A Comprehensive Quality Evaluation System for Complex Herbal Medicine Using PacBio Sequencing, PCR-Denaturing Gradient Gel Electrophoresis, and Several Chemical Approaches.

Science.gov (United States)

Zheng, Xiasheng; Zhang, Peng; Liao, Baosheng; Li, Jing; Liu, Xingyun; Shi, Yuhua; Cheng, Jinle; Lai, Zhitian; Xu, Jiang; Chen, Shilin

2017-01-01

Herbal medicine is a major component of complementary and alternative medicine, contributing significantly to the health of many people and communities. Quality control of herbal medicine is crucial to ensure that it is safe and sound for use. Here, we investigated a comprehensive quality evaluation system for a classic herbal medicine, Danggui Buxue Formula, by applying genetic-based and analytical chemistry approaches to authenticate and evaluate the quality of its samples. For authenticity, we successfully applied two novel technologies, third-generation sequencing and PCR-DGGE (denaturing gradient gel electrophoresis), to analyze the ingredient composition of the tested samples. For quality evaluation, we used high performance liquid chromatography assays to determine the content of chemical markers to help estimate the dosage relationship between its two raw materials, plant roots of Huangqi and Danggui. A series of surveys were then conducted against several exogenous contaminations, aiming to further access the efficacy and safety of the samples. In conclusion, the quality evaluation system demonstrated here can potentially address the authenticity, quality, and safety of herbal medicines, thus providing novel insight for enhancing their overall quality control. Highlight : We established a comprehensive quality evaluation system for herbal medicine, by combining two genetic-based approaches third-generation sequencing and DGGE (denaturing gradient gel electrophoresis) with analytical chemistry approaches to achieve the authentication and quality connotation of the samples.

A Comprehensive Quality Evaluation System for Complex Herbal Medicine Using PacBio Sequencing, PCR-Denaturing Gradient Gel Electrophoresis, and Several Chemical Approaches

Science.gov (United States)

Zheng, Xiasheng; Zhang, Peng; Liao, Baosheng; Li, Jing; Liu, Xingyun; Shi, Yuhua; Cheng, Jinle; Lai, Zhitian; Xu, Jiang; Chen, Shilin

2017-01-01

Herbal medicine is a major component of complementary and alternative medicine, contributing significantly to the health of many people and communities. Quality control of herbal medicine is crucial to ensure that it is safe and sound for use. Here, we investigated a comprehensive quality evaluation system for a classic herbal medicine, Danggui Buxue Formula, by applying genetic-based and analytical chemistry approaches to authenticate and evaluate the quality of its samples. For authenticity, we successfully applied two novel technologies, third-generation sequencing and PCR-DGGE (denaturing gradient gel electrophoresis), to analyze the ingredient composition of the tested samples. For quality evaluation, we used high performance liquid chromatography assays to determine the content of chemical markers to help estimate the dosage relationship between its two raw materials, plant roots of Huangqi and Danggui. A series of surveys were then conducted against several exogenous contaminations, aiming to further access the efficacy and safety of the samples. In conclusion, the quality evaluation system demonstrated here can potentially address the authenticity, quality, and safety of herbal medicines, thus providing novel insight for enhancing their overall quality control. Highlight: We established a comprehensive quality evaluation system for herbal medicine, by combining two genetic-based approaches third-generation sequencing and DGGE (denaturing gradient gel electrophoresis) with analytical chemistry approaches to achieve the authentication and quality connotation of the samples. PMID:28955365

Future possibilities in migraine genetics

DEFF Research Database (Denmark)

Rudkjøbing, Laura Aviaja; Esserlind, Ann-Louise; Olesen, Jes

2012-01-01

Migraine with and without aura (MA and MO, respectively) have a strong genetic basis. Different approaches using linkage-, candidate gene- and genome-wide association studies have been explored, yielding limited results. This may indicate that the genetic component in migraine is due to rare...... variants; capturing these will require more detailed sequencing in order to be discovered. Next-generation sequencing (NGS) techniques such as whole exome and whole genome sequencing have been successful in finding genes in especially monogenic disorders. As the molecular genetics research progresses......, the technology will follow, rendering these approaches more applicable in the search for causative migraine genes in MO and MA. To date, no studies using NGS in migraine genetics have been published. In order to gain insight into the future possibilities of migraine genetics, we have looked at NGS studies...

Process planning optimization on turning machine tool using a hybrid genetic algorithm with local search approach

Directory of Open Access Journals (Sweden)

Yuliang Su

2015-04-01

Full Text Available A turning machine tool is a kind of new type of machine tool that is equipped with more than one spindle and turret. The distinctive simultaneous and parallel processing abilities of turning machine tool increase the complexity of process planning. The operations would not only be sequenced and satisfy precedence constraints, but also should be scheduled with multiple objectives such as minimizing machining cost, maximizing utilization of turning machine tool, and so on. To solve this problem, a hybrid genetic algorithm was proposed to generate optimal process plans based on a mixed 0-1 integer programming model. An operation precedence graph is used to represent precedence constraints and help generate a feasible initial population of hybrid genetic algorithm. Encoding strategy based on data structure was developed to represent process plans digitally in order to form the solution space. In addition, a local search approach for optimizing the assignments of available turrets would be added to incorporate scheduling with process planning. A real-world case is used to prove that the proposed approach could avoid infeasible solutions and effectively generate a global optimal process plan.

Genetic technologies to enhance the Sterile Insect Technique (SIT)

International Nuclear Information System (INIS)

Alphey, Luke; Baker, Pam; Condon, George C.; Condon, Kirsty C.; Dafa'alla, Tarig H.; Fu, Guoliang; Jin, Li; Labbe, Genevieve; Morrison, Neil M.; Nimmo, Derric D.; O'Connell, Sinead; Phillips, Caroline E.; Plackett, Andrew; Scaife, Sarah; Woods, Alexander; Burton, Rosemary S.; Epton, Matthew J.; Gong, Peng

2006-01-01

The Sterile Insect Technique (SIT) has been used very successfully against range of pest insects, including various tephritid fruit flies, several moths and a small number of livestock pests. However, modern genetics could potentially provide several improvements that would increase the cost-effectiveness of SIT, and extend the range of suitable species. These include improved identification of released individuals by incorporation of a stable, heritable, genetic marker; built-in sex separation (genetic sexing); reduction of the hazard posed by non-irradiated accidental releases from mass-rearing facility (fail-safe); elimination of the need for sterilization by irradiation (genetic sterilization). We discuss applications of these methods and the state of the art, at the time of this meeting, in developing suitable strains. We have demonstrated, in several key pest species, that the required strains can be constructed by introducing a repressible dominant lethal genetic system, a method known as RIDL(trade mark). Based on field experience with Medfly, incorporation of a genetic sexing system into SIT programs for other tephritids could potentially provide a very significant improvement in cost-effectiveness. We have now been able to make efficient female-lethal strains for Medfly. One advantage of our approach is that it should be possible rapidly to extend this technology to other fruit fly species; indeed we have recently been able also to make genetic sexing strains of Medfly (Anastrepha ludens). (author)

Genetic technologies to enhance the Sterile Insect Technique (SIT)

Energy Technology Data Exchange (ETDEWEB)

Alphey, Luke; Baker, Pam; Condon, George C; Condon, Kirsty C; Dafa' alla, Tarig H; Fu, Guoliang; Jin, Li; Labbe, Genevieve; Morrison, Neil M; Nimmo, Derric D; O' Connell, Sinead; Phillips, Caroline E; Plackett, Andrew; Scaife, Sarah; Woods, Alexander [Oxitec Ltd., Oxford (United Kingdom); Burton, Rosemary S; Epton, Matthew J; Gong, Peng [University of Oxford (United Kingdom). Dept. of Zoology

2006-07-01

The Sterile Insect Technique (SIT) has been used very successfully against range of pest insects, including various tephritid fruit flies, several moths and a small number of livestock pests. However, modern genetics could potentially provide several improvements that would increase the cost-effectiveness of SIT, and extend the range of suitable species. These include improved identification of released individuals by incorporation of a stable, heritable, genetic marker; built-in sex separation (genetic sexing); reduction of the hazard posed by non-irradiated accidental releases from mass-rearing facility (fail-safe); elimination of the need for sterilization by irradiation (genetic sterilization). We discuss applications of these methods and the state of the art, at the time of this meeting, in developing suitable strains. We have demonstrated, in several key pest species, that the required strains can be constructed by introducing a repressible dominant lethal genetic system, a method known as RIDL(trade mark). Based on field experience with Medfly, incorporation of a genetic sexing system into SIT programs for other tephritids could potentially provide a very significant improvement in cost-effectiveness. We have now been able to make efficient female-lethal strains for Medfly. One advantage of our approach is that it should be possible rapidly to extend this technology to other fruit fly species; indeed we have recently been able also to make genetic sexing strains of Medfly (Anastrepha ludens). (author)

Concrete Plant Operations Optimization Using Combined Simulation and Genetic Algorithms

NARCIS (Netherlands)

Cao, Ming; Lu, Ming; Zhang, Jian-Ping

2004-01-01

This work presents a new approach for concrete plant operations optimization by combining a ready mixed concrete (RMC) production simulation tool (called HKCONSIM) with a genetic algorithm (GA) based optimization procedure. A revamped HKCONSIM computer system can be used to automate the simulation

Introduction: integrating genetic and cultural evolutionary approaches to language.

Science.gov (United States)

Mesoudi, Alex; McElligott, Alan G; Adger, David

2011-04-01

The papers in this special issue of Human Biology address recent research in the field of language evolution, both the genetic evolution of the language faculty and the cultural evolution of specific languages. While both of these areas have received increasing interest in recent years, there is also a need to integrate these somewhat separate efforts and explore the relevant gene-culture coevolutionary interactions. Here we summarize the individual contributions, set them in the context of the wider literature, and identify outstanding future research questions. The first set of papers concerns the comparative study of nonhuman communication in primates and birds from both a behavioral and neurobiological perspective, revealing evidence for several common language-related traits in various nonhuman species and providing clues as to the evolutionary origin and function of the human language faculty. The second set of papers discusses the consequences of viewing language as a culturally evolving system in its own right, including claims that this removes the need for strong genetic biases for language acquisition, and that phylogenetic evolutionary methods can be used to reconstruct language histories. We conclude by highlighting outstanding areas for future research, including identifying the precise selection pressures that gave rise to the language faculty in ancestral hominin species, and determining the strength, domain specificity, and origin of the cultural transmission biases that shape languages as they pass along successive generations of language learners.

Optimal inverse magnetorheological damper modeling using shuffled frog-leaping algorithm–based adaptive neuro-fuzzy inference system approach

Directory of Open Access Journals (Sweden)

Xiufang Lin

2016-08-01

Full Text Available Magnetorheological dampers have become prominent semi-active control devices for vibration mitigation of structures which are subjected to severe loads. However, the damping force cannot be controlled directly due to the inherent nonlinear characteristics of the magnetorheological dampers. Therefore, for fully exploiting the capabilities of the magnetorheological dampers, one of the challenging aspects is to develop an accurate inverse model which can appropriately predict the input voltage to control the damping force. In this article, a hybrid modeling strategy combining shuffled frog-leaping algorithm and adaptive-network-based fuzzy inference system is proposed to model the inverse dynamic characteristics of the magnetorheological dampers for improving the modeling accuracy. The shuffled frog-leaping algorithm is employed to optimize the premise parameters of the adaptive-network-based fuzzy inference system while the consequent parameters are tuned by a least square estimation method, here known as shuffled frog-leaping algorithm-based adaptive-network-based fuzzy inference system approach. To evaluate the effectiveness of the proposed approach, the inverse modeling results based on the shuffled frog-leaping algorithm-based adaptive-network-based fuzzy inference system approach are compared with those based on the adaptive-network-based fuzzy inference system and genetic algorithm–based adaptive-network-based fuzzy inference system approaches. Analysis of variance test is carried out to statistically compare the performance of the proposed methods and the results demonstrate that the shuffled frog-leaping algorithm-based adaptive-network-based fuzzy inference system strategy outperforms the other two methods in terms of modeling (training accuracy and checking accuracy.

Systemic-Functional Approach to Utilities Supplys

Directory of Open Access Journals (Sweden)

Nikolay I. Komkov

2017-01-01

Full Text Available Purpose: the purpose of the article consists in statement of management approach to development of utilities supply processes based on conflict situations decision – making search. It had appeared in the period of the transition from the planned and directive management to market development. Methods: the research methodology is based on the system analysis of full life cycle processes functioning, forecasting of complex systems development, mathematical modeling of processes of services supply and innovative and investment projects modeling as well as development of supplying services processes. Results: the results of the work are concentrated in the presentation of systemic-functional approach to managing the development of processes of municipal services, able to resolve conflict situations in this sphere. Conclusions and Relevance: the traditional management approach on the basis of elimination of "bottlenecks" and emergencies prevailing within planned and directive system at its transformation in the market conditions has led to accumulation of conflict situations and unsolvable problems. The offered systemic-functional approach based on forecasting of full life cycle of the modernized processes and the services providing systems allows to consider costs of modernization, prime cost and quality of the rendered services. 

Optimal Parameter Selection of Power System Stabilizer using Genetic Algorithm

Energy Technology Data Exchange (ETDEWEB)

Chung, Hyeng Hwan; Chung, Dong Il; Chung, Mun Kyu [Dong-AUniversity (Korea); Wang, Yong Peel [Canterbury Univeristy (New Zealand)

1999-06-01

In this paper, it is suggested that the selection method of optimal parameter of power system stabilizer (PSS) with robustness in low frequency oscillation for power system using real variable elitism genetic algorithm (RVEGA). The optimal parameters were selected in the case of power system stabilizer with one lead compensator, and two lead compensator. Also, the frequency responses characteristics of PSS, the system eigenvalues criterion and the dynamic characteristics were considered in the normal load and the heavy load, which proved usefulness of RVEGA compare with Yu's compensator design theory. (author). 20 refs., 15 figs., 8 tabs.

Pre-emptive resource-constrained multimode project scheduling using genetic algorithm: A dynamic forward approach

Directory of Open Access Journals (Sweden)

Aidin Delgoshaei

2016-09-01

Full Text Available Purpose: The issue resource over-allocating is a big concern for project engineers in the process of scheduling project activities. Resource over-allocating drawback is frequently seen after scheduling of a project in practice which causes a schedule to be useless. Modifying an over-allocated schedule is very complicated and needs a lot of efforts and time. In this paper, a new and fast tracking method is proposed to schedule large scale projects which can help project engineers to schedule the project rapidly and with more confidence. Design/methodology/approach: In this article, a forward approach for maximizing net present value (NPV in multi-mode resource constrained project scheduling problem while assuming discounted positive cash flows (MRCPSP-DCF is proposed. The progress payment method is used and all resources are considered as pre-emptible. The proposed approach maximizes NPV using unscheduled resources through resource calendar in forward mode. For this purpose, a Genetic Algorithm is applied to solve. Findings: The findings show that the proposed method is an effective way to maximize NPV in MRCPSP-DCF problems while activity splitting is allowed. The proposed algorithm is very fast and can schedule experimental cases with 1000 variables and 100 resources in few seconds. The results are then compared with branch and bound method and simulated annealing algorithm and it is found the proposed genetic algorithm can provide results with better quality. Then algorithm is then applied for scheduling a hospital in practice. Originality/value: The method can be used alone or as a macro in Microsoft Office Project® Software to schedule MRCPSP-DCF problems or to modify resource over-allocated activities after scheduling a project. This can help project engineers to schedule project activities rapidly with more accuracy in practice.

Implementation and Characterization of Dynamic Genetic Networks in Vitro

OpenAIRE

Niederholtmeyer, Henrike Marie

2015-01-01

Transcription and translation (TX-TL) can be performed in vitro, outside of cells, allowing the assembly and analysis of genetic networks. This approach to engineering biological networks in a less complex and more controllable environment could one day allow rapid prototyping of network designs before implementing them in living cells. Furthermore, the in vitro approach provides insight into how natural biological systems are built and is instructive to define the rules for engineering biolo...

Contribution of genetics to ecological restoration.

Science.gov (United States)

Mijangos, Jose Luis; Pacioni, Carlo; Spencer, Peter B S; Craig, Michael D

2015-01-01

Ecological restoration of degraded ecosystems has emerged as a critical tool in the fight to reverse and ameliorate the current loss of biodiversity and ecosystem services. Approaches derived from different genetic disciplines are extending the theoretical and applied frameworks on which ecological restoration is based. We performed a search of scientific articles and identified 160 articles that employed a genetic approach within a restoration context to shed light on the links between genetics and restoration. These articles were then classified on whether they examined association between genetics and fitness or the application of genetics in demographic studies, and on the way the studies informed restoration practice. Although genetic research in restoration is rapidly growing, we found that studies could make better use of the extensive toolbox developed by applied fields in genetics. Overall, 41% of reviewed studies used genetic information to evaluate or monitor restoration, and 59% provided genetic information to guide prerestoration decision-making processes. Reviewed studies suggest that restoration practitioners often overlook the importance of including genetic aspects within their restoration goals. Even though there is a genetic basis influencing the provision of ecosystem services, few studies explored this relationship. We provide a view of research gaps, future directions and challenges in the genetics of restoration. © 2014 John Wiley & Sons Ltd.

Book Review: Organizations: A Systems Approach

DEFF Research Database (Denmark)

Schoeneborn, Dennis

2016-01-01

Review of: Stefan Kühl: Organizations. A Systems Approach (trans. P. Schmitz). Farnham: Gower Publishing, 2013. 195 pp. £14.99. ISBN 9781472413413.......Review of: Stefan Kühl: Organizations. A Systems Approach (trans. P. Schmitz). Farnham: Gower Publishing, 2013. 195 pp. £14.99. ISBN 9781472413413....

A systems approach to traditional oriental medicine

DEFF Research Database (Denmark)

Kim, Hyun Uk; Ryu, Jae Yong; Lee, Jong Ok

2015-01-01

Analyzing structural similarities between compounds derived from traditional oriental medicine and human metabolites is a systems-based approach that can help identify mechanisms of action and suggest approaches to reduce toxicity.......Analyzing structural similarities between compounds derived from traditional oriental medicine and human metabolites is a systems-based approach that can help identify mechanisms of action and suggest approaches to reduce toxicity....

Genetic architecture of gene expression in ovine skeletal muscle

DEFF Research Database (Denmark)

Kogelman, Lisette Johanna Antonia; Byrne, Keren; Vuocolo, Tony

2011-01-01

architecture to the gene expression data, which also discriminated the sire-based Estimated Breeding Value for the trait. An integrated systems biology approach was then used to identify the major functional pathways contributing to the genetics of enhanced muscling by using both Estimated Breeding Value...... has potential, amongst other mechanisms, to alter gene expression via cis- or trans-acting mechanisms in a manner that impacts the functional activities of specific pathways that contribute to muscling traits. By integrating sire-based genetic merit information for a muscling trait with progeny...

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...

Multi-taxa integrated landscape genetics for zoonotic infectious diseases: deciphering variables influencing disease emergence.

Science.gov (United States)

Leo, Sarah S T; Gonzalez, Andrew; Millien, Virginie

2016-05-01

Zoonotic disease transmission systems involve sets of species interacting with each other and their environment. This complexity impedes development of disease monitoring and control programs that require reliable identification of spatial and biotic variables and mechanisms facilitating disease emergence. To overcome this difficulty, we propose a framework that simultaneously examines all species involved in disease emergence by integrating concepts and methods from population genetics, landscape ecology, and spatial statistics. Multi-taxa integrated landscape genetics (MTILG) can reveal how interspecific interactions and landscape variables influence disease emergence patterns. We test the potential of our MTILG-based framework by modelling the emergence of a disease system across multiple species dispersal, interspecific interaction, and landscape scenarios. Our simulations showed that both interspecific-dependent dispersal patterns and landscape characteristics significantly influenced disease spread. Using our framework, we were able to detect statistically similar inter-population genetic differences and highly correlated spatial genetic patterns that imply species-dependent dispersal. Additionally, species that were assigned coupled-dispersal patterns were affected to the same degree by similar landscape variables. This study underlines the importance of an integrated approach to investigating emergence of disease systems. MTILG is a robust approach for such studies and can identify potential avenues for targeted disease management strategies.

Current Trend Towards Using Soft Computing Approaches to Phase Synchronization in Communication Systems

Science.gov (United States)

Drake, Jeffrey T.; Prasad, Nadipuram R.

1999-01-01

This paper surveys recent advances in communications that utilize soft computing approaches to phase synchronization. Soft computing, as opposed to hard computing, is a collection of complementary methodologies that act in producing the most desirable control, decision, or estimation strategies. Recently, the communications area has explored the use of the principal constituents of soft computing, namely, fuzzy logic, neural networks, and genetic algorithms, for modeling, control, and most recently for the estimation of phase in phase-coherent communications. If the receiver in a digital communications system is phase-coherent, as is often the case, phase synchronization is required. Synchronization thus requires estimation and/or control at the receiver of an unknown or random phase offset.

A bio-cultural approach to the study of food choice: The contribution of taste genetics, population and culture.

Science.gov (United States)

Risso, Davide S; Giuliani, Cristina; Antinucci, Marco; Morini, Gabriella; Garagnani, Paolo; Tofanelli, Sergio; Luiselli, Donata

2017-07-01

The study of food choice, one of the most complex human traits, requires an integrated approach that takes into account environmental, socio-cultural and biological diversity. We recruited 183 volunteers from four geo-linguistic groups and highly diversified in terms of both genetic background and food habits from whom we collected genotypes and phenotypes tightly linked to taste perception. We confirmed previous genetic associations, in particular with stevioside perception, and noted significant differences in food consumption: in particular, broccoli, mustard and beer consumption scores were significantly higher (Adjusted P = 0.02, Adjusted P diversity and cultural aspects in taste perception and food consumption. Published by Elsevier Ltd.

New Approaches in Reuseable Booster System Life Cycle Cost Modeling

Science.gov (United States)

Zapata, Edgar

2013-01-01

This paper presents the results of a 2012 life cycle cost (LCC) study of hybrid Reusable Booster Systems (RBS) conducted by NASA Kennedy Space Center (KSC) and the Air Force Research Laboratory (AFRL). The work included the creation of a new cost estimating model and an LCC analysis, building on past work where applicable, but emphasizing the integration of new approaches in life cycle cost estimation. Specifically, the inclusion of industry processes/practices and indirect costs were a new and significant part of the analysis. The focus of LCC estimation has traditionally been from the perspective of technology, design characteristics, and related factors such as reliability. Technology has informed the cost related support to decision makers interested in risk and budget insight. This traditional emphasis on technology occurs even though it is well established that complex aerospace systems costs are mostly about indirect costs, with likely only partial influence in these indirect costs being due to the more visible technology products. Organizational considerations, processes/practices, and indirect costs are traditionally derived ("wrapped") only by relationship to tangible product characteristics. This traditional approach works well as long as it is understood that no significant changes, and by relation no significant improvements, are being pursued in the area of either the government acquisition or industry?s indirect costs. In this sense then, most launch systems cost models ignore most costs. The alternative was implemented in this LCC study, whereby the approach considered technology and process/practices in balance, with as much detail for one as the other. This RBS LCC study has avoided point-designs, for now, instead emphasizing exploring the trade-space of potential technology advances joined with potential process/practice advances. Given the range of decisions, and all their combinations, it was necessary to create a model of the original model

New Approaches in Reusable Booster System Life Cycle Cost Modeling

Science.gov (United States)

Zapata, Edgar

2013-01-01

This paper presents the results of a 2012 life cycle cost (LCC) study of hybrid Reusable Booster Systems (RBS) conducted by NASA Kennedy Space Center (KSC) and the Air Force Research Laboratory (AFRL). The work included the creation of a new cost estimating model and an LCC analysis, building on past work where applicable, but emphasizing the integration of new approaches in life cycle cost estimation. Specifically, the inclusion of industry processes/practices and indirect costs were a new and significant part of the analysis. The focus of LCC estimation has traditionally been from the perspective of technology, design characteristics, and related factors such as reliability. Technology has informed the cost related support to decision makers interested in risk and budget insight. This traditional emphasis on technology occurs even though it is well established that complex aerospace systems costs are mostly about indirect costs, with likely only partial influence in these indirect costs being due to the more visible technology products. Organizational considerations, processes/practices, and indirect costs are traditionally derived ("wrapped") only by relationship to tangible product characteristics. This traditional approach works well as long as it is understood that no significant changes, and by relation no significant improvements, are being pursued in the area of either the government acquisition or industry?s indirect costs. In this sense then, most launch systems cost models ignore most costs. The alternative was implemented in this LCC study, whereby the approach considered technology and process/practices in balance, with as much detail for one as the other. This RBS LCC study has avoided point-designs, for now, instead emphasizing exploring the trade-space of potential technology advances joined with potential process/practice advances. Given the range of decisions, and all their combinations, it was necessary to create a model of the original model

A genetic algorithm approach to optimization for the radiological worker allocation problem

International Nuclear Information System (INIS)

Yan Chen; Masakuni Narita; Masashi Tsuji; Sangduk Sa

1996-01-01

The worker allocation optimization problem in radiological facilities inevitably involves various types of requirements and constraints relevant to radiological protection and labor management. Some of these goals and constraints are not amenable to a rigorous mathematical formulation. Conventional methods for this problem rely heavily on sophisticated algebraic or numerical algorithms, which cause difficulties in the search for optimal solutions in the search space of worker allocation optimization problems. Genetic algorithms (GAB) are stochastic search algorithms introduced by J. Holland in the 1970s based on ideas and techniques from genetic and evolutionary theories. The most striking characteristic of GAs is the large flexibility allowed in the formulation of the optimal problem and the process of the search for the optimal solution. In the formulation, it is not necessary to define the optimal problem in rigorous mathematical terms, as required in the conventional methods. Furthermore, by designing a model of evolution for the optimal search problem, the optimal solution can be sought efficiently with computational simple manipulations without highly complex mathematical algorithms. We reported a GA approach to the worker allocation problem in radiological facilities in the previous study. In this study, two types of hard constraints were employed to reduce the huge search space, where the optimal solution is sought in such a way as to satisfy as many of soft constraints as possible. It was demonstrated that the proposed evolutionary method could provide the optimal solution efficiently compared with conventional methods. However, although the employed hard constraints could localize the search space into a very small region, it brought some complexities in the designed genetic operators and demanded additional computational burdens. In this paper, we propose a simplified evolutionary model with less restrictive hard constraints and make comparisons between

Stress-induced variation in evolution: from behavioural plasticity to genetic assimilation.

Science.gov (United States)

Badyaev, Alexander V

2005-05-07

Extreme environments are closely associated with phenotypic evolution, yet the mechanisms behind this relationship are poorly understood. Several themes and approaches in recent studies significantly further our understanding of the importance that stress-induced variation plays in evolution. First, stressful environments modify (and often reduce) the integration of neuroendocrinological, morphological and behavioural regulatory systems. Second, such reduced integration and subsequent accommodation of stress-induced variation by developmental systems enables organismal 'memory' of a stressful event as well as phenotypic and genetic assimilation of the response to a stressor. Third, in complex functional systems, a stress-induced increase in phenotypic and genetic variance is often directional, channelled by existing ontogenetic pathways. This accounts for similarity among individuals in stress-induced changes and thus significantly facilitates the rate of adaptive evolution. Fourth, accumulation of phenotypically neutral genetic variation might be a common property of locally adapted and complex organismal systems, and extreme environments facilitate the phenotypic expression of this variance. Finally, stress-induced effects and stress-resistance strategies often persist for several generations through maternal, ecological and cultural inheritance. These transgenerational effects, along with both the complexity of developmental systems and stressor recurrence, might facilitate genetic assimilation of stress-induced effects. Accumulation of phenotypically neutral genetic variance by developmental systems and phenotypic accommodation of stress-induced effects, together with the inheritance of stress-induced modifications, ensure the evolutionary persistence of stress-response strategies and provide a link between individual adaptability and evolutionary adaptation.

Neuro-genetic system for optimization of GMI samples sensitivity.

Science.gov (United States)

Pitta Botelho, A C O; Vellasco, M M B R; Hall Barbosa, C R; Costa Silva, E

2016-03-01

Magnetic sensors are largely used in several engineering areas. Among them, magnetic sensors based on the Giant Magnetoimpedance (GMI) effect are a new family of magnetic sensing devices that have a huge potential for applications involving measurements of ultra-weak magnetic fields. The sensitivity of magnetometers is directly associated with the sensitivity of their sensing elements. The GMI effect is characterized by a large variation of the impedance (magnitude and phase) of a ferromagnetic sample, when subjected to a magnetic field. Recent studies have shown that phase-based GMI magnetometers have the potential to increase the sensitivity by about 100 times. The sensitivity of GMI samples depends on several parameters, such as sample length, external magnetic field, DC level and frequency of the excitation current. However, this dependency is yet to be sufficiently well-modeled in quantitative terms. So, the search for the set of parameters that optimizes the samples sensitivity is usually empirical and very time consuming. This paper deals with this problem by proposing a new neuro-genetic system aimed at maximizing the impedance phase sensitivity of GMI samples. A Multi-Layer Perceptron (MLP) Neural Network is used to model the impedance phase and a Genetic Algorithm uses the information provided by the neural network to determine which set of parameters maximizes the impedance phase sensitivity. The results obtained with a data set composed of four different GMI sample lengths demonstrate that the neuro-genetic system is able to correctly and automatically determine the set of conditioning parameters responsible for maximizing their phase sensitivities. Copyright © 2015 Elsevier Ltd. All rights reserved.

Rail transport systems approach

CERN Document Server

2017-01-01

This book shows how the systems approach is employed by scientists in various countries to solve specific problems concerning railway transport. In particular, the book describes the experiences of scientists from Romania, Germany, the Czech Republic, the UK, Russia, Ukraine, Lithuania and Poland. For many of these countries there is a problem with the historical differences between the railways. In particular, there are railways with different rail gauges, with different signaling and communication systems, with different energy supplies and, finally, with different political systems, which are reflected in the different approaches to the management of railway economies. The book’s content is divided into two main parts, the first of which provides a systematic analysis of individual means of providing and maintaining rail transport. In turn, the second part addresses infrastructure and management development, with particular attention to security issues. Though primarily written for professionals involved...

Development of a Laboratory Information Management System for Medical Genetic Investigations (LIMS)

OpenAIRE

Albers, K.

2006-01-01

Studying the genetic factor underlying a set of diseases with modern high- throughput techniques generates huge amounts of data, posing a challenge for data management. In this thesis a database management system called FIDB based on MySQL was developed to handle clinical and experimental genetic data. For the convenience of the users, a web interface was developed to insert, update, delete and display the data. In addition security aspects were taken care of. Currently FIDB is able to organi...

Optimization of redundancy by using genetic algorithm for reliability of plant protection system

International Nuclear Information System (INIS)

Yoo, D. W.; Seong, S. H.; Kim, D. H.; Park, H. Y.; Gu, I. S.

2000-01-01

The design and development of a reliable protection system has been becoming a key issue in industry field because the reliability of system is considered as an important factor to perform the system's function successfully. Plant Protection System(PPS) guarantees the safety of plant by accident detection and control action against the transient conditions of plant. This paper presents the analysis of PPS reliability and the formal problem statement about optimal redundancy based on the reliability of PPS. And the optimization problem is solved by genetic algorithm. The genetic algorithm is a useful tool to solve the problems, in the case of large searching, complex gradient, existence local minimum. The effectiveness of the proposed optimization technique is proved by the target reliability of one channel of PPS, using the failure rate based on the MIL-HDBK-217

A genetic fuzzy system for unstable angina risk assessment.

Science.gov (United States)

Dong, Wei; Huang, Zhengxing; Ji, Lei; Duan, Huilong

2014-02-18

Unstable Angina (UA) is widely accepted as a critical phase of coronary heart disease with patients exhibiting widely varying risks. Early risk assessment of UA is at the center of the management program, which allows physicians to categorize patients according to the clinical characteristics and stratification of risk and different prognosis. Although many prognostic models have been widely used for UA risk assessment in clinical practice, a number of studies have highlighted possible shortcomings. One serious drawback is that existing models lack the ability to deal with the intrinsic uncertainty about the variables utilized. In order to help physicians refine knowledge for the stratification of UA risk with respect to vagueness in information, this paper develops an intelligent system combining genetic algorithm and fuzzy association rule mining. In detail, it models the input information's vagueness through fuzzy sets, and then applies a genetic fuzzy system on the acquired fuzzy sets to extract the fuzzy rule set for the problem of UA risk assessment. The proposed system is evaluated using a real data-set collected from the cardiology department of a Chinese hospital, which consists of 54 patient cases. 9 numerical patient features and 17 categorical patient features that appear in the data-set are selected in the experiments. The proposed system made the same decisions as the physician in 46 (out of a total of 54) tested cases (85.2%). By comparing the results that are obtained through the proposed system with those resulting from the physician's decision, it has been found that the developed model is highly reflective of reality. The proposed system could be used for educational purposes, and with further improvements, could assist and guide young physicians in their daily work.

Genetics of allergy and bronchial hyperresponsiveness

NARCIS (Netherlands)

Howard, TD; Wiesch, DG; Koppelman, GH; Postma, DS; Meyers, DA; Bleecker, ER

Allergy and asthma are closely related complex diseases caused by a combination of both genetic and environmental influences. Two common genetic approaches, candidate gene studies and genome-wide screens, have been used to localize and evaluate potential genetic factors that confer susceptibility or

Incorporating Functional Genomic Information in Genetic Association Studies Using an Empirical Bayes Approach.

Science.gov (United States)

Spencer, Amy V; Cox, Angela; Lin, Wei-Yu; Easton, Douglas F; Michailidou, Kyriaki; Walters, Kevin

2016-04-01

There is a large amount of functional genetic data available, which can be used to inform fine-mapping association studies (in diseases with well-characterised disease pathways). Single nucleotide polymorphism (SNP) prioritization via Bayes factors is attractive because prior information can inform the effect size or the prior probability of causal association. This approach requires the specification of the effect size. If the information needed to estimate a priori the probability density for the effect sizes for causal SNPs in a genomic region isn't consistent or isn't available, then specifying a prior variance for the effect sizes is challenging. We propose both an empirical method to estimate this prior variance, and a coherent approach to using SNP-level functional data, to inform the prior probability of causal association. Through simulation we show that when ranking SNPs by our empirical Bayes factor in a fine-mapping study, the causal SNP rank is generally as high or higher than the rank using Bayes factors with other plausible values of the prior variance. Importantly, we also show that assigning SNP-specific prior probabilities of association based on expert prior functional knowledge of the disease mechanism can lead to improved causal SNPs ranks compared to ranking with identical prior probabilities of association. We demonstrate the use of our methods by applying the methods to the fine mapping of the CASP8 region of chromosome 2 using genotype data from the Collaborative Oncological Gene-Environment Study (COGS) Consortium. The data we analysed included approximately 46,000 breast cancer case and 43,000 healthy control samples. © 2016 The Authors. *Genetic Epidemiology published by Wiley Periodicals, Inc.

Commercial dissemination approaches for solar home systems

Energy Technology Data Exchange (ETDEWEB)

Terrado, E.

1997-12-01

The author discusses the issue of providing solar home systems to primarily rural areas from the perspective of how to commercialize the process. He considers two different approaches, one an open market approach and the other an exclusive market approach. He describes examples of the exclusive market approach which are in process in Argentina and Brazil. Coming from a banking background, the business aspects are discussed in detail. He points out the strengths and weaknesses of both approaches toward developing such systems.

Optimised operation of an off-grid hybrid wind-diesel-battery system using genetic algorithm

International Nuclear Information System (INIS)

Gan, Leong Kit; Shek, Jonathan K.H.; Mueller, Markus A.

2016-01-01

Highlights: • Diesel generator’s operation is optimised in a hybrid wind-diesel-battery system. • Optimisation is performed using wind speed and load demand forecasts. • The objective is to maximise wind energy utilisation with limited battery storage. • Physical modelling approach (Simscape) is used to verify mathematical model. • Sensitivity analyses are performed with synthesised wind and load forecast errors. - Abstract: In an off-grid hybrid wind-diesel-battery system, the diesel generator is often not utilised efficiently, therefore compromising its lifetime. In particular, the general rule of thumb of running the diesel generator at more than 40% of its rated capacity is often unmet. This is due to the variation in power demand and wind speed which needs to be supplied by the diesel generator. In addition, the frequent start-stop of the diesel generator leads to additional mechanical wear and fuel wastage. This research paper proposes a novel control algorithm which optimises the operation of a diesel generator, using genetic algorithm. With a given day-ahead forecast of local renewable energy resource and load demand, it is possible to optimise the operation of a diesel generator, subjected to other pre-defined constraints. Thus, the utilisation of the renewable energy sources to supply electricity can be maximised. Usually, the optimisation studies of a hybrid system are being conducted through simple analytical modelling, coupled with a selected optimisation algorithm to seek the optimised solution. The obtained solution is not verified using a more realistic system model, for instance the physical modelling approach. This often led to the question of the applicability of such optimised operation being used in reality. In order to take a step further, model-based design using Simulink is employed in this research to perform a comparison through a physical modelling approach. The Simulink model has the capability to incorporate the electrical

Males and females contribute unequally to offspring genetic diversity in the polygynandrous mating system of wild boar.

Directory of Open Access Journals (Sweden)

Javier Pérez-González

Full Text Available The maintenance of genetic diversity across generations depends on both the number of reproducing males and females. Variance in reproductive success, multiple paternity and litter size can all affect the relative contributions of male and female parents to genetic variation of progeny. The mating system of the wild boar (Sus scrofa has been described as polygynous, although evidence of multiple paternity in litters has been found. Using 14 microsatellite markers, we evaluated the contribution of males and females to genetic variation in the next generation in independent wild boar populations from the Iberian Peninsula and Hungary. Genetic contributions of males and females were obtained by distinguishing the paternal and maternal genetic component inherited by the progeny. We found that the paternally inherited genetic component of progeny was more diverse than the maternally inherited component. Simulations showed that this finding might be due to a sampling bias. However, after controlling for the bias by fitting both the genetic diversity in the adult population and the number of reproductive individuals in the models, paternally inherited genotypes remained more diverse than those inherited maternally. Our results suggest new insights into how promiscuous mating systems can help maintain genetic variation.

The Conservative Physiology of the Immune System. A Non-Metaphoric Approach to Immunological Activity

Directory of Open Access Journals (Sweden)

Nelson M. Vaz

2006-01-01

Full Text Available Historically, immunology emerged as a biomedical science, concerned with host defense and production of anti-infectious vaccines. In the late 50s, selective theories were proposed and from then on, immunology has been based in a close association with the neo-Darwinian principles, such as random generation of variants (lymphocyte clones, selection by extrinsic factors (antigens—and, more generally, on genetic determinism and functionalism. This association has had major consequences: (1 immunological jargon is full of “cognitive” metaphors, founded in the idea of “foreignness”; (2 the immune system is described with a random clonal origin, coupled to selection by random encounters; and (3 physiological events are virtually absent from immunological descriptions. In the present manuscript, we apply systemic notions to bring forth an explanation including systemic mechanisms able to generate immunological phenomena. We replace “randomness plus selection” and the notion of foreignness by a history of structural changes which are determined by the coherences of the system internal architecture at any given moment. The importance of this systemic way of seeing is that it explicitly attends to the organization that defines the immune system, within which it is possible to describe the conservative physiology of the immune system. Understanding immune physiology in a systemic way of seeing also suggests mechanisms underlying the origin of immunopathogeny and therefore suggests new insights to therapeutic approaches. However, if seriously acknowledged, this systemic/historic approach to immunology goes along with a global conceptual change which modifies virtually everything in the domain of biology, as suggested by Maturana.

Comorbidity of Alcohol Use Disorder and Chronic Pain: Genetic Influences on Brain Reward and Stress Systems.

Science.gov (United States)

Yeung, Ellen W; Craggs, Jason G; Gizer, Ian R

2017-11-01

Alcohol use disorder (AUD) is highly comorbid with chronic pain (CP). Evidence has suggested that neuroadaptive processes characterized by reward deficit and stress surfeit are involved in the development of AUD and pain chronification. Neurological data suggest that shared genetic architecture associated with the reward and stress systems may contribute to the comorbidity of AUD and CP. This monograph first delineates the prevailing theories of the development of AUD and pain chronification focusing on the reward and stress systems. It then provides a brief summary of relevant neurological findings followed by an evaluation of evidence documented by molecular genetic studies. Candidate gene association studies have provided some initial support for the genetic overlap between AUD and CP; however, these results must be interpreted with caution until studies with sufficient statistical power are conducted and replications obtained. Genomewide association studies have suggested a number of genes (e.g., TBX19, HTR7, and ADRA1A) that are either directly or indirectly related to the reward and stress systems in the AUD and CP literature. Evidence reviewed in this monograph suggests that shared genetic liability underlying the comorbidity between AUD and CP, if present, is likely to be complex. As the advancement in molecular genetic methods continues, future studies may show broader central nervous system involvement in AUD-CP comorbidity. Copyright © 2017 by the Research Society on Alcoholism.

New approaches to the treatment of orphan genetic disorders: Mitigating molecular pathologies using chemicals

Directory of Open Access Journals (Sweden)

RENATA V. VELHO

2015-08-01

Full Text Available With the advance and popularization of molecular techniques, the identification of genetic mutations that cause diseases has increased dramatically. Thus, the number of laboratories available to investigate a given disorder and the number of subsequent diagnosis have increased over time. Although it is necessary to identify mutations and provide diagnosis, it is also critical to develop specific therapeutic approaches based on this information. This review aims to highlight recent advances in mutation-targeted therapies with chemicals that mitigate mutational pathology at the molecular level, for disorders that, for the most part, have no effective treatment. Currently, there are several strategies being used to correct different types of mutations, including the following: the identification and characterization of translational readthrough compounds; antisense oligonucleotide-mediated splicing redirection; mismatch repair; and exon skipping. These therapies and other approaches are reviewed in this paper.

New approaches to the treatment of orphan genetic disorders: Mitigating molecular pathologies using chemicals.

Science.gov (United States)

Velho, Renata V; Sperb-Ludwig, Fernanda; Schwartz, Ida V D

2015-08-01

With the advance and popularization of molecular techniques, the identification of genetic mutations that cause diseases has increased dramatically. Thus, the number of laboratories available to investigate a given disorder and the number of subsequent diagnosis have increased over time. Although it is necessary to identify mutations and provide diagnosis, it is also critical to develop specific therapeutic approaches based on this information. This review aims to highlight recent advances in mutation-targeted therapies with chemicals that mitigate mutational pathology at the molecular level, for disorders that, for the most part, have no effective treatment. Currently, there are several strategies being used to correct different types of mutations, including the following: the identification and characterization of translational readthrough compounds; antisense oligonucleotide-mediated splicing redirection; mismatch repair; and exon skipping. These therapies and other approaches are reviewed in this paper.

Biomedical visual data analysis to build an intelligent diagnostic decision support system in medical genetics.

Science.gov (United States)

Kuru, Kaya; Niranjan, Mahesan; Tunca, Yusuf; Osvank, Erhan; Azim, Tayyaba

2014-10-01

In general, medical geneticists aim to pre-diagnose underlying syndromes based on facial features before performing cytological or molecular analyses where a genotype-phenotype interrelation is possible. However, determining correct genotype-phenotype interrelationships among many syndromes is tedious and labor-intensive, especially for extremely rare syndromes. Thus, a computer-aided system for pre-diagnosis can facilitate effective and efficient decision support, particularly when few similar cases are available, or in remote rural districts where diagnostic knowledge of syndromes is not readily available. The proposed methodology, visual diagnostic decision support system (visual diagnostic DSS), employs machine learning (ML) algorithms and digital image processing techniques in a hybrid approach for automated diagnosis in medical genetics. This approach uses facial features in reference images of disorders to identify visual genotype-phenotype interrelationships. Our statistical method describes facial image data as principal component features and diagnoses syndromes using these features. The proposed system was trained using a real dataset of previously published face images of subjects with syndromes, which provided accurate diagnostic information. The method was tested using a leave-one-out cross-validation scheme with 15 different syndromes, each of comprised 5-9 cases, i.e., 92 cases in total. An accuracy rate of 83% was achieved using this automated diagnosis technique, which was statistically significant (pbenefits of using hybrid image processing and ML-based computer-aided diagnostics for identifying facial phenotypes. Copyright © 2014. Published by Elsevier B.V.

An Interpretation of Part of Gilbert Gottlieb's Legacy: Developmental Systems Theory Contra Developmental Behavior Genetics

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Molenaar, Peter C. M.

2015-01-01

The main theme of this paper concerns the persistent critique of Gilbert Gottlieb on developmental behavior genetics and my reactions to this critique, the latter changing from rejection to complete acceptation. Concise characterizations of developmental behavior genetics, developmental systems theory (to which Gottlieb made essential…

A Genetic Algorithm-based Antenna Selection Approach for Large-but-Finite MIMO Networks

KAUST Repository

Makki, Behrooz

2016-12-29

We study the performance of antenna selectionbased multiple-input-multiple-output (MIMO) networks with large but finite number of transmit antennas and receivers. Considering the continuous and bursty communication scenarios with different users’ data request probabilities, we develop an efficient antenna selection scheme using genetic algorithms (GA). As demonstrated, the proposed algorithm is generic in the sense that it can be used in the cases with different objective functions, precoding methods, levels of available channel state information and channel models. Our results show that the proposed GAbased algorithm reaches (almost) the same throughput as the exhaustive search-based optimal approach, with substantially less implementation complexity.

A Genetic Algorithm-based Antenna Selection Approach for Large-but-Finite MIMO Networks

KAUST Repository

Makki, Behrooz; Ide, Anatole; Svensson, Tommy; Eriksson, Thomas; Alouini, Mohamed-Slim

2016-01-01

We study the performance of antenna selectionbased multiple-input-multiple-output (MIMO) networks with large but finite number of transmit antennas and receivers. Considering the continuous and bursty communication scenarios with different users’ data request probabilities, we develop an efficient antenna selection scheme using genetic algorithms (GA). As demonstrated, the proposed algorithm is generic in the sense that it can be used in the cases with different objective functions, precoding methods, levels of available channel state information and channel models. Our results show that the proposed GAbased algorithm reaches (almost) the same throughput as the exhaustive search-based optimal approach, with substantially less implementation complexity.

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.

The relation between multilocus population genetics and social evolution theory.

Science.gov (United States)

Gardner, Andy; West, Stuart A; Barton, Nicholas H

2007-02-01

Evolution at multiple gene positions is complicated. Direct selection on one gene disturbs the evolutionary dynamics of associated genes. Recent years have seen the development of a multilocus methodology for modeling evolution at arbitrary numbers of gene positions with arbitrary dominance and epistatic relations, mode of inheritance, genetic linkage, and recombination. We show that the approach is conceptually analogous to social evolutionary methodology, which focuses on selection acting on associated individuals. In doing so, we (1) make explicit the links between the multilocus methodology and the foundations of social evolution theory, namely, Price's theorem and Hamilton's rule; (2) relate the multilocus approach to levels-of-selection and neighbor-modulated-fitness approaches in social evolution; (3) highlight the equivalence between genetical hitchhiking and kin selection; (4) demonstrate that the multilocus methodology allows for social evolutionary analyses involving coevolution of multiple traits and genetical associations between nonrelatives, including individuals of different species; (5) show that this methodology helps solve problems of dynamic sufficiency in social evolution theory; (6) form links between invasion criteria in multilocus systems and Hamilton's rule of kin selection; (7) illustrate the generality and exactness of Hamilton's rule, which has previously been described as an approximate, heuristic result.

The influence of genetic selection and feed system on the reproductive performance of spring-calving dairy cows within future pasture-based production systems.

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Coleman, J; Pierce, K M; Berry, D P; Brennan, A; Horan, B

2009-10-01

Three genetic groups of Holstein-Friesian dairy cows were established from within the Moorepark (Teagasc, Ireland) dairy research herd: LowNA, indicative of the Irish national average-genetic-merit North American Holstein-Friesian; HighNA, high-genetic-merit North American Holstein-Friesian; HighNZ, high-genetic-merit New Zealand Holstein-Friesian. Genetic merit in this study was based on the Irish total merit index, the Economic Breeding Index. Animals from within each genetic group were randomly allocated to 1 of 2 possible post-European Union-milk-quota pasture-based feeding systems (FS): 1) The Moorepark (MP) pasture system (2.64 cows/ha and 500 kg of concentrate supplement per cow per lactation) and 2) a high output per hectare (HC) pasture system (2.85 cows/ha and 1,200 kg of concentrate supplement per cow per lactation). A total of 126, 128, and 140 spring-calving dairy cows were used during the years 2006, 2007, and 2008, respectively. Each group had an individual farmlet of 17 paddocks, and all groups were managed similarly throughout the study. The effects of genetic group, FS, and the interaction between genetic group and FS on reproductive performance, body weight, body condition score, and blood metabolite concentrations were studied using mixed models with factorial arrangements of genetic groups and FS. Odds ratios were used in the analysis of binary fertility traits, and survival analysis was used in the analysis of survival after first calving. When treatment means were compared, the HighNA and HighNZ genotypes (with greater genetic merit for fertility performance) had greater first-service pregnancy rates and had a greater proportion of cows pregnant after 42 d of the breeding season than the LowNA group. Both HighNA and HighNZ genotypes were submitted for artificial insemination earlier in the breeding season and had greater survival than the LowNA genotype. There was no significant FS or genotype by FS interactions for any of the reproductive