Eye growth and myopia development: Unifying theory and Matlab model.

PubMed

Hung, George K; Mahadas, Kausalendra; Mohammad, Faisal

2016-03-01

The aim of this article is to present an updated unifying theory of the mechanisms underlying eye growth and myopia development. A series of model simulation programs were developed to illustrate the mechanism of eye growth regulation and myopia development. Two fundamental processes are presumed to govern the relationship between physiological optics and eye growth: genetically pre-programmed signaling and blur feedback. Cornea/lens is considered to have only a genetically pre-programmed component, whereas eye growth is considered to have both a genetically pre-programmed and a blur feedback component. Moreover, based on the Incremental Retinal-Defocus Theory (IRDT), the rate of change of blur size provides the direction for blur-driven regulation. The various factors affecting eye growth are shown in 5 simulations: (1 - unregulated eye growth): blur feedback is rendered ineffective, as in the case of form deprivation, so there is only genetically pre-programmed eye growth, generally resulting in myopia; (2 - regulated eye growth): blur feedback regulation demonstrates the emmetropization process, with abnormally excessive or reduced eye growth leading to myopia and hyperopia, respectively; (3 - repeated near-far viewing): simulation of large-to-small change in blur size as seen in the accommodative stimulus/response function, and via IRDT as well as nearwork-induced transient myopia (NITM), leading to the development of myopia; (4 - neurochemical bulk flow and diffusion): release of dopamine from the inner plexiform layer of the retina, and the subsequent diffusion and relay of neurochemical cascade show that a decrease in dopamine results in a reduction of proteoglycan synthesis rate, which leads to myopia; (5 - Simulink model): model of genetically pre-programmed signaling and blur feedback components that allows for different input functions to simulate experimental manipulations that result in hyperopia, emmetropia, and myopia. These model simulation programs (available upon request) can provide a useful tutorial for the general scientist and serve as a quantitative tool for researchers in eye growth and myopia. Copyright © 2016 Elsevier Ltd. All rights reserved.

An analysis of indirect genetic effects on adult body weight of the Pacific white shrimp Litopenaeus vannamei at low rearing density.

PubMed

Luan, Sheng; Luo, Kun; Chai, Zhan; Cao, Baoxiang; Meng, Xianhong; Lu, Xia; Liu, Ning; Xu, Shengyu; Kong, Jie

2015-12-14

Our aim was to estimate the genetic parameters for the direct genetic effect (DGE) and indirect genetic effects (IGE) on adult body weight in the Pacific white shrimp. IGE is the heritable effect of an individual on the trait values of its group mates. To examine IGE on body weight, 4725 shrimp from 105 tagged families were tested in multiple small test groups (MSTG). Each family was separated into three groups (15 shrimp per group) that were randomly assigned to 105 concrete tanks with shrimp from two other families. To estimate breeding values, one large test group (OLTG) in a 300 m(2) circular concrete tank was used for the communal rearing of 8398 individuals from 105 families. Body weight was measured after a growth-test period of more than 200 days. Variance components for body weight in the MSTG programs were estimated using an animal model excluding or including IGE whereas variance components in the OLTG programs were estimated using a conventional animal model that included only DGE. The correlation of DGE between MSTG and OLTG programs was estimated by a two-trait animal model that included or excluded IGE. Heritability estimates for body weight from the conventional animal model in MSTG and OLTG programs were 0.26 ± 0.13 and 0.40 ± 0.06, respectively. The log likelihood ratio test revealed significant IGE on body weight. Total heritable variance was the sum of direct genetic variance (43.5%), direct-indirect genetic covariance (2.1%), and indirect genetic variance (54.4%). It represented 73% of the phenotypic variance and was more than two-fold greater than that (32%) obtained by using a classical heritability model for body weight. Correlations of DGE on body weight between MSTG and OLTG programs were intermediate regardless of whether IGE were included or not in the model. Our results suggest that social interactions contributed to a large part of the heritable variation in body weight. Small and non-significant direct-indirect genetic correlations implied that neutral or slightly cooperative heritable interactions, rather than competition, were dominant in this population but this may be due to the low rearing density.

Postdoctoral Fellow | Center for Cancer Research

Cancer.gov

The Genetics of Cancer Susceptibility Section in the Mouse Cancer Genetics Program at NCI is seeking a highly motivated postdoctoral researcher to identify novel genetic interactors of BRCA2 using CRISPR-based genetic screen in mouse embryonic stem cells and perform functional studies in mouse models.

A Model Program for Translational Medicine in Epilepsy Genetics

PubMed Central

Smith, Lacey A.; Ullmann, Jeremy F. P.; Olson, Heather E.; El Achkar, Christelle M.; Truglio, Gessica; Kelly, McKenna; Rosen-Sheidley, Beth; Poduri, Annapurna

2017-01-01

Recent technological advances in gene sequencing have led to a rapid increase in gene discovery in epilepsy. However, the ability to assess pathogenicity of variants, provide functional analysis, and develop targeted therapies has not kept pace with rapid advances in sequencing technology. Thus, although clinical genetic testing may lead to a specific molecular diagnosis for some patients, test results often lead to more questions than answers. As the field begins to focus on therapeutic applications of genetic diagnoses using precision medicine, developing processes that offer more than equivocal test results is essential. The success of precision medicine in epilepsy relies on establishing a correct genetic diagnosis, analyzing functional consequences of genetic variants, screening potential therapeutics in the preclinical laboratory setting, and initiating targeted therapy trials for patients. We describe the structure of a comprehensive, pediatric Epilepsy Genetics Program that can serve as a model for translational medicine in epilepsy. PMID:28056630

Information Business: Applying Infometry (Informational Geometry) in Cognitive Coordination and Genetic Programming for Electronic Information Packaging and Marketing.

ERIC Educational Resources Information Center

Tsai, Bor-sheng

1994-01-01

Describes the use of infometry, or informational geometry, to meet the challenges of information service businesses. Highlights include theoretical models for cognitive coordination and genetic programming; electronic information packaging; marketing electronic information products, including cost-benefit analyses; and recapitalization, including…

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

PubMed

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

2015-10-01

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

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

NASA Astrophysics Data System (ADS)

Sastry, Kumara Narasimha

2007-03-01

Effective and efficient rnultiscale modeling is essential to advance both the science and synthesis in a, wide array of fields such as physics, chemistry, materials science; biology, biotechnology and pharmacology. This study investigates the efficacy and potential of rising genetic algorithms for rnultiscale materials modeling and addresses some of the challenges involved in designing competent algorithms that solve hard problems quickly, reliably and accurately. In particular, this thesis demonstrates the use of genetic algorithms (GAs) and genetic programming (GP) in multiscale modeling with the help of two non-trivial case studies in materials science and chemistry. The first case study explores the utility of genetic programming (GP) in multi-timescaling alloy kinetics simulations. In essence, GP is used to bridge molecular dynamics and kinetic Monte Carlo methods to span orders-of-magnitude in simulation time. Specifically, GP is used to regress symbolically an inline barrier function from a limited set of molecular dynamics simulations to enable kinetic Monte Carlo that simulate seconds of real time. Results on a non-trivial example of vacancy-assisted migration on a surface of a face-centered cubic (fcc) Copper-Cobalt (CuxCo 1-x) alloy show that GP predicts all barriers with 0.1% error from calculations for less than 3% of active configurations, independent of type of potentials used to obtain the learning set of barriers via molecular dynamics. The resulting method enables 2--9 orders-of-magnitude increase in real-time dynamics simulations taking 4--7 orders-of-magnitude less CPU time. The second case study presents the application of multiobjective genetic algorithms (MOGAs) in multiscaling quantum chemistry simulations. Specifically, MOGAs are used to bridge high-level quantum chemistry and semiempirical methods to provide accurate representation of complex molecular excited-state and ground-state behavior. Results on ethylene and benzene---two common building blocks in organic chemistry---indicate that MOGAs produce High-quality semiempirical methods that (1) are stable to small perturbations, (2) yield accurate configuration energies on untested and critical excited states, and (3) yield ab initio quality excited-state dynamics. The proposed method enables simulations of more complex systems to realistic, multi-picosecond timescales, well beyond previous attempts or expectation of human experts, and 2--3 orders-of-magnitude reduction in computational cost. While the two applications use simple evolutionary operators, in order to tackle more complex systems, their scalability and limitations have to be investigated. The second part of the thesis addresses some of the challenges involved with a successful design of genetic algorithms and genetic programming for multiscale modeling. The first issue addressed is the scalability of genetic programming, where facetwise models are built to assess the population size required by GP to ensure adequate supply of raw building blocks and also to ensure accurate decision-making between competing building blocks. This study also presents a design of competent genetic programming, where traditional fixed recombination operators are replaced by building and sampling probabilistic models of promising candidate programs. The proposed scalable GP, called extended compact GP (eCGP), combines the ideas from extended compact genetic algorithm (eCGA) and probabilistic incremental program evolution (PIPE) and adaptively identifies, propagates and exchanges important subsolutions of a search problem. Results show that eCGP scales cubically with problem size on both GP-easy and GP-hard problems. Finally, facetwise models are developed to explore limitations of scalability of MOGAs, where the scalability of multiobjective algorithms in reliably maintaining Pareto-optimal solutions is addressed. The results show that even when the building blocks are accurately identified, massive multimodality of the search problems can easily overwhelm the nicher (diversity preserving operator) and lead to exponential scale-up. Facetwise models are developed, which incorporate the combined effects of model accuracy, decision making, and sub-structure supply, as well as the effect of niching on the population sizing, to predict a limit on the growth rate of a maximum number of sub-structures that can compete in the two objectives to circumvent the failure of the niching method. The results show that if the number of competing building blocks between multiple objectives is less than the proposed limit, multiobjective GAs scale-up polynomially with the problem size on boundedly-difficult problems.

Developing a Model of Advanced Training to Promote Career Advancement for Certified Genetic Counselors: An Investigation of Expanded Skills, Advanced Training Paths, and Professional Opportunities.

PubMed

Baty, Bonnie J; Trepanier, Angela; Bennett, Robin L; Davis, Claire; Erby, Lori; Hippman, Catriona; Lerner, Barbara; Matthews, Anne; Myers, Melanie F; Robbins, Carol B; Singletary, Claire N

2016-08-01

There are currently multiple paths through which genetic counselors can acquire advanced knowledge and skills. However, outside of continuing education opportunities, there are few formal training programs designed specifically for the advanced training of genetic counselors. In the genetic counseling profession, there is currently considerable debate about the paths that should be available to attain advanced skills, as well as the skills that might be needed for practice in the future. The Association of Genetic Counseling Program Directors (AGCPD) convened a national committee, the Committee on Advanced Training for Certified Genetic Counselors (CATCGC), to investigate varied paths to post-master's training and career development. The committee began its work by developing three related grids that view career advancement from the viewpoints of the skills needed to advance (skills), ways to obtain these skills (paths), and existing genetic counselor positions that offer career change or advancement (positions). Here we describe previous work related to genetic counselor career advancement, the charge of the CATCGC, our preliminary work in developing a model through which to view genetic counselor advanced training and career advancement opportunities, and our next steps in further developing and disseminating the model.

Systems Engineering Design Via Experimental Operation Research: Complex Organizational Metric for Programmatic Risk Environments (COMPRE)

NASA Technical Reports Server (NTRS)

Mog, Robert A.

1999-01-01

Unique and innovative graph theory, neural network, organizational modeling, and genetic algorithms are applied to the design and evolution of programmatic and organizational architectures. Graph theory representations of programs and organizations increase modeling capabilities and flexibility, while illuminating preferable programmatic/organizational design features. Treating programs and organizations as neural networks results in better system synthesis, and more robust data modeling. Organizational modeling using covariance structures enhances the determination of organizational risk factors. Genetic algorithms improve programmatic evolution characteristics, while shedding light on rulebase requirements for achieving specified technological readiness levels, given budget and schedule resources. This program of research improves the robustness and verifiability of systems synthesis tools, including the Complex Organizational Metric for Programmatic Risk Environments (COMPRE).

Mendelian Genetics: Paradigm, Conjecture, or Research Program.

ERIC Educational Resources Information Center

Oldham, V.; Brouwer, W.

1984-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Reprogramming: A Preventive Strategy in Hypertension Focusing on the Kidney

PubMed Central

Tain, You-Lin; Joles, Jaap A.

2015-01-01

Adulthood hypertension can be programmed in response to a suboptimal environment in early life. However, developmental plasticity also implies that one can prevent hypertension in adult life by administrating appropriate compounds during early development. We have termed this reprogramming. While the risk of hypertension has been assessed in many mother-child cohorts of human developmental programming, interventions necessary to prove causation and provide a reprogramming strategy are lacking. Since the developing kidney is particularly vulnerable to environmental insults and blood pressure is determined by kidney function, renal programming is considered key in developmental programming of hypertension. Common pathways, whereby both genetic and acquired developmental programming converge into the same phenotype, have been recognized. For instance, the same reprogramming interventions aimed at shifting nitric oxide (NO)-reactive oxygen species (ROS) balance, such as perinatal citrulline or melatonin supplements, can be protective in both genetic and developmentally programmed hypertension. Furthermore, a significantly increased expression of gene Ephx2 (soluble epoxide hydrolase) was noted in both genetic and acquired animal models of hypertension. Since a suboptimal environment is often multifactorial, such common reprogramming pathways are a practical finding for translation to the clinic. This review provides an overview of potential clinical applications of reprogramming strategies to prevent programmed hypertension. We emphasize the kidney in the following areas: mechanistic insights from human studies and animal models to interpret programmed hypertension; identified risk factors of human programmed hypertension from mother-child cohorts; and the impact of reprogramming strategies on programmed hypertension from animal models. It is critical that the observed effects on developmental reprogramming in animal models are replicated in human studies. PMID:26712746

Breeding strategies for north central tree improvement programs

Treesearch

Ronald P. Overton; Hyun Kang

1985-01-01

The rationales and concepts of long-term tree breeding are discussed and compared with those for short-term breeding. A model breeding program is reviewed which maximizes short-term genetic gain for currently important traits and provides genetic resources that can be used effectively in future short-term breeding. The resources of the north-central region are examined...

Modeling the Volcanic Source at Long Valley, CA, Using a Genetic Algorithm Technique

NASA Technical Reports Server (NTRS)

Tiampo, Kristy F.

1999-01-01

In this project, we attempted to model the deformation pattern due to the magmatic source at Long Valley caldera using a real-value coded genetic algorithm (GA) inversion similar to that found in Michalewicz, 1992. The project has been both successful and rewarding. The genetic algorithm, coded in the C programming language, performs stable inversions over repeated trials, with varying initial and boundary conditions. The original model used a GA in which the geophysical information was coded into the fitness function through the computation of surface displacements for a Mogi point source in an elastic half-space. The program was designed to invert for a spherical magmatic source - its depth, horizontal location and volume - using the known surface deformations. It also included the capability of inverting for multiple sources.

Neural Correlates of the Y Chromosome in Autism: XYY Syndrome as a Genetic Model

DTIC Science & Technology

2017-09-01

AWARD NUMBER: W81XWH-15-1-0354 TITLE: Neural correlates of the Y chromosome in autism: XYY Syndrome as Genetic Model PRINCIPAL INVESTIGATOR...0354 XYY Syndrome as a Genetic Model 5b. GRANT NUMBER 15T c. PROGRAM ELEMENT NUMBER 15T6. AUTHOR(S) Timothy Roberts 15T d. PROJECT NUMBER Judith...remaining 12 months of this award. 15T 5. SUBJECT TERMS Autism spectrum disorder, ASD; 47,XYY syndrome (XYY); neuroimaging; MRI; MEG; Comorbid behaviors

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

NASA Astrophysics Data System (ADS)

Ravansalar, Masoud; Rajaee, Taher; Kisi, Ozgur

2017-06-01

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

CDFISH: an individual-based, spatially-explicit, landscape genetics simulator for aquatic species in complex riverscapes

USGS Publications Warehouse

Erin L. Landguth,; Muhlfeld, Clint C.; Luikart, Gordon

2012-01-01

We introduce Cost Distance FISHeries (CDFISH), a simulator of population genetics and connectivity in complex riverscapes for a wide range of environmental scenarios of aquatic organisms. The spatially-explicit program implements individual-based genetic modeling with Mendelian inheritance and k-allele mutation on a riverscape with resistance to movement. The program simulates individuals in subpopulations through time employing user-defined functions of individual migration, reproduction, mortality, and dispersal through straying on a continuous resistance surface.

The Alberta Hereditary Diseases Program: a regional model for delivery of genetic services.

PubMed Central

Lowry, R B; Bowen, P

1990-01-01

Genetic counselling and related services are generally provided at major university medical centres because they are very specialized. The need for rurally based genetic services prompted the inclusion of an outreached program in the Alberta Hereditary Diseases Program (AHDP), which was established in 1979; the AHDP was designed to provide services to the entire province through two regional centres and seven outreach clinics. There is a community health nurse in almost every health unit whose duties are either totally or partially devoted to the AHDP; thus, genetic help and information are as close as a rural health unit. The AHDP is designed to provide complete clinical (diagnostic, counselling and some management) services and laboratory (cytogenetic, biochemical and molecular) services for genetic disorders. In addition, the program emphasizes education and publishes a quarterly bulletin, which is sent free of charge to all physicians, hospitals, public health units, social service units, major radio and television stations, newspapers and public libraries and to selected individuals and groups in Alberta. PMID:2302614

Streamflow prediction using multi-site rainfall obtained from hydroclimatic teleconnection

NASA Astrophysics Data System (ADS)

Kashid, S. S.; Ghosh, Subimal; Maity, Rajib

2010-12-01

SummarySimultaneous variations in weather and climate over widely separated regions are commonly known as "hydroclimatic teleconnections". Rainfall and runoff patterns, over continents, are found to be significantly teleconnected, with large-scale circulation patterns, through such hydroclimatic teleconnections. Though such teleconnections exist in nature, it is very difficult to model them, due to their inherent complexity. Statistical techniques and Artificial Intelligence (AI) tools gain popularity in modeling hydroclimatic teleconnection, based on their ability, in capturing the complicated relationship between the predictors (e.g. sea surface temperatures) and predictand (e.g., rainfall). Genetic Programming is such an AI tool, which is capable of capturing nonlinear relationship, between predictor and predictand, due to its flexible functional structure. In the present study, gridded multi-site weekly rainfall is predicted from El Niño Southern Oscillation (ENSO) indices, Equatorial Indian Ocean Oscillation (EQUINOO) indices, Outgoing Longwave Radiation (OLR) and lag rainfall at grid points, over the catchment, using Genetic Programming. The predicted rainfall is further used in a Genetic Programming model to predict streamflows. The model is applied for weekly forecasting of streamflow in Mahanadi River, India, and satisfactory performance is observed.

Creation of a National, At-home Model for Ashkenazi Jewish Carrier Screening.

PubMed

Grinzaid, Karen Arnovitz; Page, Patricia Zartman; Denton, Jessica Johnson; Ginsberg, Jessica

2015-06-01

Ethnicity-based carrier screening for the Ashkenazi Jewish population has been available and encouraged by advocacy and community groups since the early 1970's. Both the American College of Medical Genetics and the American Congress of Obstetricians and Gynecologists recommend carrier screening for this population (Obstetrics and Gynecology, 114(4), 950-953, 2009; Genetics in Medicine, 10(1), 55-56, 2008). While many physicians inquire about ethnic background and offer appropriate carrier screening, studies show that a gap remains in implementing recommendations (Genetic testing and molecular biomarkers, 2011). In addition, education and outreach efforts targeting Jewish communities have had limited success in reaching this at-risk population. Despite efforts by the medical and Jewish communities, many Jews of reproductive age are not aware of screening, and remain at risk for having children with preventable diseases. Reaching this population, preferably pre-conception, and facilitating access to screening is critically important. To address this need, genetic counselors at Emory University developed JScreen, a national Jewish genetic disease screening program. The program includes a national marketing and PR campaign, online education, at-home saliva-based screening, post-test genetic counseling via telephone or secure video conferencing, and referrals for face-to-face genetic counseling as needed. Our goals are to create a successful education and screening program for this population and to develop a model that could potentially be used for other at-risk populations.

Efficient identification and referral of low-income women at high risk for hereditary breast cancer: a practice-based approach.

PubMed

Joseph, G; Kaplan, C; Luce, J; Lee, R; Stewart, S; Guerra, C; Pasick, R

2012-01-01

Identification of low-income women with the rare but serious risk of hereditary cancer and their referral to appropriate services presents an important public health challenge. We report the results of formative research to reach thousands of women for efficient identification of those at high risk and expedient access to free genetic services. External validity is maximized by emphasizing intervention fit with the two end-user organizations who must connect to make this possible. This study phase informed the design of a subsequent randomized controlled trial. We conducted a randomized controlled pilot study (n = 38) to compare two intervention models for feasibility and impact. The main outcome was receipt of genetic counseling during a two-month intervention period. Model 1 was based on the usual outcall protocol of an academic hospital genetic risk program, and Model 2 drew on the screening and referral procedures of a statewide toll-free phone line through which large numbers of high-risk women can be identified. In Model 1, the risk program proactively calls patients to schedule genetic counseling; for Model 2, women are notified of their eligibility for counseling and make the call themselves. We also developed and pretested a family history screener for administration by phone to identify women appropriate for genetic counseling. There was no statistically significant difference in receipt of genetic counseling between women randomized to Model 1 (3/18) compared with Model 2 (3/20) during the intervention period. However, when unresponsive women in Model 2 were called after 2 months, 7 more obtained counseling; 4 women from Model 1 were also counseled after the intervention. Thus, the intervention model that closely aligned with the risk program's outcall to high-risk women was found to be feasible and brought more low-income women to free genetic counseling. Our screener was easy to administer by phone and appeared to identify high-risk callers effectively. The model and screener are now in use in the main trial to test the effectiveness of this screening and referral intervention. A validation analysis of the screener is also underway. Identification of intervention strategies and tools, and their systematic comparison for impact and efficiency in the context where they will ultimately be used are critical elements of practice-based research. Copyright © 2012 S. Karger AG, Basel.

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

NASA Astrophysics Data System (ADS)

Danandeh Mehr, Ali; Kahya, Ercan

2017-06-01

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

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

PubMed

Catania, Francesco; Schmitz, Jürgen

2015-01-01

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

Stream Flow Prediction by Remote Sensing and Genetic Programming

NASA Technical Reports Server (NTRS)

Chang, Ni-Bin

2009-01-01

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

Evidence for transgenerational metabolic programming in Drosophila

PubMed Central

Buescher, Jessica L.; Musselman, Laura P.; Wilson, Christina A.; Lang, Tieming; Keleher, Madeline; Baranski, Thomas J.; Duncan, Jennifer G.

2013-01-01

SUMMARY Worldwide epidemiologic studies have repeatedly demonstrated an association between prenatal nutritional environment, birth weight and susceptibility to adult diseases including obesity, cardiovascular disease and type 2 diabetes. Despite advances in mammalian model systems, the molecular mechanisms underlying this phenomenon are unclear, but might involve programming mechanisms such as epigenetics. Here we describe a new system for evaluating metabolic programming mechanisms using a simple, genetically tractable Drosophila model. We examined the effect of maternal caloric excess on offspring and found that a high-sugar maternal diet alters body composition of larval offspring for at least two generations, augments an obese-like phenotype under suboptimal (high-calorie) feeding conditions in adult offspring, and modifies expression of metabolic genes. Our data indicate that nutritional programming mechanisms could be highly conserved and support the use of Drosophila as a model for evaluating the underlying genetic and epigenetic contributions to this phenomenon. PMID:23649823

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

PubMed

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

2017-02-01

We compared the outcome of mating programs based on different evaluation models that included nonadditive genetic effects (dominance and heterozygosity) in addition to additive effects. The additive and dominance marker effects and the values of regression on average heterozygosity were estimated using 632,003 single nucleotide polymorphisms from 7,902 and 7,510 Holstein cows with calving interval and production (milk, fat, and protein yields) records, respectively. Expected progeny values were computed based on the estimated genetic effects and genotype probabilities of hypothetical progeny from matings between the available genotyped cows and the top 50 young genomic bulls. An index combining the traits based on their economic values was developed and used to evaluate the performance of different mating scenarios in terms of dollar profit. We observed that mating programs with nonadditive genetic effects performed better than a model with only additive effects. Mating programs with dominance and heterozygosity effects increased milk, fat, and protein yields by up to 38, 1.57, and 1.21 kg, respectively. The inclusion of dominance and heterozygosity effects decreased calving interval by up to 0.70 d compared with random mating. The average reduction in progeny inbreeding by the inclusion of nonadditive genetic effects in matings compared with random mating was between 0.25 to 1.57 and 0.64 to 1.57 percentage points for calving interval and production traits, respectively. The reduction in inbreeding was accompanied by an average of A$8.42 (Australian dollars) more profit per mating for a model with additive, dominance, and heterozygosity effects compared with random mating. Mate allocations that benefit from nonadditive genetic effects can improve progeny performance only in the generation where it is being implemented, and the gain from specific combining abilities cannot be accumulated over generations. Continuous updating of genomic predictions and mate allocation programs are required to benefit from nonadditive genetic effects in the long term. The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

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

NASA Astrophysics Data System (ADS)

Chung, K. K.; Do, D. Q.

2010-09-01

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

Relieving the Bottleneck: An Investigation of Barriers to Expansion of Supervision Networks at Genetic Counseling Training Programs.

PubMed

Berg, Jordan; Hoskovec, Jennifer; Hashmi, S Shahrukh; McCarthy Veach, Patricia; Ownby, Allison; Singletary, Claire N

2018-02-01

Rapid growth in the demand for genetic counselors has led to a workforce shortage. There is a prevailing assumption that the number of training slots for genetic counseling students is linked to the availability of clinical supervisors. This study aimed to determine and compare barriers to expansion of supervision networks at genetic counseling training programs as perceived by supervisors, non-supervisors, and Program Directors. Genetic counselors were recruited via National Society of Genetic Counselors e-blast; Program Directors received personal emails. Online surveys were completed by 216 supervisors, 98 non-supervisors, and 23 Program Directors. Respondents rated impact of 35 barriers; comparisons were made using Kruskal-Wallis and Wilcoxon ranked sum tests. Half of supervisors (51%) indicated willingness to increase supervision. All non-supervisors were willing to supervise. However, all agreed that being too busy impacted ability to supervise, highlighted by supervisors' most impactful barriers: lack of time, other responsibilities, intensive nature of supervision, desire for breaks, and unfilled positions. Non-supervisors noted unique barriers: distance, institutional barriers, and non-clinical roles. Program Directors' perceptions were congruent with those of genetic counselors with three exceptions they rated as impactful: lack of money, prefer not to supervise, and never been asked. In order to expand supervision networks and provide comprehensive student experiences, the profession must examine service delivery models to increase workplace efficiency, reconsider the supervision paradigm, and redefine what constitutes a countable case or place value on non-direct patient care experiences.

Genetic Simulation Resources: a website for the registration and discovery of genetic data simulators

PubMed Central

Peng, Bo; Chen, Huann-Sheng; Mechanic, Leah E.; Racine, Ben; Clarke, John; Clarke, Lauren; Gillanders, Elizabeth; Feuer, Eric J.

2013-01-01

Summary: Many simulation methods and programs have been developed to simulate genetic data of the human genome. These data have been widely used, for example, to predict properties of populations retrospectively or prospectively according to mathematically intractable genetic models, and to assist the validation, statistical inference and power analysis of a variety of statistical models. However, owing to the differences in type of genetic data of interest, simulation methods, evolutionary features, input and output formats, terminologies and assumptions for different applications, choosing the right tool for a particular study can be a resource-intensive process that usually involves searching, downloading and testing many different simulation programs. Genetic Simulation Resources (GSR) is a website provided by the National Cancer Institute (NCI) that aims to help researchers compare and choose the appropriate simulation tools for their studies. This website allows authors of simulation software to register their applications and describe them with well-defined attributes, thus allowing site users to search and compare simulators according to specified features. Availability: http://popmodels.cancercontrol.cancer.gov/gsr. Contact: gsr@mail.nih.gov PMID:23435068

Simulating Drosophila Genetics with the Computer.

ERIC Educational Resources Information Center

Small, James W., Jr.; Edwards, Kathryn L.

1979-01-01

Presents some techniques developed to help improve student understanding of Mendelian principles through the use of a computer simulation model by the genetic system of the fruit fly. Includes discussion and evaluation of this computer assisted program. (MA)

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

PubMed

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

2004-11-01

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

Applications of genetic programming in cancer research.

PubMed

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

2009-02-01

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

A Theory of Information Genetics: How Four Subforces Generate Information and the Implications for Total Quality Knowledge Management.

ERIC Educational Resources Information Center

Tsai, Bor-sheng

2002-01-01

Proposes a model called information genetics to elaborate on the origin of information generating. Explains conceptual and data models; and describes a software program that was developed for citation data mining, infomapping, and information repackaging for total quality knowledge management in Web representation. (Contains 112 references.)…

Integrating modelling and phenotyping approaches to identify and screen complex traits - Illustration for transpiration efficiency in cereals.

PubMed

Chenu, K; van Oosterom, E J; McLean, G; Deifel, K S; Fletcher, A; Geetika, G; Tirfessa, A; Mace, E S; Jordan, D R; Sulman, R; Hammer, G L

2018-02-21

Following advances in genetics, genomics, and phenotyping, trait selection in breeding is limited by our ability to understand interactions within the plants and with their environments, and to target traits of most relevance for the target population of environments. We propose an integrated approach that combines insights from crop modelling, physiology, genetics, and breeding to identify traits valuable for yield gain in the target population of environments, develop relevant high-throughput phenotyping platforms, and identify genetic controls and their values in production environments. This paper uses transpiration efficiency (biomass produced per unit of water used) as an example of a complex trait of interest to illustrate how the approach can guide modelling, phenotyping, and selection in a breeding program. We believe that this approach, by integrating insights from diverse disciplines, can increase the resource use efficiency of breeding programs for improving yield gains in target populations of environments.

Public health implications from COGS and potential for risk stratification and screening.

PubMed

Burton, Hilary; Chowdhury, Susmita; Dent, Tom; Hall, Alison; Pashayan, Nora; Pharoah, Paul

2013-04-01

The PHG Foundation led a multidisciplinary program, which used results from COGS research identifying genetic variants associated with breast, ovarian and prostate cancers to model risk-stratified prevention for breast and prostate cancers. Implementing such strategies would require attention to the use and storage of genetic information, the development of risk assessment tools, new protocols for consent and programs of professional education and public engagement.

Automatic reactor model synthesis with genetic programming.

PubMed

Dürrenmatt, David J; Gujer, Willi

2012-01-01

Successful modeling of wastewater treatment plant (WWTP) processes requires an accurate description of the plant hydraulics. Common methods such as tracer experiments are difficult and costly and thus have limited applicability in practice; engineers are often forced to rely on their experience only. An implementation of grammar-based genetic programming with an encoding to represent hydraulic reactor models as program trees should fill this gap: The encoding enables the algorithm to construct arbitrary reactor models compatible with common software used for WWTP modeling by linking building blocks, such as continuous stirred-tank reactors. Discharge measurements and influent and effluent concentrations are the only required inputs. As shown in a synthetic example, the technique can be used to identify a set of reactor models that perform equally well. Instead of being guided by experience, the most suitable model can now be chosen by the engineer from the set. In a second example, temperature measurements at the influent and effluent of a primary clarifier are used to generate a reactor model. A virtual tracer experiment performed on the reactor model has good agreement with a tracer experiment performed on-site.

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

PubMed

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

2014-01-01

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

Learning directed acyclic graphs from large-scale genomics data.

PubMed

Nikolay, Fabio; Pesavento, Marius; Kritikos, George; Typas, Nassos

2017-09-20

In this paper, we consider the problem of learning the genetic interaction map, i.e., the topology of a directed acyclic graph (DAG) of genetic interactions from noisy double-knockout (DK) data. Based on a set of well-established biological interaction models, we detect and classify the interactions between genes. We propose a novel linear integer optimization program called the Genetic-Interactions-Detector (GENIE) to identify the complex biological dependencies among genes and to compute the DAG topology that matches the DK measurements best. Furthermore, we extend the GENIE program by incorporating genetic interaction profile (GI-profile) data to further enhance the detection performance. In addition, we propose a sequential scalability technique for large sets of genes under study, in order to provide statistically significant results for real measurement data. Finally, we show via numeric simulations that the GENIE program and the GI-profile data extended GENIE (GI-GENIE) program clearly outperform the conventional techniques and present real data results for our proposed sequential scalability technique.

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

NASA Astrophysics Data System (ADS)

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

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

LIGO detector characterization with genetic programming

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

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

NASA Astrophysics Data System (ADS)

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

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

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

PubMed

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

2017-11-04

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

Feature extraction from multiple data sources using genetic programming

NASA Astrophysics Data System (ADS)

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

2002-08-01

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

Investigation on application of genetic algorithms to optimal reactive power dispatch of power systems

NASA Astrophysics Data System (ADS)

Wu, Q. H.; Ma, J. T.

1993-09-01

A primary investigation into application of genetic algorithms in optimal reactive power dispatch and voltage control is presented. The application was achieved, based on (the United Kingdom) National Grid 48 bus network model, using a novel genetic search approach. Simulation results, compared with that obtained using nonlinear programming methods, are included to show the potential of applications of the genetic search methodology in power system economical and secure operations.

Application of a soft computing technique in predicting the percentage of shear force carried by walls in a rectangular channel with non-homogeneous roughness.

PubMed

Khozani, Zohreh Sheikh; Bonakdari, Hossein; Zaji, Amir Hossein

2016-01-01

Two new soft computing models, namely genetic programming (GP) and genetic artificial algorithm (GAA) neural network (a combination of modified genetic algorithm and artificial neural network methods) were developed in order to predict the percentage of shear force in a rectangular channel with non-homogeneous roughness. The ability of these methods to estimate the percentage of shear force was investigated. Moreover, the independent parameters' effectiveness in predicting the percentage of shear force was determined using sensitivity analysis. According to the results, the GP model demonstrated superior performance to the GAA model. A comparison was also made between the GP program determined as the best model and five equations obtained in prior research. The GP model with the lowest error values (root mean square error ((RMSE) of 0.0515) had the best function compared with the other equations presented for rough and smooth channels as well as smooth ducts. The equation proposed for rectangular channels with rough boundaries (RMSE of 0.0642) outperformed the prior equations for smooth boundaries.

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

PubMed Central

MAXIMINO, Luciana Paula; PICOLINI-PEREIRA, Mirela Machado; CARVALHO, José Luiz Brito

2014-01-01

With the high occurrence of genetic anomalies in Brazil and the manifestations of communication disorders associated with these conditions, the development of educative actions that comprise these illnesses can bring unique benefits in the identification and appropriate treatment of these clinical pictures. Objective The aim of this study was to develop and analyze an educational program in genetic syndromes for elementary students applied in two Brazilian states, using an Interactive Tele-education model. Material and Methods The study was carried out in 4 schools: two in the state of São Paulo, Southeast Region, Brazil, and two in the state of Amazonas, North Region, Brazil. Forty-five students, both genders, aged between 13 and 14 years, of the 9th grade of the basic education of both public and private system, were divided into two groups: 21 of São Paulo Group (SPG) and 24 of Amazonas Group (AMG). The educational program lasted about 3 months and was divided into two stages including both classroom and distance activities on genetic syndromes. The classroom activity was carried out separately in each school, with expository lessons, graphs and audiovisual contents. In the activity at a distance the educational content was presented to students by means of the Interactive Tele-education model. In this stage, the students had access a Cybertutor, using the Young Doctor Project methodology. In order to measure the effectiveness of the educational program, the Problem Situation Questionnaire (PSQ) and the Web Site Motivational Analysis Checklist adapted (FPM) were used. Results The program developed was effective for knowledge acquisition in 80% of the groups. FPM showed a high satisfaction index from the participants in relation to the Interactive Tele-education, evaluating the program as "awesome course". No statistically significant differences between the groups regarding type of school or state were observed. Conclusion Thus, the Tele-Education Program can be used as a tool for educational purposes in genetic syndromes of other populations, in several regions of Brazil. PMID:25591016

Epstein-Barr virus latency switch in human B-cells: a physico-chemical model.

PubMed

Werner, Maria; Ernberg, Ingemar; Zou, Jiezhi; Almqvist, Jenny; Aurell, Erik

2007-08-31

The Epstein-Barr virus is widespread in all human populations and is strongly associated with human disease, ranging from infectious mononucleosis to cancer. In infected cells the virus can adopt several different latency programs, affecting the cells' behaviour. Experimental results indicate that a specific genetic switch between viral latency programs, reprograms human B-cells between proliferative and resting states. Each of these two latency programs makes use of a different viral promoter, Cp and Qp, respectively. The hypothesis tested in this study is that this genetic switch is controlled by both human and viral transcription factors; Oct-2 and EBNA-1. We build a physico-chemical model to investigate quantitatively the dynamical properties of the promoter regulation and experimentally examine protein level variations between the two latency programs. Our experimental results display significant differences in EBNA-1 and Oct-2 levels between resting and proliferating programs. With the model we identify two stable latency programs, corresponding to a resting and proliferating cell. The two programs differ in robustness and transcriptional activity. The proliferating state is markedly more stable, with a very high transcriptional activity from its viral promoter. We predict the promoter activities to be mutually exclusive in the two different programs, and our relative promoter activities correlate well with experimental data. Transitions between programs can be induced, by affecting the protein levels of our transcription factors. Simulated time scales are in line with experimental results. We show that fundamental properties of the Epstein-Barr virus involvement in latent infection, with implications for tumor biology, can be modelled and understood mathematically. We conclude that EBNA-1 and Oct-2 regulation of Cp and Qp is sufficient to establish mutually exclusive expression patterns. Moreover, the modelled genetic control predict both mono- and bistable behavior and a considerable difference in transition dynamics, based on program stability and promoter activities. Both these phenomena we hope can be further investigated experimentally, to increase the understanding of this important switch. Our results also stress the importance of the little known regulation of human transcription factor Oct-2.

Chance-constrained multi-objective optimization of groundwater remediation design at DNAPLs-contaminated sites using a multi-algorithm genetically adaptive method

NASA Astrophysics Data System (ADS)

Ouyang, Qi; Lu, Wenxi; Hou, Zeyu; Zhang, Yu; Li, Shuai; Luo, Jiannan

2017-05-01

In this paper, a multi-algorithm genetically adaptive multi-objective (AMALGAM) method is proposed as a multi-objective optimization solver. It was implemented in the multi-objective optimization of a groundwater remediation design at sites contaminated by dense non-aqueous phase liquids. In this study, there were two objectives: minimization of the total remediation cost, and minimization of the remediation time. A non-dominated sorting genetic algorithm II (NSGA-II) was adopted to compare with the proposed method. For efficiency, the time-consuming surfactant-enhanced aquifer remediation simulation model was replaced by a surrogate model constructed by a multi-gene genetic programming (MGGP) technique. Similarly, two other surrogate modeling methods-support vector regression (SVR) and Kriging (KRG)-were employed to make comparisons with MGGP. In addition, the surrogate-modeling uncertainty was incorporated in the optimization model by chance-constrained programming (CCP). The results showed that, for the problem considered in this study, (1) the solutions obtained by AMALGAM incurred less remediation cost and required less time than those of NSGA-II, indicating that AMALGAM outperformed NSGA-II. It was additionally shown that (2) the MGGP surrogate model was more accurate than SVR and KRG; and (3) the remediation cost and time increased with the confidence level, which can enable decision makers to make a suitable choice by considering the given budget, remediation time, and reliability.

Genetic Simulation Tools for Post-Genome Wide Association Studies of Complex Diseases

PubMed Central

Amos, Christopher I.; Bafna, Vineet; Hauser, Elizabeth R.; Hernandez, Ryan D.; Li, Chun; Liberles, David A.; McAllister, Kimberly; Moore, Jason H.; Paltoo, Dina N.; Papanicolaou, George J.; Peng, Bo; Ritchie, Marylyn D.; Rosenfeld, Gabriel; Witte, John S.

2014-01-01

Genetic simulation programs are used to model data under specified assumptions to facilitate the understanding and study of complex genetic systems. Standardized data sets generated using genetic simulation are essential for the development and application of novel analytical tools in genetic epidemiology studies. With continuing advances in high-throughput genomic technologies and generation and analysis of larger, more complex data sets, there is a need for updating current approaches in genetic simulation modeling. To provide a forum to address current and emerging challenges in this area, the National Cancer Institute (NCI) sponsored a workshop, entitled “Genetic Simulation Tools for Post-Genome Wide Association Studies of Complex Diseases” at the National Institutes of Health (NIH) in Bethesda, Maryland on March 11-12, 2014. The goals of the workshop were to: (i) identify opportunities, challenges and resource needs for the development and application of genetic simulation models; (ii) improve the integration of tools for modeling and analysis of simulated data; and (iii) foster collaborations to facilitate development and applications of genetic simulation. During the course of the meeting the group identified challenges and opportunities for the science of simulation, software and methods development, and collaboration. This paper summarizes key discussions at the meeting, and highlights important challenges and opportunities to advance the field of genetic simulation. PMID:25371374

The statistical analysis of multi-environment data: modeling genotype-by-environment interaction and its genetic basis

PubMed Central

Malosetti, Marcos; Ribaut, Jean-Marcel; van Eeuwijk, Fred A.

2013-01-01

Genotype-by-environment interaction (GEI) is an important phenomenon in plant breeding. This paper presents a series of models for describing, exploring, understanding, and predicting GEI. All models depart from a two-way table of genotype by environment means. First, a series of descriptive and explorative models/approaches are presented: Finlay–Wilkinson model, AMMI model, GGE biplot. All of these approaches have in common that they merely try to group genotypes and environments and do not use other information than the two-way table of means. Next, factorial regression is introduced as an approach to explicitly introduce genotypic and environmental covariates for describing and explaining GEI. Finally, QTL modeling is presented as a natural extension of factorial regression, where marker information is translated into genetic predictors. Tests for regression coefficients corresponding to these genetic predictors are tests for main effect QTL expression and QTL by environment interaction (QEI). QTL models for which QEI depends on environmental covariables form an interesting model class for predicting GEI for new genotypes and new environments. For realistic modeling of genotypic differences across multiple environments, sophisticated mixed models are necessary to allow for heterogeneity of genetic variances and correlations across environments. The use and interpretation of all models is illustrated by an example data set from the CIMMYT maize breeding program, containing environments differing in drought and nitrogen stress. To help readers to carry out the statistical analyses, GenStat® programs, 15th Edition and Discovery® version, are presented as “Appendix.” PMID:23487515

On Using Surrogates with Genetic Programming.

PubMed

Hildebrandt, Torsten; Branke, Jürgen

2015-01-01

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

Genetic evaluation and selection response for growth in meat-type quail through random regression models using B-spline functions and Legendre polynomials.

PubMed

Mota, L F M; Martins, P G M A; Littiere, T O; Abreu, L R A; Silva, M A; Bonafé, C M

2018-04-01

The objective was to estimate (co)variance functions using random regression models (RRM) with Legendre polynomials, B-spline function and multi-trait models aimed at evaluating genetic parameters of growth traits in meat-type quail. A database containing the complete pedigree information of 7000 meat-type quail was utilized. The models included the fixed effects of contemporary group and generation. Direct additive genetic and permanent environmental effects, considered as random, were modeled using B-spline functions considering quadratic and cubic polynomials for each individual segment, and Legendre polynomials for age. Residual variances were grouped in four age classes. Direct additive genetic and permanent environmental effects were modeled using 2 to 4 segments and were modeled by Legendre polynomial with orders of fit ranging from 2 to 4. The model with quadratic B-spline adjustment, using four segments for direct additive genetic and permanent environmental effects, was the most appropriate and parsimonious to describe the covariance structure of the data. The RRM using Legendre polynomials presented an underestimation of the residual variance. Lesser heritability estimates were observed for multi-trait models in comparison with RRM for the evaluated ages. In general, the genetic correlations between measures of BW from hatching to 35 days of age decreased as the range between the evaluated ages increased. Genetic trend for BW was positive and significant along the selection generations. The genetic response to selection for BW in the evaluated ages presented greater values for RRM compared with multi-trait models. In summary, RRM using B-spline functions with four residual variance classes and segments were the best fit for genetic evaluation of growth traits in meat-type quail. In conclusion, RRM should be considered in genetic evaluation of breeding programs.

Genetic programming applied to RFI mitigation in radio astronomy

NASA Astrophysics Data System (ADS)

Staats, K.

2016-12-01

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

Genetic analysis of resistance to ticks, gastrointestinal nematodes and Eimeria spp. in Nellore cattle.

PubMed

Passafaro, Tiago Luciano; Carrera, Juan Pablo Botero; dos Santos, Livia Loiola; Raidan, Fernanda Santos Silva; dos Santos, Dalinne Chrystian Carvalho; Cardoso, Eduardo Penteado; Leite, Romário Cerqueira; Toral, Fabio Luiz Buranelo

2015-06-15

The aim of the present study was to obtain genetic parameters for resistance to ticks, gastrointestinal nematodes (worms) and Eimeria spp. in Nellore cattle, analyze the inclusion of resistance traits in Nellore breeding programs and evaluate genetic selection as a complementary tool in parasite control programs. Counting of ticks, gastrointestinal nematode eggs and Eimeria spp. oocysts per gram of feces totaling 4270; 3872 and 3872 records from 1188; 1142 and 1142 animals, respectively, aged 146 to 597 days were used. The animals were classified as resistant (counts equal to zero) or susceptible (counts above zero) to each parasite. The statistical models included systematics effects of contemporary groups and the mean trajectory. The random effects included additive genetic effects, direct permanent environmental effects and residual. The mean trajectory and random effects were modeled with linear Legendre polynomials for all traits except for the mean trajectory of resistance to Eimeria spp., which employed the cubic polynomial. Heritability estimates were of low to moderate magnitude and ranged from 0.06 to 0.30, 0.06 to 0.33 and 0.04 to 0.33 for resistance to ticks, gastrointestinal nematodes and Eimeria spp., respectively. The posterior mean of genetic and environmental correlations for the same trait at different ages (205, 365, 450 and 550 days) were favorable at adjacent ages and unfavorable at distant ages. In general, the posterior mean of the genetic and environmental correlations between traits of resistance were low and high-density intervals were large and included zero in many cases. The heritability estimates support the inclusion of resistance to ticks, gastrointestinal nematodes and Eimeria spp. in Nellore breeding programs. Genetic selection can increase the frequency of resistant animals and be used as a complementary tool in parasite control programs. Copyright © 2015 Elsevier B.V. All rights reserved.

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

PubMed

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

2013-08-01

In conventional small ruminant breeding programs, only pedigree and phenotype records are used to make selection decisions but prospects of including genomic information are now under consideration. The objective of this study was to assess the potential benefits of genomic selection on the genetic gain in French sheep and goat breeding designs of today. Traditional and genomic scenarios were modeled with deterministic methods for 3 breeding programs. The models included decisional variables related to male selection candidates, progeny testing capacity, and economic weights that were optimized to maximize annual genetic gain (AGG) of i) a meat sheep breeding program that improved a meat trait of heritability (h(2)) = 0.30 and a maternal trait of h(2) = 0.09 and ii) dairy sheep and goat breeding programs that improved a milk trait of h(2) = 0.30. Values of ±0.20 of genetic correlation between meat and maternal traits were considered to study their effects on AGG. The Bulmer effect was accounted for and the results presented here are the averages of AGG after 10 generations of selection. Results showed that current traditional breeding programs provide an AGG of 0.095 genetic standard deviation (σa) for meat and 0.061 σa for maternal trait in meat breed and 0.147 σa and 0.120 σa in sheep and goat dairy breeds, respectively. By optimizing decisional variables, the AGG with traditional selection methods increased to 0.139 σa for meat and 0.096 σa for maternal traits in meat breeding programs and to 0.174 σa and 0.183 σa in dairy sheep and goat breeding programs, respectively. With a medium-sized reference population (nref) of 2,000 individuals, the best genomic scenarios gave an AGG that was 17.9% greater than with traditional selection methods with optimized values of decisional variables for combined meat and maternal traits in meat sheep, 51.7% in dairy sheep, and 26.2% in dairy goats. The superiority of genomic schemes increased with the size of the reference population and genomic selection gave the best results when nref > 1,000 individuals for dairy breeds and nref > 2,000 individuals for meat breed. Genetic correlation between meat and maternal traits had a large impact on the genetic gain of both traits. Changes in AGG due to correlation were greatest for low heritable maternal traits. As a general rule, AGG was increased both by optimizing selection designs and including genomic information.

Unleashing the power of human genetic variation knowledge: New Zealand stakeholder perspectives.

PubMed

Gu, Yulong; Warren, James Roy; Day, Karen Jean

2011-01-01

This study aimed to characterize the challenges in using genetic information in health care and to identify opportunities for improvement. Taking a grounded theory approach, semistructured interviews were conducted with 48 participants to collect multiple stakeholder perspectives on genetic services in New Zealand. Three themes emerged from the data: (1) four service delivery models were identified in operation, including both those expected models involving genetic counselors and variations that do not route through the formal genetic service program; (2) multiple barriers to sharing and using genetic information were perceived, including technological, organizational, institutional, legal, ethical, and social issues; and (3) impediments to wider use of genetic testing technology, including variable understanding of genetic test utilities among clinicians and the limited capacity of clinical genetic services. Targeting these problems, information technologies and knowledge management tools have the potential to support key tasks in genetic services delivery, improve knowledge processes, and enhance knowledge networks. Because of the effect of issues in genetic information and knowledge management, the potential of human genetic variation knowledge to enhance health care delivery has been put on a "leash."

Impact of computer-assisted data collection, evaluation and management on the cancer genetic counselor's time providing patient care.

PubMed

Cohen, Stephanie A; McIlvried, Dawn E

2011-06-01

Cancer genetic counseling sessions traditionally encompass collecting medical and family history information, evaluating that information for the likelihood of a genetic predisposition for a hereditary cancer syndrome, conveying that information to the patient, offering genetic testing when appropriate, obtaining consent and subsequently documenting the encounter with a clinic note and pedigree. Software programs exist to collect family and medical history information electronically, intending to improve efficiency and simplicity of collecting, managing and storing this data. This study compares the genetic counselor's time spent in cancer genetic counseling tasks in a traditional model and one using computer-assisted data collection, which is then used to generate a pedigree, risk assessment and consult note. Genetic counselor time spent collecting family and medical history and providing face-to-face counseling for a new patient session decreased from an average of 85-69 min when using the computer-assisted data collection. However, there was no statistically significant change in overall genetic counselor time on all aspects of the genetic counseling process, due to an increased amount of time spent generating an electronic pedigree and consult note. Improvements in the computer program's technical design would potentially minimize data manipulation. Certain aspects of this program, such as electronic collection of family history and risk assessment, appear effective in improving cancer genetic counseling efficiency while others, such as generating an electronic pedigree and consult note, do not.

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

PubMed Central

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

2017-01-01

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

Evaluation of traffic signal timing optimization methods using a stochastic and microscopic simulation program.

DOT National Transportation Integrated Search

2003-01-01

This study evaluated existing traffic signal optimization programs including Synchro,TRANSYT-7F, and genetic algorithm optimization using real-world data collected in Virginia. As a first step, a microscopic simulation model, VISSIM, was extensively ...

Interactive evolution of camouflage.

PubMed

Reynolds, Craig

2011-01-01

This article presents an abstract computation model of the evolution of camouflage in nature. The 2D model uses evolved textures for prey, a background texture representing the environment, and a visual predator. A human observer, acting as the predator, is shown a cohort of 10 evolved textures overlaid on the background texture. The observer clicks on the five most conspicuous prey to remove ("eat") them. These lower-fitness textures are removed from the population and replaced with newly bred textures. Biological morphogenesis is represented in this model by procedural texture synthesis. Nested expressions of generators and operators form a texture description language. Natural evolution is represented by genetic programming (GP), a variant of the genetic algorithm. GP searches the space of texture description programs for those that appear least conspicuous to the predator.

Insulin and IGF1 Receptors Are Essential for XX and XY Gonadal Differentiation and Adrenal Development in Mice

PubMed Central

Romero, Yannick; Conne, Béatrice; Truong, Vy; Papaioannou, Marilena D.; Schaad, Olivier; Docquier, Mylène; Herrera, Pedro Luis; Wilhelm, Dagmar; Nef, Serge

2013-01-01

Mouse sex determination provides an attractive model to study how regulatory genetic networks and signaling pathways control cell specification and cell fate decisions. This study characterizes in detail the essential role played by the insulin receptor (INSR) and the IGF type I receptor (IGF1R) in adrenogenital development and primary sex determination. Constitutive ablation of insulin/IGF signaling pathway led to reduced proliferation rate of somatic progenitor cells in both XX and XY gonads prior to sex determination together with the downregulation of hundreds of genes associated with the adrenal, testicular, and ovarian genetic programs. These findings indicate that prior to sex determination somatic progenitors in Insr;Igf1r mutant gonads are not lineage primed and thus incapable of upregulating/repressing the male and female genetic programs required for cell fate restriction. In consequence, embryos lacking functional insulin/IGF signaling exhibit (i) complete agenesis of the adrenal cortex, (ii) embryonic XY gonadal sex reversal, with a delay of Sry upregulation and the subsequent failure of the testicular genetic program, and (iii) a delay in ovarian differentiation so that Insr;Igf1r mutant gonads, irrespective of genetic sex, remained in an extended undifferentiated state, before the ovarian differentiation program ultimately is initiated at around E16.5. PMID:23300479

Chance-constrained multi-objective optimization of groundwater remediation design at DNAPLs-contaminated sites using a multi-algorithm genetically adaptive method.

PubMed

Ouyang, Qi; Lu, Wenxi; Hou, Zeyu; Zhang, Yu; Li, Shuai; Luo, Jiannan

2017-05-01

In this paper, a multi-algorithm genetically adaptive multi-objective (AMALGAM) method is proposed as a multi-objective optimization solver. It was implemented in the multi-objective optimization of a groundwater remediation design at sites contaminated by dense non-aqueous phase liquids. In this study, there were two objectives: minimization of the total remediation cost, and minimization of the remediation time. A non-dominated sorting genetic algorithm II (NSGA-II) was adopted to compare with the proposed method. For efficiency, the time-consuming surfactant-enhanced aquifer remediation simulation model was replaced by a surrogate model constructed by a multi-gene genetic programming (MGGP) technique. Similarly, two other surrogate modeling methods-support vector regression (SVR) and Kriging (KRG)-were employed to make comparisons with MGGP. In addition, the surrogate-modeling uncertainty was incorporated in the optimization model by chance-constrained programming (CCP). The results showed that, for the problem considered in this study, (1) the solutions obtained by AMALGAM incurred less remediation cost and required less time than those of NSGA-II, indicating that AMALGAM outperformed NSGA-II. It was additionally shown that (2) the MGGP surrogate model was more accurate than SVR and KRG; and (3) the remediation cost and time increased with the confidence level, which can enable decision makers to make a suitable choice by considering the given budget, remediation time, and reliability. Copyright © 2017 Elsevier B.V. All rights reserved.

An atomistic geometrical model of the B-DNA configuration for DNA-radiation interaction simulations

NASA Astrophysics Data System (ADS)

Bernal, M. A.; Sikansi, D.; Cavalcante, F.; Incerti, S.; Champion, C.; Ivanchenko, V.; Francis, Z.

2013-12-01

In this paper, an atomistic geometrical model for the B-DNA configuration is explained. This model accounts for five organization levels of the DNA, up to the 30 nm chromatin fiber. However, fragments of this fiber can be used to construct the whole genome. The algorithm developed in this work is capable to determine which is the closest atom with respect to an arbitrary point in space. It can be used in any application in which a DNA geometrical model is needed, for instance, in investigations related to the effects of ionizing radiations on the human genetic material. Successful consistency checks were carried out to test the proposed model. Catalogue identifier: AEPZ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEPZ_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 1245 No. of bytes in distributed program, including test data, etc.: 6574 Distribution format: tar.gz Programming language: FORTRAN. Computer: Any. Operating system: Multi-platform. RAM: 2 Gb Classification: 3. Nature of problem: The Monte Carlo method is used to simulate the interaction of ionizing radiation with the human genetic material in order to determine DNA damage yields per unit absorbed dose. To accomplish this task, an algorithm to determine if a given energy deposition lies within a given target is needed. This target can be an atom or any other structure of the genetic material. Solution method: This is a stand-alone subroutine describing an atomic-resolution geometrical model of the B-DNA configuration. It is able to determine the closest atom to an arbitrary point in space. This model accounts for five organization levels of the human genetic material, from the nucleotide pair up to the 30 nm chromatin fiber. This subroutine carries out a series of coordinate transformations to find which is the closest atom containing an arbitrary point in space. Atom sizes are according to the corresponding van der Waals radii. Restrictions: The geometrical model presented here does not include the chromosome organization level but it could be easily build up by using fragments of the 30 nm chromatin fiber. Unusual features: To our knowledge, this is the first open source atomic-resolution DNA geometrical model developed for DNA-radiation interaction Monte Carlo simulations. In our tests, the current model took into account the explicit position of about 56×106 atoms, although the user may enhance this amount according to the necessities. Running time: This subroutine can process about 2 million points within a few minutes in a typical current computer.

Fuzzy multi-objective chance-constrained programming model for hazardous materials transportation

NASA Astrophysics Data System (ADS)

Du, Jiaoman; Yu, Lean; Li, Xiang

2016-04-01

Hazardous materials transportation is an important and hot issue of public safety. Based on the shortest path model, this paper presents a fuzzy multi-objective programming model that minimizes the transportation risk to life, travel time and fuel consumption. First, we present the risk model, travel time model and fuel consumption model. Furthermore, we formulate a chance-constrained programming model within the framework of credibility theory, in which the lengths of arcs in the transportation network are assumed to be fuzzy variables. A hybrid intelligent algorithm integrating fuzzy simulation and genetic algorithm is designed for finding a satisfactory solution. Finally, some numerical examples are given to demonstrate the efficiency of the proposed model and algorithm.

A new mathematical modeling for pure parsimony haplotyping problem.

PubMed

Feizabadi, R; Bagherian, M; Vaziri, H R; Salahi, M

2016-11-01

Pure parsimony haplotyping (PPH) problem is important in bioinformatics because rational haplotyping inference plays important roles in analysis of genetic data, mapping complex genetic diseases such as Alzheimer's disease, heart disorders and etc. Haplotypes and genotypes are m-length sequences. Although several integer programing models have already been presented for PPH problem, its NP-hardness characteristic resulted in ineffectiveness of those models facing the real instances especially instances with many heterozygous sites. In this paper, we assign a corresponding number to each haplotype and genotype and based on those numbers, we set a mixed integer programing model. Using numbers, instead of sequences, would lead to less complexity of the new model in comparison with previous models in a way that there are neither constraints nor variables corresponding to heterozygous nucleotide sites in it. Experimental results approve the efficiency of the new model in producing better solution in comparison to two state-of-the art haplotyping approaches. Copyright © 2016 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Muduli, Pradyut; Das, Sarat

2014-06-01

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

Implementation of inpatient models of pharmacogenetics programs

PubMed Central

Cavallari, Larisa H.; Lee, Craig R.; Duarte, Julio D.; Nutescu, Edith A.; Weitzel, Kristin W.; Stouffer, George A.; Johnson, Julie A.

2017-01-01

Purpose The operational elements essential for establishing an inpatient pharmacogenetic service are reviewed, and the role of the pharmacist in the provision of genotype-guided drug therapy in pharmacogenetics programs at three institutions is highlighted. Summary Pharmacists are well positioned to assume important roles in facilitating the clinical use of genetic information to optimize drug therapy given their expertise in clinical pharmacology and therapeutics. Pharmacists have assumed important roles in implementing inpatient pharmacogenetics programs. This includes programs designed to incorporate genetic test results to optimize antiplatelet drug selection after percutaneous coronary intervention and personalize warfarin dosing. Pharmacist involvement occurs on many levels, including championing and leading pharmacogenetics implementation efforts, establishing clinical processes to support genotype-guided therapy, assisting the clinical staff with interpreting genetic test results and applying them to prescribing decisions, and educating other healthcare providers and patients on genomic medicine. The three inpatient pharmacogenetics programs described use reactive versus preemptive genotyping, the most feasible approach under the current third-party payment structure. All three sites also follow Clinical Pharmacogenetics Implementation Consortium guidelines for drug therapy recommendations based on genetic test results. Conclusion With the clinical emergence of pharmacogenetics into the inpatient setting, it is important that pharmacists caring for hospitalized patients are well prepared to serve as experts in interpreting and applying genetic test results to guide drug therapy decisions. Since genetic test results may not be available until after patient discharge, pharmacists practicing in the ambulatory care setting should also be prepared to assist with genotype-guided drug therapy as part of transitions in care. PMID:27864202

Implementation of inpatient models of pharmacogenetics programs.

PubMed

Cavallari, Larisa H; Lee, Craig R; Duarte, Julio D; Nutescu, Edith A; Weitzel, Kristin W; Stouffer, George A; Johnson, Julie A

2016-12-01

The operational elements essential for establishing an inpatient pharmacogenetic service are reviewed, and the role of the pharmacist in the provision of genotype-guided drug therapy in pharmacogenetics programs at three institutions is highlighted. Pharmacists are well positioned to assume important roles in facilitating the clinical use of genetic information to optimize drug therapy given their expertise in clinical pharmacology and therapeutics. Pharmacists have assumed important roles in implementing inpatient pharmacogenetics programs. This includes programs designed to incorporate genetic test results to optimize antiplatelet drug selection after percutaneous coronary intervention and personalize warfarin dosing. Pharmacist involvement occurs on many levels, including championing and leading pharmacogenetics implementation efforts, establishing clinical processes to support genotype-guided therapy, assisting the clinical staff with interpreting genetic test results and applying them to prescribing decisions, and educating other healthcare providers and patients on genomic medicine. The three inpatient pharmacogenetics programs described use reactive versus preemptive genotyping, the most feasible approach under the current third-party payment structure. All three sites also follow Clinical Pharmacogenetics Implementation Consortium guidelines for drug therapy recommendations based on genetic test results. With the clinical emergence of pharmacogenetics into the inpatient setting, it is important that pharmacists caring for hospitalized patients are well prepared to serve as experts in interpreting and applying genetic test results to guide drug therapy decisions. Since genetic test results may not be available until after patient discharge, pharmacists practicing in the ambulatory care setting should also be prepared to assist with genotype-guided drug therapy as part of transitions in care. Copyright © 2016 by the American Society of Health-System Pharmacists, Inc. All rights reserved.

A multi-product green supply chain under government supervision with price and demand uncertainty

NASA Astrophysics Data System (ADS)

Hafezalkotob, Ashkan; Zamani, Soma

2018-05-01

In this paper, a bi-level game-theoretic model is proposed to investigate the effects of governmental financial intervention on green supply chain. This problem is formulated as a bi-level program for a green supply chain that produces various products with different environmental pollution levels. The problem is also regard uncertainties in market demand and sale price of raw materials and products. The model is further transformed into a single-level nonlinear programming problem by replacing the lower-level optimization problem with its Karush-Kuhn-Tucker optimality conditions. Genetic algorithm is applied as a solution methodology to solve nonlinear programming model. Finally, to investigate the validity of the proposed method, the computational results obtained through genetic algorithm are compared with global optimal solution attained by enumerative method. Analytical results indicate that the proposed GA offers better solutions in large size problems. Also, we conclude that financial intervention by government consists of green taxation and subsidization is an effective method to stabilize green supply chain members' performance.

Mendelian genetics: Paradigm, conjecture, or research program

NASA Astrophysics Data System (ADS)

Oldham, V.; Brouwer, W.

Kuhn's model of the structure of scientific revolutions, Popper's hypothetic-deductive model of science, and Lakatos's methodology of competing research programs are applied to a historical episode in biology. Each of these three models offers a different explanatory system for the development, neglect, and eventual acceptance of Mendel's paradigm of inheritance. The authors conclude that both rational and nonrational criteria play an important role during times of crisis in science, when different research programs compete for acceptance. It is suggested that Kuhn's model, emphasizing the nonrational basis of science, and Popper's model, emphasizing the rational basis of science, can be used fruitfully in high school science courses.

Genetic parameter estimation for pre- and post-weaning traits in Brahman cattle in Brazil.

PubMed

Vargas, Giovana; Buzanskas, Marcos Eli; Guidolin, Diego Gomes Freire; Grossi, Daniela do Amaral; Bonifácio, Alexandre da Silva; Lôbo, Raysildo Barbosa; da Fonseca, Ricardo; Oliveira, João Ademir de; Munari, Danísio Prado

2014-10-01

Beef cattle producers in Brazil use body weight traits as breeding program selection criteria due to their great economic importance. The objectives of this study were to evaluate different animal models, estimate genetic parameters, and define the most fitting model for Brahman cattle body weight standardized at 120 (BW120), 210 (BW210), 365 (BW365), 450 (BW450), and 550 (BW550) days of age. To estimate genetic parameters, single-, two-, and multi-trait analyses were performed using the animal model. The likelihood ratio test was verified between all models. For BW120 and BW210, additive direct genetic, maternal genetic, maternal permanent environment, and residual effects were considered, while for BW365 and BW450, additive direct genetic, maternal genetic, and residual effects were considered. Finally, for BW550, additive direct genetic and residual effects were considered. Estimates of direct heritability for BW120 were similar in all analyses; however, for the other traits, multi-trait analysis resulted in higher estimates. The maternal heritability and proportion of maternal permanent environmental variance to total variance were minimal in multi-trait analyses. Genetic, environmental, and phenotypic correlations were of high magnitude between all traits. Multi-trait analyses would aid in the parameter estimation for body weight at older ages because they are usually affected by a lower number of animals with phenotypic information due to culling and mortality.

Genetic aspect of Alzheimer disease: Results of complex segregation analysis

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

Sadonvick, A.D.; Lee, I.M.L.; Bailey-Wilson, J.E.

1994-09-01

The study was designed to evaluate the possibility that a single major locus will explain the segregation of Alzheimer disease (AD). The data were from the population-based AD Genetic Database and consisted of 402 consecutive, unrelated probands, diagnosed to have either `probable` or `autopsy confirmed` AD and their 2,245 first-degree relatives. In this analysis, a relative was considered affected with AD only when there were sufficient medical/autopsy data to support diagnosis of AD being the most likely cause of the dementia. Transmission probability models allowing for a genotype-dependent and logistically distributed age-of-onset were used. The program REGTL in the S.A.G.E.more » computer program package was used for a complex segregation analysis. The models included correction for single ascertainment. Regressive familial effects were not estimated. The data were analyzed to test for single major locus (SML), random transmission and no transmission (environmental) hypotheses. The results of the complex segregation analysis showed that (1) the SML was the best fit, and (2) the non-genetic models could be rejected.« less

Selection Experiments in the Penna Model for Biological Aging

NASA Astrophysics Data System (ADS)

Medeiros, G.; Idiart, M. A.; de Almeida, R. M. C.

We consider the Penna model for biological aging to investigate correlations between early fertility and late life survival rates in populations at equilibrium. We consider inherited initial reproduction ages together with a reproduction cost translated in a probability that mother and offspring die at birth, depending on the mother age. For convenient sets of parameters, the equilibrated populations present genetic variability in what regards both genetically programmed death age and initial reproduction age. In the asexual Penna model, a negative correlation between early life fertility and late life survival rates naturally emerges in the stationary solutions. In the sexual Penna model, selection experiments are performed where individuals are sorted by initial reproduction age from the equilibrated populations and the separated populations are evolved independently. After a transient, a negative correlation between early fertility and late age survival rates also emerges in the sense that populations that start reproducing earlier present smaller average genetically programmed death age. These effects appear due to the age structure of populations in the steady state solution of the evolution equations. We claim that the same demographic effects may be playing an important role in selection experiments in the laboratory.

The effect of genetic selection for Johne's disease resistance in dairy cattle: Results of a genetic-epidemiological model.

PubMed

van Hulzen, K J E; Koets, A P; Nielen, M; Heuven, H C M; van Arendonk, J A M; Klinkenberg, D

2014-03-01

The objective of this study was to model genetic selection for Johne's disease resistance and to study the effect of different selection strategies on the prevalence in the dairy cattle population. In the Netherlands, a certification-and-surveillance program is in use to reduce prevalence and presence of sources of infection in milk by culling ELISA-positive dairy cows in infected herds. To investigate the additional genetic effect of this program, a genetic-epidemiological model was developed to assess the effect of selection of cows that test negative for Johne's disease (dam selection). The genetic effect of selection at the sire level was also considered (sire selection), assuming selection of 80% of sires producing the most resistant offspring based on their breeding values, as well as the combined effect. Parameters assumed to be affected by genetic selection were the length of the latent period, susceptibility (i.e., the number of infectious doses needed to become infected), or the length of susceptible period as a calf. The effect of selection was measured by the time in years required to eliminate infection. Sensitivity analysis was performed for heritability, accuracy of selection, and intensity of selection. For dam selection, responses to selection were small, requiring 379 to 702 yr for elimination. For sire selection, responses were much larger, although elimination still required 147 to 223 yr. The response to selection was largest if genetic selection affected the length of the susceptible period, followed by the susceptibility, and finally the length of the latent period. Genetic selection for Johne's disease resistance by certification and surveillance is too slow for practical purpose, but that selection on the sire level is able to contribute to the control of Johne's disease in the long run. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Integer programming model for optimizing bus timetable using genetic algorithm

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

Inheritance of astigmatism: evidence for a major autosomal dominant locus.

PubMed Central

Clementi, M; Angi, M; Forabosco, P; Di Gianantonio, E; Tenconi, R

1998-01-01

Although astigmatism is a frequent refractive error, its mode of inheritance remains uncertain. Complex segregation analysis was performed, by the POINTER and COMDS programs, with data from a geographically well-defined sample of 125 nuclear families of individuals affected by astigmatism. POINTER could not distinguish between alternative genetic models, and only the hypothesis of no familial transmission could be rejected. After inclusion of the severity parameter, COMDS results defined a genetic model for corneal astigmatism and provided evidence for single-major-locus inheritance. These results suggest that genetic linkage studies could be implemented and that they should be limited to multiplex families with severely affected individuals. PMID:9718344

Optimizing DNA assembly based on statistical language modelling.

PubMed

Fang, Gang; Zhang, Shemin; Dong, Yafei

2017-12-15

By successively assembling genetic parts such as BioBrick according to grammatical models, complex genetic constructs composed of dozens of functional blocks can be built. However, usually every category of genetic parts includes a few or many parts. With increasing quantity of genetic parts, the process of assembling more than a few sets of these parts can be expensive, time consuming and error prone. At the last step of assembling it is somewhat difficult to decide which part should be selected. Based on statistical language model, which is a probability distribution P(s) over strings S that attempts to reflect how frequently a string S occurs as a sentence, the most commonly used parts will be selected. Then, a dynamic programming algorithm was designed to figure out the solution of maximum probability. The algorithm optimizes the results of a genetic design based on a grammatical model and finds an optimal solution. In this way, redundant operations can be reduced and the time and cost required for conducting biological experiments can be minimized. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Human genetic susceptibility and infection with Leishmania peruviana

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

Shaw, M.A.; Davis, C.R.; Collins, A.

1995-11-01

Racial differences, familial clustering, and murine studies are suggestive of host genetic control of Leishmania infections. Complex segregation analysis has been carried out by use of the programs POINTER and COMDS and data from a total population survey, comprising 636 nuclear families, from an L. perurviana endemic area. The data support genetic components controlling susceptibility to clinical leishmaniasis, influencing severity of disease and resistance to disease among healthy individuals. A multifactorial model is favored over a sporadic model. Two-locus models provided the best fit to the data, the optimal model being a recessive gene (frequency .57) plus a modifier locus.more » Individuals infected at an early age and with recurrent lesions are genetically more susceptible than those infected with a single episode of disease at a later age. Among people with no lesions, those with a positive skin-test response are genetically less susceptible than those with a negative response. The possibility of the involvement of more than one gene together with environmental effects has implications for the design of future linkage studies. 31 refs., 7 tabs.« less

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

NASA Astrophysics Data System (ADS)

Taylan, Fatih

2011-04-01

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

Genetics on the Fly: A Primer on the Drosophila Model System

PubMed Central

Hales, Karen G.; Korey, Christopher A.; Larracuente, Amanda M.; Roberts, David M.

2015-01-01

Fruit flies of the genus Drosophila have been an attractive and effective genetic model organism since Thomas Hunt Morgan and colleagues made seminal discoveries with them a century ago. Work with Drosophila has enabled dramatic advances in cell and developmental biology, neurobiology and behavior, molecular biology, evolutionary and population genetics, and other fields. With more tissue types and observable behaviors than in other short-generation model organisms, and with vast genome data available for many species within the genus, the fly’s tractable complexity will continue to enable exciting opportunities to explore mechanisms of complex developmental programs, behaviors, and broader evolutionary questions. This primer describes the organism’s natural history, the features of sequenced genomes within the genus, the wide range of available genetic tools and online resources, the types of biological questions Drosophila can help address, and historical milestones. PMID:26564900

Comparative data mining analysis for information retrieval of MODIS images: monitoring lake turbidity changes at Lake Okeechobee, Florida

NASA Astrophysics Data System (ADS)

Chang, Ni-Bin; Daranpob, Ammarin; Yang, Y. Jeffrey; Jin, Kang-Ren

2009-09-01

In the remote sensing field, a frequently recurring question is: Which computational intelligence or data mining algorithms are most suitable for the retrieval of essential information given that most natural systems exhibit very high non-linearity. Among potential candidates might be empirical regression, neural network model, support vector machine, genetic algorithm/genetic programming, analytical equation, etc. This paper compares three types of data mining techniques, including multiple non-linear regression, artificial neural networks, and genetic programming, for estimating multi-temporal turbidity changes following hurricane events at Lake Okeechobee, Florida. This retrospective analysis aims to identify how the major hurricanes impacted the water quality management in 2003-2004. The Moderate Resolution Imaging Spectroradiometer (MODIS) Terra 8-day composite imageries were used to retrieve the spatial patterns of turbidity distributions for comparison against the visual patterns discernible in the in-situ observations. By evaluating four statistical parameters, the genetic programming model was finally selected as the most suitable data mining tool for classification in which the MODIS band 1 image and wind speed were recognized as the major determinants by the model. The multi-temporal turbidity maps generated before and after the major hurricane events in 2003-2004 showed that turbidity levels were substantially higher after hurricane episodes. The spatial patterns of turbidity confirm that sediment-laden water travels to the shore where it reduces the intensity of the light necessary to submerged plants for photosynthesis. This reduction results in substantial loss of biomass during the post-hurricane period.

Genetic Programming Transforms in Linear Regression Situations

NASA Astrophysics Data System (ADS)

Castillo, Flor; Kordon, Arthur; Villa, Carlos

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

Genetic algorithm for neural networks optimization

NASA Astrophysics Data System (ADS)

Setyawati, Bina R.; Creese, Robert C.; Sahirman, Sidharta

2004-11-01

This paper examines the forecasting performance of multi-layer feed forward neural networks in modeling a particular foreign exchange rates, i.e. Japanese Yen/US Dollar. The effects of two learning methods, Back Propagation and Genetic Algorithm, in which the neural network topology and other parameters fixed, were investigated. The early results indicate that the application of this hybrid system seems to be well suited for the forecasting of foreign exchange rates. The Neural Networks and Genetic Algorithm were programmed using MATLAB«.

Clumpak: a program for identifying clustering modes and packaging population structure inferences across K.

PubMed

Kopelman, Naama M; Mayzel, Jonathan; Jakobsson, Mattias; Rosenberg, Noah A; Mayrose, Itay

2015-09-01

The identification of the genetic structure of populations from multilocus genotype data has become a central component of modern population-genetic data analysis. Application of model-based clustering programs often entails a number of steps, in which the user considers different modelling assumptions, compares results across different predetermined values of the number of assumed clusters (a parameter typically denoted K), examines multiple independent runs for each fixed value of K, and distinguishes among runs belonging to substantially distinct clustering solutions. Here, we present Clumpak (Cluster Markov Packager Across K), a method that automates the postprocessing of results of model-based population structure analyses. For analysing multiple independent runs at a single K value, Clumpak identifies sets of highly similar runs, separating distinct groups of runs that represent distinct modes in the space of possible solutions. This procedure, which generates a consensus solution for each distinct mode, is performed by the use of a Markov clustering algorithm that relies on a similarity matrix between replicate runs, as computed by the software Clumpp. Next, Clumpak identifies an optimal alignment of inferred clusters across different values of K, extending a similar approach implemented for a fixed K in Clumpp and simplifying the comparison of clustering results across different K values. Clumpak incorporates additional features, such as implementations of methods for choosing K and comparing solutions obtained by different programs, models, or data subsets. Clumpak, available at http://clumpak.tau.ac.il, simplifies the use of model-based analyses of population structure in population genetics and molecular ecology. © 2015 John Wiley & Sons Ltd.

Between acculturation and ambivalence: knowledge of genetics and attitudes towards genetic testing in a consanguineous bedouin community.

PubMed

Raz, Aviad E; Atar, Marcela; Rodnay, Maya; Shoham-Vardi, Ilana; Carmi, Rivka

2003-01-01

The Bedouins of the Negev (Southern part of Israel) are a community at increased risk for genetic diseases and congenital anomalies as a result of frequent consanguinity (particularly patrilateral parallel-cousin marriage) and underutilization of prenatal genetic tests due to a Muslim ban on abortion. To assess the knowledge and attitudes of Bedouin schoolchildren and their teachers towards a community-based, premarital carrier-matching program aimed at reducing the prevalence at birth of genetic diseases. A questionnaire was presented to 61 teachers and 40 schoolchildren as part of guided interaction in small groups, conducted in Bedouin schools between 1999 and 2001. Susceptibility as well as knowledge of genetics were found to correlate with a positive attitude towards the genetics program among both teachers and pupils. However, pupils had a lower knowledge index as compared to teachers, and their attitudes were slightly less positive. The difference between teachers and pupils is discussed in the context of the latter's acculturation, which contradicts tradition and parental authority and can generate ambivalence. Attitudes are further discussed in the context of the Health Belief Model and the complex interplay of tradition, Islam, cousin marriage and biomedicine. Copyright 2003 S. Karger AG, Basel

Developmental Programming Mediated by Complementary Roles of Imprinted Grb10 in Mother and Pup

PubMed Central

Cowley, Michael; Garfield, Alastair S.; Madon-Simon, Marta; Charalambous, Marika; Clarkson, Richard W.; Smalley, Matthew J.; Kendrick, Howard; Isles, Anthony R.; Parry, Aled J.; Carney, Sara; Oakey, Rebecca J.; Heisler, Lora K.; Moorwood, Kim; Wolf, Jason B.; Ward, Andrew

2014-01-01

Developmental programming links growth in early life with health status in adulthood. Although environmental factors such as maternal diet can influence the growth and adult health status of offspring, the genetic influences on this process are poorly understood. Using the mouse as a model, we identify the imprinted gene Grb10 as a mediator of nutrient supply and demand in the postnatal period. The combined actions of Grb10 expressed in the mother, controlling supply, and Grb10 expressed in the offspring, controlling demand, jointly regulate offspring growth. Furthermore, Grb10 determines the proportions of lean and fat tissue during development, thereby influencing energy homeostasis in the adult. Most strikingly, we show that the development of normal lean/fat proportions depends on the combined effects of Grb10 expressed in the mother, which has the greater effect on offspring adiposity, and Grb10 expressed in the offspring, which influences lean mass. These distinct functions of Grb10 in mother and pup act complementarily, which is consistent with a coadaptation model of imprinting evolution, a model predicted but for which there is limited experimental evidence. In addition, our findings identify Grb10 as a key genetic component of developmental programming, and highlight the need for a better understanding of mother-offspring interactions at the genetic level in predicting adult disease risk. PMID:24586114

Drag reduction of a car model by linear genetic programming control

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Methods for cost estimation in software project management

NASA Astrophysics Data System (ADS)

Briciu, C. V.; Filip, I.; Indries, I. I.

2016-02-01

The speed in which the processes used in software development field have changed makes it very difficult the task of forecasting the overall costs for a software project. By many researchers, this task has been considered unachievable, but there is a group of scientist for which this task can be solved using the already known mathematical methods (e.g. multiple linear regressions) and the new techniques as genetic programming and neural networks. The paper presents a solution for building a model for the cost estimation models in the software project management using genetic algorithms starting from the PROMISE datasets related COCOMO 81 model. In the first part of the paper, a summary of the major achievements in the research area of finding a model for estimating the overall project costs is presented together with the description of the existing software development process models. In the last part, a basic proposal of a mathematical model of a genetic programming is proposed including here the description of the chosen fitness function and chromosome representation. The perspective of model described it linked with the current reality of the software development considering as basis the software product life cycle and the current challenges and innovations in the software development area. Based on the author's experiences and the analysis of the existing models and product lifecycle it was concluded that estimation models should be adapted with the new technologies and emerging systems and they depend largely by the chosen software development method.

Perceived knowledge and clinical comfort with genetics among Taiwanese nurses enrolled in a RN-to-BSN program.

PubMed

Hsiao, Chiu-Yueh; Lee, Shu-Hsin; Chen, Suh-Jen; Lin, Shu-Chin

2013-08-01

Advances in genetics have had a profound impact on health care. Yet, many nurses, as well as other health care providers, have limited genetic knowledge and feel uncomfortable integrating genetics into their practice. Very little is known about perceived genetic knowledge and clinical comfort among Taiwanese nurses enrolled in a Registered Nurse to Bachelor of Science in Nursing program. To examine perceived knowledge and clinical comfort with genetics among Taiwanese nurses enrolled in a Registered Nurse to Bachelor of Science in Nursing program and to assess how genetics has been integrated into their past and current nursing programs. The study also sought to examine correlations among perceived knowledge, integration of genetics into the nursing curriculum, and clinical comfort with genetics. A descriptive, cross-sectional study. Taiwanese nurses enrolled in a Registered Nurse to Bachelor of Science in Nursing program were recruited. A total of 190 of 220 nurses returned the completed survey (86.36% response rate). Descriptive statistics and the Pearson product-moment correlation were used for data analysis. Most nurses indicated limited perceived knowledge and clinical comfort with genetics. Curricular hours focused on genetics in a current nursing program were greater than those in past nursing programs. The use of genetic materials, attendance at genetic workshops and conferences, and clinically relevant genetics in nursing practice significantly related with perceived knowledge and clinical comfort with genetics. However, there were no correlations between prior genetic-based health care, perceived knowledge, and clinical comfort with genetics. This study demonstrated the need for emphasizing genetic education and practice to ensure health-related professionals become knowledgeable about genetic information. Given the rapidly developing genetic revolution, nurses and other health care providers need to utilize genetic discoveries to optimize health outcomes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Using Workflow Modeling to Identify Areas to Improve Genetic Test Processes in the University of Maryland Translational Pharmacogenomics Project.

PubMed

Cutting, Elizabeth M; Overby, Casey L; Banchero, Meghan; Pollin, Toni; Kelemen, Mark; Shuldiner, Alan R; Beitelshees, Amber L

Delivering genetic test results to clinicians is a complex process. It involves many actors and multiple steps, requiring all of these to work together in order to create an optimal course of treatment for the patient. We used information gained from focus groups in order to illustrate the current process of delivering genetic test results to clinicians. We propose a business process model and notation (BPMN) representation of this process for a Translational Pharmacogenomics Project being implemented at the University of Maryland Medical Center, so that personalized medicine program implementers can identify areas to improve genetic testing processes. We found that the current process could be improved to reduce input errors, better inform and notify clinicians about the implications of certain genetic tests, and make results more easily understood. We demonstrate our use of BPMN to improve this important clinical process for CYP2C19 genetic testing in patients undergoing invasive treatment of coronary heart disease.

Using Workflow Modeling to Identify Areas to Improve Genetic Test Processes in the University of Maryland Translational Pharmacogenomics Project

PubMed Central

Cutting, Elizabeth M.; Overby, Casey L.; Banchero, Meghan; Pollin, Toni; Kelemen, Mark; Shuldiner, Alan R.; Beitelshees, Amber L.

2015-01-01

Delivering genetic test results to clinicians is a complex process. It involves many actors and multiple steps, requiring all of these to work together in order to create an optimal course of treatment for the patient. We used information gained from focus groups in order to illustrate the current process of delivering genetic test results to clinicians. We propose a business process model and notation (BPMN) representation of this process for a Translational Pharmacogenomics Project being implemented at the University of Maryland Medical Center, so that personalized medicine program implementers can identify areas to improve genetic testing processes. We found that the current process could be improved to reduce input errors, better inform and notify clinicians about the implications of certain genetic tests, and make results more easily understood. We demonstrate our use of BPMN to improve this important clinical process for CYP2C19 genetic testing in patients undergoing invasive treatment of coronary heart disease. PMID:26958179

Decade Review (1999-2009): Artificial Intelligence Techniques in Student Modeling

NASA Astrophysics Data System (ADS)

Drigas, Athanasios S.; Argyri, Katerina; Vrettaros, John

Artificial Intelligence applications in educational field are getting more and more popular during the last decade (1999-2009) and that is why much relevant research has been conducted. In this paper, we present the most interesting attempts to apply artificial intelligence methods such as fuzzy logic, neural networks, genetic programming and hybrid approaches such as neuro - fuzzy systems and genetic programming neural networks (GPNN) in student modeling. This latest research trend is a part of every Intelligent Tutoring System and aims at generating and updating a student model in order to modify learning content to fit individual needs or to provide reliable assessment and feedback to student's answers. In this paper, we make a brief presentation of methods used to point out their qualities and then we attempt a navigation to the most representative studies sought in the decade of our interest after classifying them according to the principal aim they attempted to serve.

Fuzzy multiobjective models for optimal operation of a hydropower system

NASA Astrophysics Data System (ADS)

Teegavarapu, Ramesh S. V.; Ferreira, André R.; Simonovic, Slobodan P.

2013-06-01

Optimal operation models for a hydropower system using new fuzzy multiobjective mathematical programming models are developed and evaluated in this study. The models use (i) mixed integer nonlinear programming (MINLP) with binary variables and (ii) integrate a new turbine unit commitment formulation along with water quality constraints used for evaluation of reservoir downstream impairment. Reardon method used in solution of genetic algorithm optimization problems forms the basis for development of a new fuzzy multiobjective hydropower system optimization model with creation of Reardon type fuzzy membership functions. The models are applied to a real-life hydropower reservoir system in Brazil. Genetic Algorithms (GAs) are used to (i) solve the optimization formulations to avoid computational intractability and combinatorial problems associated with binary variables in unit commitment, (ii) efficiently address Reardon method formulations, and (iii) deal with local optimal solutions obtained from the use of traditional gradient-based solvers. Decision maker's preferences are incorporated within fuzzy mathematical programming formulations to obtain compromise operating rules for a multiobjective reservoir operation problem dominated by conflicting goals of energy production, water quality and conservation releases. Results provide insight into compromise operation rules obtained using the new Reardon fuzzy multiobjective optimization framework and confirm its applicability to a variety of multiobjective water resources problems.

A Road Map for 21st Century Genetic Restoration: Gene Pool Enrichment of the Black-Footed Ferret.

PubMed

Wisely, Samantha M; Ryder, Oliver A; Santymire, Rachel M; Engelhardt, John F; Novak, Ben J

2015-01-01

Interspecies somatic cell nuclear transfer (iSCNT) could benefit recovery programs of critically endangered species but must be weighed with the risks of failure. To weigh the risks and benefits, a decision-making process that evaluates progress is needed. Experiments that evaluate the efficiency and efficacy of blastocyst, fetal, and post-parturition development are necessary to determine the success or failure or species-specific iSCNT programs. Here, we use the black-footed ferret (Mustela nigripes) as a case study for evaluating this emerging biomedical technology as a tool for genetic restoration. The black-footed ferret has depleted genetic variation yet genome resource banks contain genetic material of individuals not currently represented in the extant lineage. Thus, genetic restoration of the species is in theory possible and could help reduce the persistent erosion of genetic diversity from drift. Extensive genetic, genomic, and reproductive science tools have previously been developed in black-footed ferrets and would aid in the process of developing an iSCNT protocol for this species. Nonetheless, developing reproductive cloning will require years of experiments and a coordinated effort among recovery partners. The information gained from a well-planned research effort with the goal of genetic restoration via reproductive cloning could establish a 21st century model for evaluating and implementing conservation breeding that would be applicable to other genetically impoverished species. © The American Genetic Association. 2015.

Data Based Prediction of Blood Glucose Concentrations Using Evolutionary Methods.

PubMed

Hidalgo, J Ignacio; Colmenar, J Manuel; Kronberger, Gabriel; Winkler, Stephan M; Garnica, Oscar; Lanchares, Juan

2017-08-08

Predicting glucose values on the basis of insulin and food intakes is a difficult task that people with diabetes need to do daily. This is necessary as it is important to maintain glucose levels at appropriate values to avoid not only short-term, but also long-term complications of the illness. Artificial intelligence in general and machine learning techniques in particular have already lead to promising results in modeling and predicting glucose concentrations. In this work, several machine learning techniques are used for the modeling and prediction of glucose concentrations using as inputs the values measured by a continuous monitoring glucose system as well as also previous and estimated future carbohydrate intakes and insulin injections. In particular, we use the following four techniques: genetic programming, random forests, k-nearest neighbors, and grammatical evolution. We propose two new enhanced modeling algorithms for glucose prediction, namely (i) a variant of grammatical evolution which uses an optimized grammar, and (ii) a variant of tree-based genetic programming which uses a three-compartment model for carbohydrate and insulin dynamics. The predictors were trained and tested using data of ten patients from a public hospital in Spain. We analyze our experimental results using the Clarke error grid metric and see that 90% of the forecasts are correct (i.e., Clarke error categories A and B), but still even the best methods produce 5 to 10% of serious errors (category D) and approximately 0.5% of very serious errors (category E). We also propose an enhanced genetic programming algorithm that incorporates a three-compartment model into symbolic regression models to create smoothed time series of the original carbohydrate and insulin time series.

Concordant but Varied Phenotypes among Duchenne Muscular Dystrophy Patient-Specific Myoblasts Derived using a Human iPSC-Based Model.

PubMed

Choi, In Young; Lim, HoTae; Estrellas, Kenneth; Mula, Jyothi; Cohen, Tatiana V; Zhang, Yuanfan; Donnelly, Christopher J; Richard, Jean-Philippe; Kim, Yong Jun; Kim, Hyesoo; Kazuki, Yasuhiro; Oshimura, Mitsuo; Li, Hongmei Lisa; Hotta, Akitsu; Rothstein, Jeffrey; Maragakis, Nicholas; Wagner, Kathryn R; Lee, Gabsang

2016-06-07

Duchenne muscular dystrophy (DMD) remains an intractable genetic disease. Althogh there are several animal models of DMD, there is no human cell model that carries patient-specific DYSTROPHIN mutations. Here, we present a human DMD model using human induced pluripotent stem cells (hiPSCs). Our model reveals concordant disease-related phenotypes with patient-dependent variation, which are partially reversed by genetic and pharmacological approaches. Our "chemical-compound-based" strategy successfully directs hiPSCs into expandable myoblasts, which exhibit a myogenic transcriptional program, forming striated contractile myofibers and participating in muscle regeneration in vivo. DMD-hiPSC-derived myoblasts show disease-related phenotypes with patient-to-patient variability, including aberrant expression of inflammation or immune-response genes and collagens, increased BMP/TGFβ signaling, and reduced fusion competence. Furthermore, by genetic correction and pharmacological "dual-SMAD" inhibition, the DMD-hiPSC-derived myoblasts and genetically corrected isogenic myoblasts form "rescued" multi-nucleated myotubes. In conclusion, our findings demonstrate the feasibility of establishing a human "DMD-in-a-dish" model using hiPSC-based disease modeling. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

Data sharing as a national quality improvement program: reporting on BRCA1 and BRCA2 variant-interpretation comparisons through the Canadian Open Genetics Repository (COGR).

PubMed

Lebo, Matthew S; Zakoor, Kathleen-Rose; Chun, Kathy; Speevak, Marsha D; Waye, John S; McCready, Elizabeth; Parboosingh, Jillian S; Lamont, Ryan E; Feilotter, Harriet; Bosdet, Ian; Tucker, Tracy; Young, Sean; Karsan, Aly; Charames, George S; Agatep, Ronald; Spriggs, Elizabeth L; Chisholm, Caitlin; Vasli, Nasim; Daoud, Hussein; Jarinova, Olga; Tomaszewski, Robert; Hume, Stacey; Taylor, Sherryl; Akbari, Mohammad R; Lerner-Ellis, Jordan

2018-03-01

PurposeThe purpose of this study was to develop a national program for Canadian diagnostic laboratories to compare DNA-variant interpretations and resolve discordant-variant classifications using the BRCA1 and BRCA2 genes as a case study.MethodsBRCA1 and BRCA2 variant data were uploaded and shared through the Canadian Open Genetics Repository (COGR; http://www.opengenetics.ca). A total of 5,554 variant observations were submitted; classification differences were identified and comparison reports were sent to participating laboratories. Each site had the opportunity to reclassify variants. The data were analyzed before and after the comparison report process to track concordant- or discordant-variant classifications by three different models.ResultsVariant-discordance rates varied by classification model: 38.9% of variants were discordant when using a five-tier model, 26.7% with a three-tier model, and 5.0% with a two-tier model. After the comparison report process, the proportion of discordant variants dropped to 30.7% with the five-tier model, to 14.2% with the three-tier model, and to 0.9% using the two-tier model.ConclusionWe present a Canadian interinstitutional quality improvement program for DNA-variant interpretations. Sharing of variant knowledge by clinical diagnostic laboratories will allow clinicians and patients to make more informed decisions and lead to better patient outcomes.

Discovering Link Communities in Complex Networks by an Integer Programming Model and a Genetic Algorithm

PubMed Central

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

2013-01-01

Identification of communities in complex networks is an important topic and issue in many fields such as sociology, biology, and computer science. Communities are often defined as groups of related nodes or links that correspond to functional subunits in the corresponding complex systems. While most conventional approaches have focused on discovering communities of nodes, some recent studies start partitioning links to find overlapping communities straightforwardly. In this paper, we propose a new quantity function for link community identification in complex networks. Based on this quantity function we formulate the link community partition problem into an integer programming model which allows us to partition a complex network into overlapping communities. We further propose a genetic algorithm for link community detection which can partition a network into overlapping communities without knowing the number of communities. We test our model and algorithm on both artificial networks and real-world networks. The results demonstrate that the model and algorithm are efficient in detecting overlapping community structure in complex networks. PMID:24386268

Learning oncogenetic networks by reducing to mixed integer linear programming.

PubMed

Shahrabi Farahani, Hossein; Lagergren, Jens

2013-01-01

Cancer can be a result of accumulation of different types of genetic mutations such as copy number aberrations. The data from tumors are cross-sectional and do not contain the temporal order of the genetic events. Finding the order in which the genetic events have occurred and progression pathways are of vital importance in understanding the disease. In order to model cancer progression, we propose Progression Networks, a special case of Bayesian networks, that are tailored to model disease progression. Progression networks have similarities with Conjunctive Bayesian Networks (CBNs) [1],a variation of Bayesian networks also proposed for modeling disease progression. We also describe a learning algorithm for learning Bayesian networks in general and progression networks in particular. We reduce the hard problem of learning the Bayesian and progression networks to Mixed Integer Linear Programming (MILP). MILP is a Non-deterministic Polynomial-time complete (NP-complete) problem for which very good heuristics exists. We tested our algorithm on synthetic and real cytogenetic data from renal cell carcinoma. We also compared our learned progression networks with the networks proposed in earlier publications. The software is available on the website https://bitbucket.org/farahani/diprog.

Flow discharge prediction in compound channels using linear genetic programming

NASA Astrophysics Data System (ADS)

Azamathulla, H. Md.; Zahiri, A.

2012-08-01

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

Simulating a base population in honey bee for molecular genetic studies

PubMed Central

2012-01-01

Background Over the past years, reports have indicated that honey bee populations are declining and that infestation by an ecto-parasitic mite (Varroa destructor) is one of the main causes. Selective breeding of resistant bees can help to prevent losses due to the parasite, but it requires that a robust breeding program and genetic evaluation are implemented. Genomic selection has emerged as an important tool in animal breeding programs and simulation studies have shown that it yields more accurate breeding value estimates, higher genetic gain and low rates of inbreeding. Since genomic selection relies on marker data, simulations conducted on a genomic dataset are a pre-requisite before selection can be implemented. Although genomic datasets have been simulated in other species undergoing genetic evaluation, simulation of a genomic dataset specific to the honey bee is required since this species has a distinct genetic and reproductive biology. Our software program was aimed at constructing a base population by simulating a random mating honey bee population. A forward-time population simulation approach was applied since it allows modeling of genetic characteristics and reproductive behavior specific to the honey bee. Results Our software program yielded a genomic dataset for a base population in linkage disequilibrium. In addition, information was obtained on (1) the position of markers on each chromosome, (2) allele frequency, (3) χ2 statistics for Hardy-Weinberg equilibrium, (4) a sorted list of markers with a minor allele frequency less than or equal to the input value, (5) average r2 values of linkage disequilibrium between all simulated marker loci pair for all generations and (6) average r2 value of linkage disequilibrium in the last generation for selected markers with the highest minor allele frequency. Conclusion We developed a software program that takes into account the genetic and reproductive biology specific to the honey bee and that can be used to constitute a genomic dataset compatible with the simulation studies necessary to optimize breeding programs. The source code together with an instruction file is freely accessible at http://msproteomics.org/Research/Misc/honeybeepopulationsimulator.html PMID:22520469

Simulating a base population in honey bee for molecular genetic studies.

PubMed

Gupta, Pooja; Conrad, Tim; Spötter, Andreas; Reinsch, Norbert; Bienefeld, Kaspar

2012-06-27

Over the past years, reports have indicated that honey bee populations are declining and that infestation by an ecto-parasitic mite (Varroa destructor) is one of the main causes. Selective breeding of resistant bees can help to prevent losses due to the parasite, but it requires that a robust breeding program and genetic evaluation are implemented. Genomic selection has emerged as an important tool in animal breeding programs and simulation studies have shown that it yields more accurate breeding value estimates, higher genetic gain and low rates of inbreeding. Since genomic selection relies on marker data, simulations conducted on a genomic dataset are a pre-requisite before selection can be implemented. Although genomic datasets have been simulated in other species undergoing genetic evaluation, simulation of a genomic dataset specific to the honey bee is required since this species has a distinct genetic and reproductive biology. Our software program was aimed at constructing a base population by simulating a random mating honey bee population. A forward-time population simulation approach was applied since it allows modeling of genetic characteristics and reproductive behavior specific to the honey bee. Our software program yielded a genomic dataset for a base population in linkage disequilibrium. In addition, information was obtained on (1) the position of markers on each chromosome, (2) allele frequency, (3) χ(2) statistics for Hardy-Weinberg equilibrium, (4) a sorted list of markers with a minor allele frequency less than or equal to the input value, (5) average r(2) values of linkage disequilibrium between all simulated marker loci pair for all generations and (6) average r2 value of linkage disequilibrium in the last generation for selected markers with the highest minor allele frequency. We developed a software program that takes into account the genetic and reproductive biology specific to the honey bee and that can be used to constitute a genomic dataset compatible with the simulation studies necessary to optimize breeding programs. The source code together with an instruction file is freely accessible at http://msproteomics.org/Research/Misc/honeybeepopulationsimulator.html.

Caenorhabditis elegans: An Emerging Model in Biomedical and Environmental Toxicology

PubMed Central

Leung, Maxwell C. K.; Williams, Phillip L.; Benedetto, Alexandre; Au, Catherine; Helmcke, Kirsten J.; Aschner, Michael; Meyer, Joel N.

2008-01-01

The nematode Caenorhabditis elegans has emerged as an important animal model in various fields including neurobiology, developmental biology, and genetics. Characteristics of this animal model that have contributed to its success include its genetic manipulability, invariant and fully described developmental program, well-characterized genome, ease of maintenance, short and prolific life cycle, and small body size. These same features have led to an increasing use of C. elegans in toxicology, both for mechanistic studies and high-throughput screening approaches. We describe some of the research that has been carried out in the areas of neurotoxicology, genetic toxicology, and environmental toxicology, as well as high-throughput experiments with C. elegans including genome-wide screening for molecular targets of toxicity and rapid toxicity assessment for new chemicals. We argue for an increased role for C. elegans in complementing other model systems in toxicological research. PMID:18566021

CDMetaPOP: An individual-based, eco-evolutionary model for spatially explicit simulation of landscape demogenetics

USGS Publications Warehouse

Landguth, Erin L; Bearlin, Andrew; Day, Casey; Dunham, Jason B.

2016-01-01

1. Combining landscape demographic and genetics models offers powerful methods for addressing questions for eco-evolutionary applications.2. Using two illustrative examples, we present Cost–Distance Meta-POPulation, a program to simulate changes in neutral and/or selection-driven genotypes through time as a function of individual-based movement, complex spatial population dynamics, and multiple and changing landscape drivers.3. Cost–Distance Meta-POPulation provides a novel tool for questions in landscape genetics by incorporating population viability analysis, while linking directly to conservation applications.

A Road Map for 21st Century Genetic Restoration: Gene Pool Enrichment of the Black-Footed Ferret

PubMed Central

Ryder, Oliver A.; Santymire, Rachel M.; Engelhardt, John F.; Novak, Ben J.

2015-01-01

Interspecies somatic cell nuclear transfer (iSCNT) could benefit recovery programs of critically endangered species but must be weighed with the risks of failure. To weigh the risks and benefits, a decision-making process that evaluates progress is needed. Experiments that evaluate the efficiency and efficacy of blastocyst, fetal, and post-parturition development are necessary to determine the success or failure or species-specific iSCNT programs. Here, we use the black-footed ferret (Mustela nigripes) as a case study for evaluating this emerging biomedical technology as a tool for genetic restoration. The black-footed ferret has depleted genetic variation yet genome resource banks contain genetic material of individuals not currently represented in the extant lineage. Thus, genetic restoration of the species is in theory possible and could help reduce the persistent erosion of genetic diversity from drift. Extensive genetic, genomic, and reproductive science tools have previously been developed in black-footed ferrets and would aid in the process of developing an iSCNT protocol for this species. Nonetheless, developing reproductive cloning will require years of experiments and a coordinated effort among recovery partners. The information gained from a well-planned research effort with the goal of genetic restoration via reproductive cloning could establish a 21st century model for evaluating and implementing conservation breeding that would be applicable to other genetically impoverished species. PMID:26304983

Genetic programming assisted stochastic optimization strategies for optimization of glucose to gluconic acid fermentation.

PubMed

Cheema, Jitender Jit Singh; Sankpal, Narendra V; Tambe, Sanjeev S; Kulkarni, Bhaskar D

2002-01-01

This article presents two hybrid strategies for the modeling and optimization of the glucose to gluconic acid batch bioprocess. In the hybrid approaches, first a novel artificial intelligence formalism, namely, genetic programming (GP), is used to develop a process model solely from the historic process input-output data. In the next step, the input space of the GP-based model, representing process operating conditions, is optimized using two stochastic optimization (SO) formalisms, viz., genetic algorithms (GAs) and simultaneous perturbation stochastic approximation (SPSA). These SO formalisms possess certain unique advantages over the commonly used gradient-based optimization techniques. The principal advantage of the GP-GA and GP-SPSA hybrid techniques is that process modeling and optimization can be performed exclusively from the process input-output data without invoking the detailed knowledge of the process phenomenology. The GP-GA and GP-SPSA techniques have been employed for modeling and optimization of the glucose to gluconic acid bioprocess, and the optimized process operating conditions obtained thereby have been compared with those obtained using two other hybrid modeling-optimization paradigms integrating artificial neural networks (ANNs) and GA/SPSA formalisms. Finally, the overall optimized operating conditions given by the GP-GA method, when verified experimentally resulted in a significant improvement in the gluconic acid yield. The hybrid strategies presented here are generic in nature and can be employed for modeling and optimization of a wide variety of batch and continuous bioprocesses.

Data protection in biomaterial banks for Parkinson's disease research: the model of GEPARD (Gene Bank Parkinson's Disease Germany).

PubMed

Eggert, Karla; Wüllner, Ullrich; Antony, Gisela; Gasser, Thomas; Janetzky, Bernd; Klein, Christine; Schöls, Ludger; Oertel, Wolfgang

2007-04-15

Parkinson's disease (PD) is the second most common neurodegenerative disease. Although 10 gene loci have been identified to cause a Parkinsonian syndrome, these loci account only for a minority of PD patients. Large, systematic research programs are required to collect, store, and analyze DNA samples and clinical information to support further discovery of additional genetic components of PD or other movement disorders. Such programs facilitate research into the relationship between genotype and phenotype. The German Competence Network on Parkinson's disease (CNP) initiated the Gene Bank Parkinson's Disease Germany (GEPARD), providing an administrative and scientific infrastructure for the storage of DNA and clinical data that are electronically accessible and protective of patient rights. In this article, we offer guidance on how to establish a framework for a clinical genetic data and DNA bank, and describe GEPARD as a model that may be useful to other local, national, and international research groups developing similar programs.

A 100-Year Review: Methods and impact of genetic selection in dairy cattle-From daughter-dam comparisons to deep learning algorithms.

PubMed

Weigel, K A; VanRaden, P M; Norman, H D; Grosu, H

2017-12-01

In the early 1900s, breed society herdbooks had been established and milk-recording programs were in their infancy. Farmers wanted to improve the productivity of their cattle, but the foundations of population genetics, quantitative genetics, and animal breeding had not been laid. Early animal breeders struggled to identify genetically superior families using performance records that were influenced by local environmental conditions and herd-specific management practices. Daughter-dam comparisons were used for more than 30 yr and, although genetic progress was minimal, the attention given to performance recording, genetic theory, and statistical methods paid off in future years. Contemporary (herdmate) comparison methods allowed more accurate accounting for environmental factors and genetic progress began to accelerate when these methods were coupled with artificial insemination and progeny testing. Advances in computing facilitated the implementation of mixed linear models that used pedigree and performance data optimally and enabled accurate selection decisions. Sequencing of the bovine genome led to a revolution in dairy cattle breeding, and the pace of scientific discovery and genetic progress accelerated rapidly. Pedigree-based models have given way to whole-genome prediction, and Bayesian regression models and machine learning algorithms have joined mixed linear models in the toolbox of modern animal breeders. Future developments will likely include elucidation of the mechanisms of genetic inheritance and epigenetic modification in key biological pathways, and genomic data will be used with data from on-farm sensors to facilitate precision management on modern dairy farms. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Accuracies of univariate and multivariate genomic prediction models in African cassava.

PubMed

Okeke, Uche Godfrey; Akdemir, Deniz; Rabbi, Ismail; Kulakow, Peter; Jannink, Jean-Luc

2017-12-04

Genomic selection (GS) promises to accelerate genetic gain in plant breeding programs especially for crop species such as cassava that have long breeding cycles. Practically, to implement GS in cassava breeding, it is necessary to evaluate different GS models and to develop suitable models for an optimized breeding pipeline. In this paper, we compared (1) prediction accuracies from a single-trait (uT) and a multi-trait (MT) mixed model for a single-environment genetic evaluation (Scenario 1), and (2) accuracies from a compound symmetric multi-environment model (uE) parameterized as a univariate multi-kernel model to a multivariate (ME) multi-environment mixed model that accounts for genotype-by-environment interaction for multi-environment genetic evaluation (Scenario 2). For these analyses, we used 16 years of public cassava breeding data for six target cassava traits and a fivefold cross-validation scheme with 10-repeat cycles to assess model prediction accuracies. In Scenario 1, the MT models had higher prediction accuracies than the uT models for all traits and locations analyzed, which amounted to on average a 40% improved prediction accuracy. For Scenario 2, we observed that the ME model had on average (across all locations and traits) a 12% improved prediction accuracy compared to the uE model. We recommend the use of multivariate mixed models (MT and ME) for cassava genetic evaluation. These models may be useful for other plant species.

Genetic variation and correlated changes in reproductive performance of a red tilapia line selected for improved growth over three generations.

PubMed

Thoa, Ngo Phu; Hamzah, Azhar; Nguyen, Nguyen Hong

2017-09-01

The present study examines genetic variation and correlated changes in reproductive performance traits in a red tilapia (Oreochromis spp.) population selected over three generations for improved growth. A total of 328 breeding females (offspring of 111 sires and 118 dams) had measurements of body weight prior to spawning (WBS), number of fry at hatching (NFH), total fry weight (TFW) and number of dead fry (NDF) or mortality of fry including unhatched eggs at hatching (MFH). Restricted maximum likelihood (REML) analysis in a multi-trait model showed that there are heritable genetic components for all traits studied. The heritability for WBS was very high (0.80). The estimates for traits related to fecundity (NFH, TFW) and survival (NDF) were low and they were associated with high standard errors. Genetic correlations of WBS with other reproductive performance traits (NFH, TFW and NDF) were generally positive. However, NFH was negatively correlated genetically with TFW. As expected, body measurements during growth stage exhibited strong positive genetic correlations with WBS. The genetic correlations between body traits and reproductive performance (NFH, TFW, NDF) were not significant. Correlated responses in reproductive traits were measured as changes in least squares means between generations or spawning years. Except for WBS that increased with the selection programs, the phenotypic changes in other reproductive traits observed were not statistically significant (P>0.05). It is concluded that the selection program for red tilapia has resulted in very little changes in reproductive performance of the animals after three generations. However, periodic monitoring of genetic changes in fecundity and fitness related traits such as NDF or MFH should be made in selective breeding programs for red tilapia. Copyright © 2017 Elsevier B.V. All rights reserved.

Inequities in genetic testing for hereditary breast cancer: implications for public health practice.

PubMed

Sayani, Ambreen

2018-05-20

The Ontario Breast Screening Program for women with a genetic predisposition to breast cancer is one of the first international models of a government-funded public health service that offers systematic genetic screening to women at a high risk of breast cancer. However, since the implementation of the program in 2011, enrolment rates have been lower than anticipated. Whilst there may be several reasons for this to happen, it does call into consideration the 'inverse equity law', whereby the more advantaged in society are the first to participate and benefit from universal health services. An outcome of this phenomenon is an increase in the health divide between those that are at a social advantage versus those that are not. Using an intersectionality lens, this paper explores the role of the social determinants of health and social identity in creating possible barriers in the access to genetic screening for hereditary breast cancer, and the implications for public health practice in recognising and ameliorating these differences.

Methods for identifying SNP interactions: a review on variations of Logic Regression, Random Forest and Bayesian logistic regression.

PubMed

Chen, Carla Chia-Ming; Schwender, Holger; Keith, Jonathan; Nunkesser, Robin; Mengersen, Kerrie; Macrossan, Paula

2011-01-01

Due to advancements in computational ability, enhanced technology and a reduction in the price of genotyping, more data are being generated for understanding genetic associations with diseases and disorders. However, with the availability of large data sets comes the inherent challenges of new methods of statistical analysis and modeling. Considering a complex phenotype may be the effect of a combination of multiple loci, various statistical methods have been developed for identifying genetic epistasis effects. Among these methods, logic regression (LR) is an intriguing approach incorporating tree-like structures. Various methods have built on the original LR to improve different aspects of the model. In this study, we review four variations of LR, namely Logic Feature Selection, Monte Carlo Logic Regression, Genetic Programming for Association Studies, and Modified Logic Regression-Gene Expression Programming, and investigate the performance of each method using simulated and real genotype data. We contrast these with another tree-like approach, namely Random Forests, and a Bayesian logistic regression with stochastic search variable selection.

An economic evaluation of a genetic screening program for Tay-Sachs disease.

PubMed Central

Nelson, W B; Swint, J M; Caskey, C T

1978-01-01

The resolution of policy questions relating to medical genetic screening programs will not be without considerable difficulty. Examples include such issues as the optimal degree of screening program expansion, the relative values of screening for different genetic diseases, the appropriate sources of program funding (public vs. private), and the relative value of funding expanded genetic screening programs vs. research directed toward elimination of genetic traits themselves. Information on the net impact of the relevant alternatives is greatly needed, and this need will increase if the National Genetics Act receives funding approval. We have provided what is hopefully a contribution toward this end. While our analysis pertains to a specific disease and a specific screening program for that disease, the methodology is readily generalizable to other genetic diseases, as well as programs of any size or structure. Hopefully, this will serve to stimulate further research efforts that we believe are needed for the objective consideration of resource allocation alternatives. PMID:418675

An economic evaluation of a genetic screening program for Tay-Sachs disease.

PubMed

Nelson, W B; Swint, J M; Caskey, C T

1978-03-01

The resolution of policy questions relating to medical genetic screening programs will not be without considerable difficulty. Examples include such issues as the optimal degree of screening program expansion, the relative values of screening for different genetic diseases, the appropriate sources of program funding (public vs. private), and the relative value of funding expanded genetic screening programs vs. research directed toward elimination of genetic traits themselves. Information on the net impact of the relevant alternatives is greatly needed, and this need will increase if the National Genetics Act receives funding approval. We have provided what is hopefully a contribution toward this end. While our analysis pertains to a specific disease and a specific screening program for that disease, the methodology is readily generalizable to other genetic diseases, as well as programs of any size or structure. Hopefully, this will serve to stimulate further research efforts that we believe are needed for the objective consideration of resource allocation alternatives.

Applications of population genetics to animal breeding, from wright, fisher and lush to genomic prediction.

PubMed

Hill, William G

2014-01-01

Although animal breeding was practiced long before the science of genetics and the relevant disciplines of population and quantitative genetics were known, breeding programs have mainly relied on simply selecting and mating the best individuals on their own or relatives' performance. This is based on sound quantitative genetic principles, developed and expounded by Lush, who attributed much of his understanding to Wright, and formalized in Fisher's infinitesimal model. Analysis at the level of individual loci and gene frequency distributions has had relatively little impact. Now with access to genomic data, a revolution in which molecular information is being used to enhance response with "genomic selection" is occurring. The predictions of breeding value still utilize multiple loci throughout the genome and, indeed, are largely compatible with additive and specifically infinitesimal model assumptions. I discuss some of the history and genetic issues as applied to the science of livestock improvement, which has had and continues to have major spin-offs into ideas and applications in other areas.

Bio-Inspired Genetic Algorithms with Formalized Crossover Operators for Robotic Applications.

PubMed

Zhang, Jie; Kang, Man; Li, Xiaojuan; Liu, Geng-Yang

2017-01-01

Genetic algorithms are widely adopted to solve optimization problems in robotic applications. In such safety-critical systems, it is vitally important to formally prove the correctness when genetic algorithms are applied. This paper focuses on formal modeling of crossover operations that are one of most important operations in genetic algorithms. Specially, we for the first time formalize crossover operations with higher-order logic based on HOL4 that is easy to be deployed with its user-friendly programing environment. With correctness-guaranteed formalized crossover operations, we can safely apply them in robotic applications. We implement our technique to solve a path planning problem using a genetic algorithm with our formalized crossover operations, and the results show the effectiveness of our technique.

Use of qualitative environmental and phenotypic variables in the context of allele distribution models: detecting signatures of selection in the genome of Lake Victoria cichlids.

PubMed

Joost, Stéphane; Kalbermatten, Michael; Bezault, Etienne; Seehausen, Ole

2012-01-01

When searching for loci possibly under selection in the genome, an alternative to population genetics theoretical models is to establish allele distribution models (ADM) for each locus to directly correlate allelic frequencies and environmental variables such as precipitation, temperature, or sun radiation. Such an approach implementing multiple logistic regression models in parallel was implemented within a computing program named MATSAM: . Recently, this application was improved in order to support qualitative environmental predictors as well as to permit the identification of associations between genomic variation and individual phenotypes, allowing the detection of loci involved in the genetic architecture of polymorphic characters. Here, we present the corresponding methodological developments and compare the results produced by software implementing population genetics theoretical models (DFDIST: and BAYESCAN: ) and ADM (MATSAM: ) in an empirical context to detect signatures of genomic divergence associated with speciation in Lake Victoria cichlid fishes.

SDMtoolbox 2.0: the next generation Python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses.

PubMed

Brown, Jason L; Bennett, Joseph R; French, Connor M

2017-01-01

SDMtoolbox 2.0 is a software package for spatial studies of ecology, evolution, and genetics. The release of SDMtoolbox 2.0 allows researchers to use the most current ArcGIS software and MaxEnt software, and reduces the amount of time that would be spent developing common solutions. The central aim of this software is to automate complicated and repetitive spatial analyses in an intuitive graphical user interface. One core tenant facilitates careful parameterization of species distribution models (SDMs) to maximize each model's discriminatory ability and minimize overfitting. This includes carefully processing of occurrence data, environmental data, and model parameterization. This program directly interfaces with MaxEnt, one of the most powerful and widely used species distribution modeling software programs, although SDMtoolbox 2.0 is not limited to species distribution modeling or restricted to modeling in MaxEnt. Many of the SDM pre- and post-processing tools have 'universal' analogs for use with any modeling software. The current version contains a total of 79 scripts that harness the power of ArcGIS for macroecology, landscape genetics, and evolutionary studies. For example, these tools allow for biodiversity quantification (such as species richness or corrected weighted endemism), generation of least-cost paths and corridors among shared haplotypes, assessment of the significance of spatial randomizations, and enforcement of dispersal limitations of SDMs projected into future climates-to only name a few functions contained in SDMtoolbox 2.0. Lastly, dozens of generalized tools exists for batch processing and conversion of GIS data types or formats, which are broadly useful to any ArcMap user.

Reparametrization-based estimation of genetic parameters in multi-trait animal model using Integrated Nested Laplace Approximation.

PubMed

Mathew, Boby; Holand, Anna Marie; Koistinen, Petri; Léon, Jens; Sillanpää, Mikko J

2016-02-01

A novel reparametrization-based INLA approach as a fast alternative to MCMC for the Bayesian estimation of genetic parameters in multivariate animal model is presented. Multi-trait genetic parameter estimation is a relevant topic in animal and plant breeding programs because multi-trait analysis can take into account the genetic correlation between different traits and that significantly improves the accuracy of the genetic parameter estimates. Generally, multi-trait analysis is computationally demanding and requires initial estimates of genetic and residual correlations among the traits, while those are difficult to obtain. In this study, we illustrate how to reparametrize covariance matrices of a multivariate animal model/animal models using modified Cholesky decompositions. This reparametrization-based approach is used in the Integrated Nested Laplace Approximation (INLA) methodology to estimate genetic parameters of multivariate animal model. Immediate benefits are: (1) to avoid difficulties of finding good starting values for analysis which can be a problem, for example in Restricted Maximum Likelihood (REML); (2) Bayesian estimation of (co)variance components using INLA is faster to execute than using Markov Chain Monte Carlo (MCMC) especially when realized relationship matrices are dense. The slight drawback is that priors for covariance matrices are assigned for elements of the Cholesky factor but not directly to the covariance matrix elements as in MCMC. Additionally, we illustrate the concordance of the INLA results with the traditional methods like MCMC and REML approaches. We also present results obtained from simulated data sets with replicates and field data in rice.

Solving deterministic non-linear programming problem using Hopfield artificial neural network and genetic programming techniques

NASA Astrophysics Data System (ADS)

Vasant, P.; Ganesan, T.; Elamvazuthi, I.

2012-11-01

A fairly reasonable result was obtained for non-linear engineering problems using the optimization techniques such as neural network, genetic algorithms, and fuzzy logic independently in the past. Increasingly, hybrid techniques are being used to solve the non-linear problems to obtain better output. This paper discusses the use of neuro-genetic hybrid technique to optimize the geological structure mapping which is known as seismic survey. It involves the minimization of objective function subject to the requirement of geophysical and operational constraints. In this work, the optimization was initially performed using genetic programming, and followed by hybrid neuro-genetic programming approaches. Comparative studies and analysis were then carried out on the optimized results. The results indicate that the hybrid neuro-genetic hybrid technique produced better results compared to the stand-alone genetic programming method.

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

PubMed

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.

Identification of cancer genes that are independent of dominant proliferation and lineage programs

PubMed Central

Selfors, Laura M.; Stover, Daniel G.; Harris, Isaac S.; Brugge, Joan S.; Coloff, Jonathan L.

2017-01-01

Large, multidimensional cancer datasets provide a resource that can be mined to identify candidate therapeutic targets for specific subgroups of tumors. Here, we analyzed human breast cancer data to identify transcriptional programs associated with tumors bearing specific genetic driver alterations. Using an unbiased approach, we identified thousands of genes whose expression was enriched in tumors with specific genetic alterations. However, expression of the vast majority of these genes was not enriched if associations were analyzed within individual breast tumor molecular subtypes, across multiple tumor types, or after gene expression was normalized to account for differences in proliferation or tumor lineage. Together with linear modeling results, these findings suggest that most transcriptional programs associated with specific genetic alterations in oncogenes and tumor suppressors are highly context-dependent and are predominantly linked to differences in proliferation programs between distinct breast cancer subtypes. We demonstrate that such proliferation-dependent gene expression dominates tumor transcriptional programs relative to matched normal tissues. However, we also identified a relatively small group of cancer-associated genes that are both proliferation- and lineage-independent. A subset of these genes are attractive candidate targets for combination therapy because they are essential in breast cancer cell lines, druggable, enriched in stem-like breast cancer cells, and resistant to chemotherapy-induced down-regulation. PMID:29229826

Golden Ratio Genetic Algorithm Based Approach for Modelling and Analysis of the Capacity Expansion of Urban Road Traffic Network

PubMed Central

Zhang, Lun; Zhang, Meng; Yang, Wenchen; Dong, Decun

2015-01-01

This paper presents the modelling and analysis of the capacity expansion of urban road traffic network (ICURTN). Thebilevel programming model is first employed to model the ICURTN, in which the utility of the entire network is maximized with the optimal utility of travelers' route choice. Then, an improved hybrid genetic algorithm integrated with golden ratio (HGAGR) is developed to enhance the local search of simple genetic algorithms, and the proposed capacity expansion model is solved by the combination of the HGAGR and the Frank-Wolfe algorithm. Taking the traditional one-way network and bidirectional network as the study case, three numerical calculations are conducted to validate the presented model and algorithm, and the primary influencing factors on extended capacity model are analyzed. The calculation results indicate that capacity expansion of road network is an effective measure to enlarge the capacity of urban road network, especially on the condition of limited construction budget; the average computation time of the HGAGR is 122 seconds, which meets the real-time demand in the evaluation of the road network capacity. PMID:25802512

PAQ: Partition Analysis of Quasispecies.

PubMed

Baccam, P; Thompson, R J; Fedrigo, O; Carpenter, S; Cornette, J L

2001-01-01

The complexities of genetic data may not be accurately described by any single analytical tool. Phylogenetic analysis is often used to study the genetic relationship among different sequences. Evolutionary models and assumptions are invoked to reconstruct trees that describe the phylogenetic relationship among sequences. Genetic databases are rapidly accumulating large amounts of sequences. Newly acquired sequences, which have not yet been characterized, may require preliminary genetic exploration in order to build models describing the evolutionary relationship among sequences. There are clustering techniques that rely less on models of evolution, and thus may provide nice exploratory tools for identifying genetic similarities. Some of the more commonly used clustering methods perform better when data can be grouped into mutually exclusive groups. Genetic data from viral quasispecies, which consist of closely related variants that differ by small changes, however, may best be partitioned by overlapping groups. We have developed an intuitive exploratory program, Partition Analysis of Quasispecies (PAQ), which utilizes a non-hierarchical technique to partition sequences that are genetically similar. PAQ was used to analyze a data set of human immunodeficiency virus type 1 (HIV-1) envelope sequences isolated from different regions of the brain and another data set consisting of the equine infectious anemia virus (EIAV) regulatory gene rev. Analysis of the HIV-1 data set by PAQ was consistent with phylogenetic analysis of the same data, and the EIAV rev variants were partitioned into two overlapping groups. PAQ provides an additional tool which can be used to glean information from genetic data and can be used in conjunction with other tools to study genetic similarities and genetic evolution of viral quasispecies.

In-Vivo Expression Profiling of Pseudomonas aeruginosa Infections Reveals Niche-Specific and Strain-Independent Transcriptional Programs

PubMed Central

Bielecki, Piotr; Puchałka, Jacek; Wos-Oxley, Melissa L.; Loessner, Holger; Glik, Justyna; Kawecki, Marek; Nowak, Mariusz; Tümmler, Burkhard; Weiss, Siegfried; dos Santos, Vítor A. P. Martins

2011-01-01

Pseudomonas aeruginosa is a threatening, opportunistic pathogen causing disease in immunocompromised individuals. The hallmark of P. aeruginosa virulence is its multi-factorial and combinatorial nature. It renders such bacteria infectious for many organisms and it is often resistant to antibiotics. To gain insights into the physiology of P. aeruginosa during infection, we assessed the transcriptional programs of three different P. aeruginosa strains directly after isolation from burn wounds of humans. We compared the programs to those of the same strains using two infection models: a plant model, which consisted of the infection of the midrib of lettuce leaves, and a murine tumor model, which was obtained by infection of mice with an induced tumor in the abdomen. All control conditions of P. aeruginosa cells growing in suspension and as a biofilm were added to the analysis. We found that these different P. aeruginosa strains express a pool of distinct genetic traits that are activated under particular infection conditions regardless of their genetic variability. The knowledge herein generated will advance our understanding of P. aeruginosa virulence and provide valuable cues for the definition of prospective targets to develop novel intervention strategies. PMID:21931663

In-vivo expression profiling of Pseudomonas aeruginosa infections reveals niche-specific and strain-independent transcriptional programs.

PubMed

Bielecki, Piotr; Puchałka, Jacek; Wos-Oxley, Melissa L; Loessner, Holger; Glik, Justyna; Kawecki, Marek; Nowak, Mariusz; Tümmler, Burkhard; Weiss, Siegfried; dos Santos, Vítor A P Martins

2011-01-01

Pseudomonas aeruginosa is a threatening, opportunistic pathogen causing disease in immunocompromised individuals. The hallmark of P. aeruginosa virulence is its multi-factorial and combinatorial nature. It renders such bacteria infectious for many organisms and it is often resistant to antibiotics. To gain insights into the physiology of P. aeruginosa during infection, we assessed the transcriptional programs of three different P. aeruginosa strains directly after isolation from burn wounds of humans. We compared the programs to those of the same strains using two infection models: a plant model, which consisted of the infection of the midrib of lettuce leaves, and a murine tumor model, which was obtained by infection of mice with an induced tumor in the abdomen. All control conditions of P. aeruginosa cells growing in suspension and as a biofilm were added to the analysis. We found that these different P. aeruginosa strains express a pool of distinct genetic traits that are activated under particular infection conditions regardless of their genetic variability. The knowledge herein generated will advance our understanding of P. aeruginosa virulence and provide valuable cues for the definition of prospective targets to develop novel intervention strategies.

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

PubMed

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

2009-01-01

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

Learning genetic inquiry through the use, revision, and justification of explanatory models

NASA Astrophysics Data System (ADS)

Cartier, Jennifer Lorraine

Central to the process of inquiry in science is the construction and assessment of models that can be used to explain (and in some cases, predict) natural phenomena. This dissertation is a qualitative study of student learning in a high school biology course that was designed to give students opportunities to learn about genetic inquiry in part by providing them with authentic experiences doing inquiry in the discipline. With the aid of a computer program that generates populations of "fruit flies", the students in this class worked in groups structured like scientific communities to build, revise, and defend explanatory models for various inheritance phenomena. Analysis of the ways in which the first cohort of students assessed their inheritance models revealed that all students assessed models based upon empirical fit (data/model match). However, in contrast to the practice of scientists and despite explicit instruction, students did not consistently apply conceptual assessment criteria to their models. That is, they didn't seek consistency between underlying concepts or processes in their models and those of other important genetic models, such as meiosis. This is perhaps in part because they lacked an understanding of models as conceptual rather than physical entities. Subsequently, the genetics curriculum was altered in order to create more opportunities for students to address epistemological issues associated with model assessment throughout the course. The second cohort of students' understanding of models changed over the nine-week period: initially the majority of students equated scientific models with "proof" (generally physical) of "theories"; at the end of the course, most students demonstrated understanding of the conceptual nature of scientific models and the need to justify such knowledge according to both its empirical utility and conceptual consistency. Through model construction and assessment (i.e. scientific inquiry), students were able to come to a rich understanding of both the central concepts of transmission genetics and important epistemological aspects of genetic practice.

Hunter disease eClinic: interactive, computer-assisted, problem-based approach to independent learning about a rare genetic disease.

PubMed

Al-Jasmi, Fatma; Moldovan, Laura; Clarke, Joe T R

2010-10-25

Computer-based teaching (CBT) is a well-known educational device, but it has never been applied systematically to the teaching of a complex, rare, genetic disease, such as Hunter disease (MPS II). To develop interactive teaching software functioning as a virtual clinic for the management of MPS II. The Hunter disease eClinic, a self-training, user-friendly educational software program, available at the Lysosomal Storage Research Group (http://www.lysosomalstorageresearch.ca), was developed using the Adobe Flash multimedia platform. It was designed to function both to provide a realistic, interactive virtual clinic and instantaneous access to supporting literature on Hunter disease. The Hunter disease eClinic consists of an eBook and an eClinic. The eClinic is the interactive virtual clinic component of the software. Within an environment resembling a real clinic, the trainee is instructed to perform a medical history, to examine the patient, and to order appropriate investigation. The program provides clinical data derived from the management of actual patients with Hunter disease. The eBook provides instantaneous, electronic access to a vast collection of reference information to provide detailed background clinical and basic science, including relevant biochemistry, physiology, and genetics. In the eClinic, the trainee is presented with quizzes designed to provide immediate feedback on both trainee effectiveness and efficiency. User feedback on the merits of the program was collected at several seminars and formal clinical rounds at several medical centres, primarily in Canada. In addition, online usage statistics were documented for a 2-year period. Feedback was consistently positive and confirmed the practical benefit of the program. The online English-language version is accessed daily by users from all over the world; a Japanese translation of the program is also available. The Hunter disease eClinic employs a CBT model providing the trainee with realistic clinical problems, coupled with comprehensive basic and clinical reference information by instantaneous access to an electronic textbook, the eBook. The program was rated highly by attendees at national and international presentations. It provides a potential model for use as an educational approach to other rare genetic diseases.

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

PubMed

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

2016-01-01

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

Discovering Knowledge from Noisy Databases Using Genetic Programming.

ERIC Educational Resources Information Center

Wong, Man Leung; Leung, Kwong Sak; Cheng, Jack C. Y.

2000-01-01

Presents a framework that combines Genetic Programming and Inductive Logic Programming, two approaches in data mining, to induce knowledge from noisy databases. The framework is based on a formalism of logic grammars and is implemented as a data mining system called LOGENPRO (Logic Grammar-based Genetic Programming System). (Contains 34…

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Neurogenetics in Child Neurology: Redefining a Discipline in the Twenty-first Century.

PubMed

Kaufmann, Walter E

2016-12-01

Increasing knowledge on genetic etiology of pediatric neurologic disorders is affecting the practice of the specialty. I reviewed here the history of pediatric neurologic disorder classification and the role of genetics in the process. I also discussed the concept of clinical neurogenetics, with its role in clinical practice, education, and research. Finally, I propose a flexible model for clinical neurogenetics in child neurology in the twenty-first century. In combination with disorder-specific clinical programs, clinical neurogenetics can become a home for complex clinical issues, repository of genetic diagnostic advances, educational resource, and research engine in child neurology.

Computational challenges in modeling gene regulatory events.

PubMed

Pataskar, Abhijeet; Tiwari, Vijay K

2016-10-19

Cellular transcriptional programs driven by genetic and epigenetic mechanisms could be better understood by integrating "omics" data and subsequently modeling the gene-regulatory events. Toward this end, computational biology should keep pace with evolving experimental procedures and data availability. This article gives an exemplified account of the current computational challenges in molecular biology.

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

Szymanski, J. J.; Brumby, Steven P.; Pope, P. A.

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

The Relationship Between the Genetic and Environmental Influences on Common Externalizing Psychopathology and Mental Wellbeing

PubMed Central

Kendler, Kenneth S.; Myers, John M.; Keyes, Corey L. M.

2012-01-01

To determine the relationship between the genetic and environmental risk factors for externalizing psychopathology and mental wellbeing, we examined detailed measures of emotional, social and psychological wellbeing, and a history of alcohol-related problems and smoking behavior in the last year in 1,386 individual twins from same-sex pairs from the MIDUS national US sample assessed in 1995. Cholesky decomposition analyses were performed with the Mx program. The best fit model contained one highly heritable common externalizing psychopathology factor for both substance use/abuse measures, and one strongly heritable common factor for the three wellbeing measures. Genetic and environmental risk factors for externalizing psychopathology were both negatively associated with levels of mental wellbeing and accounted for, respectively, 7% and 21% of its genetic and environmental influences. Adding internalizing psychopathology assessed in the last year to the model, genetic risk factors unique for externalizing psychopathology were now positively related to levels of mental wellbeing, although accounting for only 5% of the genetic variance. Environmental risk factors unique to externalizing psychopathology continued to be negatively associated with mental wellbeing, accounting for 26% of the environmental variance. When both internalizing psychopathology and externalizing psychopathology are associated with mental wellbeing, the strongest risk factors for low mental wellbeing are genetic factors that impact on both internalizing psychopathology and externalizing psychopathology, and environmental factors unique to externalizing psychopathology. In this model, genetic risk factors for externalizing psychopathology predict, albeit weakly, higher levels of mental wellbeing. PMID:22506307

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

PubMed Central

Mendyk, Aleksander; Güres, Sinan; Szlęk, Jakub; Wiśniowska, Barbara; Kleinebudde, Peter

2015-01-01

The purpose of this work was to develop a mathematical model of the drug dissolution (Q) from the solid lipid extrudates based on the empirical approach. Artificial neural networks (ANNs) and genetic programming (GP) tools were used. Sensitivity analysis of ANNs provided reduction of the original input vector. GP allowed creation of the mathematical equation in two major approaches: (1) direct modeling of Q versus extrudate diameter (d) and the time variable (t) and (2) indirect modeling through Weibull equation. ANNs provided also information about minimum achievable generalization error and the way to enhance the original dataset used for adjustment of the equations' parameters. Two inputs were found important for the drug dissolution: d and t. The extrudates length (L) was found not important. Both GP modeling approaches allowed creation of relatively simple equations with their predictive performance comparable to the ANNs (root mean squared error (RMSE) from 2.19 to 2.33). The direct mode of GP modeling of Q versus d and t resulted in the most robust model. The idea of how to combine ANNs and GP in order to escape ANNs' black-box drawback without losing their superior predictive performance was demonstrated. Open Source software was used to deliver the state-of-the-art models and modeling strategies. PMID:26101544

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

PubMed

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

2015-01-01

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

Stock enhancement or sea ranching? Insights from monitoring the genetic diversity, relatedness and effective population size in a seeded great scallop population (Pecten maximus).

PubMed

Morvezen, R; Boudry, P; Laroche, J; Charrier, G

2016-09-01

The mass release of hatchery-propagated stocks raises numerous questions concerning its efficiency in terms of local recruitment and effect on the genetic diversity of wild populations. A seeding program, consisting of mass release of hatchery-produced juveniles in the local naturally occurring population of great scallops (Pecten maximus L.), was initiated in the early 1980s in the Bay of Brest (France). The present study aims at evaluating whether this seeding program leads to actual population enhancement, with detectable effects on genetic diversity and effective population size, or consists of sea ranching with limited genetic consequences on the wild stock. To address this question, microsatellite-based genetic monitoring of three hatchery-born and naturally recruited populations was conducted over a 5-year period. Results showed a limited reduction in allelic richness but a strong alteration of allelic frequencies in hatchery populations, while genetic diversity appeared very stable over time in the wild populations. A temporal increase in relatedness was observed in both cultured stock and wild populations. Effective population size (Ne) estimates were low and variable in the wild population. Moreover, the application of the Ryman-Laikre model suggested a high contribution of hatchery-born scallops to the reproductive output of the wild population. Overall, the data suggest that the main objective of the seeding program, which is stock enhancement, is fulfilled. Moreover, gene flow from surrounding populations and/or the reproductive input of undetected sub-populations within the bay may buffer the Ryman-Laikre effect and ensure the retention of the local genetic variability.

Modeling of biological intelligence for SCM system optimization.

PubMed

Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

2012-01-01

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

Modeling of Biological Intelligence for SCM System Optimization

PubMed Central

Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

2012-01-01

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms. PMID:22162724

Genetic and environmental bases of the interplay between magical ideation and personality.

PubMed

Brambilla, Paolo; Fagnani, Corrado; Cecchetto, Filippo; Medda, Emanuela; Bellani, Marcella; Salemi, Miriam; Picardi, Angelo; Stazi, Maria Antonietta

2014-02-28

Sub-threshold psychotic symptoms are quite commonly present in general population. Among these, Magical Ideation (MI) has been proved to be a valid predictor of psychosis. However, the genetic and environmental influences on the interplay between MI and personality have not fully been explored. A total of 534 adult twins from the population-based Italian Twin Register were assessed for MI using the MI Scale (MIS) and for personality with the temperament and character inventory (TCI). A Multivariate Cholesky model was applied with Mx statistical program. The best-fitting model showed that additive genetic and unshared environmental factors explain approximately the same proportion of variance in MI, whereas a less strong genetic influence on personality traits emerged. Relevant correlations between MI and specific personality traits (novelty seeking, cooperativeness, self-directedness, self-transcendence) were found, suggesting shared influences for MI and these traits. Both genetic and environmental factors explained these correlations, with genetic factors playing a predominant role. Moderate-to-substantial genetic effects on MI and personality were found. Shared genetic and environmental effects underlie the phenotypic correlation between MI (psychosis-proneness) and personality traits, i.e. self-directedness (negative association) and self-transcendence (positive association), potentially representing predictive markers of psychosis liability related to schizotypy and personality. © 2013 Published by Elsevier Ireland Ltd.

Genetic Counseling as an Educational Process.

ERIC Educational Resources Information Center

Eddy, James M.; St. Pierre, Richard

Historically genetic counseling programs have not included strong educational components or sound educational foundations. This paper deals with some of the drawbacks of current genetic counseling programs and the implications for education in the genetic counseling process. The author adopts a broad definition of genetic counseling which…

Ortho Image and DTM Generation with Intelligent Methods

NASA Astrophysics Data System (ADS)

Bagheri, H.; Sadeghian, S.

2013-10-01

Nowadays the artificial intelligent algorithms has considered in GIS and remote sensing. Genetic algorithm and artificial neural network are two intelligent methods that are used for optimizing of image processing programs such as edge extraction and etc. these algorithms are very useful for solving of complex program. In this paper, the ability and application of genetic algorithm and artificial neural network in geospatial production process like geometric modelling of satellite images for ortho photo generation and height interpolation in raster Digital Terrain Model production process is discussed. In first, the geometric potential of Ikonos-2 and Worldview-2 with rational functions, 2D & 3D polynomials were tested. Also comprehensive experiments have been carried out to evaluate the viability of the genetic algorithm for optimization of rational function, 2D & 3D polynomials. Considering the quality of Ground Control Points, the accuracy (RMSE) with genetic algorithm and 3D polynomials method for Ikonos-2 Geo image was 0.508 pixel sizes and the accuracy (RMSE) with GA algorithm and rational function method for Worldview-2 image was 0.930 pixel sizes. For more another optimization artificial intelligent methods, neural networks were used. With the use of perceptron network in Worldview-2 image, a result of 0.84 pixel sizes with 4 neurons in middle layer was gained. The final conclusion was that with artificial intelligent algorithms it is possible to optimize the existing models and have better results than usual ones. Finally the artificial intelligence methods, like genetic algorithms as well as neural networks, were examined on sample data for optimizing interpolation and for generating Digital Terrain Models. The results then were compared with existing conventional methods and it appeared that these methods have a high capacity in heights interpolation and that using these networks for interpolating and optimizing the weighting methods based on inverse distance leads to a high accurate estimation of heights.

Education and certification of genetic counselors.

PubMed

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

1999-01-01

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

Genetic structure and diversity of the selfing model grass Brachypodium stacei (Poaceae) in Western Mediterranean: out of the Iberian Peninsula and into the islands.

PubMed

Shiposha, Valeriia; Catalán, Pilar; Olonova, Marina; Marques, Isabel

2016-01-01

Annual Mediterranean species of the genus Brachypodium are promising model plants for energy crops since their selfing nature and short-life cycles are an advantage in breeding programs. The false brome, B. distachyon, has already been sequenced and new genomic initiatives have triggered the de-novo genome sequencing of its close relatives such as B. stacei, a species that was until recently mistaken for B. distachyon. However, the success of these initiatives hinges on detailed knowledge about the distribution of genetic variation within and among populations for the effective use of germplasm in a breeding program. Understanding population genetic diversity and genetic structure is also an important prerequisite for designing effective experimental populations for genomic wide studies. However, population genetic data are still limited in B. stacei. We therefore selected and amplified 10 nuclear microsatellite markers to depict patterns of population structure and genetic variation among 181 individuals from 19 populations of B. stacei occurring in its predominant range, the western Mediterranean area: mainland Iberian Peninsula, continental Balearic Islands and oceanic Canary Islands. Our genetic results support the occurrence of a predominant selfing system with extremely high levels of homozygosity across the analyzed populations. Despite the low level of genetic variation found, two different genetic clusters were retrieved, one clustering all SE Iberian mainland populations and the island of Minorca and another one grouping all S Iberian mainland populations, the Canary Islands and all Majorcan populations except one that clustered with the former group. These results, together with a high sharing of alleles (89%) suggest different colonization routes from the mainland Iberian Peninsula into the islands. A recent colonization scenario could explain the relatively low levels of genetic diversity and low number of alleles found in the Canary Islands populations while older colonization events are hypothesized to explain the high genetic diversity values found in the Majorcan populations. Our study provides widely applicable information about geographical patterns of genetic variation in B. stacei. Among others, the genetic pattern and the existence of local alleles will need to be adequately reflected in the germplasm collection of B. stacei for efficient genome wide association studies.

Genetic structure and diversity of the selfing model grass Brachypodium stacei (Poaceae) in Western Mediterranean: out of the Iberian Peninsula and into the islands

PubMed Central

Shiposha, Valeriia; Catalán, Pilar; Olonova, Marina

2016-01-01

Annual Mediterranean species of the genus Brachypodium are promising model plants for energy crops since their selfing nature and short-life cycles are an advantage in breeding programs. The false brome, B. distachyon, has already been sequenced and new genomic initiatives have triggered the de-novo genome sequencing of its close relatives such as B. stacei, a species that was until recently mistaken for B. distachyon. However, the success of these initiatives hinges on detailed knowledge about the distribution of genetic variation within and among populations for the effective use of germplasm in a breeding program. Understanding population genetic diversity and genetic structure is also an important prerequisite for designing effective experimental populations for genomic wide studies. However, population genetic data are still limited in B. stacei. We therefore selected and amplified 10 nuclear microsatellite markers to depict patterns of population structure and genetic variation among 181 individuals from 19 populations of B. stacei occurring in its predominant range, the western Mediterranean area: mainland Iberian Peninsula, continental Balearic Islands and oceanic Canary Islands. Our genetic results support the occurrence of a predominant selfing system with extremely high levels of homozygosity across the analyzed populations. Despite the low level of genetic variation found, two different genetic clusters were retrieved, one clustering all SE Iberian mainland populations and the island of Minorca and another one grouping all S Iberian mainland populations, the Canary Islands and all Majorcan populations except one that clustered with the former group. These results, together with a high sharing of alleles (89%) suggest different colonization routes from the mainland Iberian Peninsula into the islands. A recent colonization scenario could explain the relatively low levels of genetic diversity and low number of alleles found in the Canary Islands populations while older colonization events are hypothesized to explain the high genetic diversity values found in the Majorcan populations. Our study provides widely applicable information about geographical patterns of genetic variation in B. stacei. Among others, the genetic pattern and the existence of local alleles will need to be adequately reflected in the germplasm collection of B. stacei for efficient genome wide association studies. PMID:27651993

Applications of Population Genetics to Animal Breeding, from Wright, Fisher and Lush to Genomic Prediction

PubMed Central

Hill, William G.

2014-01-01

Although animal breeding was practiced long before the science of genetics and the relevant disciplines of population and quantitative genetics were known, breeding programs have mainly relied on simply selecting and mating the best individuals on their own or relatives’ performance. This is based on sound quantitative genetic principles, developed and expounded by Lush, who attributed much of his understanding to Wright, and formalized in Fisher’s infinitesimal model. Analysis at the level of individual loci and gene frequency distributions has had relatively little impact. Now with access to genomic data, a revolution in which molecular information is being used to enhance response with “genomic selection” is occurring. The predictions of breeding value still utilize multiple loci throughout the genome and, indeed, are largely compatible with additive and specifically infinitesimal model assumptions. I discuss some of the history and genetic issues as applied to the science of livestock improvement, which has had and continues to have major spin-offs into ideas and applications in other areas. PMID:24395822

Computational challenges in modeling gene regulatory events

PubMed Central

Pataskar, Abhijeet; Tiwari, Vijay K.

2016-01-01

ABSTRACT Cellular transcriptional programs driven by genetic and epigenetic mechanisms could be better understood by integrating “omics” data and subsequently modeling the gene-regulatory events. Toward this end, computational biology should keep pace with evolving experimental procedures and data availability. This article gives an exemplified account of the current computational challenges in molecular biology. PMID:27390891

From Theory to Air Force Practice: Applications and Non-Binary Extensions of Probabilistic Model-Building Genetic Algorithms

DTIC Science & Technology

2006-05-31

dynamics (MD) and kinetic Monte Carlo ( KMC ) procedures. In 2D surface modeling our calculations project speedups of 9 orders of magnitude at 300 degrees...programming is used to perform customized statistical mechanics by bridging the different time scales of MD and KMC quickly and well. Speedups in

Review: Optimization methods for groundwater modeling and management

NASA Astrophysics Data System (ADS)

Yeh, William W.-G.

2015-09-01

Optimization methods have been used in groundwater modeling as well as for the planning and management of groundwater systems. This paper reviews and evaluates the various optimization methods that have been used for solving the inverse problem of parameter identification (estimation), experimental design, and groundwater planning and management. Various model selection criteria are discussed, as well as criteria used for model discrimination. The inverse problem of parameter identification concerns the optimal determination of model parameters using water-level observations. In general, the optimal experimental design seeks to find sampling strategies for the purpose of estimating the unknown model parameters. A typical objective of optimal conjunctive-use planning of surface water and groundwater is to minimize the operational costs of meeting water demand. The optimization methods include mathematical programming techniques such as linear programming, quadratic programming, dynamic programming, stochastic programming, nonlinear programming, and the global search algorithms such as genetic algorithms, simulated annealing, and tabu search. Emphasis is placed on groundwater flow problems as opposed to contaminant transport problems. A typical two-dimensional groundwater flow problem is used to explain the basic formulations and algorithms that have been used to solve the formulated optimization problems.

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

PubMed Central

Kenen, R H; Schmidt, R M

1978-01-01

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

Genetic algorithms using SISAL parallel programming language

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

Tejada, S.

1994-05-06

Genetic algorithms are a mathematical optimization technique developed by John Holland at the University of Michigan [1]. The SISAL programming language possesses many of the characteristics desired to implement genetic algorithms. SISAL is a deterministic, functional programming language which is inherently parallel. Because SISAL is functional and based on mathematical concepts, genetic algorithms can be efficiently translated into the language. Several of the steps involved in genetic algorithms, such as mutation, crossover, and fitness evaluation, can be parallelized using SISAL. In this paper I will l discuss the implementation and performance of parallel genetic algorithms in SISAL.

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

PubMed

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

2017-01-01

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

Human Inspired Self-developmental Model of Neural Network (HIM): Introducing Content/Form Computing

NASA Astrophysics Data System (ADS)

Krajíček, Jiří

This paper presents cross-disciplinary research between medical/psychological evidence on human abilities and informatics needs to update current models in computer science to support alternative methods for computation and communication. In [10] we have already proposed hypothesis introducing concept of human information model (HIM) as cooperative system. Here we continue on HIM design in detail. In our design, first we introduce Content/Form computing system which is new principle of present methods in evolutionary computing (genetic algorithms, genetic programming). Then we apply this system on HIM (type of artificial neural network) model as basic network self-developmental paradigm. Main inspiration of our natural/human design comes from well known concept of artificial neural networks, medical/psychological evidence and Sheldrake theory of "Nature as Alive" [22].

Artificial Intelligence-Based Models for the Optimal and Sustainable Use of Groundwater in Coastal Aquifers

NASA Astrophysics Data System (ADS)

Sreekanth, J.; Datta, Bithin

2011-07-01

Overexploitation of the coastal aquifers results in saltwater intrusion. Once saltwater intrusion occurs, it involves huge cost and long-term remediation measures to remediate these contaminated aquifers. Hence, it is important to have strategies for the sustainable use of coastal aquifers. This study develops a methodology for the optimal management of saltwater intrusion prone aquifers. A linked simulation-optimization-based management strategy is developed. The methodology uses genetic-programming-based models for simulating the aquifer processes, which is then linked to a multi-objective genetic algorithm to obtain optimal management strategies in terms of groundwater extraction from potential well locations in the aquifer.

Software For Genetic Algorithms

NASA Technical Reports Server (NTRS)

Wang, Lui; Bayer, Steve E.

1992-01-01

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

Genetics Education in Nurse Residency Programs: A Natural Fit.

PubMed

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

2017-08-01

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

Stochastic dynamics of genetic broadcasting networks

NASA Astrophysics Data System (ADS)

Potoyan, Davit A.; Wolynes, Peter G.

2017-11-01

The complex genetic programs of eukaryotic cells are often regulated by key transcription factors occupying or clearing out of a large number of genomic locations. Orchestrating the residence times of these factors is therefore important for the well organized functioning of a large network. The classic models of genetic switches sidestep this timing issue by assuming the binding of transcription factors to be governed entirely by thermodynamic protein-DNA affinities. Here we show that relying on passive thermodynamics and random release times can lead to a "time-scale crisis" for master genes that broadcast their signals to a large number of binding sites. We demonstrate that this time-scale crisis for clearance in a large broadcasting network can be resolved by actively regulating residence times through molecular stripping. We illustrate these ideas by studying a model of the stochastic dynamics of the genetic network of the central eukaryotic master regulator NFκ B which broadcasts its signals to many downstream genes that regulate immune response, apoptosis, etc.

SDMtoolbox 2.0: the next generation Python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses

PubMed Central

Bennett, Joseph R.; French, Connor M.

2017-01-01

SDMtoolbox 2.0 is a software package for spatial studies of ecology, evolution, and genetics. The release of SDMtoolbox 2.0 allows researchers to use the most current ArcGIS software and MaxEnt software, and reduces the amount of time that would be spent developing common solutions. The central aim of this software is to automate complicated and repetitive spatial analyses in an intuitive graphical user interface. One core tenant facilitates careful parameterization of species distribution models (SDMs) to maximize each model’s discriminatory ability and minimize overfitting. This includes carefully processing of occurrence data, environmental data, and model parameterization. This program directly interfaces with MaxEnt, one of the most powerful and widely used species distribution modeling software programs, although SDMtoolbox 2.0 is not limited to species distribution modeling or restricted to modeling in MaxEnt. Many of the SDM pre- and post-processing tools have ‘universal’ analogs for use with any modeling software. The current version contains a total of 79 scripts that harness the power of ArcGIS for macroecology, landscape genetics, and evolutionary studies. For example, these tools allow for biodiversity quantification (such as species richness or corrected weighted endemism), generation of least-cost paths and corridors among shared haplotypes, assessment of the significance of spatial randomizations, and enforcement of dispersal limitations of SDMs projected into future climates—to only name a few functions contained in SDMtoolbox 2.0. Lastly, dozens of generalized tools exists for batch processing and conversion of GIS data types or formats, which are broadly useful to any ArcMap user. PMID:29230356

Multi-objective optimal design of sandwich panels using a genetic algorithm

NASA Astrophysics Data System (ADS)

Xu, Xiaomei; Jiang, Yiping; Pueh Lee, Heow

2017-10-01

In this study, an optimization problem concerning sandwich panels is investigated by simultaneously considering the two objectives of minimizing the panel mass and maximizing the sound insulation performance. First of all, the acoustic model of sandwich panels is discussed, which provides a foundation to model the acoustic objective function. Then the optimization problem is formulated as a bi-objective programming model, and a solution algorithm based on the non-dominated sorting genetic algorithm II (NSGA-II) is provided to solve the proposed model. Finally, taking an example of a sandwich panel that is expected to be used as an automotive roof panel, numerical experiments are carried out to verify the effectiveness of the proposed model and solution algorithm. Numerical results demonstrate in detail how the core material, geometric constraints and mechanical constraints impact the optimal designs of sandwich panels.

Pricing and location decisions in multi-objective facility location problem with M/M/m/k queuing systems

NASA Astrophysics Data System (ADS)

Tavakkoli-Moghaddam, Reza; Vazifeh-Noshafagh, Samira; Taleizadeh, Ata Allah; Hajipour, Vahid; Mahmoudi, Amin

2017-01-01

This article presents a new multi-objective model for a facility location problem with congestion and pricing policies. This model considers situations in which immobile service facilities are congested by a stochastic demand following M/M/m/k queues. The presented model belongs to the class of mixed-integer nonlinear programming models and NP-hard problems. To solve such a hard model, a new multi-objective optimization algorithm based on a vibration theory, namely multi-objective vibration damping optimization (MOVDO), is developed. In order to tune the algorithms parameters, the Taguchi approach using a response metric is implemented. The computational results are compared with those of the non-dominated ranking genetic algorithm and non-dominated sorting genetic algorithm. The outputs demonstrate the robustness of the proposed MOVDO in large-sized problems.

Atmospheric Downscaling using Genetic Programming

NASA Astrophysics Data System (ADS)

Zerenner, Tanja; Venema, Victor; Simmer, Clemens

2013-04-01

Coupling models for the different components of the Soil-Vegetation-Atmosphere-System requires up-and downscaling procedures. Subject of our work is the downscaling scheme used to derive high resolution forcing data for land-surface and subsurface models from coarser atmospheric model output. The current downscaling scheme [Schomburg et. al. 2010, 2012] combines a bi-quadratic spline interpolation, deterministic rules and autoregressive noise. For the development of the scheme, training and validation data sets have been created by carrying out high-resolution runs of the atmospheric model. The deterministic rules in this scheme are partly based on known physical relations and partly determined by an automated search for linear relationships between the high resolution fields of the atmospheric model output and high resolution data on surface characteristics. Up to now deterministic rules are available for downscaling surface pressure and partially, depending on the prevailing weather conditions, for near surface temperature and radiation. Aim of our work is to improve those rules and to find deterministic rules for the remaining variables, which require downscaling, e.g. precipitation or near surface specifc humidity. To accomplish that, we broaden the search by allowing for interdependencies between different atmospheric parameters, non-linear relations, non-local and time-lagged relations. To cope with the vast number of possible solutions, we use genetic programming, a method from machine learning, which is based on the principles of natural evolution. We are currently working with GPLAB, a Genetic Programming toolbox for Matlab. At first we have tested the GP system to retrieve the known physical rule for downscaling surface pressure, i.e. the hydrostatic equation, from our training data. We have found this to be a simple task to the GP system. Furthermore we have improved accuracy and efficiency of the GP solution by implementing constant variation and optimization as genetic operators. Next we have worked on an improvement of the downscaling rule for the two-meter-temperature. We have added an if-function with four input arguments to the function set. Since this has shown to increase bloat we have additionally modified our fitness function by including penalty terms for both the size of the solutions and the number intron nodes, i.e program parts that are never evaluated. Starting from the known downscaling rule for the two-meter temperature, which linearly exploits the orography anomalies allowed or disallowed by a certain temperature gradient, our GP system has been able to find an improvement. The rule produced by the GP clearly shows a better performance concerning the reproduced small-scale variability.

Series Hybrid Electric Vehicle Power System Optimization Based on Genetic Algorithm

NASA Astrophysics Data System (ADS)

Zhu, Tianjun; Li, Bin; Zong, Changfu; Wu, Yang

2017-09-01

Hybrid electric vehicles (HEV), compared with conventional vehicles, have complex structures and more component parameters. If variables optimization designs are carried on all these parameters, it will increase the difficulty and the convergence of algorithm program, so this paper chooses the parameters which has a major influence on the vehicle fuel consumption to make it all work at maximum efficiency. First, HEV powertrain components modelling are built. Second, taking a tandem hybrid structure as an example, genetic algorithm is used in this paper to optimize fuel consumption and emissions. Simulation results in ADVISOR verify the feasibility of the proposed genetic optimization algorithm.

Data Sufficiency Assessment and Pumping Test Design for Groundwater Prediction Using Decision Theory and Genetic Algorithms

NASA Astrophysics Data System (ADS)

McPhee, J.; William, Y. W.

2005-12-01

This work presents a methodology for pumping test design based on the reliability requirements of a groundwater model. Reliability requirements take into consideration the application of the model results in groundwater management, expressed in this case as a multiobjective management model. The pumping test design is formulated as a mixed-integer nonlinear programming (MINLP) problem and solved using a combination of genetic algorithm (GA) and gradient-based optimization. Bayesian decision theory provides a formal framework for assessing the influence of parameter uncertainty over the reliability of the proposed pumping test. The proposed methodology is useful for selecting a robust design that will outperform all other candidate designs under most potential 'true' states of the system

Developmental programming of the metabolic syndrome - critical windows for intervention

PubMed Central

Vickers, Mark H

2011-01-01

Metabolic disease results from a complex interaction of many factors, including genetic, physiological, behavioral and environmental influences. The recent rate at which these diseases have increased suggests that environmental and behavioral influences, rather than genetic causes, are fuelling the present epidemic. In this context, the developmental origins of health and disease hypothesis has highlighted the link between the periconceptual, fetal and early infant phases of life and the subsequent development of adult obesity and the metabolic syndrome. Although the mechanisms are yet to be fully elucidated, this programming was generally considered an irreversible change in developmental trajectory. Recent work in animal models suggests that developmental programming of metabolic disorders is potentially reversible by nutritional or targeted therapeutic interventions during the period of developmental plasticity. This review will discuss critical windows of developmental plasticity and possible avenues to ameliorate the development of postnatal metabolic disorders following an adverse early life environment. PMID:21954418

Genetic parameters for different growth scales in GIFT strain of Nile tilapia (Oreochromis niloticus).

PubMed

He, J; Gao, H; Xu, P; Yang, R

2015-12-01

Body weight, length, width and depth at two growth stages were observed for a total of 5015 individuals of GIFT strain, along with a pedigree including 5588 individuals from 104 sires and 162 dams was collected. Multivariate animal models and a random regression model were used to genetically analyse absolute and relative growth scales of these growth traits. In absolute growth scale, the observed growth traits had moderate heritabilities ranging from 0.321 to 0.576, while pairwise ratios between body length, width and depth were lowly inherited and maximum heritability was only 0.146 for length/depth. All genetic correlations were above 0.5 between pairwise growth traits and genetic correlation between length/width and length/depth varied between both growth stages. Based on those estimates, selection index of multiple traits of interest can be formulated in future breeding program to improve genetically body weight and morphology of the GIFT strain. In relative growth scale, heritabilities in relative growths of body length, width and depth to body weight were 0.257, 0.412 and 0.066, respectively, while genetic correlations among these allometry scalings were above 0.8. Genetic analysis for joint allometries of body weight to body length, width and depth will contribute to genetically regulate the growth rate between body shape and body weight. © 2015 Blackwell Verlag GmbH.

Correlated changes in body shape after five generations of selection to improve growth rate in a breeding program for Nile tilapia Oreochromis niloticus in Brazil.

PubMed

de Oliveira, Carlos Antonio Lopes; Ribeiro, Ricardo Pereira; Yoshida, Grazyella Massako; Kunita, Natali Miwa; Rizzato, Gabriel Soriani; de Oliveira, Sheila Nogueira; Dos Santos, Alexandra Inês; Nguyen, Nguyen Hong

2016-11-01

Body shape is a commercial trait of great interest as it impacts profit and productivity of aquaculture enterprises. In the present study, we examined correlated changes in two measures of body shape (depth to length ratio, DL-R and ellipticity of mid sagittal plane, EL-H) from a selection program for high daily weight gain in a Nile tilapia population reared in freshwater cages in Brazil. Genetic parameters for body shape and its genetic association with growth traits (body weight and daily gain) were also estimated from 8,725 individuals with growth performance recorded over five generations from 2008 to 2013. Mixed model analysis showed that the selection program resulted in substantial improvement in growth performance (about 4 % genetic gain per generation or per year) and also brought about trivial changes in body shape. The heritabilities ranged from 0.470 to 0.564 for growth traits and 0.180 to 0.289 for body shape. The common family effects were low for all traits studied, accounting for only 3-11 % of total phenotypic variance. The genetic correlations between body shape and growth traits were weak, i.e., -0.385 between EL-H and growth traits and 0.28 between DL-R and body weight or daily gain. Strong and negative genetic association was found between the two body shape traits (rg = --0.955). Harvest body weight and daily gain are essentially the same traits, as indicated by the close to one genetic correlations between the two characters. Our results demonstrated that the selection process to increase growth rate had small, but slowly constant effect in body shape traits; and in the long term, the fish would have become rotund.

A hybrid intelligent algorithm for portfolio selection problem with fuzzy returns

NASA Astrophysics Data System (ADS)

Li, Xiang; Zhang, Yang; Wong, Hau-San; Qin, Zhongfeng

2009-11-01

Portfolio selection theory with fuzzy returns has been well developed and widely applied. Within the framework of credibility theory, several fuzzy portfolio selection models have been proposed such as mean-variance model, entropy optimization model, chance constrained programming model and so on. In order to solve these nonlinear optimization models, a hybrid intelligent algorithm is designed by integrating simulated annealing algorithm, neural network and fuzzy simulation techniques, where the neural network is used to approximate the expected value and variance for fuzzy returns and the fuzzy simulation is used to generate the training data for neural network. Since these models are used to be solved by genetic algorithm, some comparisons between the hybrid intelligent algorithm and genetic algorithm are given in terms of numerical examples, which imply that the hybrid intelligent algorithm is robust and more effective. In particular, it reduces the running time significantly for large size problems.

Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models

PubMed Central

Cuevas, Jaime; Crossa, José; Montesinos-López, Osval A.; Burgueño, Juan; Pérez-Rodríguez, Paulino; de los Campos, Gustavo

2016-01-01

The phenomenon of genotype × environment (G × E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects (u) that can be assessed by the Kronecker product of variance–covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP) and Gaussian (Gaussian kernel, GK). The other model has the same genetic component as the first model (u) plus an extra component, f, that captures random effects between environments that were not captured by the random effects u. We used five CIMMYT data sets (one maize and four wheat) that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with u and f over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect u. PMID:27793970

Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models.

PubMed

Cuevas, Jaime; Crossa, José; Montesinos-López, Osval A; Burgueño, Juan; Pérez-Rodríguez, Paulino; de Los Campos, Gustavo

2017-01-05

The phenomenon of genotype × environment (G × E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects [Formula: see text] that can be assessed by the Kronecker product of variance-covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP) and Gaussian (Gaussian kernel, GK). The other model has the same genetic component as the first model [Formula: see text] plus an extra component, F: , that captures random effects between environments that were not captured by the random effects [Formula: see text] We used five CIMMYT data sets (one maize and four wheat) that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with [Formula: see text] over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect [Formula: see text]. Copyright © 2017 Cuevas et al.

Navigation Constellation Design Using a Multi-Objective Genetic Algorithm

DTIC Science & Technology

2015-03-26

programs. This specific tool not only offers high fidelity simulations, but it also offers the visual aid provided by STK . The ability to...MATLAB and STK . STK is a program that allows users to model, analyze, and visualize space systems. Users can create objects such as satellites and...position dilution of precision (PDOP) and system cost. This thesis utilized Satellite Tool Kit ( STK ) to calculate PDOP values of navigation

Using genetic algorithm to solve a new multi-period stochastic optimization model

NASA Astrophysics Data System (ADS)

Zhang, Xin-Li; Zhang, Ke-Cun

2009-09-01

This paper presents a new asset allocation model based on the CVaR risk measure and transaction costs. Institutional investors manage their strategic asset mix over time to achieve favorable returns subject to various uncertainties, policy and legal constraints, and other requirements. One may use a multi-period portfolio optimization model in order to determine an optimal asset mix. Recently, an alternative stochastic programming model with simulated paths was proposed by Hibiki [N. Hibiki, A hybrid simulation/tree multi-period stochastic programming model for optimal asset allocation, in: H. Takahashi, (Ed.) The Japanese Association of Financial Econometrics and Engineering, JAFFE Journal (2001) 89-119 (in Japanese); N. Hibiki A hybrid simulation/tree stochastic optimization model for dynamic asset allocation, in: B. Scherer (Ed.), Asset and Liability Management Tools: A Handbook for Best Practice, Risk Books, 2003, pp. 269-294], which was called a hybrid model. However, the transaction costs weren't considered in that paper. In this paper, we improve Hibiki's model in the following aspects: (1) The risk measure CVaR is introduced to control the wealth loss risk while maximizing the expected utility; (2) Typical market imperfections such as short sale constraints, proportional transaction costs are considered simultaneously. (3) Applying a genetic algorithm to solve the resulting model is discussed in detail. Numerical results show the suitability and feasibility of our methodology.

Constraints in Genetic Programming

NASA Technical Reports Server (NTRS)

Janikow, Cezary Z.

1996-01-01

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

MetaGenyo: a web tool for meta-analysis of genetic association studies.

PubMed

Martorell-Marugan, Jordi; Toro-Dominguez, Daniel; Alarcon-Riquelme, Marta E; Carmona-Saez, Pedro

2017-12-16

Genetic association studies (GAS) aims to evaluate the association between genetic variants and phenotypes. In the last few years, the number of this type of study has increased exponentially, but the results are not always reproducible due to experimental designs, low sample sizes and other methodological errors. In this field, meta-analysis techniques are becoming very popular tools to combine results across studies to increase statistical power and to resolve discrepancies in genetic association studies. A meta-analysis summarizes research findings, increases statistical power and enables the identification of genuine associations between genotypes and phenotypes. Meta-analysis techniques are increasingly used in GAS, but it is also increasing the amount of published meta-analysis containing different errors. Although there are several software packages that implement meta-analysis, none of them are specifically designed for genetic association studies and in most cases their use requires advanced programming or scripting expertise. We have developed MetaGenyo, a web tool for meta-analysis in GAS. MetaGenyo implements a complete and comprehensive workflow that can be executed in an easy-to-use environment without programming knowledge. MetaGenyo has been developed to guide users through the main steps of a GAS meta-analysis, covering Hardy-Weinberg test, statistical association for different genetic models, analysis of heterogeneity, testing for publication bias, subgroup analysis and robustness testing of the results. MetaGenyo is a useful tool to conduct comprehensive genetic association meta-analysis. The application is freely available at http://bioinfo.genyo.es/metagenyo/ .

The Genetic Programming of Industrial Microorganisms.

ERIC Educational Resources Information Center

Hopwood, David A.

1981-01-01

Traces the development of the field of industrial microbial genetics, describing a range of techniques for genetic programing. Includes a discussion of site-directed mutagenesis, protoplast fusion, and recombinant DNA manipulations. (CS)

An Optimization Model for the Selection of Bus-Only Lanes in a City.

PubMed

Chen, Qun

2015-01-01

The planning of urban bus-only lane networks is an important measure to improve bus service and bus priority. To determine the effective arrangement of bus-only lanes, a bi-level programming model for urban bus lane layout is developed in this study that considers accessibility and budget constraints. The goal of the upper-level model is to minimize the total travel time, and the lower-level model is a capacity-constrained traffic assignment model that describes the passenger flow assignment on bus lines, in which the priority sequence of the transfer times is reflected in the passengers' route-choice behaviors. Using the proposed bi-level programming model, optimal bus lines are selected from a set of candidate bus lines; thus, the corresponding bus lane network on which the selected bus lines run is determined. The solution method using a genetic algorithm in the bi-level programming model is developed, and two numerical examples are investigated to demonstrate the efficacy of the proposed model.

Health effects model for nuclear power plant accident consequence analysis. Part I. Introduction, integration, and summary. Part II. Scientific basis for health effects models

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

Evans, J.S.; Moeller, D.W.; Cooper, D.W.

1985-07-01

Analysis of the radiological health effects of nuclear power plant accidents requires models for predicting early health effects, cancers and benign thyroid nodules, and genetic effects. Since the publication of the Reactor Safety Study, additional information on radiological health effects has become available. This report summarizes the efforts of a program designed to provide revised health effects models for nuclear power plant accident consequence modeling. The new models for early effects address four causes of mortality and nine categories of morbidity. The models for early effects are based upon two parameter Weibull functions. They permit evaluation of the influence ofmore » dose protraction and address the issue of variation in radiosensitivity among the population. The piecewise-linear dose-response models used in the Reactor Safety Study to predict cancers and thyroid nodules have been replaced by linear and linear-quadratic models. The new models reflect the most recently reported results of the follow-up of the survivors of the bombings of Hiroshima and Nagasaki and permit analysis of both morbidity and mortality. The new models for genetic effects allow prediction of genetic risks in each of the first five generations after an accident and include information on the relative severity of various classes of genetic effects. The uncertainty in modeloling radiological health risks is addressed by providing central, upper, and lower estimates of risks. An approach is outlined for summarizing the health consequences of nuclear power plant accidents. 298 refs., 9 figs., 49 tabs.« less

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

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

Pryor, Richard J.; Schaller, Mark J.

2003-10-01

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

Hunter disease eClinic: interactive, computer-assisted, problem-based approach to independent learning about a rare genetic disease

PubMed Central

2010-01-01

Background Computer-based teaching (CBT) is a well-known educational device, but it has never been applied systematically to the teaching of a complex, rare, genetic disease, such as Hunter disease (MPS II). Aim To develop interactive teaching software functioning as a virtual clinic for the management of MPS II. Implementation and Results The Hunter disease eClinic, a self-training, user-friendly educational software program, available at the Lysosomal Storage Research Group (http://www.lysosomalstorageresearch.ca), was developed using the Adobe Flash multimedia platform. It was designed to function both to provide a realistic, interactive virtual clinic and instantaneous access to supporting literature on Hunter disease. The Hunter disease eClinic consists of an eBook and an eClinic. The eClinic is the interactive virtual clinic component of the software. Within an environment resembling a real clinic, the trainee is instructed to perform a medical history, to examine the patient, and to order appropriate investigation. The program provides clinical data derived from the management of actual patients with Hunter disease. The eBook provides instantaneous, electronic access to a vast collection of reference information to provide detailed background clinical and basic science, including relevant biochemistry, physiology, and genetics. In the eClinic, the trainee is presented with quizzes designed to provide immediate feedback on both trainee effectiveness and efficiency. User feedback on the merits of the program was collected at several seminars and formal clinical rounds at several medical centres, primarily in Canada. In addition, online usage statistics were documented for a 2-year period. Feedback was consistently positive and confirmed the practical benefit of the program. The online English-language version is accessed daily by users from all over the world; a Japanese translation of the program is also available. Conclusions The Hunter disease eClinic employs a CBT model providing the trainee with realistic clinical problems, coupled with comprehensive basic and clinical reference information by instantaneous access to an electronic textbook, the eBook. The program was rated highly by attendees at national and international presentations. It provides a potential model for use as an educational approach to other rare genetic diseases. PMID:20973983

Successful technical trading agents using genetic programming.

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

Othling, Andrew S.; Kelly, John A.; Pryor, Richard J.

2004-10-01

Genetic programming (GP) has proved to be a highly versatile and useful tool for identifying relationships in data for which a more precise theoretical construct is unavailable. In this project, we use a GP search to develop trading strategies for agent based economic models. These strategies use stock prices and technical indicators, such as the moving average convergence/divergence and various exponentially weighted moving averages, to generate buy and sell signals. We analyze the effect of complexity constraints on the strategies as well as the relative performance of various indicators. We also present innovations in the classical genetic programming algorithm thatmore » appear to improve convergence for this problem. Technical strategies developed by our GP algorithm can be used to control the behavior of agents in economic simulation packages, such as ASPEN-D, adding variety to the current market fundamentals approach. The exploitation of arbitrage opportunities by technical analysts may help increase the efficiency of the simulated stock market, as it does in the real world. By improving the behavior of simulated stock markets, we can better estimate the effects of shocks to the economy due to terrorism or natural disasters.« less

Mouse Models for Investigating the Developmental Bases of Human Birth Defects

PubMed Central

MOON, ANNE M.

2006-01-01

Clinicians and basic scientists share an interest in discovering how genetic or environmental factors interact to perturb normal development and cause birth defects and human disease. Given the complexity of such interactions, it is not surprising that 4% of human infants are born with a congenital malformation, and cardiovascular defects occur in nearly 1%. Our research is based on the fundamental hypothesis that an understanding of normal and abnormal development will permit us to generate effective strategies for both prevention and treatment of human birth defects. Animal models are invaluable in these efforts because they allow one to interrogate the genetic, molecular and cellular events that distinguish normal from abnormal development. Several features of the mouse make it a particularly powerful experimental model: it is a mammalian system with similar embryology, anatomy and physiology to humans; genes, proteins and regulatory programs are largely conserved between human and mouse; and finally, gene targeting in murine embryonic stem cells has made the mouse genome amenable to sophisticated genetic manipulation currently unavailable in any other model organism. PMID:16641221

Genetic researches on growth traits of Japanese quail

NASA Astrophysics Data System (ADS)

Atalay, Sertaç

2017-04-01

The main objective of the poultry industry is to increase genetic capacity of animals. Growth is one of the most important economic trait in poultry production. Thus, to obtain genetically superior animals related to growth traits is one of the most important issues of poultry breeding programs. Japanese quail is one of the most productive animals in poultry species. Although Japanese quail is small body size, It has high meat and egg production yield. Japanese quail has also important breeding advantages such as short time generation interval, capacity to have a great number of birds per unit area, great reproductive performance, high resistance to diseases and low breeding cost. Therefore, Japanese quail has great advantages for genetic researches and can be used as model animal for major poultry species.

Genetic Algorithm Approaches for Actuator Placement

NASA Technical Reports Server (NTRS)

Crossley, William A.

2000-01-01

This research investigated genetic algorithm approaches for smart actuator placement to provide aircraft maneuverability without requiring hinged flaps or other control surfaces. The effort supported goals of the Multidisciplinary Design Optimization focus efforts in NASA's Aircraft au program. This work helped to properly identify various aspects of the genetic algorithm operators and parameters that allow for placement of discrete control actuators/effectors. An improved problem definition, including better definition of the objective function and constraints, resulted from this research effort. The work conducted for this research used a geometrically simple wing model; however, an increasing number of potential actuator placement locations were incorporated to illustrate the ability of the GA to determine promising actuator placement arrangements. This effort's major result is a useful genetic algorithm-based approach to assist in the discrete actuator/effector placement problem.

MIP models and hybrid algorithms for simultaneous job splitting and scheduling on unrelated parallel machines.

PubMed

Eroglu, Duygu Yilmaz; Ozmutlu, H Cenk

2014-01-01

We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms.

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

NASA Astrophysics Data System (ADS)

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

2013-01-01

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

Cucumber as a Model for Organellar Genetics

USDA-ARS?s Scientific Manuscript database

Mitochondria are found in the cells of all eukaryotes, are imperative for energy production, and play important roles in programmed cell death, ageing, and disease development. Mitochondria possess their own DNA and encode for approximately 20 proteins, as well as their own ribosomal and transfer R...

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

PubMed

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

2014-01-01

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

Genetics of PCOS: A systematic bioinformatics approach to unveil the proteins responsible for PCOS.

PubMed

Panda, Pritam Kumar; Rane, Riya; Ravichandran, Rahul; Singh, Shrinkhla; Panchal, Hetalkumar

2016-06-01

Polycystic ovary syndrome (PCOS) is a hormonal imbalance in women, which causes problems during menstrual cycle and in pregnancy that sometimes results in fatality. Though the genetics of PCOS is not fully understood, early diagnosis and treatment can prevent long-term effects. In this study, we have studied the proteins involved in PCOS and the structural aspects of the proteins that are taken into consideration using computational tools. The proteins involved are modeled using Modeller 9v14 and Ab-initio programs. All the 43 proteins responsible for PCOS were subjected to phylogenetic analysis to identify the relatedness of the proteins. Further, microarray data analysis of PCOS datasets was analyzed that was downloaded from GEO datasets to find the significant protein-coding genes responsible for PCOS, which is an addition to the reported protein-coding genes. Various statistical analyses were done using R programming to get an insight into the structural aspects of PCOS that can be used as drug targets to treat PCOS and other related reproductive diseases.

A reverse engineering algorithm for neural networks, applied to the subthalamopallidal network of basal ganglia.

PubMed

Floares, Alexandru George

2008-01-01

Modeling neural networks with ordinary differential equations systems is a sensible approach, but also very difficult. This paper describes a new algorithm based on linear genetic programming which can be used to reverse engineer neural networks. The RODES algorithm automatically discovers the structure of the network, including neural connections, their signs and strengths, estimates its parameters, and can even be used to identify the biophysical mechanisms involved. The algorithm is tested on simulated time series data, generated using a realistic model of the subthalamopallidal network of basal ganglia. The resulting ODE system is highly accurate, and results are obtained in a matter of minutes. This is because the problem of reverse engineering a system of coupled differential equations is reduced to one of reverse engineering individual algebraic equations. The algorithm allows the incorporation of common domain knowledge to restrict the solution space. To our knowledge, this is the first time a realistic reverse engineering algorithm based on linear genetic programming has been applied to neural networks.

Simplified process model discovery based on role-oriented genetic mining.

PubMed

Zhao, Weidong; Liu, Xi; Dai, Weihui

2014-01-01

Process mining is automated acquisition of process models from event logs. Although many process mining techniques have been developed, most of them are based on control flow. Meanwhile, the existing role-oriented process mining methods focus on correctness and integrity of roles while ignoring role complexity of the process model, which directly impacts understandability and quality of the model. To address these problems, we propose a genetic programming approach to mine the simplified process model. Using a new metric of process complexity in terms of roles as the fitness function, we can find simpler process models. The new role complexity metric of process models is designed from role cohesion and coupling, and applied to discover roles in process models. Moreover, the higher fitness derived from role complexity metric also provides a guideline for redesigning process models. Finally, we conduct case study and experiments to show that the proposed method is more effective for streamlining the process by comparing with related studies.

Hybrid Neural-Network: Genetic Algorithm Technique for Aircraft Engine Performance Diagnostics Developed and Demonstrated

NASA Technical Reports Server (NTRS)

Kobayashi, Takahisa; Simon, Donald L.

2002-01-01

As part of the NASA Aviation Safety Program, a unique model-based diagnostics method that employs neural networks and genetic algorithms for aircraft engine performance diagnostics has been developed and demonstrated at the NASA Glenn Research Center against a nonlinear gas turbine engine model. Neural networks are applied to estimate the internal health condition of the engine, and genetic algorithms are used for sensor fault detection, isolation, and quantification. This hybrid architecture combines the excellent nonlinear estimation capabilities of neural networks with the capability to rank the likelihood of various faults given a specific sensor suite signature. The method requires a significantly smaller data training set than a neural network approach alone does, and it performs the combined engine health monitoring objectives of performance diagnostics and sensor fault detection and isolation in the presence of nominal and degraded engine health conditions.

A genetic algorithm-based job scheduling model for big data analytics.

PubMed

Lu, Qinghua; Li, Shanshan; Zhang, Weishan; Zhang, Lei

Big data analytics (BDA) applications are a new category of software applications that process large amounts of data using scalable parallel processing infrastructure to obtain hidden value. Hadoop is the most mature open-source big data analytics framework, which implements the MapReduce programming model to process big data with MapReduce jobs. Big data analytics jobs are often continuous and not mutually separated. The existing work mainly focuses on executing jobs in sequence, which are often inefficient and consume high energy. In this paper, we propose a genetic algorithm-based job scheduling model for big data analytics applications to improve the efficiency of big data analytics. To implement the job scheduling model, we leverage an estimation module to predict the performance of clusters when executing analytics jobs. We have evaluated the proposed job scheduling model in terms of feasibility and accuracy.

DnaSAM: Software to perform neutrality testing for large datasets with complex null models.

PubMed

Eckert, Andrew J; Liechty, John D; Tearse, Brandon R; Pande, Barnaly; Neale, David B

2010-05-01

Patterns of DNA sequence polymorphisms can be used to understand the processes of demography and adaptation within natural populations. High-throughput generation of DNA sequence data has historically been the bottleneck with respect to data processing and experimental inference. Advances in marker technologies have largely solved this problem. Currently, the limiting step is computational, with most molecular population genetic software allowing a gene-by-gene analysis through a graphical user interface. An easy-to-use analysis program that allows both high-throughput processing of multiple sequence alignments along with the flexibility to simulate data under complex demographic scenarios is currently lacking. We introduce a new program, named DnaSAM, which allows high-throughput estimation of DNA sequence diversity and neutrality statistics from experimental data along with the ability to test those statistics via Monte Carlo coalescent simulations. These simulations are conducted using the ms program, which is able to incorporate several genetic parameters (e.g. recombination) and demographic scenarios (e.g. population bottlenecks). The output is a set of diversity and neutrality statistics with associated probability values under a user-specified null model that are stored in easy to manipulate text file. © 2009 Blackwell Publishing Ltd.

Genetic programs can be compressed and autonomously decompressed in live cells

NASA Astrophysics Data System (ADS)

Lapique, Nicolas; Benenson, Yaakov

2018-04-01

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

SEQassembly: A Practical Tools Program for Coding Sequences Splicing

NASA Astrophysics Data System (ADS)

Lee, Hongbin; Yang, Hang; Fu, Lei; Qin, Long; Li, Huili; He, Feng; Wang, Bo; Wu, Xiaoming

CDS (Coding Sequences) is a portion of mRNA sequences, which are composed by a number of exon sequence segments. The construction of CDS sequence is important for profound genetic analysis such as genotyping. A program in MATLAB environment is presented, which can process batch of samples sequences into code segments under the guide of reference exon models, and splice these code segments of same sample source into CDS according to the exon order in queue file. This program is useful in transcriptional polymorphism detection and gene function study.

An 8-Year Breeding Program for Asian Seabass Lates calcarifer: Genetic Evaluation, Experiences, and Challenges.

PubMed

Khang, Pham Van; Phuong, Truong Ha; Dat, Nguyen Khac; Knibb, Wayne; Nguyen, Nguyen Hong

2018-01-01

Selective breeding for marine finfish is challenging due to difficulties in reproduction, larval rearing, and on-growth in captive environments. The farming of Asian seabass ( Lates calcarifer ) has all these problems and our knowledge of the quantitative genetic information (heritability and correlations) of traits necessary for commercial exploitation is poor. The present study was conducted to address this knowledge gap and to provide information that can be applied to sea bass and other aquaculture species. We carried out a comprehensive genetic evaluation for three traits (body weight, total length, and survival) collected from a breeding population for Asian seabass over an eight-year period from 2010 to 2017. Statistical analysis was carried out on 4,567 adult fish at 105, 180, 270, 360, 450, and 570 days post-hatch (dph). The heritabilities (h 2 ) estimated for body weight and length using linear mixed model were moderate to high (0.12 to 0.78 and 0.41 to 0.85, respectively) and they differed between the measurement periods. Survival during grow-out phase was analyzed using threshold logistic and probit models. The heritability estimates for survival rate on the underlying liability scale ( h L 2 ) varied from 0.05 to 0.21. When the observed heritability obtained from the linear mixed model was back-transformed to the liability scale, they were similar but not significant. In addition, we examined effects of genotype by environment (G × E) interaction on body traits. The genetic correlation for body weight between tank and sea cage cultures were high (0.91-0.94) in the first and second rearing periods (180 and 270 dph) but the correlation was decreased to 0.59 ± 0.33 at 360 dph. This suggests that the genotype by environment interaction is important for body traits in this population. Furthermore, the genetic correlations of body weights between different measurement periods were moderate but different from one. This suggests that body weights measured at different time points may be different traits and selection for improved early weight may not capture all genetic expressions in subsequent rearing periods in Asian seabass. Selection of the nucleus in sea cages may produce genotypes that do not perform equally well in tanks, although this deserves further studies to determine a suitable selection environment and optimize the breeding program. This paper discusses challenges encountered during implementation of the selection program for L. calcarifer .

Genetic analyses of partial egg production in Japanese quail using multi-trait random regression models.

PubMed

Karami, K; Zerehdaran, S; Barzanooni, B; Lotfi, E

2017-12-01

1. The aim of the present study was to estimate genetic parameters for average egg weight (EW) and egg number (EN) at different ages in Japanese quail using multi-trait random regression (MTRR) models. 2. A total of 8534 records from 900 quail, hatched between 2014 and 2015, were used in the study. Average weekly egg weights and egg numbers were measured from second until sixth week of egg production. 3. Nine random regression models were compared to identify the best order of the Legendre polynomials (LP). The most optimal model was identified by the Bayesian Information Criterion. A model with second order of LP for fixed effects, second order of LP for additive genetic effects and third order of LP for permanent environmental effects (MTRR23) was found to be the best. 4. According to the MTRR23 model, direct heritability for EW increased from 0.26 in the second week to 0.53 in the sixth week of egg production, whereas the ratio of permanent environment to phenotypic variance decreased from 0.48 to 0.1. Direct heritability for EN was low, whereas the ratio of permanent environment to phenotypic variance decreased from 0.57 to 0.15 during the production period. 5. For each trait, estimated genetic correlations among weeks of egg production were high (from 0.85 to 0.98). Genetic correlations between EW and EN were low and negative for the first two weeks, but they were low and positive for the rest of the egg production period. 6. In conclusion, random regression models can be used effectively for analysing egg production traits in Japanese quail. Response to selection for increased egg weight would be higher at older ages because of its higher heritability and such a breeding program would have no negative genetic impact on egg production.

Optimal Refueling Pattern Search for a CANDU Reactor Using a Genetic Algorithm

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

Quang Binh, DO; Gyuhong, ROH; Hangbok, CHOI

2006-07-01

This paper presents the results from the application of genetic algorithms to a refueling optimization of a Canada deuterium uranium (CANDU) reactor. This work aims at making a mathematical model of the refueling optimization problem including the objective function and constraints and developing a method based on genetic algorithms to solve the problem. The model of the optimization problem and the proposed method comply with the key features of the refueling strategy of the CANDU reactor which adopts an on-power refueling operation. In this study, a genetic algorithm combined with an elitism strategy was used to automatically search for themore » refueling patterns. The objective of the optimization was to maximize the discharge burn-up of the refueling bundles, minimize the maximum channel power, or minimize the maximum change in the zone controller unit (ZCU) water levels. A combination of these objectives was also investigated. The constraints include the discharge burn-up, maximum channel power, maximum bundle power, channel power peaking factor and the ZCU water level. A refueling pattern that represents the refueling rate and channels was coded by a one-dimensional binary chromosome, which is a string of binary numbers 0 and 1. A computer program was developed in FORTRAN 90 running on an HP 9000 workstation to conduct the search for the optimal refueling patterns for a CANDU reactor at the equilibrium state. The results showed that it was possible to apply genetic algorithms to automatically search for the refueling channels of the CANDU reactor. The optimal refueling patterns were compared with the solutions obtained from the AUTOREFUEL program and the results were consistent with each other. (authors)« less

Generation of Genetically Modified Organotypic Skin Cultures Using Devitalized Human Dermis.

PubMed

Li, Jingting; Sen, George L

2015-12-14

Organotypic cultures allow the reconstitution of a 3D environment critical for cell-cell contact and cell-matrix interactions which mimics the function and physiology of their in vivo tissue counterparts. This is exemplified by organotypic skin cultures which faithfully recapitulates the epidermal differentiation and stratification program. Primary human epidermal keratinocytes are genetically manipulable through retroviruses where genes can be easily overexpressed or knocked down. These genetically modified keratinocytes can then be used to regenerate human epidermis in organotypic skin cultures providing a powerful model to study genetic pathways impacting epidermal growth, differentiation, and disease progression. The protocols presented here describe methods to prepare devitalized human dermis as well as to genetically manipulate primary human keratinocytes in order to generate organotypic skin cultures. Regenerated human skin can be used in downstream applications such as gene expression profiling, immunostaining, and chromatin immunoprecipitations followed by high throughput sequencing. Thus, generation of these genetically modified organotypic skin cultures will allow the determination of genes that are critical for maintaining skin homeostasis.

An Expressed Sequence Tag (EST)-enriched genetic map of turbot (Scophthalmus maximus): a useful framework for comparative genomics across model and farmed teleosts

PubMed Central

2012-01-01

Background The turbot (Scophthalmus maximus) is a relevant species in European aquaculture. The small turbot genome provides a source for genomics strategies to use in order to understand the genetic basis of productive traits, particularly those related to sex, growth and pathogen resistance. Genetic maps represent essential genomic screening tools allowing to localize quantitative trait loci (QTL) and to identify candidate genes through comparative mapping. This information is the backbone to develop marker-assisted selection (MAS) programs in aquaculture. Expressed sequenced tag (EST) resources have largely increased in turbot, thus supplying numerous type I markers suitable for extending the previous linkage map, which was mostly based on anonymous loci. The aim of this study was to construct a higher-resolution turbot genetic map using EST-linked markers, which will turn out to be useful for comparative mapping studies. Results A consensus gene-enriched genetic map of the turbot was constructed using 463 SNP and microsatellite markers in nine reference families. This map contains 438 markers, 180 EST-linked, clustered at 24 linkage groups. Linkage and comparative genomics evidences suggested additional linkage group fusions toward the consolidation of turbot map according to karyotype information. The linkage map showed a total length of 1402.7 cM with low average intermarker distance (3.7 cM; ~2 Mb). A global 1.6:1 female-to-male recombination frequency (RF) ratio was observed, although largely variable among linkage groups and chromosome regions. Comparative sequence analysis revealed large macrosyntenic patterns against model teleost genomes, significant hits decreasing from stickleback (54%) to zebrafish (20%). Comparative mapping supported particular chromosome rearrangements within Acanthopterygii and aided to assign unallocated markers to specific turbot linkage groups. Conclusions The new gene-enriched high-resolution turbot map represents a useful genomic tool for QTL identification, positional cloning strategies, and future genome assembling. This map showed large synteny conservation against model teleost genomes. Comparative genomics and data mining from landmarks will provide straightforward access to candidate genes, which will be the basis for genetic breeding programs and evolutionary studies in this species. PMID:22747677

Genetic diversity trend in Indian rice varieties: an analysis using SSR markers.

PubMed

Singh, Nivedita; Choudhury, Debjani Roy; Tiwari, Gunjan; Singh, Amit Kumar; Kumar, Sundeep; Srinivasan, Kalyani; Tyagi, R K; Sharma, A D; Singh, N K; Singh, Rakesh

2016-09-05

The knowledge of the extent and pattern of diversity in the crop species is a prerequisite for any crop improvement as it helps breeders in deciding suitable breeding strategies for their future improvement. Rice is the main staple crop in India with the large number of varieties released every year. Studies based on the small set of rice genotypes have reported a loss in genetic diversity especially after green revolution. However, a detailed study of the trend of diversity in Indian rice varieties is lacking. SSR markers have proven to be a marker of choice for studying the genetic diversity. Therefore, the present study was undertaken with the aim to characterize and assess trends of genetic diversity in a large set of Indian rice varieties (released between 1940-2013), conserved in the National Gene Bank of India using SSR markers. A set of 729 Indian rice varieties were genotyped using 36 HvSSR markers to assess the genetic diversity and genetic relationship. A total of 112 alleles was amplified with an average of 3.11 alleles per locus with mean Polymorphic Information Content (PIC) value of 0.29. Cluster analysis grouped these varieties into two clusters whereas the model based population structure divided them into three populations. AMOVA study based on hierarchical cluster and model based approach showed 3 % and 11 % variation between the populations, respectively. Decadal analysis for gene diversity and PIC showed increasing trend from 1940 to 2005, thereafter values for both the parameters showed decreasing trend between years 2006-2013. In contrast to this, allele number demonstrated increasing trend in these varieties released and notified between1940 to 1985, it remained nearly constant during 1986 to 2005 and again showed an increasing trend. Our results demonstrated that the Indian rice varieties harbors huge amount of genetic diversity. However, the trait based improvement program in the last decades forced breeders to rely on few parents, which resulted in loss of gene diversity during 2006 to 2013. The present study indicates the need for broadening the genetic base of Indian rice varieties through the use of diverse parents in the current breeding program.

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

NASA Astrophysics Data System (ADS)

Kashid, Satishkumar S.; Maity, Rajib

2012-08-01

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

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

PubMed

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

2017-09-01

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

Breeding value accuracy estimates for growth traits using random regression and multi-trait models in Nelore cattle.

PubMed

Boligon, A A; Baldi, F; Mercadante, M E Z; Lobo, R B; Pereira, R J; Albuquerque, L G

2011-06-28

We quantified the potential increase in accuracy of expected breeding value for weights of Nelore cattle, from birth to mature age, using multi-trait and random regression models on Legendre polynomials and B-spline functions. A total of 87,712 weight records from 8144 females were used, recorded every three months from birth to mature age from the Nelore Brazil Program. For random regression analyses, all female weight records from birth to eight years of age (data set I) were considered. From this general data set, a subset was created (data set II), which included only nine weight records: at birth, weaning, 365 and 550 days of age, and 2, 3, 4, 5, and 6 years of age. Data set II was analyzed using random regression and multi-trait models. The model of analysis included the contemporary group as fixed effects and age of dam as a linear and quadratic covariable. In the random regression analyses, average growth trends were modeled using a cubic regression on orthogonal polynomials of age. Residual variances were modeled by a step function with five classes. Legendre polynomials of fourth and sixth order were utilized to model the direct genetic and animal permanent environmental effects, respectively, while third-order Legendre polynomials were considered for maternal genetic and maternal permanent environmental effects. Quadratic polynomials were applied to model all random effects in random regression models on B-spline functions. Direct genetic and animal permanent environmental effects were modeled using three segments or five coefficients, and genetic maternal and maternal permanent environmental effects were modeled with one segment or three coefficients in the random regression models on B-spline functions. For both data sets (I and II), animals ranked differently according to expected breeding value obtained by random regression or multi-trait models. With random regression models, the highest gains in accuracy were obtained at ages with a low number of weight records. The results indicate that random regression models provide more accurate expected breeding values than the traditionally finite multi-trait models. Thus, higher genetic responses are expected for beef cattle growth traits by replacing a multi-trait model with random regression models for genetic evaluation. B-spline functions could be applied as an alternative to Legendre polynomials to model covariance functions for weights from birth to mature age.

Routine human-competitive machine intelligence by means of genetic programming

NASA Astrophysics Data System (ADS)

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

2004-01-01

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

Comparison of linear, skewed-linear, and proportional hazard models for the analysis of lambing interval in Ripollesa ewes.

PubMed

Casellas, J; Bach, R

2012-06-01

Lambing interval is a relevant reproductive indicator for sheep populations under continuous mating systems, although there is a shortage of selection programs accounting for this trait in the sheep industry. Both the historical assumption of small genetic background and its unorthodox distribution pattern have limited its implementation as a breeding objective. In this manuscript, statistical performances of 3 alternative parametrizations [i.e., symmetric Gaussian mixed linear (GML) model, skew-Gaussian mixed linear (SGML) model, and piecewise Weibull proportional hazard (PWPH) model] have been compared to elucidate the preferred methodology to handle lambing interval data. More specifically, flock-by-flock analyses were performed on 31,986 lambing interval records (257.3 ± 0.2 d) from 6 purebred Ripollesa flocks. Model performances were compared in terms of deviance information criterion (DIC) and Bayes factor (BF). For all flocks, PWPH models were clearly preferred; they generated a reduction of 1,900 or more DIC units and provided BF estimates larger than 100 (i.e., PWPH models against linear models). These differences were reduced when comparing PWPH models with different number of change points for the baseline hazard function. In 4 flocks, only 2 change points were required to minimize the DIC, whereas 4 and 6 change points were needed for the 2 remaining flocks. These differences demonstrated a remarkable degree of heterogeneity across sheep flocks that must be properly accounted for in genetic evaluation models to avoid statistical biases and suboptimal genetic trends. Within this context, all 6 Ripollesa flocks revealed substantial genetic background for lambing interval with heritabilities ranging between 0.13 and 0.19. This study provides the first evidence of the suitability of PWPH models for lambing interval analysis, clearly discarding previous parametrizations focused on mixed linear models.

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

PubMed

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

2010-06-01

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

Guidelines on the use of molecular genetics in reintroduction programs

Treesearch

Michael K. Schwartz

2005-01-01

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

Genetic and environmental influences on the transmission of parental depression to children's depression and conduct disturbance: an extended Children of Twins study.

PubMed

Silberg, Judy L; Maes, Hermine; Eaves, Lindon J

2010-06-01

Despite the increased risk of depression and conduct problems in children of depressed parents, the mechanism by which parental depression affects their children's behavioral and emotional functioning is not well understood. The present study was undertaken to determine whether parental depression represents a genuine environmental risk factor in children's psychopathology, or whether children's depression/conduct can be explained as a secondary consequence of the genetic liability transmitted from parents to their offspring. Children of Twins (COT) data collected on 2,674 adult female and male twins, their spouses, and 2,940 of their children were used to address whether genetic and/or family environmental factors best account for the association between depression in parents and depression and conduct problems in their children. Data collected on juvenile twins from the Virginia Twin Study of Adolescent Behavioral Development (VTSABD) were also included to estimate child-specific genetic and environmental influences apart from those effects arising from the transmission of the parental depression itself. The fit of alternative Children of Twin models were evaluated using the statistical program Mx. The most compelling model for the association between parental and juvenile depression was a model of direct environmental risk. Both family environmental and genetic factors accounted for the association between parental depression and child conduct disturbance. These findings illustrate how a genetically mediated behavior such as parental depression can have both an environmental and genetic impact on children's behavior. We find developmentally specific genetic factors underlying risk to juvenile and adult depression. A shared genetic liability influences both parental depression and juvenile conduct disturbance, implicating child conduct disturbance (CD) as an early indicator of genetic risk for depression in adulthood. In summary, our analyses demonstrate differences in the impact of parental depression on different forms of child psychopathology, and at various stages of development.

Genetic and environmental influences on the transmission of parental depression to children’s depression and conduct disturbance: An extended Children of Twins study

PubMed Central

Silberg, Judy L.; Maes, Hermine; Eaves, Lindon J.

2010-01-01

Background Despite the increased risk of depression and conduct problems in children of depressed parents, the mechanism by which parental depression affects their children’s behavioral and emotional functioning is not well understood. The present study was undertaken to determine whether parental depression represents a genuine environmental risk factor in children’s psychopathology, or whether children’s depression/conduct can be explained as a secondary consequence of the genetic liability transmitted from parents to their offspring. Methods Children of Twins (COT) data collected on 2,674 adult female and male twins, their spouses, and 2,940 of their children were used to address whether genetic and/or family environmental factors best account for the association between depression in parents and depression and conduct problems in their children. Data collected on juvenile twins from the Virginia Twin Study of Adolescent Behavioral Development (VTSABD) were also included to estimate child-specific genetic and environmental influences apart from those effects arising from the transmission of the parental depression itself. The fit of alternative Children of Twin models were evaluated using the statistical program Mx. Results The most compelling model for the association between parental and juvenile depression was a model of direct environmental risk. Both family environmental and genetic factors accounted for the association between parental depression and child conduct disturbance. Conclusions These findings illustrate how a genetically mediated behavior such as parental depression can have both an environmental and genetic impact on children’s behavior. We find developmentally specific genetic factors underlying risk to juvenile and adult depression. A shared genetic liability influence both parental depression and juvenile conduct disturbance, implicating child CD as an early indicator of genetic risk for depression in adulthood. In summary, our analyses demonstrate differences in the impact of parental depression on different forms of child psychopathology, and at various stages of development. PMID:20163497

SoftLab: A Soft-Computing Software for Experimental Research with Commercialization Aspects

NASA Technical Reports Server (NTRS)

Akbarzadeh-T, M.-R.; Shaikh, T. S.; Ren, J.; Hubbell, Rob; Kumbla, K. K.; Jamshidi, M

1998-01-01

SoftLab is a software environment for research and development in intelligent modeling/control using soft-computing paradigms such as fuzzy logic, neural networks, genetic algorithms, and genetic programs. SoftLab addresses the inadequacies of the existing soft-computing software by supporting comprehensive multidisciplinary functionalities from management tools to engineering systems. Furthermore, the built-in features help the user process/analyze information more efficiently by a friendly yet powerful interface, and will allow the user to specify user-specific processing modules, hence adding to the standard configuration of the software environment.

The “Genetic Program”: Behind the Genesis of an Influential Metaphor

PubMed Central

Peluffo, Alexandre E.

2015-01-01

The metaphor of the “genetic program,” indicating the genome as a set of instructions required to build a phenotype, has been very influential in biology despite various criticisms over the years. This metaphor, first published in 1961, is thought to have been invented independently in two different articles, one by Ernst Mayr and the other by François Jacob and Jacques Monod. Here, after a detailed analysis of what both parties meant by “genetic program,” I show, using unpublished archives, the strong resemblance between the ideas of Mayr and Monod and suggest that their idea of genetic program probably shares a common origin. I explore the possibility that the two men met before 1961 and also exchanged their ideas through common friends and colleagues in the field of molecular biology. Based on unpublished correspondence of Jacob and Monod, I highlight the important events that influenced the preparation of their influential paper, which introduced the concept of the genetic program. Finally, I suggest that the genetic program metaphor may have preceded both papers and that it was probably used informally before 1961. PMID:26170444

Landscape genetics of the nonnative red fox of California.

PubMed

Sacks, Benjamin N; Brazeal, Jennifer L; Lewis, Jeffrey C

2016-07-01

Invasive mammalian carnivores contribute disproportionately to declines in global biodiversity. In California, nonnative red foxes (Vulpes vulpes) have significantly impacted endangered ground-nesting birds and native canids. These foxes derive primarily from captive-reared animals associated with the fur-farming industry. Over the past five decades, the cumulative area occupied by nonnative red fox increased to cover much of central and southern California. We used a landscape-genetic approach involving mitochondrial DNA (mtDNA) sequences and 13 microsatellites of 402 nonnative red foxes removed in predator control programs to investigate source populations, contemporary connectivity, and metapopulation dynamics. Both markers indicated high population structuring consistent with origins from multiple introductions and low subsequent gene flow. Landscape-genetic modeling indicated that population connectivity was especially low among coastal sampling sites surrounded by mountainous wildlands but somewhat higher through topographically flat, urban and agricultural landscapes. The genetic composition of populations tended to be stable for multiple generations, indicating a degree of demographic resilience to predator removal programs. However, in two sites where intensive predator control reduced fox abundance, we observed increases in immigration, suggesting potential for recolonization to counter eradication attempts. These findings, along with continued genetic monitoring, can help guide localized management of foxes by identifying points of introductions and routes of spread and evaluating the relative importance of reproduction and immigration in maintaining populations. More generally, the study illustrates the utility of a landscape-genetic approach for understanding invasion dynamics and metapopulation structure of one of the world's most destructive invasive mammals, the red fox.

Precision Oncology and Genetic Risk Information: Exploring Patients' Preferences and Responses

Cancer.gov

Dr. Jada Hamilton is an Assistant Member at Memorial Sloan Kettering Cancer Center, as well as an Assistant Attending Psychologist in the Behavioral Sciences Service, Department of Psychiatry and Behavioral Sciences and in the Clinical Genetics Service, Department of Medicine at Memorial Hospital in New York, New York.  She leads a program of research at the intersection of behavioral science, cancer prevention, and genomics, with the goal of translating advances in genetic and genomic medicine into improved cancer care that is of high quality, aligned with patient preferences, and ultimately improves public health.  Dr. Hamilton is also currently leading a study to assess how patients and their families respond to inherited risk information that is revealed as part of tumor sequencing (funded through a Mentored Research Scholar Grant from the American Cancer Society), as well as studies to evaluate alternative models for offering genetic counseling and testing to patients with cancer, and to examine the effects of novel breast cancer genetic risk feedback on patients’ decision-making, psychological, and behavioral outcomes. Prior to joining the faculty of Memorial Sloan Kettering, Dr. Hamilton received a BA in Genetics and Psychology from Ohio Wesleyan University (2004), an MA and PhD in Social and Health Psychology from Stony Brook University (2006, 2009), and an MPH from the Mailman School of Public Health at Columbia University (2010).  She also completed a postdoctoral fellowship as part of the National Cancer Institute’s Cancer Prevention Fellowship Program.

Farm-by-farm analysis of microsatellite, mtDNA and SNP genotype data reveals inbreeding and crossbreeding as threats to the survival of a native Spanish pig breed.

PubMed

Herrero-Medrano, J M; Megens, H J; Crooijmans, R P; Abellaneda, J M; Ramis, G

2013-06-01

The Chato Murciano (CM), a pig breed from the Murcia region in the southeastern region of Spain, is a good model for endangered livestock populations. The remaining populations are bred on approximately 15 small farms, and no herdbook exists. To assess the genetic threats to the integrity and survival of the CM breed, and to aid in designing a conservation program, three genetic marker systems - microsatellites, SNPs and mtDNA - were applied across the majority of the total breeding stock. In addition, mtDNA and SNPs were genotyped in breeds that likely contributed genetically to the current CM gene pool. The analyses revealed the levels of genetic diversity within the range of other European local breeds (H(e) = 0.53). However, when the eight farms that rear at least 10 CM pigs were independently analyzed, high levels of inbreeding were found in some. Despite the evidence for recent crossbreeding with commercial breeds on a few farms, the entire breeding stock remains readily identifiable as CM, facilitating the design of traceability assays. The genetic management of the breed is consistent with farm size, farm owner and presence of other pig breeds on the farm, demonstrating the highly ad hoc nature of current CM breeding. The results of genetic diversity and substructure of the entire breed, as well as admixture and crossbreeding obtained in the present study, provide a benchmark to develop future conservation strategies. Furthermore, this study demonstrates that identifying farm-based practices and farm-based breeding stocks can aid in the design of a sustainable breeding program for minority breeds. © 2012 The Authors, Animal Genetics © 2012 Stichting International Foundation for Animal Genetics.

An Introduction to Computational Physics

NASA Astrophysics Data System (ADS)

Pang, Tao

2010-07-01

Preface to first edition; Preface; Acknowledgements; 1. Introduction; 2. Approximation of a function; 3. Numerical calculus; 4. Ordinary differential equations; 5. Numerical methods for matrices; 6. Spectral analysis; 7. Partial differential equations; 8. Molecular dynamics simulations; 9. Modeling continuous systems; 10. Monte Carlo simulations; 11. Genetic algorithm and programming; 12. Numerical renormalization; References; Index.

Rat Models of Cardiovascular Disease Demonstrate Distinctive Pulmonary Gene Expressions for Vascular Response Genes: Impact of Ozone Exposure

EPA Science Inventory

Comparative gene expression profiling of multiple tissues from rat strains with genetic predisposition to diverse cardiovascular diseases (CVD) can help decode the transcriptional program that governs organ-specific functions. We examined expressions of CVD genes in the lungs of ...

Electrochemical impedance spectroscopy of supercapacitors: A novel analysis approach using evolutionary programming

NASA Astrophysics Data System (ADS)

Oz, Alon; Hershkovitz, Shany; Tsur, Yoed

2014-11-01

In this contribution we present a novel approach to analyze impedance spectroscopy measurements of supercapacitors. Transforming the impedance data into frequency-dependent capacitance allows us to use Impedance Spectroscopy Genetic Programming (ISGP) in order to find the distribution function of relaxation times (DFRT) of the processes taking place in the tested device. Synthetic data was generated in order to demonstrate this technique and a model for supercapacitor ageing process has been obtained.

Role-playing is an effective instructional strategy for genetic counseling training: an investigation and comparative study.

PubMed

Xu, Xiao-Feng; Wang, Yan; Wang, Yan-Yan; Song, Ming; Xiao, Wen-Gang; Bai, Yun

2016-09-02

Genetic diseases represent a significant public health challenge in China that will need to be addressed by a correspondingly large number of professional genetic counselors. However, neither an official training program for genetic counseling, nor formal board certification, was available in China before 2015. In 2009, a genetic counseling training program based on role-playing was implemented as a pilot study at the Third Military Medical University to train third-year medical students. Questionnaires on participant attitudes to the program and role-playing were randomly administered to 324 students after they had finished their training. Pre- and post-training instructional tests, focusing on 42 key components of genetic counseling, were administered randomly to 200 participants to assess mastery of each component. Finally, scores in final examinations of 578 participants from 2009 to 2011 were compared to scores obtained by 614 non-participating students from 2006 to 2008 to further assess program efficacy. Both the training program and the instructional strategy of role-playing were accepted by most participants. Students believed that role-playing improved their practice of genetic counseling and medical genetics, enhanced their communication skills, and would likely contribute to future professional performance. The average understanding of 40 of the key points in genetic counseling was significantly improved, and most students approached excellent levels of mastery. Scores in final examinations and the percentages of students scoring above 90 were also significantly elevated. Role-playing is a feasible and effective instructional strategy for training genetic counselors in China as well as in other developing countries.

Catalysis and biocatalysis program

NASA Technical Reports Server (NTRS)

1991-01-01

The annual report presents the fiscal year (FY) 1990 research activities and accomplishments for the Catalysis and Biocatalysis Program of the Advanced Industrial Concepts Division (AICD), Office of Industrial Technologies of the Department of Energy (DOE). The mission of the AICD is to create a balanced program of high risk, long term, directed interdisciplinary research and development that will improve energy efficiency and enhance fuel flexibility in the industrial sector. The Catalysis and Biocatalysis Program's technical activities were organized into five work elements: the Molecular Modeling and Catalysis by Design element; the Applied Microbiology and Genetics element; the Bioprocess Engineering element; the Separations and Novel Chemical Processes element; and the Process Design and Analysis element.

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

PubMed

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

2018-05-01

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

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

PubMed Central

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

2010-01-01

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

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

PubMed

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

2010-12-28

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

A nonlinear bi-level programming approach for product portfolio management.

PubMed

Ma, Shuang

2016-01-01

Product portfolio management (PPM) is a critical decision-making for companies across various industries in today's competitive environment. Traditional studies on PPM problem have been motivated toward engineering feasibilities and marketing which relatively pay less attention to other competitors' actions and the competitive relations, especially in mathematical optimization domain. The key challenge lies in that how to construct a mathematical optimization model to describe this Stackelberg game-based leader-follower PPM problem and the competitive relations between them. The primary work of this paper is the representation of a decision framework and the optimization model to leverage the PPM problem of leader and follower. A nonlinear, integer bi-level programming model is developed based on the decision framework. Furthermore, a bi-level nested genetic algorithm is put forward to solve this nonlinear bi-level programming model for leader-follower PPM problem. A case study of notebook computer product portfolio optimization is reported. Results and analyses reveal that the leader-follower bi-level optimization model is robust and can empower product portfolio optimization.

A Data-Driven Approach to Develop Physically Sound Predictors: Application to Depth-Averaged Velocities and Drag Coefficients on Vegetated Flows

NASA Astrophysics Data System (ADS)

Tinoco, R. O.; Goldstein, E. B.; Coco, G.

2016-12-01

We use a machine learning approach to seek accurate, physically sound predictors, to estimate two relevant flow parameters for open-channel vegetated flows: mean velocities and drag coefficients. A genetic programming algorithm is used to find a robust relationship between properties of the vegetation and flow parameters. We use data published from several laboratory experiments covering a broad range of conditions to obtain: a) in the case of mean flow, an equation that matches the accuracy of other predictors from recent literature while showing a less complex structure, and b) for drag coefficients, a predictor that relies on both single element and array parameters. We investigate different criteria for dataset size and data selection to evaluate their impact on the resulting predictor, as well as simple strategies to obtain only dimensionally consistent equations, and avoid the need for dimensional coefficients. The results show that a proper methodology can deliver physically sound models representative of the processes involved, such that genetic programming and machine learning techniques can be used as powerful tools to study complicated phenomena and develop not only purely empirical, but "hybrid" models, coupling results from machine learning methodologies into physics-based models.

Genetics and the unity of biology. Program

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

Not Available

1988-12-31

International Congresses of Genetics, convened just once every five years, provide a rare opportunity for overview in the field of genetic engineering. The Congress, held August 20-27, 1988 in Toronto, Canada focused on the theme Genetics and the Unity of Biology, which was chosen because the concepts of modern genetics have provided biology with a unifying theoretical structure. This program guide contains a schedule of all Congress activities and a listing of all Symposia, Workshops and Poster Sessions held.

Experimental Design for Estimating Unknown Hydraulic Conductivity in a Confined Aquifer using a Genetic Algorithm and a Reduced Order Model

NASA Astrophysics Data System (ADS)

Ushijima, T.; Yeh, W.

2013-12-01

An optimal experimental design algorithm is developed to select locations for a network of observation wells that provides the maximum information about unknown hydraulic conductivity in a confined, anisotropic aquifer. The design employs a maximal information criterion that chooses, among competing designs, the design that maximizes the sum of squared sensitivities while conforming to specified design constraints. Because that the formulated problem is non-convex and contains integer variables (necessitating a combinatorial search), for a realistically-scaled model, the problem may be difficult, if not impossible, to solve through traditional mathematical programming techniques. Genetic Algorithms (GAs) are designed to search out the global optimum; however because a GA requires a large number of calls to a groundwater model, the formulated optimization problem may still be infeasible to solve. To overcome this, Proper Orthogonal Decomposition (POD) is applied to the groundwater model to reduce its dimension. The information matrix in the full model space can then be searched without solving the full model.

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

PubMed

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

2006-10-11

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

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

PubMed Central

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

2006-01-01

Background Morus boninensis, is an endemic plant of the Bonin (Ogasawara) Islands of Japan and is categorized as "critically endangered" in the Japanese red data book. However, little information is available about its ecological, evolutionary and genetic status, despite the urgent need for guidelines for the conservation of the species. Therefore, we adopted Moritz's MU concept, based on the species' current genetic structure, to define management units and to select mother tree candidates for seed orchards. Results Nearly all individuals of the species were genotyped on the basis of seven microsatellite markers. Genetic diversity levels in putative natural populations were higher than in putative man-made populations with the exception of those on Otouto-jima Island. This is because a limited number of maternal trees are likely to have been used for seed collection to establish the man-made populations. A model-based clustering analysis clearly distinguished individuals into nine clusters, with a large difference in genetic composition between the population on Otouto-jima Island, the putative natural populations and the putative man-made populations. The Otouto-jima population appeared to be genetically differentiated from the others; a finding that was also supported by pairwise FST and RST analysis. Although multiple clusters were detected in the putative man-made populations, the pattern of genetic diversity was monotonous in comparison to the natural populations. Conclusion The genotyping by microsatellite markers revealed strong genetic structures. Typically, artificial propagation of this species has ignored the genetic structure, relying only on seeds from Otouto-jima for replanting on other islands, because of a problem with inter-specific hybridization on Chichi-jima and Haha-jima Islands. However, this study demonstrates that we should be taking into consideration the genetic structure of the species when designing a propagation program for the conservation of this species. PMID:17034624

Characterization of Neurofibromas of the Skin and Spinal Roots in a Mouse Model

DTIC Science & Technology

2011-02-01

renewal program of stem/progenitor cells can cause tumorigenesis. By utilizing genetically engineered mouse models of neurofibromatosis type 1 (NF1...pathetic ganglia and adrenal medulla and died at birth (Gitler et al., 2003). To circumvent early lethality of the Nf1NC mice, we utilized a previously...Supplemental experimental procedures Tissue Processing For histological analysis, we utilized both paraffin sections and frozen sections. For both

Analyzing Population Genetics Data: A Comparison of the Software

USDA-ARS?s Scientific Manuscript database

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

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Increased genetic gains in sheep, beef and dairy breeding programs from using female reproductive technologies combined with optimal contribution selection and genomic breeding values.

PubMed

Granleese, Tom; Clark, Samuel A; Swan, Andrew A; van der Werf, Julius H J

2015-09-14

Female reproductive technologies such as multiple ovulation and embryo transfer (MOET) and juvenile in vitro embryo production and embryo transfer (JIVET) can boost rates of genetic gain but they can also increase rates of inbreeding. Inbreeding can be managed using the principles of optimal contribution selection (OCS), which maximizes genetic gain while placing a penalty on the rate of inbreeding. We evaluated the potential benefits and synergies that exist between genomic selection (GS) and reproductive technologies under OCS for sheep and cattle breeding programs. Various breeding program scenarios were simulated stochastically including: (1) a sheep breeding program for the selection of a single trait that could be measured either early or late in life; (2) a beef breeding program with an early or late trait; and (3) a dairy breeding program with a sex limited trait. OCS was applied using a range of penalties (severe to no penalty) on co-ancestry of selection candidates, with the possibility of using multiple ovulation and embryo transfer (MOET) and/or juvenile in vitro embryo production and embryo transfer (JIVET) for females. Each breeding program was simulated with and without genomic selection. All breeding programs could be penalized to result in an inbreeding rate of 1 % increase per generation. The addition of MOET to artificial insemination or natural breeding (AI/N), without the use of GS yielded an extra 25 to 60 % genetic gain. The further addition of JIVET did not yield an extra genetic gain. When GS was used, MOET and MOET + JIVET programs increased rates of genetic gain by 38 to 76 % and 51 to 81 % compared to AI/N, respectively. Large increases in genetic gain were found across species when female reproductive technologies combined with genomic selection were applied and inbreeding was managed, especially for breeding programs that focus on the selection of traits measured late in life or that are sex-limited. Optimal contribution selection was an effective tool to optimally allocate different combinations of reproductive technologies. Applying a range of penalties to co-ancestry of selection candidates allows a comprehensive exploration of the inbreeding vs. genetic gain space.

Cancer Genetics and Signaling | Center for Cancer Research

Cancer.gov

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

Genetic programming and serial processing for time series classification.

PubMed

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

2014-01-01

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

Genomic Selection in Plant Breeding: Methods, Models, and Perspectives.

PubMed

Crossa, José; Pérez-Rodríguez, Paulino; Cuevas, Jaime; Montesinos-López, Osval; Jarquín, Diego; de Los Campos, Gustavo; Burgueño, Juan; González-Camacho, Juan M; Pérez-Elizalde, Sergio; Beyene, Yoseph; Dreisigacker, Susanne; Singh, Ravi; Zhang, Xuecai; Gowda, Manje; Roorkiwal, Manish; Rutkoski, Jessica; Varshney, Rajeev K

2017-11-01

Genomic selection (GS) facilitates the rapid selection of superior genotypes and accelerates the breeding cycle. In this review, we discuss the history, principles, and basis of GS and genomic-enabled prediction (GP) as well as the genetics and statistical complexities of GP models, including genomic genotype×environment (G×E) interactions. We also examine the accuracy of GP models and methods for two cereal crops and two legume crops based on random cross-validation. GS applied to maize breeding has shown tangible genetic gains. Based on GP results, we speculate how GS in germplasm enhancement (i.e., prebreeding) programs could accelerate the flow of genes from gene bank accessions to elite lines. Recent advances in hyperspectral image technology could be combined with GS and pedigree-assisted breeding. Copyright © 2017 Elsevier Ltd. All rights reserved.

ECUT: Energy Conversion and Utilization Technologies program - Biocatalysis research activity

NASA Technical Reports Server (NTRS)

Wilcox, R.

1984-01-01

The activities of the Biocatalysis Research Activity are organized into the Biocatalysis and Molecular Modeling work elements and a supporting planning and analysis function. In the Biocatalysis work element, progress is made in developing a method for stabilizing genetically engineered traits in microorganisms, refining a technique for monitoring cells that are genetically engineered, and identifying strains of fungi for highly efficient preprocessing of biomass for optimizing the efficiency of bioreactors. In the Molecular Modeling work element, a preliminary model of the behavior of enzymes is developed. A preliminary investigation of the potential for synthesizing enzymes for use in electrochemical processes is completed. Contact with industry and universities is made to define key biocatalysis technical issues and to broaden the range of potential participants in the activity. Analyses are conducted to identify and evaluate potential concepts for future research funding.

The Spring of Systems Biology-Driven Breeding.

PubMed

Lavarenne, Jérémy; Guyomarc'h, Soazig; Sallaud, Christophe; Gantet, Pascal; Lucas, Mikaël

2018-05-12

Genetics and molecular biology have contributed to the development of rationalized plant breeding programs. Recent developments in both high-throughput experimental analyses of biological systems and in silico data processing offer the possibility to address the whole gene regulatory network (GRN) controlling a given trait. GRN models can be applied to identify topological features helping to shortlist potential candidate genes for breeding purposes. Time-series data sets can be used to support dynamic modelling of the network. This will enable a deeper comprehension of network behaviour and the identification of the few elements to be genetically rewired to push the system towards a modified phenotype of interest. This paves the way to design more efficient, systems biology-based breeding strategies. Copyright © 2018 Elsevier Ltd. All rights reserved.

MIP Models and Hybrid Algorithms for Simultaneous Job Splitting and Scheduling on Unrelated Parallel Machines

PubMed Central

Ozmutlu, H. Cenk

2014-01-01

We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms. PMID:24977204

An intelligent subtitle detection model for locating television commercials.

PubMed

Huang, Yo-Ping; Hsu, Liang-Wei; Sandnes, Frode-Eika

2007-04-01

A strategy for locating television (TV) commercials in TV programs is proposed. Based on the observation that most TV commercials do not have subtitles, the first stage exploits six subtitle constraints and an adaptive neurofuzzy inference system model to determine whether a frame contains a subtitle or not. The second stage involves locating the mark-in/mark-out points using a genetic algorithm. An interactive user interface allows users to efficiently identify and fine-tune the exact boundaries separating the commercials from the program content. Furthermore, erroneous boundaries are manually corrected. Experimental results show that the precision rate and recall rates exceed 90%.

Genetic and environmental influences on dimensional representations of DSM-IV cluster C personality disorders: a population-based multivariate twin study.

PubMed

Reichborn-Kjennerud, Ted; Czajkowski, Nikolai; Neale, Michael C; Ørstavik, Ragnhild E; Torgersen, Svenn; Tambs, Kristian; Røysamb, Espen; Harris, Jennifer R; Kendler, Kenneth S

2007-05-01

The DSM-IV cluster C Axis II disorders include avoidant (AVPD), dependent (DEPD) and obsessive-compulsive (OCPD) personality disorders. We aimed to estimate the genetic and environmental influences on dimensional representations of these disorders and examine the validity of the cluster C construct by determining to what extent common familial factors influence the individual PDs. PDs were assessed using the Structured Interview for DSM-IV Personality (SIDP-IV) in a sample of 1386 young adult twin pairs from the Norwegian Institute of Public Health Twin Panel (NIPHTP). A single-factor independent pathway multivariate model was applied to the number of endorsed criteria for the three cluster C disorders, using the statistical modeling program Mx. The best-fitting model included genetic and unique environmental factors only, and equated parameters for males and females. Heritability ranged from 27% to 35%. The proportion of genetic variance explained by a common factor was 83, 48 and 15% respectively for AVPD, DEPD and OCPD. Common genetic and environmental factors accounted for 54% and 64% respectively of the variance in AVPD and DEPD but only 11% of the variance in OCPD. Cluster C PDs are moderately heritable. No evidence was found for shared environmental or sex effects. Common genetic and individual environmental factors account for a substantial proportion of the variance in AVPD and DEPD. However, OCPD appears to be largely etiologically distinct from the other two PDs. The results do not support the validity of the DSM-IV cluster C construct in its present form.

Intertransaction Class Association Rule Mining Based on Genetic Network Programming and Its Application to Stock Market Prediction

NASA Astrophysics Data System (ADS)

Yang, Yuchen; Mabu, Shingo; Shimada, Kaoru; Hirasawa, Kotaro

Intertransaction association rules have been reported to be useful in many fields such as stock market prediction, but still there are not so many efficient methods to dig them out from large data sets. Furthermore, how to use and measure these more complex rules should be considered carefully. In this paper, we propose a new intertransaction class association rule mining method based on Genetic Network Programming (GNP), which has the ability to overcome some shortages of Apriori-like based intertransaction association methods. Moreover, a general classifier model for intertransaction rules is also introduced. In experiments on the real world application of stock market prediction, the method shows its efficiency and ability to obtain good results and can bring more benefits with a suitable classifier considering larger interval span.

Modeling Structure-Function Relationships in Synthetic DNA Sequences using Attribute Grammars

PubMed Central

Cai, Yizhi; Lux, Matthew W.; Adam, Laura; Peccoud, Jean

2009-01-01

Recognizing that certain biological functions can be associated with specific DNA sequences has led various fields of biology to adopt the notion of the genetic part. This concept provides a finer level of granularity than the traditional notion of the gene. However, a method of formally relating how a set of parts relates to a function has not yet emerged. Synthetic biology both demands such a formalism and provides an ideal setting for testing hypotheses about relationships between DNA sequences and phenotypes beyond the gene-centric methods used in genetics. Attribute grammars are used in computer science to translate the text of a program source code into the computational operations it represents. By associating attributes with parts, modifying the value of these attributes using rules that describe the structure of DNA sequences, and using a multi-pass compilation process, it is possible to translate DNA sequences into molecular interaction network models. These capabilities are illustrated by simple example grammars expressing how gene expression rates are dependent upon single or multiple parts. The translation process is validated by systematically generating, translating, and simulating the phenotype of all the sequences in the design space generated by a small library of genetic parts. Attribute grammars represent a flexible framework connecting parts with models of biological function. They will be instrumental for building mathematical models of libraries of genetic constructs synthesized to characterize the function of genetic parts. This formalism is also expected to provide a solid foundation for the development of computer assisted design applications for synthetic biology. PMID:19816554

Heritability estimates for Mycobacterium avium subspecies paratuberculosis status of German Holstein cows tested by fecal culture.

PubMed

Küpper, J; Brandt, H; Donat, K; Erhardt, G

2012-05-01

The objective of this study was to estimate genetic manifestation of Mycobacterium avium ssp. paratuberculosis (MAP) infection in German Holstein cows. Incorporated into this study were 11,285 German Holstein herd book cows classified as MAP-positive and MAP-negative animals using fecal culture results and originating from 15 farms in Thuringia, Germany involved in a paratuberculosis voluntary control program from 2008 to 2009. The frequency of MAP-positive animals per farm ranged from 2.7 to 67.6%. The fixed effects of farm and lactation number had a highly significant effect on MAP status. An increase in the frequency of positive animals from the first to the third lactation could be observed. Threshold animal and sire models with sire relationship were used as statistical models to estimate genetic parameters. Heritability estimates of fecal culture varied from 0.157 to 0.228. To analyze the effect of prevalence on genetic parameter estimates, the total data set was divided into 2 subsets of data into farms with prevalence rates below 10% and those above 10%. The data set with prevalence above 10% show higher heritability estimates in both models compared with the data set with prevalence below 10%. For all data sets, the sire model shows higher heritabilities than the equivalent animal model. This study demonstrates that genetic variation exists in dairy cattle for paratuberculosis infection susceptibility and furthermore, leads to the conclusion that MAP detection by fecal culture shows a higher genetic background than ELISA test results. In conclusion, fecal culture seems to be a better trait to control the disease, as well as an appropriate feature for further genomic analyses to detect MAP-associated chromosome regions. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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

PubMed

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

2018-02-01

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

Estimating black bear population density and genetic diversity at Tensas River, Louisiana using microsatellite DNA markers

USGS Publications Warehouse

Boersen, Mark R.; Clark, Joseph D.; King, Tim L.

2003-01-01

The Recovery Plan for the federally threatened Louisiana black bear (Ursus americanus luteolus) mandates that remnant populations be estimated and monitored. In 1999 we obtained genetic material with barbed-wire hair traps to estimate bear population size and genetic diversity at the 329-km2 Tensas River Tract, Louisiana. We constructed and monitored 122 hair traps, which produced 1,939 hair samples. Of those, we randomly selected 116 subsamples for genetic analysis and used up to 12 microsatellite DNA markers to obtain multilocus genotypes for 58 individuals. We used Program CAPTURE to compute estimates of population size using multiple mark-recapture models. The area of study was almost entirely circumscribed by agricultural land, thus the population was geographically closed. Also, study-area boundaries were biologically discreet, enabling us to accurately estimate population density. Using model Chao Mh to account for possible effects of individual heterogeneity in capture probabilities, we estimated the population size to be 119 (SE=29.4) bears, or 0.36 bears/km2. We were forced to examine a substantial number of loci to differentiate between some individuals because of low genetic variation. Despite the probable introduction of genes from Minnesota bears in the 1960s, the isolated population at Tensas exhibited characteristics consistent with inbreeding and genetic drift. Consequently, the effective population size at Tensas may be as few as 32, which warrants continued monitoring or possibly genetic augmentation.

Which BRCA genetic testing programs are ready for implementation in health care? A systematic review of economic evaluations.

PubMed

D'Andrea, Elvira; Marzuillo, Carolina; De Vito, Corrado; Di Marco, Marco; Pitini, Erica; Vacchio, Maria Rosaria; Villari, Paolo

2016-12-01

There is considerable evidence regarding the efficacy and effectiveness of BRCA genetic testing programs, but whether they represent good use of financial resources is not clear. Therefore, we aimed to identify the main health-care programs for BRCA testing and to evaluate their cost-effectiveness. We performed a systematic review of full economic evaluations of health-care programs involving BRCA testing. Nine economic evaluations were included, and four main categories of BRCA testing programs were identified: (i) population-based genetic screening of individuals without cancer, either comprehensive or targeted based on ancestry; (ii) family history (FH)-based genetic screening, i.e., testing individuals without cancer but with FH suggestive of BRCA mutation; (iii) familial mutation (FM)-based genetic screening, i.e., testing individuals without cancer but with known familial BRCA mutation; and (iv) cancer-based genetic screening, i.e., testing individuals with BRCA-related cancers. Currently BRCA1/2 population-based screening represents good value for the money among Ashkenazi Jews only. FH-based screening is potentially very cost-effective, although further studies that include costs of identifying high-risk women are needed. There is no evidence of cost-effectiveness for BRCA screening of all newly diagnosed cases of breast/ovarian cancers followed by cascade testing of relatives, but programs that include tools for identifying affected women at higher risk for inherited forms are promising. Cost-effectiveness is highly sensitive to the cost of BRCA1/2 testing.Genet Med 18 12, 1171-1180.

Genetic architecture of sex determination in fish: applications to sex ratio control in aquaculture

PubMed Central

Martínez, Paulino; Viñas, Ana M.; Sánchez, Laura; Díaz, Noelia; Ribas, Laia; Piferrer, Francesc

2014-01-01

Controlling the sex ratio is essential in finfish farming. A balanced sex ratio is usually good for broodstock management, since it enables to develop appropriate breeding schemes. However, in some species the production of monosex populations is desirable because the existence of sexual dimorphism, primarily in growth or first time of sexual maturation, but also in color or shape, can render one sex more valuable. The knowledge of the genetic architecture of sex determination (SD) is convenient for controlling sex ratio and for the implementation of breeding programs. Unlike mammals and birds, which show highly conserved master genes that control a conserved genetic network responsible for gonad differentiation (GD), a huge diversity of SD mechanisms has been reported in fish. Despite theory predictions, more than one gene is in many cases involved in fish SD and genetic differences have been observed in the GD network. Environmental factors also play a relevant role and epigenetic mechanisms are becoming increasingly recognized for the establishment and maintenance of the GD pathways. Although major genetic factors are frequently involved in fish SD, these observations strongly suggest that SD in this group resembles a complex trait. Accordingly, the application of quantitative genetics combined with genomic tools is desirable to address its study and in fact, when applied, it has frequently demonstrated a multigene trait interacting with environmental factors in model and cultured fish species. This scenario has notable implications for aquaculture and, depending upon the species, from chromosome manipulation or environmental control techniques up to classical selection or marker assisted selection programs, are being applied. In this review, we selected four relevant species or fish groups to illustrate this diversity and hence the technologies that can be used by the industry for the control of sex ratio: turbot and European sea bass, two reference species of the European aquaculture, and salmonids and tilapia, representing the fish for which there are well established breeding programs. PMID:25324858

New experimental models of skin homeostasis and diseases.

PubMed

Larcher, F; Espada, J; Díaz-Ley, B; Jaén, P; Juarranz, A; Quintanilla, M

2015-01-01

Homeostasis, whose regulation at the molecular level is still poorly understood, is intimately related to the functions of epidermal stem cells. Five research groups have been brought together to work on new in vitro and in vivo skin models through the SkinModel-CM program, under the auspices of the Spanish Autonomous Community of Madrid. This project aims to analyze the functions of DNA methyltransferase 1, endoglin, and podoplanin in epidermal stem cell activity, homeostasis, and skin cancer. These new models include 3-dimensional organotypic cultures, immunodeficient skin-humanized mice, and genetically modified mice. Another aim of the program is to use skin-humanized mice to model dermatoses such as Gorlin syndrome and xeroderma pigmentosum in order to optimize new protocols for photodynamic therapy. Copyright © 2013 Elsevier España, S.L.U. and AEDV. All rights reserved.

Genetic Parallel Programming: design and implementation.

PubMed

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

2006-01-01

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

Application of GA package in functional packaging

NASA Astrophysics Data System (ADS)

Belousova, D. A.; Noskova, E. E.; Kapulin, D. V.

2018-05-01

The approach to application program for the task of configuration of the elements of the commutation circuit for design of the radio-electronic equipment on the basis of the genetic algorithm is offered. The efficiency of the used approach for commutation circuits with different characteristics for computer-aided design on radio-electronic manufacturing is shown. The prototype of the computer-aided design subsystem on the basis of a package GA for R with a set of the general functions for optimization of multivariate models is programmed.

Genetic data simulators and their applications: an overview

PubMed Central

Peng, Bo; Chen, Huann-Sheng; Mechanic, Leah E.; Racine, Ben; Clarke, John; Gillanders, Elizabeth; Feuer, Eric J.

2016-01-01

Computer simulations have played an indispensable role in the development and application of statistical models and methods for genetic studies across multiple disciplines. The need to simulate complex evolutionary scenarios and pseudo-datasets for various studies has fueled the development of dozens of computer programs with varying reliability, performance, and application areas. To help researchers compare and choose the most appropriate simulators for their studies, we have created the Genetic Simulation Resources (GSR) website, which allows authors of simulation software to register their applications and describe them with more than 160 defined attributes. This article summarizes the properties of 93 simulators currently registered at GSR and provides an overview of the development and applications of genetic simulators. Unlike other review articles that address technical issues or compare simulators for particular application areas, we focus on software development, maintenance, and features of simulators, often from a historical perspective. Publications that cite these simulators are used to summarize both the applications of genetic simulations and the utilization of simulators. PMID:25504286

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

ERIC Educational Resources Information Center

Bachmann, B. J.; And Others

1973-01-01

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

Stochastic dynamics of genetic broadcasting networks

NASA Astrophysics Data System (ADS)

Potoyan, Davit; Wolynes, Peter

The complex genetic programs of eukaryotic cells are often regulated by key transcription factors occupying or clearing out of a large number of genomic locations. Orchestrating the residence times of these factors is therefore important for the well organized functioning of a large network. The classic models of genetic switches sidestep this timing issue by assuming the binding of transcription factors to be governed entirely by thermodynamic protein-DNA affinities. Here we show that relying on passive thermodynamics and random release times can lead to a ''time-scale crisis'' of master genes that broadcast their signals to large number of binding sites. We demonstrate that this ''time-scale crisis'' can be resolved by actively regulating residence times through molecular stripping. We illustrate these ideas by studying the stochastic dynamics of the genetic network of the central eukaryotic master regulator NFκB which broadcasts its signals to many downstream genes that regulate immune response, apoptosis etc.

The Collaborative Cross at Oak Ridge National Laboratory: developing a powerful resource for systems genetics

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

Chesler, Elissa J; Branstetter, Lisa R; Churchill, Gary A

2008-01-01

Complex traits and disease co-morbidity in humans and in model organisms are the result of naturally occurring polymorphisms that interact with each other and with the environment. To ensure the availability of the resources needed to investigate biomolecular networks and ultimately systems level phenotypes, we have initiated breeding of a new genetic reference population of mice, the Collaborative Cross. This population has been designed to optimally support systems genetics analysis. Its novel and important features include high levels of genetic diversity, a large population size to ensure sufficient power in high-dimensional studies, and high mapping precision through accumulation of independentmore » recombination events. Implementation of the Collaborative Cross has been in progress at the Oak Ridge National Laboratory (ORNL) since May 2005. This is achieved through a software assisted breeding program with fully traceable lineages, performed in a uniform environment. Currently, there are 650 lines in production with almost 200 lines over seven generations of inbreeding. Retired breeders enter a high-throughput phenotyping protocol and DNA samples are banked for analysis of recombination history, allele loss, and population structure. Herein we present a progress report of the Collaborative Cross breeding program at ORNL and a description of the kinds of investigations that this resource will support.« less

Cultural differences define diagnosis and genomic medicine practice: implications for undiagnosed diseases program in China.

PubMed

Duan, Xiaohong; Markello, Thomas; Adams, David; Toro, Camilo; Tifft, Cynthia; Gahl, William A; Boerkoel, Cornelius F

2013-09-01

Despite the current acceleration and increasing leadership of Chinese genetics research, genetics and its clinical application have largely been imported to China from the Occident. Neither genetics nor the scientific reductionism underpinning its clinical application is integral to the traditional Chinese worldview. Given that disease concepts and their incumbent diagnoses are historically derived and culturally meaningful, we hypothesize that the cultural expectations of genetic diagnoses and medical genetics practice differ between the Occident and China. Specifically, we suggest that an undiagnosed diseases program in China will differ from the recently established Undiagnosed Diseases Program at the United States National Institutes of Health; a culturally sensitive concept will integrate traditional Chinese understanding of disease with the scientific reductionism of Occidental medicine.

Ideotype Development in Southern Pines: Rationale and Strategies for Overcoming Scale-Related Obstacles

Treesearch

Timothy A. Martin; Kurt H. Johnsen; Timothy L. White

2001-01-01

Indirect genetic selection for early growth and disease resistance of southern pines has proven remarkably successful over the past several decades. However, several benefits could be derived for southern pine breeding programs by incorporating ideotypes, conceptual models which explicitly describe plant phenotypic characteristics that are hypothesized to produce...

An Introduction to Computational Physics - 2nd Edition

NASA Astrophysics Data System (ADS)

Pang, Tao

2006-01-01

Preface to first edition; Preface; Acknowledgements; 1. Introduction; 2. Approximation of a function; 3. Numerical calculus; 4. Ordinary differential equations; 5. Numerical methods for matrices; 6. Spectral analysis; 7. Partial differential equations; 8. Molecular dynamics simulations; 9. Modeling continuous systems; 10. Monte Carlo simulations; 11. Genetic algorithm and programming; 12. Numerical renormalization; References; Index.

Hybrid striped bass national breeding program: research towards genetic improvement of a non-model species

USDA-ARS?s Scientific Manuscript database

The hybrid striped bass (HSB) farming industry at present relies almost totally on wild broodstock for annual production of larvae and fingerlings, and industry efforts to domesticate the parent species of the HSB (white bass: WB, Morone chrysops; striped bass: SB, M. saxatilis) have been fairly lim...

Hybrid striped bass National Breeding Program: Research towards genetic improvement of a non-model species

USDA-ARS?s Scientific Manuscript database

The hybrid striped bass (HSB) farming industry at present relies almost totally on wild broodstock for annual production of larvae and fingerlings, and industry efforts to domesticate the parent species of the HSB (white bass: WB, Morone chrysops; striped bass: SB, M. saxatilis) have been fairly lim...

Combining-Ability Determinations for Incomplete Mating Designs

Treesearch

E.B. Snyder

1975-01-01

It is shown how general combining ability values (GCA's) from cross-, open-, and self-pollinated progeny can be derived in a single analysis. Breeding values are employed to facilitate explaining genetic models of the expected family means and the derivation of the GCA's. A FORTRAN computer program also includes computation of specific combining ability...

Toward Genomics-Based Breeding in C3 Cool-Season Perennial Grasses.

PubMed

Talukder, Shyamal K; Saha, Malay C

2017-01-01

Most important food and feed crops in the world belong to the C3 grass family. The future of food security is highly reliant on achieving genetic gains of those grasses. Conventional breeding methods have already reached a plateau for improving major crops. Genomics tools and resources have opened an avenue to explore genome-wide variability and make use of the variation for enhancing genetic gains in breeding programs. Major C3 annual cereal breeding programs are well equipped with genomic tools; however, genomic research of C3 cool-season perennial grasses is lagging behind. In this review, we discuss the currently available genomics tools and approaches useful for C3 cool-season perennial grass breeding. Along with a general review, we emphasize the discussion focusing on forage grasses that were considered orphan and have little or no genetic information available. Transcriptome sequencing and genotype-by-sequencing technology for genome-wide marker detection using next-generation sequencing (NGS) are very promising as genomics tools. Most C3 cool-season perennial grass members have no prior genetic information; thus NGS technology will enhance collinear study with other C3 model grasses like Brachypodium and rice. Transcriptomics data can be used for identification of functional genes and molecular markers, i.e., polymorphism markers and simple sequence repeats (SSRs). Genome-wide association study with NGS-based markers will facilitate marker identification for marker-assisted selection. With limited genetic information, genomic selection holds great promise to breeders for attaining maximum genetic gain of the cool-season C3 perennial grasses. Application of all these tools can ensure better genetic gains, reduce length of selection cycles, and facilitate cultivar development to meet the future demand for food and fodder.

New scheduling rules for a dynamic flexible flow line problem with sequence-dependent setup times

NASA Astrophysics Data System (ADS)

Kia, Hamidreza; Ghodsypour, Seyed Hassan; Davoudpour, Hamid

2017-09-01

In the literature, the application of multi-objective dynamic scheduling problem and simple priority rules are widely studied. Although these rules are not efficient enough due to simplicity and lack of general insight, composite dispatching rules have a very suitable performance because they result from experiments. In this paper, a dynamic flexible flow line problem with sequence-dependent setup times is studied. The objective of the problem is minimization of mean flow time and mean tardiness. A 0-1 mixed integer model of the problem is formulated. Since the problem is NP-hard, four new composite dispatching rules are proposed to solve it by applying genetic programming framework and choosing proper operators. Furthermore, a discrete-event simulation model is made to examine the performances of scheduling rules considering four new heuristic rules and the six adapted heuristic rules from the literature. It is clear from the experimental results that composite dispatching rules that are formed from genetic programming have a better performance in minimization of mean flow time and mean tardiness than others.

Obesity-programmed mice are rescued by early genetic intervention

PubMed Central

Bumaschny, Viviana F.; Yamashita, Miho; Casas-Cordero, Rodrigo; Otero-Corchón, Verónica; de Souza, Flávio S.J.; Rubinstein, Marcelo; Low, Malcolm J.

2012-01-01

Obesity is a chronic metabolic disorder affecting half a billion people worldwide. Major difficulties in managing obesity are the cessation of continued weight loss in patients after an initial period of responsiveness and rebound to pretreatment weight. It is conceivable that chronic weight gain unrelated to physiological needs induces an allostatic regulatory state that defends a supranormal adipose mass despite its maladaptive consequences. To challenge this hypothesis, we generated a reversible genetic mouse model of early-onset hyperphagia and severe obesity by selectively blocking the expression of the proopiomelanocortin gene (Pomc) in hypothalamic neurons. Eutopic reactivation of central POMC transmission at different stages of overweight progression normalized or greatly reduced food intake in these obesity-programmed mice. Hypothalamic Pomc rescue also attenuated comorbidities such as hyperglycemia, hyperinsulinemia, and hepatic steatosis and normalized locomotor activity. However, effectiveness of treatment to normalize body weight and adiposity declined progressively as the level of obesity at the time of Pomc induction increased. Thus, our study using a novel reversible monogenic obesity model reveals the critical importance of early intervention for the prevention of subsequent allostatic overload that auto-perpetuates obesity. PMID:23093774

Parallel Markov chain Monte Carlo - bridging the gap to high-performance Bayesian computation in animal breeding and genetics.

PubMed

Wu, Xiao-Lin; Sun, Chuanyu; Beissinger, Timothy M; Rosa, Guilherme Jm; Weigel, Kent A; Gatti, Natalia de Leon; Gianola, Daniel

2012-09-25

Most Bayesian models for the analysis of complex traits are not analytically tractable and inferences are based on computationally intensive techniques. This is true of Bayesian models for genome-enabled selection, which uses whole-genome molecular data to predict the genetic merit of candidate animals for breeding purposes. In this regard, parallel computing can overcome the bottlenecks that can arise from series computing. Hence, a major goal of the present study is to bridge the gap to high-performance Bayesian computation in the context of animal breeding and genetics. Parallel Monte Carlo Markov chain algorithms and strategies are described in the context of animal breeding and genetics. Parallel Monte Carlo algorithms are introduced as a starting point including their applications to computing single-parameter and certain multiple-parameter models. Then, two basic approaches for parallel Markov chain Monte Carlo are described: one aims at parallelization within a single chain; the other is based on running multiple chains, yet some variants are discussed as well. Features and strategies of the parallel Markov chain Monte Carlo are illustrated using real data, including a large beef cattle dataset with 50K SNP genotypes. Parallel Markov chain Monte Carlo algorithms are useful for computing complex Bayesian models, which does not only lead to a dramatic speedup in computing but can also be used to optimize model parameters in complex Bayesian models. Hence, we anticipate that use of parallel Markov chain Monte Carlo will have a profound impact on revolutionizing the computational tools for genomic selection programs.

Parallel Markov chain Monte Carlo - bridging the gap to high-performance Bayesian computation in animal breeding and genetics

PubMed Central

2012-01-01

Background Most Bayesian models for the analysis of complex traits are not analytically tractable and inferences are based on computationally intensive techniques. This is true of Bayesian models for genome-enabled selection, which uses whole-genome molecular data to predict the genetic merit of candidate animals for breeding purposes. In this regard, parallel computing can overcome the bottlenecks that can arise from series computing. Hence, a major goal of the present study is to bridge the gap to high-performance Bayesian computation in the context of animal breeding and genetics. Results Parallel Monte Carlo Markov chain algorithms and strategies are described in the context of animal breeding and genetics. Parallel Monte Carlo algorithms are introduced as a starting point including their applications to computing single-parameter and certain multiple-parameter models. Then, two basic approaches for parallel Markov chain Monte Carlo are described: one aims at parallelization within a single chain; the other is based on running multiple chains, yet some variants are discussed as well. Features and strategies of the parallel Markov chain Monte Carlo are illustrated using real data, including a large beef cattle dataset with 50K SNP genotypes. Conclusions Parallel Markov chain Monte Carlo algorithms are useful for computing complex Bayesian models, which does not only lead to a dramatic speedup in computing but can also be used to optimize model parameters in complex Bayesian models. Hence, we anticipate that use of parallel Markov chain Monte Carlo will have a profound impact on revolutionizing the computational tools for genomic selection programs. PMID:23009363

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

Steinhaus, K.A.; Bennett, R.L.; Resta, R.G.

To determine consistency in usage of pedigree symbols by genetics professionals, we reviewed pedigrees printed in 10 human genetic and medical journals and 24 medical genetics textbooks. We found no consistent symbolization for common situations such as pregnancy, spontaneous abortion, death, or test results. Inconsistency in pedigree design can create difficulties in the interpretation of family studies and detract from the pedigree`s basic strength of simple and accurate communication of medical information. We recommend the development of standard pedigree symbols, and their incorporation into genetic publications, professional genetics training programs, pedigree software programs, and genetic board examinations. 5 refs., 11more » figs., 2 tabs.« less

Unraveling the mechanisms of synapse formation and axon regeneration: the awesome power of C. elegans genetics.

PubMed

Jin, YiShi

2015-11-01

Since Caenorhabditis elegans was chosen as a model organism by Sydney Brenner in 1960's, genetic studies in this organism have been instrumental in discovering the function of genes and in deciphering molecular signaling network. The small size of the organism and the simple nervous system enable the complete reconstruction of the first connectome. The stereotypic developmental program and the anatomical reproducibility of synaptic connections provide a blueprint to dissect the mechanisms underlying synapse formation. Recent technological innovation using laser surgery of single axons and in vivo imaging has also made C. elegans a new model for axon regeneration. Importantly, genes regulating synaptogenesis and axon regeneration are highly conserved in function across animal phyla. This mini-review will summarize the main approaches and the key findings in understanding the mechanisms underlying the development and maintenance of the nervous system. The impact of such findings underscores the awesome power of C. elegans genetics.

Direct-to-patient BRCA1 testing: the Twoj Styl experience.

PubMed

Gronwald, Jacek; Huzarski, Tomasz; Byrski, Tomasz; Debniak, Tadeusz; Metcalfe, Kelly; Narod, Steven A; Lubiński, Jan

2006-12-01

Ideally, a genetic screening program for cancer should offer testing to all women who qualify, and who wish to participate, and who might benefit from the test. As the number of preventive options for women at high risk for hereditary breast cancer expands, the demand for testing increases. However, many women do not have ready access to testing because of cost, and many others have not been recognized by their physicians to be candidates for testing. It is possible to increase women's awareness about hereditary cancer through the popular press. Genetic testing was offered to 5000 Polish women through an announcement placed in a popular women's magazine (Twoj Styl) in October 2001. A total of 5024 women who qualified received a free genetic test for three mutations in BRCA1 which are common in Poland. Out of these, 198 women (3.9%) were found to carry a BRCA1 mutation. The overall cost per mutation detected was 630 US dollars--approximately 50-100 times less than the equivalent cost in North America. Genetic counseling was offered to women with a positive test or with a significant family history of breast or ovarian cancer. The great majority of women who took part in the program expressed a high degree of satisfaction and after one year approximately two-thirds of identified mutation carriers had complied with our recommendations for breast cancer screening. We found this model of genetic testing and delivery of genetic information to be very efficient in a population in which founder mutations predominate. There is a need for similar studies in other populations.

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

ERIC Educational Resources Information Center

Dewhurst, D. G.; And Others

1989-01-01

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

Cancer Genetics and Signaling | Center for Cancer Research

Cancer.gov

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

Multidisciplinary research program directed toward utilization of solar energy through bioconversion of renewable resources

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

Not Available

1980-07-01

Progress is reported in this multidisciplinary research program. Genetic selection of superior trees, physiological basis of vigor, tissue culture systems leading to cloning of diploid and haploid cell lines are discussed in the Program A report. The physiological basis of enhanced oleoresin formation in southern pines when treated with sublethal concentrations of the herbicide paraquat was investigated in Program B. In Program C, metabolic changes in the stems of slash pine, in vivo, after application with paraquat were determined. The use of phdoem and xylem tissue slices as a laboratory model for studying paraquat associated- and normal-terpene synthesis in pinesmore » is discussed. The biochemistry and physiology of methane formation from cellulose during anaerobic fermentation are discussed in the Program D report. (DMC)« less

Do-it-yourself statistics: A computer-assisted likelihood approach to analysis of data from genetic crosses.

PubMed Central

Robbins, L G

2000-01-01

Graduate school programs in genetics have become so full that courses in statistics have often been eliminated. In addition, typical introductory statistics courses for the "statistics user" rather than the nascent statistician are laden with methods for analysis of measured variables while genetic data are most often discrete numbers. These courses are often seen by students and genetics professors alike as largely irrelevant cookbook courses. The powerful methods of likelihood analysis, although commonly employed in human genetics, are much less often used in other areas of genetics, even though current computational tools make this approach readily accessible. This article introduces the MLIKELY.PAS computer program and the logic of do-it-yourself maximum-likelihood statistics. The program itself, course materials, and expanded discussions of some examples that are only summarized here are available at http://www.unisi. it/ricerca/dip/bio_evol/sitomlikely/mlikely.h tml. PMID:10628965

Genetic counseling for beta-thalassemia trait following health screening in a health maintenance organization: comparison of programmed and conventional counseling.

PubMed Central

Fisher, L; Rowley, P T; Lipkin, M

1981-01-01

Providing adequate counseling of patients identified in genetic screening programs is a major responsibility and expense. Adults in a health maintenance organization, unselected for interest, were screened for beta-thalassemia trait as part of preventive health care. Counseling was provided by either a trained physician (conventional counseling) or by a videotape containing the same information followed by an opportunity to question a trained physician (programmed counseling). Immediately before and after counseling, knowledge of thalassemia, knowledge of genetics, and mood change were assessed by questionnaire. Comparable mood changes and similar learning about thalassemia and genetics occurred with both counseling methods. Thus, as judged by immediate effects on knowledge and mood, videotaped instruction can greatly reduce professional time required for genetic counseling and facilitate the incorporation of genetic screening into primary health care. PMID:7325162

Genetic Programming for Automatic Hydrological Modelling

NASA Astrophysics Data System (ADS)

Chadalawada, Jayashree; Babovic, Vladan

2017-04-01

One of the recent challenges for the hydrologic research community is the need for the development of coupled systems that involves the integration of hydrologic, atmospheric and socio-economic relationships. This poses a requirement for novel modelling frameworks that can accurately represent complex systems, given, the limited understanding of underlying processes, increasing volume of data and high levels of uncertainity. Each of the existing hydrological models vary in terms of conceptualization and process representation and is the best suited to capture the environmental dynamics of a particular hydrological system. Data driven approaches can be used in the integration of alternative process hypotheses in order to achieve a unified theory at catchment scale. The key steps in the implementation of integrated modelling framework that is influenced by prior understanding and data, include, choice of the technique for the induction of knowledge from data, identification of alternative structural hypotheses, definition of rules, constraints for meaningful, intelligent combination of model component hypotheses and definition of evaluation metrics. This study aims at defining a Genetic Programming based modelling framework that test different conceptual model constructs based on wide range of objective functions and evolves accurate and parsimonious models that capture dominant hydrological processes at catchment scale. In this paper, GP initializes the evolutionary process using the modelling decisions inspired from the Superflex framework [Fenicia et al., 2011] and automatically combines them into model structures that are scrutinized against observed data using statistical, hydrological and flow duration curve based performance metrics. The collaboration between data driven and physical, conceptual modelling paradigms improves the ability to model and manage hydrologic systems. Fenicia, F., D. Kavetski, and H. H. Savenije (2011), Elements of a flexible approach for conceptual hydrological modeling: 1. Motivation and theoretical development, Water Resources Research, 47(11).

Developmental programming of growth: genetic variant in GH2 gene encoding placental growth hormone contributes to adult height determination.

PubMed

Timasheva, Y; Putku, M; Kivi, R; Kožich, V; Männik, J; Laan, M

2013-11-01

Given the physiological role of placental growth hormone (PGH) during intrauterine development and growth, genetic variation in the coding Growth hormone 2 (GH2) gene may modulate developmental programming of adult stature. Two major GH2 variants were described worldwide, determined by single polymorphism (rs2006123; c.171 + 50C > A). We sought to study whether GH2 variants may contribute to adult anthropometric measurements. Genotyping of GH2 SNP rs2006123 by RFLP, testing its genetic association with adult height and Body Mass Index (BMI) by linear regression analysis, and combining the results of three individual study samples in meta-analysis. HYPEST (Estonia), n = 1464 (506 men/958 women), CADCZ (Czech), n = 871 (518/353); UFA (Bashkortostan), n = 954 (655/299); meta-analysis, n = 3289 (1679/1610). Meta-analysis across HYPEST, CADCZ and UFA samples (n = 3289) resulted in significant association of GH2 rs2006123 with height (recessive model: AA-homozygote effect: beta (SE) = 1.26 (0.46), P = 5.90 × 10⁻³; additive model: A-allele effect: beta (SE) = 0.45 (0.18), P = 1.40 × 10⁻²). Among men (n = 1679), the association of the A-allele with taller stature remained significant after multiple-testing correction (additive effect: beta = 0.86 (0.28), P = 1.83 × 10⁻³). No association was detected with BMI. Notably, rs2006123 was in strong LD (r² ≥ 0.87) with SNPs significantly associated with height (rs2665838, rs7209435, rs11658329) and mapped near GH2 in three independent meta-analyses of GWA studies. This is the first study demonstrating a link between a placental gene variant and programming of growth potential in adulthood. The detected association between PGH encoding GH2 and adult height promotes further research on the role of placental genes in prenatal programming of human metabolism. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

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

PubMed

Frank, Margaret H; Scanlon, Michael J

2015-02-01

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

Developmental Etiologies of Alcohol Use and Their Relations to Parent and Peer Influences Over Adolescence and Young Adulthood: A Genetically Informed Approach.

PubMed

Deutsch, Arielle R; Wood, Phillip K; Slutske, Wendy S

2017-12-01

Distinct changes in alcohol use etiologies occur during adolescence and young adulthood. Additionally, measured environments known to influence alcohol use such as peers and parenting practice can interact or be associated with this genetic influence. However, change in genetic and environmental influences over age, as well as how associations with measured environments change over age, is understudied. The National Longitudinal Study of Adolescent Health (Add Health) sibling subsample was used to examine data-driven biometric models of alcohol use over ages 13 to 27. Associations between friends' drinking, parental autonomy granting, and maternal closeness were also examined. The best-fitting model included a 5-factor model consisting of early (ages 13 to 20) and overall (ages 13 to 27) additive genetic and unique environmental factors, as well as 1 overall common environment factor. The overall additive genetic factor and the early unique environment factor explained the preponderance of mean differences in the alcohol use over this portion of the life span. The most important factors explaining variance attributed to alcohol use changed over age. Additionally, friend use had the strongest associations with genetic and environmental factors at all ages, while parenting practices had almost no associations at any age. These results supplement previous studies indicating changes in genetic and environmental influences in alcohol use over adolescence and adulthood. However, prior research suggesting that constraining exogenous predictors of genetic and environmental factors to have effects of the same magnitude across age overlooks the differential role of factors associated with alcohol use during adolescence. Consonant with previous research, friend use appears to have a more pervasive influence on alcohol use than parental influence during this age. Interventions and prevention programs geared toward reducing alcohol use in younger populations may benefit from focus on peer influence. Copyright © 2017 by the Research Society on Alcoholism.

A novel recruitment message to increase enrollment into a smoking cessation treatment program: preliminary results from a randomized trial.

PubMed

Schnoll, Robert A; Cappella, Joseph; Lerman, Caryn; Pinto, Angela; Patterson, Freda; Wileyto, E Paul; Bigman, Cabral; Leone, Frank

2011-12-01

Most smokers do not utilize approved interventions for nicotine dependence, reducing the probability of cessation. Smoking cessation programs typically use recruitment messages emphasizing the health threats of smoking. Augmenting this threat message by describing the genetic aspects of nicotine addiction may enhance enrollment into a cessation program. During telephone recruitment, 125 treatment-seeking smokers were randomized to receive by phone either a standard threat message or a threat plus genetic prime message and were offered open-label varenicline and counseling. There was a greater rate of enrollment into the cessation program for the threat plus genetic prime participants (51.7%) versus the threat-only participants (37.7%; p = .03). Smokers who self-identified from racial/ethnic minority groups were less likely to enroll in the cessation program (p = .01) versus smokers who self-identified as Caucasian. These preliminary data suggest that a simple, affordable, and transportable communication approach enhances enrollment of smokers into a smoking cessation program. A larger clinical trial to evaluate a genetic prime message for improving recruitment into smoking cessation programs is warranted.

Descriptive survey of Summer Genetics Institute nurse graduates in the USA.

PubMed

Hickey, Kathleen T; Sciacca, Robert R; McCarthy, Mary S

2013-03-01

The purpose of this study was to describe the clinical, research, educational, and professional activities that nurses are engaged in following participation in a 2 month intramural genetics training program. An online survey was administered in 2010 to graduates of the program sponsored by the US National Institute of Nursing Research from 2000 to 2009, in Bethesda, Maryland, USA. The electronic, voluntary survey was sent to 189 graduates via email. The survey included demographic characteristics, educational preparation, professional roles and responsibilities, and attitudes about genetic testing and privacy issues. Of the 95 graduates responding to the survey, 74% had doctorates and 70% were advanced practice nurses. All respondents reported incorporating genetics knowledge into daily clinical, academic, or research practices since completing the program, with 72% reporting being involved in genetically-focused research (52% with research funding), 32% incorporating genetics into patient care, and 79% providing genetics education. Respondents working in a hospital setting or academic institution were more likely to desire additional training in genetics. National Institute of Nursing Research graduates have successfully integrated genomics into a variety of nursing practices. © 2012 Wiley Publishing Asia Pty Ltd.

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

PubMed

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

2009-10-15

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

Quantitative trait nucleotide analysis using Bayesian model selection.

PubMed

Blangero, John; Goring, Harald H H; Kent, Jack W; Williams, Jeff T; Peterson, Charles P; Almasy, Laura; Dyer, Thomas D

2005-10-01

Although much attention has been given to statistical genetic methods for the initial localization and fine mapping of quantitative trait loci (QTLs), little methodological work has been done to date on the problem of statistically identifying the most likely functional polymorphisms using sequence data. In this paper we provide a general statistical genetic framework, called Bayesian quantitative trait nucleotide (BQTN) analysis, for assessing the likely functional status of genetic variants. The approach requires the initial enumeration of all genetic variants in a set of resequenced individuals. These polymorphisms are then typed in a large number of individuals (potentially in families), and marker variation is related to quantitative phenotypic variation using Bayesian model selection and averaging. For each sequence variant a posterior probability of effect is obtained and can be used to prioritize additional molecular functional experiments. An example of this quantitative nucleotide analysis is provided using the GAW12 simulated data. The results show that the BQTN method may be useful for choosing the most likely functional variants within a gene (or set of genes). We also include instructions on how to use our computer program, SOLAR, for association analysis and BQTN analysis.

Genethics: project accountability via evaluation of teacher and student growth.

PubMed

Hendrix, J R; Mertens, T R

1992-10-01

Accountability through demonstrated learning is increasingly being demanded by agencies funding science education projects. For example, the National Science Foundation requires evidence of the educational impact of programs designed to increase the scientific understanding and competencies of teachers and their students. The purpose of this paper is to share our human genetics educational experiences and accountability model with colleagues interested in serving the genetics educational needs of in-service secondary school science teachers and their students. Our accountability model is facilitated through (1) identifying the educational needs of the population of teachers to be served, (2) articulating goals and measurable objectives to meet these needs, and (3) then designing and implementing pretest/posttest questions to measure whether the objectives have been achieved. Comparison of entry and exit levels of performance on a 50-item test showed that teacher-participants learned a statistically significant amount of genetics content in our NSF-funded workshops. Teachers, in turn, administered a 25-item pretest/posttest to their secondary school students, and collective data from 121 classrooms across the United States revealed statistically significant increases in student knowledge of genetics content. Methods describing our attempts to evaluate teachers' use of pedagogical techniques and bioethical decision-making skills are briefly addressed.

Mapping of epistatic quantitative trait loci in four-way crosses.

PubMed

He, Xiao-Hong; Qin, Hongde; Hu, Zhongli; Zhang, Tianzhen; Zhang, Yuan-Ming

2011-01-01

Four-way crosses (4WC) involving four different inbred lines often appear in plant and animal commercial breeding programs. Direct mapping of quantitative trait loci (QTL) in these commercial populations is both economical and practical. However, the existing statistical methods for mapping QTL in a 4WC population are built on the single-QTL genetic model. This simple genetic model fails to take into account QTL interactions, which play an important role in the genetic architecture of complex traits. In this paper, therefore, we attempted to develop a statistical method to detect epistatic QTL in 4WC population. Conditional probabilities of QTL genotypes, computed by the multi-point single locus method, were used to sample the genotypes of all putative QTL in the entire genome. The sampled genotypes were used to construct the design matrix for QTL effects. All QTL effects, including main and epistatic effects, were simultaneously estimated by the penalized maximum likelihood method. The proposed method was confirmed by a series of Monte Carlo simulation studies and real data analysis of cotton. The new method will provide novel tools for the genetic dissection of complex traits, construction of QTL networks, and analysis of heterosis.

A suppression hierarchy among competing motor programs drives sequential grooming in Drosophila

PubMed Central

Seeds, Andrew M; Ravbar, Primoz; Chung, Phuong; Hampel, Stefanie; Midgley, Frank M; Mensh, Brett D; Simpson, Julie H

2014-01-01

Motor sequences are formed through the serial execution of different movements, but how nervous systems implement this process remains largely unknown. We determined the organizational principles governing how dirty fruit flies groom their bodies with sequential movements. Using genetically targeted activation of neural subsets, we drove distinct motor programs that clean individual body parts. This enabled competition experiments revealing that the motor programs are organized into a suppression hierarchy; motor programs that occur first suppress those that occur later. Cleaning one body part reduces the sensory drive to its motor program, which relieves suppression of the next movement, allowing the grooming sequence to progress down the hierarchy. A model featuring independently evoked cleaning movements activated in parallel, but selected serially through hierarchical suppression, was successful in reproducing the grooming sequence. This provides the first example of an innate motor sequence implemented by the prevailing model for generating human action sequences. DOI: http://dx.doi.org/10.7554/eLife.02951.001 PMID:25139955

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

PubMed

García-Sancho, Miguel

2012-03-01

This paper argues that the history of the computer, of the practice of computation and of the notions of 'data' and 'programme' are essential for a critical account of the emergence and implications of data-driven research. In order to show this, I focus on the transition that the investigations on the worm C. elegans experienced in the Laboratory of Molecular Biology of Cambridge (UK). Throughout the 1980s, this research programme evolved from a study of the genetic basis of the worm's development and behaviour to a DNA mapping and sequencing initiative. By examining the changing computing technologies which were used at the Laboratory, I demonstrate that by the time of this transition researchers shifted from modelling the worm's genetic programme on a mainframe apparatus to writing minicomputer programs aimed at providing map and sequence data which was then circulated to other groups working on the genetics of C. elegans. The shift in the worm research should thus not be simply explained in the application of computers which transformed the project from hypothesis-driven to a data-intensive endeavour. The key factor was rather a historically specific technology-in-house and easy programmable minicomputers-which redefined the way of achieving the project's long-standing goal, leading the genetic programme to co-evolve with the practices of data production and distribution. Copyright © 2011 Elsevier Ltd. All rights reserved.

Genetic Evolution of Shape-Altering Programs for Supersonic Aerodynamics

NASA Technical Reports Server (NTRS)

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

2002-01-01

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

Understanding GINA and How GINA Affects Nurses.

PubMed

Delk, Kayla L

2015-11-01

The Genetic Information Nondiscrimination Act (GINA) is a federal law that became fully effective in 2009 and is intended to prevent employers and health insurers from discriminating against individuals based on their genetic or family history. The article discusses the sections of GINA, what information constitutes genetic information, who enforces GINA, and scenarios in which GINA does not apply. Also discussed are the instances in which an employer may request genetic information from employees, including wellness or genetic monitoring programs. Finally, the article offers a look at how GINA affects nurses who are administering wellness or genetic monitoring programs on behalf of employers. © 2015 The Author(s).

Experimental design for estimating unknown groundwater pumping using genetic algorithm and reduced order model

NASA Astrophysics Data System (ADS)

Ushijima, Timothy T.; Yeh, William W.-G.

2013-10-01

An optimal experimental design algorithm is developed to select locations for a network of observation wells that provide maximum information about unknown groundwater pumping in a confined, anisotropic aquifer. The design uses a maximal information criterion that chooses, among competing designs, the design that maximizes the sum of squared sensitivities while conforming to specified design constraints. The formulated optimization problem is non-convex and contains integer variables necessitating a combinatorial search. Given a realistic large-scale model, the size of the combinatorial search required can make the problem difficult, if not impossible, to solve using traditional mathematical programming techniques. Genetic algorithms (GAs) can be used to perform the global search; however, because a GA requires a large number of calls to a groundwater model, the formulated optimization problem still may be infeasible to solve. As a result, proper orthogonal decomposition (POD) is applied to the groundwater model to reduce its dimensionality. Then, the information matrix in the full model space can be searched without solving the full model. Results from a small-scale test case show identical optimal solutions among the GA, integer programming, and exhaustive search methods. This demonstrates the GA's ability to determine the optimal solution. In addition, the results show that a GA with POD model reduction is several orders of magnitude faster in finding the optimal solution than a GA using the full model. The proposed experimental design algorithm is applied to a realistic, two-dimensional, large-scale groundwater problem. The GA converged to a solution for this large-scale problem.

Origin and function of myofibroblasts in kidney fibrosis.

PubMed

LeBleu, Valerie S; Taduri, Gangadhar; O'Connell, Joyce; Teng, Yingqi; Cooke, Vesselina G; Woda, Craig; Sugimoto, Hikaru; Kalluri, Raghu

2013-08-01

Myofibroblasts are associated with organ fibrosis, but their precise origin and functional role remain unknown. We used multiple genetically engineered mice to track, fate map and ablate cells to determine the source and function of myofibroblasts in kidney fibrosis. Through this comprehensive analysis, we identified that the total pool of myofibroblasts is split, with 50% arising from local resident fibroblasts through proliferation. The nonproliferating myofibroblasts derive through differentiation from bone marrow (35%), the endothelial-to-mesenchymal transition program (10%) and the epithelial-to-mesenchymal transition program (5%). Specific deletion of Tgfbr2 in α-smooth muscle actin (αSMA)(+) cells revealed the importance of this pathway in the recruitment of myofibroblasts through differentiation. Using genetic mouse models and a fate-mapping strategy, we determined that vascular pericytes probably do not contribute to the emergence of myofibroblasts or fibrosis. Our data suggest that targeting diverse pathways is required to substantially inhibit the composite accumulation of myofibroblasts in kidney fibrosis.

Origin and Function of Myofibroblasts in Kidney Fibrosis

PubMed Central

LeBleu, Valerie S.; Taduri, Gangadhar; O’Connell, Joyce; Teng, Yingqi; Cooke, Vesselina G.; Woda, Craig; Sugimoto, Hikaru; Kalluri, Raghu

2014-01-01

Myofibroblasts are associated with organ fibrosis but their precise origin and functional role remain unknown. We employed multiple genetically engineered mice to track, fate-map and ablate cells to determine the source and function of myofibroblasts in kidney fibrosis. Such comprehensive analysis identified that the total pool of myofibroblasts is split, with 50% arising from local resident fibroblasts via proliferation. The non-proliferating myofibroblasts derive via differentiation from bone marrow (35%), endothelial to mesenchymal transition (EndMT) program (10%) and epithelial to mesenchymal transition (EMT) program (5%). Specific deletion of Tgfbr2 in αSMA+ cells revealed the importance of this pathway in recruitment of myofibroblasts via differentiation. Using genetic mouse models and fate-mapping strategy we determined that vascular pericytes likely do not contribute to the emergence of myofibroblasts or fibrosis. This study suggests that targeting diverse pathways is required to significantly inhibit composite accumulation of myofibroblasts in kidney fibrosis. PMID:23817022

Postdoctoral Fellow | Center for Cancer Research

Cancer.gov

Dr. St. Croix’s laboratory at the Mouse Cancer Genetics Program (MCGP), National Cancer Institute, USA has an open postdoctoral position. We seek a highly motivated, creative and bright individual to participate in a collaborative project that involves the targeting of tumor-associated stroma using T-cells engineered to express chimeric antigen receptors (CARs). The laboratory focuses on the characterization and exploitation of molecules associated with tumor angiogenesis. The successful candidate would be involved in developing, producing and characterizing new therapeutic antibodies and CARs that recognize cancer cells or its associated stroma, and preclinical testing of these agents using mouse tumor models. The tumor angiogenesis lab is located at the National Cancer Institute in Frederick with access to state-of-the-art facilities for antibody engineering, genomic analysis, pathology, and small animal imaging, among others. Detailed information about Dr. St. Croix’s research and publications can be accessed at https://ccr.cancer.gov/Mouse-Cancer-Genetics-Program/brad-st-croix.

Texture segmentation by genetic programming.

PubMed

Song, Andy; Ciesielski, Vic

2008-01-01

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

A genetically informative developmental study of the relationship between conduct disorder and peer deviance in males

PubMed Central

Kendler, K. S.; Jacobson, K.; Myers, J. M.; Eaves, L. J.

2014-01-01

Background Conduct disorder (CD) and peer deviance (PD) both powerfully predict future externalizing behaviors. Although levels of CD and PD are strongly correlated, the causal relationship between them has remained controversial and has not been examined by a genetically informative study. Method Levels of CD and PD were assessed in 746 adult male–male twin pairs at personal interview for ages 8–11, 12–14 and 15–17 years using a life history calendar. Model fitting was performed using the Mx program. Results The best-fit model indicated an active developmental relationship between CD and PD including forward transmission of both traits over time and strong causal relationships between CD and PD within time periods. The best-fit model indicated that the causal relationship for genetic risk factors was from CD to PD and was constant over time. For common environmental factors, the causal pathways ran from PD to CD and were stronger in earlier than later age periods. Conclusions A genetically informative model revealed causal pathways difficult to elucidate by other methods. Genes influence risk for CD, which, through social selection, impacts on the deviance of peers. Shared environment, through family and community processes, encourages or discourages adolescent deviant behavior, which, via social influence, alters risk for CD. Social influence is more important than social selection in childhood, but by late adolescence social selection becomes predominant. These findings have implications for prevention efforts for CD and associated externalizing disorders. PMID:17935643

A Web-Based Genetic Polymorphism Learning Approach for High School Students and Science Teachers

ERIC Educational Resources Information Center

Amenkhienan, Ehichoya; Smith, Edward J.

2006-01-01

Variation and polymorphism are concepts that are central to genetics and genomics, primary biological disciplines in which high school students and undergraduates require a solid foundation. From 1998 through 2002, a web-based genetics education program was developed for high school teachers and students. The program included an exercise on using…

Assessing the Effects of Tutorial and Edutainment Software Programs on Students' Achievements, Misconceptions and Attitudes towards Biology

ERIC Educational Resources Information Center

Kara, Yilmaz; Yesilyurt, Selami

2007-01-01

The purpose of this study was to investigate the effects of tutorial and edutainment software programs related to "genetic concepts" topic on student achievements, misconceptions and attitudes. An experimental research design including the genetic concepts achievement test (GAT), the genetic concept test (GCT) and biology attitude scale…

Race, Genetic West African Ancestry, and Prostate Cancer Prediction by PSA in Prospectively Screened High-Risk Men

PubMed Central

Giri, Veda N.; Egleston, Brian; Ruth, Karen; Uzzo, Robert G.; Chen, David Y.T.; Buyyounouski, Mark; Raysor, Susan; Hooker, Stanley; Torres, Jada Benn; Ramike, Teniel; Mastalski, Kathleen; Kim, Taylor Y.; Kittles, Rick

2008-01-01

Introduction “Race-specific” PSA needs evaluation in men at high-risk for prostate cancer (PCA) for optimizing early detection. Baseline PSA and longitudinal prediction for PCA was examined by self-reported race and genetic West African (WA) ancestry in the Prostate Cancer Risk Assessment Program, a prospective high-risk cohort. Materials and Methods Eligibility criteria are age 35–69 years, FH of PCA, African American (AA) race, or BRCA1/2 mutations. Biopsies have been performed at low PSA values (<4.0 ng/mL). WA ancestry was discerned by genotyping 100 ancestry informative markers. Cox proportional hazards models evaluated baseline PSA, self-reported race, and genetic WA ancestry. Cox models were used for 3-year predictions for PCA. Results 646 men (63% AA) were analyzed. Individual WA ancestry estimates varied widely among self-reported AA men. “Race-specific” differences in baseline PSA were not found by self-reported race or genetic WA ancestry. Among men with ≥ 1 follow-up visit (405 total, 54% AA), three-year prediction for PCA with a PSA of 1.5–4.0 ng/mL was higher in AA men with age in the model (p=0.025) compared to EA men. Hazard ratios of PSA for PCA were also higher by self-reported race (1.59 for AA vs. 1.32 for EA, p=0.04). There was a trend for increasing prediction for PCA with increasing genetic WA ancestry. Conclusions “Race-specific” PSA may need to be redefined as higher prediction for PCA at any given PSA in AA men. Large-scale studies are needed to confirm if genetic WA ancestry explains these findings to make progress in personalizing PCA early detection. PMID:19240249

DEM interpolation weight calculation modulus based on maximum entropy

NASA Astrophysics Data System (ADS)

Chen, Tian-wei; Yang, Xia

2015-12-01

There is negative-weight in traditional interpolation of gridding DEM, in the article, the principle of Maximum Entropy is utilized to analyze the model system which depends on modulus of space weight. Negative-weight problem of the DEM interpolation is researched via building Maximum Entropy model, and adding nonnegative, first and second order's Moment constraints, the negative-weight problem is solved. The correctness and accuracy of the method was validated with genetic algorithm in matlab program. The method is compared with the method of Yang Chizhong interpolation and quadratic program. Comparison shows that the volume and scaling of Maximum Entropy's weight is fit to relations of space and the accuracy is superior to the latter two.

From ecology to base pairs: nursing and genetic science.

PubMed

Williams, J K; Tripp-Reimer, T

2001-07-01

With the mapping of the human genome has come the opportunity for nursing research to explore topics of concern to the maintenance, restoration, and attainment of genetic-related health. Initially, nursing research on genetic topics originated primarily from physical anthropology and from a clinical, disease-focused perspective. Nursing research subsequently focused on psychosocial aspects of genetic conditions for individuals and their family members. As findings emerge from current human genome discovery, new programs of genetic nursing research are originating from a biobehavioral interface, ranging from the investigations of the influence of specific molecular changes on gene function to social/ethical issues of human health and disease. These initiatives reflect nursing's response to discoveries of gene mutations related to phenotypic expression in both clinical and community-based populations. Genetic research programs are needed that integrate or adapt theoretical and methodological advances in epidemiology, family systems, anthropology, and ethics with those from nursing. Research programs must address not only populations with a specific disease but also community-based genetic health care issues. As genetic health care practice evolves, so will opportunities for research by nurses who can apply genetic concepts and interventions to improve the health of the public. This article presents an analysis of the evolution of genetic nursing research and challengesfor the future.

Genetic Identity in Genebanks: Application of the SolCAP 12K SNP Array in Fingerprinting and Diversity Analysis in the Global In Trust Potato Collection.

PubMed

Ellis, David; Chavez, Oswaldo; Coombs, Joseph J; Soto, Julian V; Gomez, Rene; Douches, David S; Panta, Ana; Silvestre, Rocio; Anglin, Noelle Lynette

2018-05-24

Breeders rely on genetic integrity of material from genebanks, however, mislabeling and errors in original data can occur. Paired samples of original material and their in vitro counterparts from 250 diverse potato landrace accessions from the International Potato Center (CIP), were fingerprinted using the Infinium 12K V2 Potato Array to confirm genetic identity and evaluate genetic diversity. Diploid, triploid, and tetraploid accessions were included representing seven cultivated potato taxa (Hawkes, 1990). Fingerprints between mother field plants and in vitro clones, were used to evaluate identity, relatedness, and ancestry. Clones of the same accession grouped together, however eleven (4.4%) accessions were mismatches genetically. SNP genotypes were used to construct a phylogeny to evaluate inter- and intraspecific relationships and population structure. Data suggests that the triploids evaluated are genetically similar. STRUCTURE analysis identified several putative hybrids and suggests six populations with significant gene flow between. This study provides a model for genetic identity of plant genetic resources collections as mistakes in conservation of these collections and in genebanks is a reality and confirmed identity is critical for breeders and other users of these collections, as well as for quality management programs and to provide insights into the diversity of the accessions evaluated.

Genetic Diversity and Population Structure of Siberian apricot (Prunus sibirica L.) in China

PubMed Central

Li, Ming; Zhao, Zhong; Miao, Xingjun; Zhou, Jingjing

2014-01-01

The genetic diversity and population genetic structure of 252 accessions from 21 Prunus sibirica L. populations were investigated using 10 ISSR, SSR, and SRAP markers. The results suggest that the entire population has a relatively high level of genetic diversity, with populations HR and MY showing very high diversity. A low level of inter-population genetic differentiation and a high level of intra-population genetic differentiation was found, which is supported by a moderate level of gene flow, and largely attributable to the cross-pollination and self-incompatibility reproductive system. A STRUCTURE (model-based program) analysis revealed that the 21 populations can be divided into two main groups, mainly based on geographic differences and genetic exchanges. The entire wild Siberia apricot population in China could be divided into two subgroups, including 107 accessions in subgroup (SG) 1 and 147 accessions in SG 2. A Mantel test revealed a significant positive correlation between genetic and geographic distance matrices, and there was a very significant positive correlation among three marker datasets. Overall, we recommend a combination of conservation measures, with ex situ and in situ conservation that includes the construction of a core germplasm repository and the implement of in situ conservation for populations HR, MY, and ZY. PMID:24384840

Restoration over time and sustainability of Schinus terebinthifolius Raddi.

PubMed

Álvares-Carvalho, S V; Silva-Mann, R; Gois, I B; Melo, M F V; Oliveira, A S; Ferreira, R A; Gomes, L J

2017-05-31

The success of recovery programs on degraded areas is dependent on the genetic material to be used, which should present heterozygosity and genetic diversity in native and recovered populations. This study was carried out to evaluate the model efficiency to enable the recovery of a degraded area of the Lower São Francisco, Sergipe, Brazil. The target species for this study was Schinus terebinthifolius Raddi. Three populations were analyzed, the recovered area, seed-tree source population, and native tree population border established to the recovered area. The random amplified polymorphic DNA (RAPD) markers were used for diversity analysis. Genetic structure was estimated to evaluate the level of genetic variability existent in each population. There was no correlation between the spatial distribution and the genetic distances for all trees of the recovered area. The heterozygosity present in the recovered population was higher than the native tree population. The seed-tree source population presents genetic bottlenecks. Three clusters were suggested (ΔK = 3) with non-genetic structure. High intra-population genetic variability and inter-population differentiation are present. However, gene flow may also introduce potentially adaptive alleles in the populations of the recovered area, and the native population is necessary to ensure the sustainability and maintenance of the populations by allelic exchange.

2015 Army Science Planning and Strategy Meeting Series: Outcomes and Conclusions

DTIC Science & Technology

2017-12-21

modeling and nanoscale characterization tools to enable efficient design of hybridized manufacturing ; realtime, multiscale computational capability...to enable predictive analytics for expeditionary on-demand manufacturing • Discovery of design principles to enable programming advanced genetic...goals, significant research is needed to mature the fundamental materials science, processing and manufacturing sciences, design methodologies, data

Breed effects and genetic parameter estimates for calving difficulty and birth weight in a multi-breed population

USDA-ARS?s Scientific Manuscript database

Birth weight (BWT) and calving difficulty (CD) were recorded on 4,579 first parity females from the Germplasm Evaluation (GPE) program at the U.S. Meat Animal Research Center (USMARC). Both traits were analyzed using a bivariate animal model with direct and maternal effects. Calving difficulty was...

75 FR 21003 - National Toxicology Program (NTP); Office of Liaison, Policy and Review Meeting of the NTP Board...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-22

... appropriate animal and non-animal experimental models for mechanistic-based research, including genetically... is June 7, 2010, and for pre- registration to attend the meeting, including registering to present... Building at the NIEHS, 111 T.W. Alexander Drive, Research Triangle Park, NC 27709. Public comments on all...

Population genetics of commercial and feral honey bees in Western Australia.

PubMed

Chapman, Nadine C; Lim, Julianne; Oldroyd, Benjamin P

2008-04-01

Due to the introduction of exotic honey bee (Apis mellifera L.) diseases in the eastern states, the borders of the state of Western Australia were closed to the import of bees for breeding and other purposes > 25 yr ago. To provide genetically improved stock for the industry, a closed population breeding program was established that now provides stock for the majority of Western Australian beekeepers. Given concerns that inbreeding may have resulted from the closed population breeding structure, we assessed the genetic diversity within and between the breeding lines by using microsatellite and mitochondrial markers. We found that the breeding population still maintains considerable genetic diversity, despite 25 yr of selective breeding. We also investigated the genetic distance of the closed population breeding program to that of beekeepers outside of the program, and the feral Western Australian honey bee population. The feral population is genetically distinct from the closed population, but not from the genetic stock maintained by beekeepers outside of the program. The honey bees of Western Australia show three mitotypes, originating from two subspecies: Apis mellifera ligustica (mitotypes C1 and M7b) and Apis mellifera iberica (mitotype M6). Only mitotypes C1 and M6 are present in the commercial populations. The feral population contains all three mitotypes.

Mechanical models for the self-organization of tubular patterns.

PubMed

Guo, Chin-Lin

2013-01-01

Organogenesis, such as long tubule self-organization, requires long-range coordination of cell mechanics to arrange cell positions and to remodel the extracellular matrix. While the current mainstream in the field of tissue morphogenesis focuses primarily on genetics and chemical signaling, the influence of cell mechanics on the programming of patterning cues in tissue morphogenesis has not been adequately addressed. Here, we review experimental evidence and propose quantitative mechanical models by which cells can create tubular patterns.

Strategies for Selecting Crosses Using Genomic Prediction in Two Wheat Breeding Programs.

PubMed

Lado, Bettina; Battenfield, Sarah; Guzmán, Carlos; Quincke, Martín; Singh, Ravi P; Dreisigacker, Susanne; Peña, R Javier; Fritz, Allan; Silva, Paula; Poland, Jesse; Gutiérrez, Lucía

2017-07-01

The single most important decision in plant breeding programs is the selection of appropriate crosses. The ideal cross would provide superior predicted progeny performance and enough diversity to maintain genetic gain. The aim of this study was to compare the best crosses predicted using combinations of mid-parent value and variance prediction accounting for linkage disequilibrium (V) or assuming linkage equilibrium (V). After predicting the mean and the variance of each cross, we selected crosses based on mid-parent value, the top 10% of the progeny, and weighted mean and variance within progenies for grain yield, grain protein content, mixing time, and loaf volume in two applied wheat ( L.) breeding programs: Instituto Nacional de Investigación Agropecuaria (INIA) Uruguay and CIMMYT Mexico. Although the variance of the progeny is important to increase the chances of finding superior individuals from transgressive segregation, we observed that the mid-parent values of the crosses drove the genetic gain but the variance of the progeny had a small impact on genetic gain for grain yield. However, the relative importance of the variance of the progeny was larger for quality traits. Overall, the genomic resources and the statistical models are now available to plant breeders to predict both the performance of breeding lines per se as well as the value of progeny from any potential crosses. Copyright © 2017 Crop Science Society of America.

A comprehensive laboratory-based program for classification of variants of uncertain significance in hereditary cancer genes.

PubMed

Eggington, J M; Bowles, K R; Moyes, K; Manley, S; Esterling, L; Sizemore, S; Rosenthal, E; Theisen, A; Saam, J; Arnell, C; Pruss, D; Bennett, J; Burbidge, L A; Roa, B; Wenstrup, R J

2014-09-01

Genetic testing has the potential to guide the prevention and treatment of disease in a variety of settings, and recent technical advances have greatly increased our ability to acquire large amounts of genetic data. The interpretation of this data remains challenging, as the clinical significance of genetic variation detected in the laboratory is not always clear. Although regulatory agencies and professional societies provide some guidance regarding the classification, reporting, and long-term follow-up of variants, few protocols for the implementation of these guidelines have been described. Because the primary aim of clinical testing is to provide results to inform medical management, a variant classification program that offers timely, accurate, confident and cost-effective interpretation of variants should be an integral component of the laboratory process. Here we describe the components of our laboratory's current variant classification program (VCP), based on 20 years of experience and over one million samples tested, using the BRCA1/2 genes as a model. Our VCP has lowered the percentage of tests in which one or more BRCA1/2 variants of uncertain significance (VUSs) are detected to 2.1% in the absence of a pathogenic mutation, demonstrating how the coordinated application of resources toward classification and reclassification significantly impacts the clinical utility of testing. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A simple approach to lifetime learning in genetic programming-based symbolic regression.

PubMed

Azad, Raja Muhammad Atif; Ryan, Conor

2014-01-01

Genetic programming (GP) coarsely models natural evolution to evolve computer programs. Unlike in nature, where individuals can often improve their fitness through lifetime experience, the fitness of GP individuals generally does not change during their lifetime, and there is usually no opportunity to pass on acquired knowledge. This paper introduces the Chameleon system to address this discrepancy and augment GP with lifetime learning by adding a simple local search that operates by tuning the internal nodes of individuals. Although not the first attempt to combine local search with GP, its simplicity means that it is easy to understand and cheap to implement. A simple cache is added which leverages the local search to reduce the tuning cost to a small fraction of the expected cost, and we provide a theoretical upper limit on the maximum tuning expense given the average tree size of the population and show that this limit grows very conservatively as the average tree size of the population increases. We show that Chameleon uses available genetic material more efficiently by exploring more actively than with standard GP, and demonstrate that not only does Chameleon outperform standard GP (on both training and test data) over a number of symbolic regression type problems, it does so by producing smaller individuals and it works harmoniously with two other well-known extensions to GP, namely, linear scaling and a diversity-promoting tournament selection method.

Genetic network inference as a series of discrimination tasks.

PubMed

Kimura, Shuhei; Nakayama, Satoshi; Hatakeyama, Mariko

2009-04-01

Genetic network inference methods based on sets of differential equations generally require a great deal of time, as the equations must be solved many times. To reduce the computational cost, researchers have proposed other methods for inferring genetic networks by solving sets of differential equations only a few times, or even without solving them at all. When we try to obtain reasonable network models using these methods, however, we must estimate the time derivatives of the gene expression levels with great precision. In this study, we propose a new method to overcome the drawbacks of inference methods based on sets of differential equations. Our method infers genetic networks by obtaining classifiers capable of predicting the signs of the derivatives of the gene expression levels. For this purpose, we defined a genetic network inference problem as a series of discrimination tasks, then solved the defined series of discrimination tasks with a linear programming machine. Our experimental results demonstrated that the proposed method is capable of correctly inferring genetic networks, and doing so more than 500 times faster than the other inference methods based on sets of differential equations. Next, we applied our method to actual expression data of the bacterial SOS DNA repair system. And finally, we demonstrated that our approach relates to the inference method based on the S-system model. Though our method provides no estimation of the kinetic parameters, it should be useful for researchers interested only in the network structure of a target system. Supplementary data are available at Bioinformatics online.

The current state of genetic counseling and newborn screening: an interview with Megan Tucker

PubMed Central

Tucker, Megan

2017-01-01

Megan Tucker talks to Francesca Lake, Managing Editor: A certified genetic counselor for over 10 years, Megan is currently the director of the Indiana State University Genetic Counseling Graduate Program and the Genetic Counseling Clinic at Union Hospital (Terre Haute, IN, USA). She began her career split between the Center for Prenatal Diagnosis and the Medical Genetics and Neurodevelopmental Center at St Vincent Hospital (Indianapolis, IN, USA). During this time she was instrumental in both the development of the statewide Perinatal Loss Evaluation Program and a hospital protocol to ensure collection of cord blood to allow time to effectively genetically evaluate babies. Her current clinical focus is in cancer and psychiatric genetic counseling. PMID:28883988

Processing and population genetic analysis of multigenic datasets with ProSeq3 software.

PubMed

Filatov, Dmitry A

2009-12-01

The current tendency in molecular population genetics is to use increasing numbers of genes in the analysis. Here I describe a program for handling and population genetic analysis of DNA polymorphism data collected from multiple genes. The program includes a sequence/alignment editor and an internal relational database that simplify the preparation and manipulation of multigenic DNA polymorphism datasets. The most commonly used DNA polymorphism analyses are implemented in ProSeq3, facilitating population genetic analysis of large multigenic datasets. Extensive input/output options make ProSeq3 a convenient hub for sequence data processing and analysis. The program is available free of charge from http://dps.plants.ox.ac.uk/sequencing/proseq.htm.

The genetic basis of pectoralis major myopathies in modern broiler chicken lines

PubMed Central

Bailey, Richard A.; Watson, Kellie A.; Bilgili, S. F.; Avendano, Santiago

2015-01-01

This is the first report providing estimates of the genetic basis of breast muscle myopathies (BMM) and their relationship with growth and yield in broiler chickens. In addition, this paper addresses the hypothesis that genetic selection for increase breast yield has contributed to the onset of BMM. Data were analyzed from ongoing recording of BMM within the Aviagen breeding program. This study focused on three BMM: deep pectoral myopathy (DPM; binary trait), white striping (WS; 4 categories) and wooden breast (WB; 3 categories). Data from two purebred commercial broiler lines (A and B) were utilized providing greater than 40,000 meat quality records per line. The difference in selection history between these two lines has resulted in contrasting breast yield (BY): 29% for Line A and 21% for Line B. Data were analyzed to estimate genetic parameters using a multivariate animal model including six traits: body weight (BW), processing body weight (PW), BY, DPM, WB, and WS, in addition to the appropriate fixed effects and permanent environmental effect of the dam. Results indicate similar patterns of heritability and genetic correlations for the two lines. Heritabilities (h2) of BW, PW and BY ranged from 0.271–0.418; for DPM and WB h2 <0.1; and for WS h2 ≤0.338. Genetic correlations between the BMM and BW, PW, or BY were ≤0.132 in Line A and ≤0.248 in Line B. This paper demonstrates the polygenic nature of these traits and the low genetic relationships with BW, PW, and BY, which facilitates genetic improvement across all traits in a balanced breeding program. It also highlights the importance of understanding the environmental and/or management factors that contribute greater than 65% of the variance in the incidence of white striping of breast muscle and more than 90% of the variance of the incidence of wooden breast and deep pectoral myopathy in broiler chickens. PMID:26476091

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

PubMed

Moore, J H

1995-06-01

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

Aging in the colonial chordate, Botryllus schlosseri.

PubMed

Munday, Roma; Rodriguez, Delany; Di Maio, Alessandro; Kassmer, Susannah; Braden, Brian; Taketa, Daryl A; Langenbacher, Adam; De Tomaso, Anthony

2015-01-30

What mechanisms underlie aging? One theory, the wear-and-tear model, attributes aging to progressive deterioration in the molecular and cellular machinery which eventually lead to death through the disruption of physiological homeostasis. The second suggests that life span is genetically programmed, and aging may be derived from intrinsic processes which enforce a non-random, terminal time interval for the survivability of the organism. We are studying an organism that demonstrates both properties: the colonial ascidian, Botryllus schlosseri. Botryllus is a member of the Tunicata, the sister group to the vertebrates, and has a number of life history traits which make it an excellent model for studies on aging. First, Botryllus has a colonial life history, and grows by a process of asexual reproduction during which entire bodies, including all somatic and germline lineages, regenerate every week, resulting in a colony of genetically identical individuals. Second, previous studies of lifespan in genetically distinct Botryllus lineages suggest that a direct, heritable basis underlying mortality exists that is unlinked to reproductive effort and other life history traits. Here we will review recent efforts to take advantage of the unique life history traits of B. schlosseri and develop it into a robust model for aging research.

Prescriptive models to support decision making in genetics.

PubMed

Pauker, S G; Pauker, S P

1987-01-01

Formal prescriptive models can help patients and clinicians better understand the risks and uncertainties they face and better formulate well-reasoned decisions. Using Bayes rule, the clinician can interpret pedigrees, historical data, physical findings and laboratory data, providing individualized probabilities of various diagnoses and outcomes of pregnancy. With the advent of screening programs for genetic disease, it becomes increasingly important to consider the prior probabilities of disease when interpreting an abnormal screening test result. Decision trees provide a convenient formalism for structuring diagnostic, therapeutic and reproductive decisions; such trees can also enhance communication between clinicians and patients. Utility theory provides a mechanism for patients to understand the choices they face and to communicate their attitudes about potential reproductive outcomes in a manner which encourages the integration of those attitudes into appropriate decisions. Using a decision tree, the relevant probabilities and the patients' utilities, physicians can estimate the relative worth of various medical and reproductive options by calculating the expected utility of each. By performing relevant sensitivity analyses, clinicians and patients can understand the impact of various soft data, including the patients' attitudes toward various health outcomes, on the decision making process. Formal clinical decision analytic models can provide deeper understanding and improved decision making in clinical genetics.

Aging in the colonial chordate, Botryllus schlosseri

PubMed Central

Munday, Roma; Rodriguez, Delany; Di Maio, Alessandro; Kassmer, Susannah; Braden, Brian; Taketa, Daryl A.; Langenbacher, Adam; De Tomaso, Anthony

2015-01-01

What mechanisms underlie aging? One theory, the wear-and-tear model, attributes aging to progressive deterioration in the molecular and cellular machinery which eventually lead to death through the disruption of physiological homeostasis. The second suggests that life span is genetically programmed, and aging may be derived from intrinsic processes which enforce a non-random, terminal time interval for the survivability of the organism. We are studying an organism that demonstrates both properties: the colonial ascidian, Botryllus schlosseri. Botryllus is a member of the Tunicata, the sister group to the vertebrates, and has a number of life history traits which make it an excellent model for studies on aging. First, Botryllus has a colonial life history, and grows by a process of asexual reproduction during which entire bodies, including all somatic and germline lineages, regenerate every week, resulting in a colony of genetically identical individuals. Second, previous studies of lifespan in genetically distinct Botryllus lineages suggest that a direct, heritable basis underlying mortality exists that is unlinked to reproductive effort and other life history traits. Here we will review recent efforts to take advantage of the unique life history traits of B. schlosseri and develop it into a robust model for aging research. PMID:26136620

Off and back-on again: a tumor suppressor's tale.

PubMed

Acosta, Jonuelle; Wang, Walter; Feldser, David M

2018-06-01

Tumor suppressor genes play critical roles orchestrating anti-cancer programs that are both context dependent and mechanistically diverse. Beyond canonical tumor suppressive programs that control cell division, cell death, and genome stability, unexpected tumor suppressor gene activities that regulate metabolism, immune surveillance, the epigenetic landscape, and others have recently emerged. This diversity underscores the important roles these genes play in maintaining cellular homeostasis to suppress cancer initiation and progression, but also highlights a tremendous challenge in discerning precise context-specific programs of tumor suppression controlled by a given tumor suppressor. Fortunately, the rapid sophistication of genetically engineered mouse models of cancer has begun to shed light on these context-dependent tumor suppressor activities. By using techniques that not only toggle "off" tumor suppressor genes in nascent tumors, but also facilitate the timely restoration of gene function "back-on again" in disease specific contexts, precise mechanisms of tumor suppression can be revealed in an unbiased manner. This review discusses the development and implementation of genetic systems designed to toggle tumor suppressor genes off and back-on again and their potential to uncover the tumor suppressor's tale.

Screening Jews and genes: a consideration of the ethics of genetic screening within the Jewish community: challenges and responses.

PubMed

Levin, M

1999-01-01

Screening for genetic disorders, particularly Tay-Sachs Disease, has been traditionally welcome by the Jewish community. I review the history of genetic screening among Jews and the views from the Jewish tradition on the subject, and then discuss ethical challenges of screening and the impact of historical memories upon future acceptance of screening programs. Some rational principles to guide future design of genetic screening programs among Jews are proposed.

Ecological genetics at the USGS National Wetlands Research Center

USGS Publications Warehouse

Travis, Steven

2006-01-01

The Ecological Genetics Program at the USGS National Wetlands Research Center (NWRC) employs state-of-the-art DNA fingerprinting technologies in characterizing critical management aspects of the population biology of species of concern (fig. 1). The overarching themes of this program have been (1) the critical role that genetic diversity plays in maintaining population viability and (2) how management strategies might incorporate genetic information in preventing the decline of desirable species or in controlling the spread of invasive species.

Random regression analyses using B-spline functions to model growth of Nellore cattle.

PubMed

Boligon, A A; Mercadante, M E Z; Lôbo, R B; Baldi, F; Albuquerque, L G

2012-02-01

The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

Direct and social genetic effects on body weight at 270 days and carcass and ham quality traits in heavy pigs.

PubMed

Rostellato, R; Sartori, C; Bonfatti, V; Chiarot, G; Carnier, P

2015-01-01

The aims of this study were to estimate covariance components for BW at 270 d (BW270) and carcass and ham quality traits in heavy pigs using models accounting for social effects and to compare the ability of such models to fit the data relative to models ignoring social interactions. Phenotypic records were from 9,871 pigs sired by 293 purebred boars mated to 456 crossbred sows. Piglets were born and reared at the same farm and randomly assigned at 60 d of age to groups (6.1 pigs per group on average) housed in finishing pens, each having an area of 6 m(2). The average additive genetic relationship among group mates was 0.11. Pigs were slaughtered at 277 ± 3 d of age and 169.7 ± 13.9 kg BW in groups of nearly 70 animals each. Four univariate animal models were compared: a basic model (M1) including only direct additive genetic effects, a model (M2) with nonheritable social group (pen) effects in addition to effects in M1, a model (M3) accounting for litter effects in addition to M2, and a model (M4) accounting for social genetic effects in addition to effects in M3. Restricted maximum likelihood estimates of covariance components were obtained for BW270; carcass backfat depth; carcass lean meat content (CLM); iodine number (IOD); and linoleic acid content (LIA) of raw ham subcutaneous fat; subcutaneous fat depth in the proximity of semimembranosus muscle (SFD1) and quadriceps femoris muscle (SFD2); and linear scores for ham round shape (RS), subcutaneous fat (SF), and marbling. Likelihood ratio tests indicated that, for all traits, M2 fit the data better than M1 and that M3 was superior to M2 except for SFD1 and SFD2. Model M4 was significantly better than M3 for BW270 (P < 0.001) and CLM, IOD, RS, and SF (P < 0.05). The contribution of social genetic effects to the total heritable variance was large for CLM and BW270, ranging from 33.2 to 35%, whereas the one for ham quality traits ranged from 6.8 (RS) to 11.2% (SF). Direct and social genetic effects on BW270 were uncorrelated, whereas there was a negative genetic covariance between direct and social effects on CLM, IOD, RS, and SF, which reduced the total heritable variance. This variance, measured relative to phenotypic variance, ranged from 21 (CLM) to 54% (BW270). Results indicate that social genetic effects affect variation in traits relevant for heavy pigs used in dry-cured hams manufacturing. Such effects should be exploited and taken into account in design of breeding programs for heavy pigs.

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

PubMed

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

2012-03-01

Genetic algorithm (GA) has been used in this study for a new approach of suboptimal model reduction in the Nyquist plane and optimal time domain tuning of proportional-integral-derivative (PID) and fractional-order (FO) PI(λ)D(μ) controllers. Simulation studies show that the new Nyquist-based model reduction technique outperforms the conventional H(2)-norm-based reduced parameter modeling technique. With the tuned controller parameters and reduced-order model parameter dataset, optimum tuning rules have been developed with a test-bench of higher-order processes via genetic programming (GP). The GP performs a symbolic regression on the reduced process parameters to evolve a tuning rule which provides the best analytical expression to map the data. The tuning rules are developed for a minimum time domain integral performance index described by a weighted sum of error index and controller effort. From the reported Pareto optimal front of the GP-based optimal rule extraction technique, a trade-off can be made between the complexity of the tuning formulae and the control performance. The efficacy of the single-gene and multi-gene GP-based tuning rules has been compared with the original GA-based control performance for the PID and PI(λ)D(μ) controllers, handling four different classes of representative higher-order processes. These rules are very useful for process control engineers, as they inherit the power of the GA-based tuning methodology, but can be easily calculated without the requirement for running the computationally intensive GA every time. Three-dimensional plots of the required variation in PID/fractional-order PID (FOPID) controller parameters with reduced process parameters have been shown as a guideline for the operator. Parametric robustness of the reported GP-based tuning rules has also been shown with credible simulation examples. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2011-02-01

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

The social dynamics of genetic testing: the case of Fragile-X.

PubMed

Nelkin, D

1996-12-01

This article considers a program to screen school children for Fragile-X Syndrome as a way to explore several features of the growing practice of genetic testing in American society. These include the common practice of predictive testing in nonclinical settings; the economic, entrepreneurial, and policy interests that are driving the development of genetic screening programs; and the public support for genetic testing even when there are no effective therapeutic interventions. Drawing from research on popular images of genetics, I argue that cultural beliefs and expectations, widely conveyed through popular narratives, are encouraging the search for diagnostic information and enhancing the appeal of genetic explanations for a growing range of conditions.

Computational evaluation of exome sequence data using human and model organism phenotypes improves diagnostic efficiency

PubMed Central

Bone, William P.; Washington, Nicole L.; Buske, Orion J.; Adams, David R.; Davis, Joie; Draper, David; Flynn, Elise D.; Girdea, Marta; Godfrey, Rena; Golas, Gretchen; Groden, Catherine; Jacobsen, Julius; Köhler, Sebastian; Lee, Elizabeth M. J.; Links, Amanda E.; Markello, Thomas C.; Mungall, Christopher J.; Nehrebecky, Michele; Robinson, Peter N.; Sincan, Murat; Soldatos, Ariane G.; Tifft, Cynthia J.; Toro, Camilo; Trang, Heather; Valkanas, Elise; Vasilevsky, Nicole; Wahl, Colleen; Wolfe, Lynne A.; Boerkoel, Cornelius F.; Brudno, Michael; Haendel, Melissa A.; Gahl, William A.; Smedley, Damian

2016-01-01

Purpose: Medical diagnosis and molecular or biochemical confirmation typically rely on the knowledge of the clinician. Although this is very difficult in extremely rare diseases, we hypothesized that the recording of patient phenotypes in Human Phenotype Ontology (HPO) terms and computationally ranking putative disease-associated sequence variants improves diagnosis, particularly for patients with atypical clinical profiles. Genet Med 18 6, 608–617. Methods: Using simulated exomes and the National Institutes of Health Undiagnosed Diseases Program (UDP) patient cohort and associated exome sequence, we tested our hypothesis using Exomiser. Exomiser ranks candidate variants based on patient phenotype similarity to (i) known disease–gene phenotypes, (ii) model organism phenotypes of candidate orthologs, and (iii) phenotypes of protein–protein association neighbors. Genet Med 18 6, 608–617. Results: Benchmarking showed Exomiser ranked the causal variant as the top hit in 97% of known disease–gene associations and ranked the correct seeded variant in up to 87% when detectable disease–gene associations were unavailable. Using UDP data, Exomiser ranked the causative variant(s) within the top 10 variants for 11 previously diagnosed variants and achieved a diagnosis for 4 of 23 cases undiagnosed by clinical evaluation. Genet Med 18 6, 608–617. Conclusion: Structured phenotyping of patients and computational analysis are effective adjuncts for diagnosing patients with genetic disorders. Genet Med 18 6, 608–617. PMID:26562225

Time dependent genetic analysis links field and controlled environment phenotypes in the model C 4 grass Setaria

DOE PAGES

Feldman, Max J.; Paul, Rachel E.; Banan, Darshi; ...

2017-06-23

Vertical growth of plants is a dynamic process that is influenced by genetic and environmental factors and has a pronounced effect on overall plant architecture and biomass composition. For this research, we have performed six controlled growth trials of an interspecific Setaria italica x Setaria viridis recombinant inbred line population to assess how the genetic architecture of plant height is influenced by developmental queues, water availability and planting density. The non-destructive nature of plant height measurements has enabled us to monitor height throughout the plant life cycle in both field and controlled environments. We find that plant height is reducedmore » under water limitation and high density planting and affected by growth environment (field vs. growth chamber). The results support a model where plant height is a heritable, polygenic trait and that the major genetic loci that influence plant height function independent of growth environment. The identity and contribution of loci that influence height changes dynamically throughout development and the reduction of growth observed in water limited environments is a consequence of delayed progression through the genetic program which establishes plant height in Setaria. In this population, alleles inherited from the weedy S. viridis parent act to increase plant height early, whereas a larger number of small effect alleles inherited from the domesticated S. italica parent collectively act to increase plant height later in development.« less

Time dependent genetic analysis links field and controlled environment phenotypes in the model C 4 grass Setaria

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

Feldman, Max J.; Paul, Rachel E.; Banan, Darshi

Vertical growth of plants is a dynamic process that is influenced by genetic and environmental factors and has a pronounced effect on overall plant architecture and biomass composition. For this research, we have performed six controlled growth trials of an interspecific Setaria italica x Setaria viridis recombinant inbred line population to assess how the genetic architecture of plant height is influenced by developmental queues, water availability and planting density. The non-destructive nature of plant height measurements has enabled us to monitor height throughout the plant life cycle in both field and controlled environments. We find that plant height is reducedmore » under water limitation and high density planting and affected by growth environment (field vs. growth chamber). The results support a model where plant height is a heritable, polygenic trait and that the major genetic loci that influence plant height function independent of growth environment. The identity and contribution of loci that influence height changes dynamically throughout development and the reduction of growth observed in water limited environments is a consequence of delayed progression through the genetic program which establishes plant height in Setaria. In this population, alleles inherited from the weedy S. viridis parent act to increase plant height early, whereas a larger number of small effect alleles inherited from the domesticated S. italica parent collectively act to increase plant height later in development.« less

Association mapping unveils favorable alleles for grain iron and zinc concentrations in lentil (Lens culinaris subsp. culinaris)

PubMed Central

Singh, Akanksha; Sharma, Vinay; Dikshit, Harsh Kumar; Aski, Muraleedhar; Kumar, Harish; Thirunavukkarasu, Nepolean; Patil, Basavanagouda S.; Kumar, Shiv; Sarker, Ashutosh

2017-01-01

Lentil is a major cool-season grain legume grown in South Asia, West Asia, and North Africa. Populations in developing countries of these regions have micronutrient deficiencies; therefore, breeding programs should focus more on improving the micronutrient content of food. In the present study, a set of 96 diverse germplasm lines were evaluated at three different locations in India to examine the variation in iron (Fe) and zinc (Zn) concentration and identify simple sequence repeat (SSR) markers that associate with the genetic variation. The genetic variation among genotypes of the association mapping (AM) panel was characterized using a genetic distance-based and a general model-based clustering method. The model-based analysis identified six subpopulations, which satisfactorily explained the genetic structure of the AM panel. AM analysis identified three SSRs (PBALC 13, PBALC 206, and GLLC 563) associated with grain Fe concentration explaining 9% to 11% of phenotypic variation and four SSRs (PBALC 353, SSR 317–1, PLC 62, and PBALC 217) were associated with grain Zn concentration explaining 14%, to 21% of phenotypic variation. These identified SSRs exhibited consistent performance across locations. These candidate SSRs can be used in marker-assisted genetic improvement for developing Fe and Zn fortified lentil varieties. Favorable alleles and promising genotypes identified in this study can be utilized for lentil biofortification. PMID:29161321

Time dependent genetic analysis links field and controlled environment phenotypes in the model C4 grass Setaria

PubMed Central

Paul, Rachel E.; Sebastian, Jose; Yee, Muh-Ching; Jiang, Hui; Lipka, Alexander E.; Brutnell, Thomas P.; Dinneny, José R.; Leakey, Andrew D. B.

2017-01-01

Vertical growth of plants is a dynamic process that is influenced by genetic and environmental factors and has a pronounced effect on overall plant architecture and biomass composition. We have performed six controlled growth trials of an interspecific Setaria italica x Setaria viridis recombinant inbred line population to assess how the genetic architecture of plant height is influenced by developmental queues, water availability and planting density. The non-destructive nature of plant height measurements has enabled us to monitor height throughout the plant life cycle in both field and controlled environments. We find that plant height is reduced under water limitation and high density planting and affected by growth environment (field vs. growth chamber). The results support a model where plant height is a heritable, polygenic trait and that the major genetic loci that influence plant height function independent of growth environment. The identity and contribution of loci that influence height changes dynamically throughout development and the reduction of growth observed in water limited environments is a consequence of delayed progression through the genetic program which establishes plant height in Setaria. In this population, alleles inherited from the weedy S. viridis parent act to increase plant height early, whereas a larger number of small effect alleles inherited from the domesticated S. italica parent collectively act to increase plant height later in development. PMID:28644860

Time dependent genetic analysis links field and controlled environment phenotypes in the model C4 grass Setaria.

PubMed

Feldman, Max J; Paul, Rachel E; Banan, Darshi; Barrett, Jennifer F; Sebastian, Jose; Yee, Muh-Ching; Jiang, Hui; Lipka, Alexander E; Brutnell, Thomas P; Dinneny, José R; Leakey, Andrew D B; Baxter, Ivan

2017-06-01

Vertical growth of plants is a dynamic process that is influenced by genetic and environmental factors and has a pronounced effect on overall plant architecture and biomass composition. We have performed six controlled growth trials of an interspecific Setaria italica x Setaria viridis recombinant inbred line population to assess how the genetic architecture of plant height is influenced by developmental queues, water availability and planting density. The non-destructive nature of plant height measurements has enabled us to monitor height throughout the plant life cycle in both field and controlled environments. We find that plant height is reduced under water limitation and high density planting and affected by growth environment (field vs. growth chamber). The results support a model where plant height is a heritable, polygenic trait and that the major genetic loci that influence plant height function independent of growth environment. The identity and contribution of loci that influence height changes dynamically throughout development and the reduction of growth observed in water limited environments is a consequence of delayed progression through the genetic program which establishes plant height in Setaria. In this population, alleles inherited from the weedy S. viridis parent act to increase plant height early, whereas a larger number of small effect alleles inherited from the domesticated S. italica parent collectively act to increase plant height later in development.

Drosophila sex combs as a model of evolutionary innovations.

PubMed

Kopp, Artyom

2011-01-01

The diversity of animal and plant forms is shaped by nested evolutionary innovations. Understanding the genetic and molecular changes responsible for these innovations is therefore one of the key goals of evolutionary biology. From the genetic point of view, the origin of novel traits implies the origin of new regulatory pathways to control their development. To understand how these new pathways are assembled in the course of evolution, we need model systems that combine relatively recent innovations with a powerful set of genetic and molecular tools. One such model is provided by the Drosophila sex comb-a male-specific morphological structure that evolved in a relatively small lineage related to the model species D. melanogaster. Our extensive knowledge of sex comb development in D. melanogaster provides the basis for investigating the genetic changes responsible for sex comb origin and diversification. At the same time, sex combs can change on microevolutionary timescales and differ spectacularly among closely related species, providing opportunities for direct genetic analysis and for integrating developmental and population-genetic approaches. Sex comb evolution is associated with the origin of novel interactions between Hox and sex determination genes. Activity of the sex determination pathway was brought under the control of the Hox code to become segment-specific, while Hox gene expression became sexually dimorphic. At the same time, both Hox and sex determination genes were integrated into the intrasegmental spatial patterning network, and acquired new joint downstream targets. Phylogenetic analysis shows that similar sex comb morphologies evolved independently in different lineages. Convergent evolution at the phenotypic level reflects convergent changes in the expression of Hox and sex determination genes, involving both independent gains and losses of regulatory interactions. However, the downstream cell-differentiation programs have diverged between species, and in some lineages, similar adult morphologies are produced by different morphogenetic mechanisms. These features make the sex comb an excellent model for examining not only the genetic changes responsible for its evolution, but also the cellular processes that translate DNA sequence changes into morphological diversity. The origin and diversification of sex combs provides insights into the roles of modularity, cooption, and regulatory changes in evolutionary innovations, and can serve as a model for understanding the origin of the more drastic novelties that define higher order taxa. © 2011 Wiley Periodicals, Inc.

Drosophila Sex Combs as a Model of Evolutionary Innovations

PubMed Central

Kopp, Artyom

2011-01-01

The diversity of animal and plant forms is shaped by nested evolutionary innovations. Understanding the genetic and molecular changes responsible for these innovations is therefore one of the key goals of evolutionary biology. From the genetic point of view, the origin of novel traits implies the origin of new regulatory pathways to control their development. To understand how these new pathways are assembled in the course of evolution, we need model systems that combine relatively recent innovations with a powerful set of genetic and molecular tools. One such model is provided by the Drosophila sex comb – a male-specific morphological structure that evolved in a relatively small lineage related to the model species D. melanogaster. Our extensive knowledge of sex comb development in D. melanogaster provides the basis for investigating the genetic changes responsible for sex comb origin and diversification. At the same time, sex combs can change on microevolutionary timescales and differ spectacularly among closely related species, providing opportunities for direct genetic analysis and for integrating developmental and population-genetic approaches. Sex comb evolution is associated with the origin of novel interactions between HOX and sex determination genes. Activity of the sex determination pathway was brought under the control of the HOX code to become segment-specific, while HOX gene expression became sexually dimorphic. At the same time, both HOX and sex determination genes were integrated into the intrasegmental spatial patterning network, and acquired new joint downstream targets. Phylogenetic analysis shows that similar sex comb morphologies evolved independently in different lineages. Convergent evolution at the phenotypic level reflects convergent changes in the expression of HOX and sex determination genes, involving both independent gains and losses of regulatory interactions. However, the downstream cell differentiation programs have diverged between species, and in some lineages similar adult morphologies are produced by different morphogenetic mechanisms. These features make the sex comb an excellent model for examining not only the genetic changes responsible for its evolution, but also the cellular processes that translate DNA sequence changes into morphological diversity. The origin and diversification of sex combs provides insights into the roles of modularity, cooption, and regulatory changes in evolutionary innovations, and can serve as a model for understanding the origin of the more drastic novelties that define higher-order taxa. PMID:23016935

Genetic diversity and structure of Brazilian ginger germplasm (Zingiber officinale) revealed by AFLP markers.

PubMed

Blanco, Eleonora Zambrano; Bajay, Miklos Maximiliano; Siqueira, Marcos Vinícius Bohrer Monteiro; Zucchi, Maria Imaculada; Pinheiro, José Baldin

2016-12-01

Ginger is a vegetable with medicinal and culinary properties widely cultivated in the Southern and Southeastern Brazil. The knowledge of ginger species' genetic variability is essential to direct correctly future studies of conservation and genetic improvement, but in Brazil, little is known about this species' genetic variability. In this study, we analyzed the genetic diversity and structure of 55 Brazilian accessions and 6 Colombian accessions of ginger, using AFLP (Amplified Fragment Length Polymorphism) molecular markers. The molecular characterization was based on 13 primers combinations, which generated an average of 113.5 polymorphic loci. The genetic diversity estimates of Nei (Hj), Shannon-Weiner index (I) and an effective number of alleles (n e ) were greater in the Colombian accessions in relation to the Brazilian accessions. The analysis of molecular variance showed that most of the genetic variation occurred between the two countries while in the Brazilian populations there is no genetic structure and probably each region harbors 100 % of genetic variation found in the samples. The bayesian model-based clustering and the dendrogram using the dissimilarity's coefficient of Jaccard were congruent with each other and showed that the Brazilian accessions are highly similar between themselves, regardless of the geographic region of origin. We suggested that the exploration of the interspecific variability and the introduction of new varieties of Z.officinale are viable alternatives for generating diversity in breeding programs in Brazil. The introduction of new genetic materials will certainly contribute to a higher genetic basis of such crop.

Genetic control of complex traits, with a focus on reproduction in pigs.

PubMed

Zak, Louisa J; Gaustad, Ann Helen; Bolarin, Alfonso; Broekhuijse, Marleen L W J; Walling, Grant A; Knol, Egbert F

2017-09-01

Reproductive traits are complex, and desirable reproductive phenotypes, such as litter size or semen quality, are true polygenetic traits determined by multiple gene regulatory pathways. Each individual gene contributes to the overall variation in these traits, so genetic improvements can be achieved using conventional selection methodology. In the past, a pedigree-based-relationship matrix was used; this is now replaced by a combination of pedigree-based- and genomic-relationship matrices. The heritability of reproductive traits is low to moderate, so large-scale data recording is required to identify specific, selectable attributes. Male reproductive traits-including ejaculate volume and sperm progressive motility-are moderately heritable, and could be used in selection programs. A few high-merit artificial-insemination boars can impact many sow populations, so additional knowledge about male reproduction-specifically pre-pubertal detection of infertility and the technologies of semen cryopreservation and sex sorting-should further improve global breeding efforts. Conversely, female pig reproduction is currently a limiting factor of genetic improvement. Litter size and farrowing interval are the main obstacles to increasing selection intensity and to reducing generation interval in a breeding program. Age at puberty and weaning-to-estrus interval can be selected for, thereby reducing the number of non-productive days. The number of piglets born alive and litter weights are also reliably influenced by genetic selection. Characterization of genotype-environment interactions will provide opportunities to match genetics to specific farm systems. Continued investment to understand physiological models for improved phenotyping and the development of technologies to facilitate pig embryo production for genetic selection are warranted to ensure optimal breeding in future generations. © 2017 Wiley Periodicals, Inc.

Transcriptional signatures of ancient floral developmental genetics in avocado (Persea americana; Lauraceae).

PubMed

Chanderbali, André S; Albert, Victor A; Leebens-Mack, Jim; Altman, Naomi S; Soltis, Douglas E; Soltis, Pamela S

2009-06-02

The debate on the origin and evolution of flowers has recently entered the field of developmental genetics, with focus on the design of the ancestral floral regulatory program. Flowers can differ dramatically among angiosperm lineages, but in general, male and female reproductive organs surrounded by a sterile perianth of sepals and petals constitute the basic floral structure. However, the basal angiosperm lineages exhibit spectacular diversity in the number, arrangement, and structure of floral organs, whereas the evolutionarily derived monocot and eudicot lineages share a far more uniform floral ground plan. Here we show that broadly overlapping transcriptional programs characterize the floral transcriptome of the basal angiosperm Persea americana (avocado), whereas floral gene expression domains are considerably more organ specific in the model eudicot Arabidopsis thaliana. Our findings therefore support the "fading borders" model for organ identity determination in basal angiosperm flowers and extend it from the action of regulatory genes to downstream transcriptional programs. Furthermore, the declining expression of components of the staminal transcriptome in central and peripheral regions of Persea flowers concurs with elements of a previous hypothesis for developmental regulation in a gymnosperm "floral progenitor." Accordingly, in contrast to the canalized organ-specific regulatory apparatus of Arabidopsis, floral development may have been originally regulated by overlapping transcriptional cascades with fading gradients of influence from focal to bordering organs.

Introduction to the Arizona Sky Island Arthropod Project (ASAP): Systematics, Biogeography, Ecology, and Population Genetics of Arthropods of the Madrean Sky Islands.

PubMed

Moore, Wendy; Meyer, Wallace M; Eble, Jeffrey A; Franklin, Kimberly; Wiens, John F; Brusca, Richard C

2013-01-01

The Arizona Sky Island Arthropod Project (ASAP) is a new multi-disciplinary research program at the University of Arizona that combines systematics, biogeography, ecology, and population genetics to study origins and patterns of arthropod diversity along elevation gradients and among mountain ranges in the Madrean Sky Island Region. Arthropods represent taxonomically and ecologically diverse organisms that drive key ecosystem processes in this mountain archipelago. Using data from museum specimens and specimens we obtain during long-term collecting and monitoring programs, ASAP will document arthropod species across Arizona's Sky Islands to address a number of fundamental questions about arthropods of this region. Baseline data will be used to determine climatic boundaries for target species, which will then be integrated with climatological models to predict future changes in arthropod communities and distributions in the wake of rapid climate change. ASAP also makes use of the natural laboratory provided by the Sky Islands to investigate ecological and genetic factors that influence diversification and patterns of community assembly. Here, we introduce the project, outline overarching goals, and describe preliminary data from the first year of sampling ground-dwelling beetles and ants in the Santa Catalina Mountains.

Floral homeotic proteins modulate the genetic program for leaf development to suppress trichome formation in flowers.

PubMed

Ó'Maoiléidigh, Diarmuid S; Stewart, Darragh; Zheng, Beibei; Coupland, George; Wellmer, Frank

2018-02-13

As originally proposed by Goethe in 1790, floral organs are derived from leaf-like structures. The conversion of leaves into different types of floral organ is mediated by floral homeotic proteins, which, as described by the ABCE model of flower development, act in a combinatorial manner. However, how these transcription factors bring about this transformation process is not well understood. We have previously shown that floral homeotic proteins are involved in suppressing the formation of branched trichomes, a hallmark of leaf development, on reproductive floral organs of Arabidopsis Here, we present evidence that the activities of the C function gene AGAMOUS ( AG ) and the related SHATTERPROOF1 / 2 genes are superimposed onto the regulatory network that controls the distribution of trichome formation in an age-dependent manner. We show that AG regulates cytokinin responses and genetically interacts with the organ polarity gene KANADI1 to suppress trichome initiation on gynoecia. Thus, our results show that parts of the genetic program for leaf development remain active during flower formation but have been partially rewired through the activities of the floral homeotic proteins. © 2018. Published by The Company of Biologists Ltd.

A genetic algorithm used for solving one optimization problem

NASA Astrophysics Data System (ADS)

Shipacheva, E. N.; Petunin, A. A.; Berezin, I. M.

2017-12-01

A problem of minimizing the length of the blank run for a cutting tool during cutting of sheet materials into shaped blanks is discussed. This problem arises during the preparation of control programs for computerized numerical control (CNC) machines. A discrete model of the problem is analogous in setting to the generalized travelling salesman problem with limitations in the form of precursor conditions determined by the technological features of cutting. A certain variant of a genetic algorithm for solving this problem is described. The effect of the parameters of the developed algorithm on the solution result for the problem with limitations is investigated.

Genetics/genomics education for nongenetic health professionals: a systematic literature review.

PubMed

Talwar, Divya; Tseng, Tung-Sung; Foster, Margaret; Xu, Lei; Chen, Lei-Shih

2017-07-01

The completion of the Human Genome Project has enhanced avenues for disease prevention, diagnosis, and management. Owing to the shortage of genetic professionals, genetics/genomics training has been provided to nongenetic health professionals for years to establish their genomic competencies. We conducted a systematic literature review to summarize and evaluate the existing genetics/genomics education programs for nongenetic health professionals. Five electronic databases were searched from January 1990 to June 2016. Forty-four studies met our inclusion criteria. There was a growing publication trend. Program participants were mainly physicians and nurses. The curricula, which were most commonly provided face to face, included basic genetics; applied genetics/genomics; ethical, legal, and social implications of genetics/genomics; and/or genomic competencies/recommendations in particular professional fields. Only one-third of the curricula were theory-based. The majority of studies adopted a pre-/post-test design and lacked follow-up data collection. Nearly all studies reported participants' improvements in one or more of the following areas: knowledge, attitudes, skills, intention, self-efficacy, comfort level, and practice. However, most studies did not report participants' age, ethnicity, years of clinical practice, data validity, and data reliability. Many genetics/genomics education programs for nongenetic health professionals exist. Nevertheless, enhancement in methodological quality is needed to strengthen education initiatives.Genet Med advance online publication 20 October 2016.

The Moroccan Genetic Disease Database (MGDD): a database for DNA variations related to inherited disorders and disease susceptibility.

PubMed

Charoute, Hicham; Nahili, Halima; Abidi, Omar; Gabi, Khalid; Rouba, Hassan; Fakiri, Malika; Barakat, Abdelhamid

2014-03-01

National and ethnic mutation databases provide comprehensive information about genetic variations reported in a population or an ethnic group. In this paper, we present the Moroccan Genetic Disease Database (MGDD), a catalogue of genetic data related to diseases identified in the Moroccan population. We used the PubMed, Web of Science and Google Scholar databases to identify available articles published until April 2013. The Database is designed and implemented on a three-tier model using Mysql relational database and the PHP programming language. To date, the database contains 425 mutations and 208 polymorphisms found in 301 genes and 259 diseases. Most Mendelian diseases in the Moroccan population follow autosomal recessive mode of inheritance (74.17%) and affect endocrine, nutritional and metabolic physiology. The MGDD database provides reference information for researchers, clinicians and health professionals through a user-friendly Web interface. Its content should be useful to improve researches in human molecular genetics, disease diagnoses and design of association studies. MGDD can be publicly accessed at http://mgdd.pasteur.ma.

Genetic Introgression and the Survival of Florida Panther Kittens

PubMed Central

Hostetler, Jeffrey A.; Onorato, David P.; Nichols, James D.; Johnson, Warren E.; Roelke, Melody E.; O’Brien, Stephen J.; Jansen, Deborah; Oli, Madan K.

2010-01-01

Estimates of survival for the young of a species are critical for population models. These models can often be improved by determining the effects of management actions and population abundance on this demographic parameter. We used multiple sources of data collected during 1982-2008 and a live recapture-dead recovery modeling framework to estimate and model survival of Florida panther (Puma concolor coryi) kittens (age 0 – 1 year). Overall, annual survival of Florida panther kittens was 0.323 ± 0.071 (SE), which was lower than estimates used in previous population models. In 1995, female pumas from Texas (P. c. stanleyana) were released into occupied panther range as part of an intentional introgression program to restore genetic variability. We found that kitten survival generally increased with degree of admixture: F1 admixed and backcrossed to Texas kittens survived better than canonical Florida panther and backcrossed to canonical kittens. Average heterozygosity positively influenced kitten and older panther survival, whereas index of panther abundance negatively influenced kitten survival. Our results provide strong evidence for the positive population-level impact of genetic introgression on Florida panthers. Our approach to integrate data from multiple sources was effective at improving robustness as well as precision of estimates of Florida panther kitten survival, and can be useful in estimating vital rates for other elusive species with sparse data. PMID:21113436

Genetic introgression and the survival of Florida panther kittens

USGS Publications Warehouse

Hostetler, Jeffrey A.; Onorato, David P.; Nichols, James D.; Johnson, Warren E.; Roelke, Melody E.; O'Brien, Stephen J.; Jansen, Deborah; Oli, Madan K.

2010-01-01

Estimates of survival for the young of a species are critical for population models. These models can often be improved by determining the effects of management actions and population abundance on this demographic parameter. We used multiple sources of data collected during 1982–2008 and a live-recapture dead-recovery modeling framework to estimate and model survival of Florida panther (Puma concolor coryi) kittens (age 0–1 year). Overall, annual survival of Florida panther kittens was 0.323 ± 0.071 (SE), which was lower than estimates used in previous population models. In 1995, female pumas from Texas (P. c. stanleyana) were released into occupied panther range as part of an intentional introgression program to restore genetic variability. We found that kitten survival generally increased with degree of admixture: F1 admixed and backcrossed to Texas kittens survived better than canonical Florida panther and backcrossed to canonical kittens. Average heterozygosity positively influenced kitten and older panther survival, whereas index of panther abundance negatively influenced kitten survival. Our results provide strong evidence for the positive population-level impact of genetic introgression on Florida panthers. Our approach to integrate data from multiple sources was effective at improving robustness as well as precision of estimates of Florida panther kitten survival, and can be useful in estimating vital rates for other elusive species with sparse data.

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

PubMed

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

2018-06-04

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

Establishing a Program for Individuals at High Risk for Breast Cancer

PubMed Central

Cadiz, Fernando; Kuerer, Henry M.; Puga, Julio; Camacho, Jamile; Cunill, Eduardo; Arun, Banu

2013-01-01

Our need to create a program for individuals at high risk for breast cancer development led us to research the available data on such programs. In this paper, we summarize our findings and our thinking process as we developed our own program. Breast cancer incidence is increasing worldwide. Even though there are known risk factors for breast cancer development, approximately 60% of patients with breast cancer have no known risk factor, although this situation will probably change with further research, especially in genetics. For patients with risk factors based on personal or family history, different models are available for assessing and quantifying risk. Assignment of risk levels permits tailored screening and risk reduction strategies. Potential benefits of specialized programs for women with high breast cancer risk include more cost -effective interventions as a result of patient stratification on the basis of risk; generation of valuable data to advance science; and differentiation of breast programs from other breast cancer units, which can result in increased revenue that can be directed to further improvements in patient care. Guidelines for care of patients at high risk for breast cancer are available from various groups. However, running a high-risk breast program involves much more than applying a guideline. Each high-risk program needs to be designed by its institution with consideration of local resources and country legislation, especially related to genetic issues. Development of a successful high-risk program includes identifying strengths, weaknesses, opportunities, and threats; developing a promotion plan; choosing a risk assessment tool; defining “high risk”; and planning screening and risk reduction strategies for the specific population served by the program. The information in this article may be useful for other institutions considering creation of programs for patients with high breast cancer risk. PMID:23833688

Primer on Molecular Genetics; DOE Human Genome Program

DOE R&D Accomplishments Database

1992-04-01

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

Solving bi-level optimization problems in engineering design using kriging models

NASA Astrophysics Data System (ADS)

Xia, Yi; Liu, Xiaojie; Du, Gang

2018-05-01

Stackelberg game-theoretic approaches are applied extensively in engineering design to handle distributed collaboration decisions. Bi-level genetic algorithms (BLGAs) and response surfaces have been used to solve the corresponding bi-level programming models. However, the computational costs for BLGAs often increase rapidly with the complexity of lower-level programs, and optimal solution functions sometimes cannot be approximated by response surfaces. This article proposes a new method, namely the optimal solution function approximation by kriging model (OSFAKM), in which kriging models are used to approximate the optimal solution functions. A detailed example demonstrates that OSFAKM can obtain better solutions than BLGAs and response surface-based methods, and at the same time reduce the workload of computation remarkably. Five benchmark problems and a case study of the optimal design of a thin-walled pressure vessel are also presented to illustrate the feasibility and potential of the proposed method for bi-level optimization in engineering design.

The molecular genetics of holoprosencephaly

PubMed Central

Roessler, Erich; Muenke, Maximilian

2009-01-01

Holoprosencephaly (or HPE) has captivated the imagination of Man for millennia because its most extreme manifestation, the single-eyed cyclopic newborn infant, brings to mind the fantastical creature Cyclops from Greek mythology. Attempting to understand this common malformation of the forebrain in modern medical terms requires a systematic synthesis of genetic, cytogenetic and environmental information typical for studies of a complex disorder. However, even with the advances in our understanding of HPE in recent years, there are significant obstacles remaining to fully understand its heterogeneity and extensive variability in phenotype. General lessons learned from HPE will likely be applicable to other malformation syndromes. Here we outline the common, and rare, genetic and environmental influences on this conserved developmental program of forebrain development and illustrate the similarities and differences between these malformations in humans and those of animal models. PMID:20104595

The molecular genetics of holoprosencephaly.

PubMed

Roessler, Erich; Muenke, Maximilian

2010-02-15

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

Regulation of STATs by polycystin-1 and their role in polycystic kidney disease.

PubMed

Weimbs, Thomas; Olsan, Erin E; Talbot, Jeffrey J

2013-04-01

Autosomal-dominant polycystic kidney disease (ADPKD) is a common genetic disease caused by mutations in the gene coding for polycystin-1 (PC1). PC1 can regulate STAT transcription factors by a novel, dual mechanism. STAT3 and STAT6 are aberrantly activated in renal cysts. Genetic and pharmacological approaches to inhibit STAT3 or STAT6 have led to promising results in ADPKD mouse models. Here, we review current findings that lead to a model of PC1 as a key regulator of STAT signaling in renal tubule cells. We discuss how PC1 may orchestrate appropriate epithelial responses to renal injury, and how this system may lead to aberrant STAT activation in ADPKD thereby causing inappropriate activation of tissue repair programs that culminate in renal cyst growth and fibrosis.

Progress in a genome scan for linkage in schizophrenia in a large Swedish kindred

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

Barr, C.L.; Kennedy, J.L.; Pakstis, A.J.

1994-03-15

Genetic linkage studies of a kindred from Sweden segregating for schizophrenia have been performed using a genetic model (autosomal dominant, f - 0.72, q - 0.02, phenocopies=0.001) as described in Kennedy et al., 1988. Analyses of the restriction fragment length polymorphism (RFLP), allele-specific oligonucleotides (ASO), and short tandem repeat (STR also called microsatellite) data for 180 polymorphisms (individual probe-enzyme, ASO, or STR systems) at 155 loci have been completed using the MLINK and LIPED programs. Linkage to schizophrenia was excluded, under the given model, at 47 loci; indeterminate lod scores occurred at 108 loci. The total exclusion region across 20more » chromosomes is estimated at 330 cM; 211 cM excluded by pairwise analyses and 119 cM previously excluded by multipoint analyses. 37 refs., 2 tabs.« less

Infectious diseases: Surveillance, genetic modification and simulation

USGS Publications Warehouse

Koh, H. L.; Teh, S.Y.; De Angelis, D. L.; Jiang, J.

2011-01-01

Infectious diseases such as influenza and dengue have the potential of becoming a worldwide pandemic that may exert immense pressures on existing medical infrastructures. Careful surveillance of these diseases, supported by consistent model simulations, provides a means for tracking the disease evolution. The integrated surveillance and simulation program is essential in devising effective early warning systems and in implementing efficient emergency preparedness and control measures. This paper presents a summary of simulation analysis on influenza A (H1N1) 2009 in Malaysia. This simulation analysis provides insightful lessons regarding how disease surveillance and simulation should be performed in the future. This paper briefly discusses the controversy over the experimental field release of genetically modified (GM) Aedes aegypti mosquito in Malaysia. Model simulations indicate that the proposed release of GM mosquitoes is neither a viable nor a sustainable control strategy. ?? 2011 WIT Press.

Economic evaluation of genomic selection in small ruminants: a sheep meat breeding program.

PubMed

Shumbusho, F; Raoul, J; Astruc, J M; Palhiere, I; Lemarié, S; Fugeray-Scarbel, A; Elsen, J M

2016-06-01

Recent genomic evaluation studies using real data and predicting genetic gain by modeling breeding programs have reported moderate expected benefits from the replacement of classic selection schemes by genomic selection (GS) in small ruminants. The objectives of this study were to compare the cost, monetary genetic gain and economic efficiency of classic selection and GS schemes in the meat sheep industry. Deterministic methods were used to model selection based on multi-trait indices from a sheep meat breeding program. Decisional variables related to male selection candidates and progeny testing were optimized to maximize the annual monetary genetic gain (AMGG), that is, a weighted sum of meat and maternal traits annual genetic gains. For GS, a reference population of 2000 individuals was assumed and genomic information was available for evaluation of male candidates only. In the classic selection scheme, males breeding values were estimated from own and offspring phenotypes. In GS, different scenarios were considered, differing by the information used to select males (genomic only, genomic+own performance, genomic+offspring phenotypes). The results showed that all GS scenarios were associated with higher total variable costs than classic selection (if the cost of genotyping was 123 euros/animal). In terms of AMGG and economic returns, GS scenarios were found to be superior to classic selection only if genomic information was combined with their own meat phenotypes (GS-Pheno) or with their progeny test information. The predicted economic efficiency, defined as returns (proportional to number of expressions of AMGG in the nucleus and commercial flocks) minus total variable costs, showed that the best GS scenario (GS-Pheno) was up to 15% more efficient than classic selection. For all selection scenarios, optimization increased the overall AMGG, returns and economic efficiency. As a conclusion, our study shows that some forms of GS strategies are more advantageous than classic selection, provided that GS is already initiated (i.e. the initial reference population is available). Optimizing decisional variables of the classic selection scheme could be of greater benefit than including genomic information in optimized designs.

International review of cytology. Volume 109: A survey of cell biology

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

Bourne, G.; Jeon, K.W.; Friedlander, M.

1987-01-01

This book's contents are: Local Regulation of Testicular Function;Microtubules and DNA Replication;Differentiation of Spermatogenic Cells from Vertebrates in Vitro;The Developmental Program of Spermiogenesis in Drosophila: A Genetic Analysis;Cell Motility and Ionic Relations in Characean Cells as Revealed by Internal Perfusion and Other Cell Models;and The Culture of Oral Epithelium. Each chapter includes references.

Approaching Science by Watching TV: What Do Entertainment Programs Contribute to Viewers' Competence in Genetic Engineering?

ERIC Educational Resources Information Center

Weinmann, Carina; Löb, Charlotte; Mattheiß, Tamara; Vorderer, Peter

2013-01-01

This study examined the potential of entertainment-education (E-E) for promoting engagement with a science issue. It was assumed that certain entertaining features of a media experience increase viewers' perceived knowledge about an issue. Drawing on different theoretical models of E-E and on persuasive effects of narrative media messages, three…

Culturally Relevant Inquiry-Based Laboratory Module Implementations in Upper-Division Genetics and Cell Biology Teaching Laboratories

ERIC Educational Resources Information Center

Siritunga, Dimuth; Montero-Rojas, Maria; Carrero, Katherine; Toro, Gladys; Velez, Ana; Carrero-Martinez, Franklin A.

2011-01-01

Today, more minority students are entering undergraduate programs than ever before, but they earn only 6% of all science or engineering PhDs awarded in the United States. Many studies suggest that hands-on research activities enhance students' interest in pursuing a research career. In this paper, we present a model for the implementation of…

A gene regulatory network model for floral transition of the shoot apex in maize and its dynamic modeling.

PubMed

Dong, Zhanshan; Danilevskaya, Olga; Abadie, Tabare; Messina, Carlos; Coles, Nathan; Cooper, Mark

2012-01-01

The transition from the vegetative to reproductive development is a critical event in the plant life cycle. The accurate prediction of flowering time in elite germplasm is important for decisions in maize breeding programs and best agronomic practices. The understanding of the genetic control of flowering time in maize has significantly advanced in the past decade. Through comparative genomics, mutant analysis, genetic analysis and QTL cloning, and transgenic approaches, more than 30 flowering time candidate genes in maize have been revealed and the relationships among these genes have been partially uncovered. Based on the knowledge of the flowering time candidate genes, a conceptual gene regulatory network model for the genetic control of flowering time in maize is proposed. To demonstrate the potential of the proposed gene regulatory network model, a first attempt was made to develop a dynamic gene network model to predict flowering time of maize genotypes varying for specific genes. The dynamic gene network model is composed of four genes and was built on the basis of gene expression dynamics of the two late flowering id1 and dlf1 mutants, the early flowering landrace Gaspe Flint and the temperate inbred B73. The model was evaluated against the phenotypic data of the id1 dlf1 double mutant and the ZMM4 overexpressed transgenic lines. The model provides a working example that leverages knowledge from model organisms for the utilization of maize genomic information to predict a whole plant trait phenotype, flowering time, of maize genotypes.

Genetic parameter estimation of reproductive traits of Litopenaeus vannamei

NASA Astrophysics Data System (ADS)

Tan, Jian; Kong, Jie; Cao, Baoxiang; Luo, Kun; Liu, Ning; Meng, Xianhong; Xu, Shengyu; Guo, Zhaojia; Chen, Guoliang; Luan, Sheng

2017-02-01

In this study, the heritability, repeatability, phenotypic correlation, and genetic correlation of the reproductive and growth traits of L. vannamei were investigated and estimated. Eight traits of 385 shrimps from forty-two families, including the number of eggs (EN), number of nauplii (NN), egg diameter (ED), spawning frequency (SF), spawning success (SS), female body weight (BW) and body length (BL) at insemination, and condition factor (K), were measured,. A total of 519 spawning records including multiple spawning and 91 no spawning records were collected. The genetic parameters were estimated using an animal model, a multinomial logit model (for SF), and a sire-dam and probit model (for SS). Because there were repeated records, permanent environmental effects were included in the models. The heritability estimates for BW, BL, EN, NN, ED, SF, SS, and K were 0.49 ± 0.14, 0.51 ± 0.14, 0.12 ± 0.08, 0, 0.01 ± 0.04, 0.06 ± 0.06, 0.18 ± 0.07, and 0.10 ± 0.06, respectively. The genetic correlation was 0.99 ± 0.01 between BW and BL, 0.90 ± 0.19 between BW and EN, 0.22 ± 0.97 between BW and ED, -0.77 ± 1.14 between EN and ED, and -0.27 ± 0.36 between BW and K. The heritability of EN estimated without a covariate was 0.12 ± 0.08, and the genetic correlation was 0.90 ± 0.19 between BW and EN, indicating that improving BW may be used in selection programs to genetically improve the reproductive output of L. vannamei during the breeding. For EN, the data were also analyzed using body weight as a covariate (EN-2). The heritability of EN-2 was 0.03 ± 0.05, indicating that it is difficult to improve the reproductive output by genetic improvement. Furthermore, excessive pursuit of this selection is often at the expense of growth speed. Therefore, the selection of high-performance spawners using BW and SS may be an important strategy to improve nauplii production.

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

NASA Astrophysics Data System (ADS)

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

2008-05-01

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

Polyglot Programming in Applications Used for Genetic Data Analysis

PubMed Central

Nowak, Robert M.

2014-01-01

Applications used for the analysis of genetic data process large volumes of data with complex algorithms. High performance, flexibility, and a user interface with a web browser are required by these solutions, which can be achieved by using multiple programming languages. In this study, I developed a freely available framework for building software to analyze genetic data, which uses C++, Python, JavaScript, and several libraries. This system was used to build a number of genetic data processing applications and it reduced the time and costs of development. PMID:25197633

Polyglot programming in applications used for genetic data analysis.

PubMed

Nowak, Robert M

2014-01-01

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

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

PubMed

Khan, Mohammad Wahab; Alam, Mansaf

2012-08-01

The aim of this paper is to provide an introduction to the rapidly developing field of genetic programming (GP). Particular emphasis is placed on the application of GP to genomics. First, the basic methodology of GP is introduced. This is followed by a review of applications in the areas of gene network inference, gene expression data analysis, SNP analysis, epistasis analysis and gene annotation. Finally this paper concluded by suggesting potential avenues of possible future research on genetic programming, opportunities to extend the technique, and areas for possible practical applications. Copyright © 2012 Elsevier Inc. All rights reserved.

Genetic assessment of a summer chum salmon metapopulation in recovery

PubMed Central

Small, Maureen P; Johnson, Thom H; Bowman, Cherril; Martinez, Edith

2014-01-01

Programs to rebuild imperiled wild fish populations often include hatchery-born fish derived from wild populations to supplement natural spawner abundance. These programs require monitoring to determine their demographic, biological, and genetic effects. In 1990s in Washington State, the Summer Chum Salmon Conservation Initiative developed a recovery program for the threatened Hood Canal summer chum salmon Evolutionarily Significant Unit (ESU) (the metapopulation) that used in-river spawners (wild fish) for each respective supplementation broodstock in six tributaries. Returning spawners (wild-born and hatchery-born) composed subsequent broodstocks, and tributary-specific supplementation was limited to three generations. We assessed impacts of the programs on neutral genetic diversity in this metapopulation using 16 microsatellite loci and a thirty-year dataset spanning before and after supplementation, roughly eight generations. Following supplementation, differentiation among subpopulations decreased (but not significantly) and isolation by distance patterns remained unchanged. There was no decline in genetic diversity in wild-born fish, but hatchery-born fish sampled in the same spawning areas had significantly lower genetic diversity and unequal family representation. Despite potential for negative effects from supplementation programs, few were detected in wild-born fish. We hypothesize that chum salmon natural history makes them less vulnerable to negative impacts from hatchery supplementation. PMID:24567747

Genetic parameters for uniformity of harvest weight and body size traits in the GIFT strain of Nile tilapia.

PubMed

Marjanovic, Jovana; Mulder, Han A; Khaw, Hooi L; Bijma, Piter

2016-06-10

Animal breeding programs have been very successful in improving the mean levels of traits through selection. However, in recent decades, reducing the variability of trait levels between individuals has become a highly desirable objective. Reaching this objective through genetic selection requires that there is genetic variation in the variability of trait levels, a phenomenon known as genetic heterogeneity of environmental (residual) variance. The aim of our study was to investigate the potential for genetic improvement of uniformity of harvest weight and body size traits (length, depth, and width) in the genetically improved farmed tilapia (GIFT) strain. In order to quantify the genetic variation in uniformity of traits and estimate the genetic correlations between level and variance of the traits, double hierarchical generalized linear models were applied to individual trait values. Our results showed substantial genetic variation in uniformity of all analyzed traits, with genetic coefficients of variation for residual variance ranging from 39 to 58 %. Genetic correlation between trait level and variance was strongly positive for harvest weight (0.60 ± 0.09), moderate and positive for body depth (0.37 ± 0.13), but not significantly different from 0 for body length and width. Our results on the genetic variation in uniformity of harvest weight and body size traits show good prospects for the genetic improvement of uniformity in the GIFT strain. A high and positive genetic correlation was estimated between level and variance of harvest weight, which suggests that selection for heavier fish will also result in more variation in harvest weight. Simultaneous improvement of harvest weight and its uniformity will thus require index selection.

Shared genetic and environmental influences on early temperament and preschool psychiatric disorders in Hispanic twins

PubMed Central

Silberg, Judy L.; Gillespie, Nathan; Moore, Ashlee A.; Eaves, Lindon J.; Bates, John; Aggen, Steven; Pfister, Elizabeth; Canino, Glorisa

2015-01-01

Objective Despite an increasing recognition that psychiatric disorders can be diagnosed as early as preschool, little is known how early genetic and environmental risk factors contribute to the development of psychiatric disorders during this very early period of development. Method We assessed infant temperament at age 1, and attention deficit hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), and separation anxiety disorder (SAD) at ages 3 through 5 years in a sample of Hispanic twins. Genetic, shared, and non-shared environmental effects were estimated for each temperamental construct and psychiatric disorder using the statistical program MX. Multivariate genetic models were fitted to determine whether the same or different sets of genes and environments account for the co-occurrence between early temperament and preschool psychiatric disorders. Results Additive genetic factors accounted for 61% of the variance in ADHD, 21% in ODD, and 28% in SAD. Shared environmental factors accounted for 34% of the variance in ODD and 15% of SAD. The genetic influence on difficult temperament was significantly associated with preschool ADHD, SAD, and ODD. The association between ODD and SAD was due to both genetic and family environmental factors. The temperamental trait of resistance to control was entirely accounted for by the shared family environment. Conclusions There are different genetic and family environmental pathways between infant temperament and psychiatric diagnoses in this sample of Puerto Rican preschool age children. PMID:25728588

Shared genetic and environmental influences on early temperament and preschool psychiatric disorders in Hispanic twins.

PubMed

Silberg, Judy L; Gillespie, Nathan; Moore, Ashlee A; Eaves, Lindon J; Bates, John; Aggen, Steven; Pfister, Elizabeth; Canino, Glorisa

2015-04-01

Despite an increasing recognition that psychiatric disorders can be diagnosed as early as preschool, little is known how early genetic and environmental risk factors contribute to the development of psychiatric disorders during this very early period of development. We assessed infant temperament at age 1, and attention deficit hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), and separation anxiety disorder (SAD) at ages 3 through 5 years in a sample of Hispanic twins. Genetic, shared, and non-shared environmental effects were estimated for each temperamental construct and psychiatric disorder using the statistical program MX. Multivariate genetic models were fitted to determine whether the same or different sets of genes and environments account for the co-occurrence between early temperament and preschool psychiatric disorders. Additive genetic factors accounted for 61% of the variance in ADHD, 21% in ODD, and 28% in SAD. Shared environmental factors accounted for 34% of the variance in ODD and 15% of SAD. The genetic influence on difficult temperament was significantly associated with preschool ADHD, SAD, and ODD. The association between ODD and SAD was due to both genetic and family environmental factors. The temperamental trait of resistance to control was entirely accounted for by the shared family environment. There are different genetic and family environmental pathways between infant temperament and psychiatric diagnoses in this sample of Puerto Rican preschool age children.

No boundaries: genomes, organisms, and ecological interactions responsible for divergence and reproductive isolation.

PubMed

Etges, William J

2014-01-01

Revealing the genetic basis of traits that cause reproductive isolation, particularly premating or sexual isolation, usually involves the same challenges as most attempts at genotype-phenotype mapping and so requires knowledge of how these traits are expressed in different individuals, populations, and environments, particularly under natural conditions. Genetic dissection of speciation phenotypes thus requires understanding of the internal and external contexts in which underlying genetic elements are expressed. Gene expression is a product of complex interacting factors internal and external to the organism including developmental programs, the genetic background including nuclear-cytotype interactions, epistatic relationships, interactions among individuals or social effects, stochasticity, and prevailing variation in ecological conditions. Understanding of genomic divergence associated with reproductive isolation will be facilitated by functional expression analysis of annotated genomes in organisms with well-studied evolutionary histories, phylogenetic affinities, and known patterns of ecological variation throughout their life cycles. I review progress and prospects for understanding the pervasive role of host plant use on genetic and phenotypic expression of reproductive isolating mechanisms in cactophilic Drosophila mojavensis and suggest how this system can be used as a model for revealing the genetic basis for species formation in organisms where speciation phenotypes are under the joint influences of genetic and environmental factors. © The American Genetic Association. 2014. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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

PubMed

Simopoulos, A P

2009-01-01

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

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

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

Russell, Liane B.

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

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

PubMed

Russell, Liane B

2013-01-01

The large mouse genetics program at the Oak Ridge National Laboratory (ORNL) is often remembered chiefly for the germ-cell mutation-rate data it generated and their uses in estimating the risk of heritable radiation damage. In fact, it soon became a multi-faceted research effort that, over a period of almost 60 years, generated a wealth of information in the areas of mammalian mutagenesis, basic genetics (later enriched by molecular techniques), cytogenetics, reproductive biology, biochemistry of germ cells, and teratology. Research in the area of germ-cell mutagenesis explored the important physical and biological factors that affect the frequency and nature of induced mutations and made several unexpected discoveries, such as the major importance of the perigametic interval (the zygote stage) for the origin of spontaneous mutations and for the sensitivity to induced genetic change. Of practical value was the discovery that ethylnitrosourea was a supermutagen for point mutations, making high-efficiency mutagenesis in the mouse feasible worldwide. Teratogenesis findings resulted in recommendations still generally accepted in radiological practice. Studies supporting the mutagenesis research added whole bodies of information about mammalian germ-cell development and about molecular targets in germ cells. The early decision to not merely count but propagate genetic variants of all sorts made possible further discoveries, such as the Y-chromosome's importance in mammalian sex determination and the identification of rare X-autosome translocations, which, in turn, led to the formulation of the single-active-X hypothesis and provided tools for studies of functional mosaicism for autosomal genes, male sterility, and chromosome-pairing mechanism. Extensive genetic and then molecular analyses of large numbers of induced specific-locus mutants resulted in fine-structure physical and correlated functional mapping of significant portions of the mouse genome and constituted a valuable source of mouse models for human genetic disorders. Copyright © 2013 Elsevier B.V. All rights reserved.

Genetics and Common Disorders: Implications for Primary Care and Public Health Providers

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

McInerney, Joseph D.; Greendale, Karen; Peay, Holly L.

We developed this program for primary care providers (PCPs) and public health professionals (PHPs) who are interested in increasing their understanding of the genetics of common chronic diseases and of the implications of genetics and genomics for their fields. The program differs from virtually all previous educational efforts in genetics for health professionals in that it focuses on the genetics of common chronic disease and on the broad principles that emerge when one views disease from the perspectives of variation and individuality, which are at the heart of thinking genetically. The CD-ROM introduces users to content that will improve theirmore » understanding of topics such as: • A framework for genetics and common disease; • Basic information on genetics, genomics, genetic medicine, and public health genetics, all in the context of common chronic disease; • The status of research on genetic contributions to specific common diseases, including a review of research methods; • Genetic/environmental interaction as the new “central dogma” of public health genetics; • The importance of taking and analyzing a family history; • The likely impact of potential gene discovery and genetic testing on genetic counseling and risk assessment and on the practices of PCPs and PHPs; • Stratification of populations into low-, moderate-, and high-risk categories; • The potential role of PCPs and PHPs in identifying high-risk individuals and families, in providing limited genetics services, and in referring to clinical genetics specialists; the potential for standard referral algorithms; • Implications of genetic insights for diagnosis and treatment; • Ethical, legal, and social issues that arise from genetic testing for common chronic diseases; and • Specific prevention strategies based on understanding of genetics and genetic/ environmental interactions. The interactive content – developed by experts in genetics, primary care, and public health – is organized around two case studies designed to appeal to primary care providers (thrombophilia) and public health professionals (development of a screening grogram for colorectal cancer). NCHPEG has distributed more than 0000 copies of the CD-ROM to NCHPEG member organizations and to other organizations and individuals in response to requests. The program also is available at www.nchpeg.org.« less

Introduction to the Natural Anticipator and the Artificial Anticipator

NASA Astrophysics Data System (ADS)

Dubois, Daniel M.

2010-11-01

This short communication deals with the introduction of the concept of anticipator, which is one who anticipates, in the framework of computing anticipatory systems. The definition of anticipation deals with the concept of program. Indeed, the word program, comes from "pro-gram" meaning "to write before" by anticipation, and means a plan for the programming of a mechanism, or a sequence of coded instructions that can be inserted into a mechanism, or a sequence of coded instructions, as genes or behavioural responses, that is part of an organism. Any natural or artificial programs are thus related to anticipatory rewriting systems, as shown in this paper. All the cells in the body, and the neurons in the brain, are programmed by the anticipatory genetic code, DNA, in a low-level language with four signs. The programs in computers are also computing anticipatory systems. It will be shown, at one hand, that the genetic code DNA is a natural anticipator. As demonstrated by Nobel laureate McClintock [8], genomes are programmed. The fundamental program deals with the DNA genetic code. The properties of the DNA consist in self-replication and self-modification. The self-replicating process leads to reproduction of the species, while the self-modifying process leads to new species or evolution and adaptation in existing ones. The genetic code DNA keeps its instructions in memory in the DNA coding molecule. The genetic code DNA is a rewriting system, from DNA coding to DNA template molecule. The DNA template molecule is a rewriting system to the Messenger RNA molecule. The information is not destroyed during the execution of the rewriting program. On the other hand, it will be demonstrated that Turing machine is an artificial anticipator. The Turing machine is a rewriting system. The head reads and writes, modifying the content of the tape. The information is destroyed during the execution of the program. This is an irreversible process. The input data are lost.

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

PubMed

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

2015-01-01

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

Effects of Genotype by Environment Interaction on Genetic Gain and Genetic Parameter Estimates in Red Tilapia (Oreochromis spp.)

PubMed Central

Nguyen, Nguyen H.; Hamzah, Azhar; Thoa, Ngo P.

2017-01-01

The extent to which genetic gain achieved from selection programs under strictly controlled environments in the nucleus that can be expressed in commercial production systems is not well-documented in aquaculture species. The main aim of this paper was to assess the effects of genotype by environment interaction on genetic response and genetic parameters for four body traits (harvest weight, standard length, body depth, body width) and survival in Red tilapia (Oreochromis spp.). The growth and survival data were recorded on 19,916 individual fish from a pedigreed population undergoing three generations of selection for increased harvest weight in earthen ponds from 2010 to 2012 at the Aquaculture Extension Center, Department of Fisheries, Jitra in Kedah, Malaysia. The pedigree comprised a total of 224 sires and 262 dams, tracing back to the base population in 2009. A multivariate animal model was used to measure genetic response and estimate variance and covariance components. When the homologous body traits in freshwater pond and cage were treated as genetically distinct traits, the genetic correlations between the two environments were high (0.85–0.90) for harvest weight and square root of harvest weight but the estimates were of lower magnitudes for length, width and depth (0.63–0.79). The heritabilities estimated for the five traits studied differed between pond (0.02 to 0.22) and cage (0.07 to 0.68). The common full-sib effects were large, ranging from 0.23 to 0.59 in pond and 0.11 to 0.31 in cage across all traits. The direct and correlated responses for four body traits were generally greater in pond than in cage environments (0.011–1.561 vs. −0.033–0.567 genetic standard deviation units, respectively). Selection for increased harvest body weight resulted in positive genetic changes in survival rate in both pond and cage culture. In conclusion, the reduced selection response and the magnitude of the genetic parameter estimates in the production environment (i.e., cage) relative to those achieved in the nucleus (pond) were a result of the genotype by environment interaction and this effect should be taken into consideration in the future breeding program for Red tilapia. PMID:28659970

Geography and end use drive the diversification of worldwide winter rye populations.

PubMed

Parat, Florence; Schwertfirm, Grit; Rudolph, Ulrike; Miedaner, Thomas; Korzun, Viktor; Bauer, Eva; Schön, Chris-Carolin; Tellier, Aurélien

2016-01-01

To meet the current challenges in human food production, improved understanding of the genetic diversity of crop species that maximizes the selection efficacy in breeding programs is needed. The present study offers new insights into the diversity, genetic structure and demographic history of cultivated rye (Secale cereale L.). We genotyped 620 individuals from 14 global rye populations with a different end use (grain or forage) at 32 genome-wide simple sequence repeat markers. We reveal the relationships among these populations, their sizes and the timing of domestication events using population genetics and model-based inference with approximate Bayesian computation. Our main results demonstrate (i) a high within-population variation and genetic diversity, (ii) an unexpected absence of reduction in diversity with an increasing improvement level and (iii) patterns suggestive of multiple domestication events. We suggest that the main drivers of diversification of winter rye are the end use of rye in two early regions of cultivation: rye forage in the Mediterranean area and grain in northeast Europe. The lower diversity and stronger differentiation of eastern European populations were most likely due to more intensive cultivation and breeding of rye in this region, in contrast to the Mediterranean region where it was considered a secondary crop or even a weed. We discuss the relevance of our results for the management of gene bank resources and the pitfalls of inference methods applied to crop domestication due to violation of model assumptions and model complexity. © 2015 John Wiley & Sons Ltd.

The restoration of the endangered Sambucus palmensis after 30 years of conservation actions in the Garajonay National Park: genetic assessment and niche modeling.

PubMed

Rodríguez-Rodríguez, Priscila; Fernández de Castro, Alejandro G; Sosa, Pedro A

2018-01-01

The translocation of individuals or the reinforcement of populations are measures in the genetic rescue of endangered species. Although it can be controversial to decide which and how many individuals must be reintroduced, populations can benefit from reinforcements. Sambucus palmensis is a critically endangered endemic to the Canary Islands. During the past 30 years, the Garajonay National Park (La Gomera) has carried out an intensive program of translocations using cuttings, due to the low germination rates of seeds. To assess the effect of the restorations on the population genetics of S. palmensis in La Gomera, we collected 402 samples from all the restored sites and all known natural individuals, which were genotyped with seven microsatellite markers. In addition, we conducted a species distribution modeling approach to assess how restorations fit the ecological niche of the species. Results show that there is a high proportion of clone specimens due to the propagation method, and the natural clonal reproduction of the species. Nonetheless, the observed heterozygosity has increased with the restorations and there still are private alleles and unique genotypes in the natural populations that have not been considered in the restorations. The population of Liria constitutes a very important genetic reservoir for the species. To optimize future reintroductions, we have proposed a list of specimens that are suitable for the extraction of seeds or cuttings in a greenhouse, as well as new suitable areas obtained by the species distribution models.

Lamb survival analysis from birth to weaning in Iranian Kermani sheep.

PubMed

Barazandeh, Arsalan; Moghbeli, Sadrollah Molaei; Vatankhah, Mahmood; Hossein-Zadeh, Navid Ghavi

2012-04-01

Survival records from 1,763 Kermani lambs born between 1996 and 2004 from 294 ewes and 81 rams were used to determine genetic and non-genetic factors affecting lamb survival. Traits included were lamb survival across five periods from birth to 7, 14, 56, 70, and 90 days of age. Traits were analyzed under Weibull proportional hazard sire models. Several binary analyses were also conducted using animal models. Statistical models included the fixed class effects of sex of lamb, month and year of birth, a covariate effect of birth weight, and random genetic effects of both sire (in survival analyses) and animal (in binary analyses). The average survival to 90 days of age was 94.8%. Hazard rates ranged from 1.00 (birth to 90 days of age) to 1.73 (birth to 7 days of age) between the two sexes indicating that male lambs were at higher risk of mortality than females (P < 0.01). This study also revealed a curvilinear relationship between lamb survival and lamb birth weight, suggesting that viability and birth weight could be considered simultaneously in the selection programs to obtain optimal birth weight in Kermani lambs. Estimates of heritabilities from survival analyses were medium and ranged from 0.23 to 0.29. In addition, heritability estimates obtained from binary analyses were low and varied from 0.04 to 0.09. The results of this study suggest that progress in survival traits could be possible through managerial strategies and genetic selection.

Genetic Network Programming with Reconstructed Individuals

NASA Astrophysics Data System (ADS)

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

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

Genetics objective structured clinical exams at the Maimonides Infants & Children's Hospital of Brooklyn, New York.

PubMed

Altshuler, Lisa; Kachur, Elizabeth; Krinshpun, Shifra; Sullivan, Deborah

2008-11-01

In 2003, the Maimonides Infants & Children's Hospital received a Title VII Residency Training in Primary Care grant to integrate genetic-specific competencies into postgraduate pediatrics education. As part of that endeavor, mandatory yearly genetics objective structured clinical exams (OSCEs) were instituted for third-year residents. This article reports on the first three years of experience with this innovative educational tool.After an overview of genetic concepts, dysmorphology, and communication styles, residents complete a five-station OSCE and receive feedback from standardized patients and from the faculty who observe them. After this clinical exercise, the residents participate in a small-group debriefing session to share strategies for effective communication and clinical case management and to discuss the ethical issues that arise with these genetic cases.In three years, 60 residents have completed the genetics OSCE program. Evaluation data demonstrate that the program has been effective in both introducing genetic-specific challenges and assessing residents' clinical skills. It has helped trainees self-identify both strengths and further training needs. Pre- and postsurveys among the trainees show increased comfort levels in performing 5 of 12 genetic-related clinical tasks.We conclude that genetics OSCEs are an enriching educational tool. Merely providing trainees and practicing physicians with the latest scientific information is unlikely to prepare them for counseling patients about complex genetic issues. Developing proficiency requires focused practice and effective feedback.This article is part of a theme issue of Academic Medicine on the Title VII health professions training programs.

National Newborn Screening and Genetics Resource Center

MedlinePlus

... GENERAL INFORMATION Conditions Screened by US Programs General Resources Genetics Birth Defects Hearing Screening FOR PROFESSIONALS ACT Sheets(ACMG) General Resources Newborn Screening Genetics Birth Defects FOR FAMILIES FAQs ...

Historical changes in population structure during rice breeding programs in the northern limits of rice cultivation.

PubMed

Shinada, Hiroshi; Yamamoto, Toshio; Yamamoto, Eiji; Hori, Kiyosumi; Yonemaru, Junichi; Matsuba, Shuichi; Fujino, Kenji

2014-04-01

The rice local population was clearly differentiated into six groups over the 100-year history of rice breeding programs in the northern limit of rice cultivation over the world. Genetic improvements in plant breeding programs in local regions have led to the development of new cultivars with specific agronomic traits under environmental conditions and generated the unique genetic structures of local populations. Understanding historical changes in genome structures and phenotypic characteristics within local populations may be useful for identifying profitable genes and/or genetic resources and the creation of new gene combinations in plant breeding programs. In the present study, historical changes were elucidated in genome structures and phenotypic characteristics during 100-year rice breeding programs in Hokkaido, the northern limit of rice cultivation in the world. We selected 63 rice cultivars to represent the historical diversity of this local population from landraces to the current breeding lines. The results of the phylogenetic analysis demonstrated that these cultivars clearly differentiated into six groups over the history of rice breeding programs. Significant differences among these groups were detected in five of the seven traits, indicating that the differentiation of the Hokkaido rice population into these groups was correlated with these phenotypic changes. These results demonstrated that breeding practices in Hokkaido have created new genetic structures for adaptability to specific environmental conditions and breeding objectives. They also provide a new strategy for rice breeding programs in which such unique genes in local populations in the world can explore the genetic potentials of the local populations.

High genetic diversity of Jatropha curcas assessed by ISSR.

PubMed

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

2017-05-31

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

Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern

USGS Publications Warehouse

Landguth, Erin L.; Gedy, Bradley C.; Oyler-McCance, Sara J.; Garey, Andrew L.; Emel, Sarah L.; Mumma, Matthew; Wagner, Helene H.; Fortin, Marie-Josée; Cushman, Samuel A.

2012-01-01

The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially-explicit, individual-based program to simulate gene flow in a spatially continuous population inhabiting a landscape with gradual spatial changes in resistance to movement. We simulated a wide range of combinations of number of loci, number of alleles per locus and number of individuals sampled from the population. We assessed how these three aspects of study design influenced the statistical power to successfully identify the generating process among competing hypotheses of isolation-by-distance, isolation-by-barrier, and isolation-by-landscape resistance using a causal modelling approach with partial Mantel tests. We modelled the statistical power to identify the generating process as a response surface for equilibrium and non-equilibrium conditions after introduction of isolation-by-landscape resistance. All three variables (loci, alleles and sampled individuals) affect the power of causal modelling, but to different degrees. Stronger partial Mantel r correlations between landscape distances and genetic distances were found when more loci were used and when loci were more variable, which makes comparisons of effect size between studies difficult. Number of individuals did not affect the accuracy through mean equilibrium partial Mantel r, but larger samples decreased the uncertainty (increasing the precision) of equilibrium partial Mantel r estimates. We conclude that amplifying more (and more variable) loci is likely to increase the power of landscape genetic inferences more than increasing number of individuals.

Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern

USGS Publications Warehouse

Landguth, E.L.; Fedy, B.C.; Oyler-McCance, S.J.; Garey, A.L.; Emel, S.L.; Mumma, M.; Wagner, H.H.; Fortin, M.-J.; Cushman, S.A.

2012-01-01

The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially-explicit, individual-based program to simulate gene flow in a spatially continuous population inhabiting a landscape with gradual spatial changes in resistance to movement. We simulated a wide range of combinations of number of loci, number of alleles per locus and number of individuals sampled from the population. We assessed how these three aspects of study design influenced the statistical power to successfully identify the generating process among competing hypotheses of isolation-by-distance, isolation-by-barrier, and isolation-by-landscape resistance using a causal modelling approach with partial Mantel tests. We modelled the statistical power to identify the generating process as a response surface for equilibrium and non-equilibrium conditions after introduction of isolation-by-landscape resistance. All three variables (loci, alleles and sampled individuals) affect the power of causal modelling, but to different degrees. Stronger partial Mantel r correlations between landscape distances and genetic distances were found when more loci were used and when loci were more variable, which makes comparisons of effect size between studies difficult. Number of individuals did not affect the accuracy through mean equilibrium partial Mantel r, but larger samples decreased the uncertainty (increasing the precision) of equilibrium partial Mantel r estimates. We conclude that amplifying more (and more variable) loci is likely to increase the power of landscape genetic inferences more than increasing number of individuals. ?? 2011 Blackwell Publishing Ltd.

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

NASA Astrophysics Data System (ADS)

Yang, Wen-Xian

2006-05-01

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

Determinism and Underdetermination in Genetics: Implications for Students' Engagement in Argumentation and Epistemic Practices

NASA Astrophysics Data System (ADS)

Jiménez-Aleixandre, María Pilar

2014-02-01

In the last two decades science studies and science education research have shifted from an interest in products (of science or of learning), to an interest in processes and practices. The focus of this paper is on students' engagement in epistemic practices (Kelly in Teaching scientific inquiry: Recommendations for research and implementation. Sense Publishers, Rotterdam, pp 99-117, 2008), or on their practical epistemologies (Wickman in Sci Educ 88(3):325-344, 2004). In order to support these practices in genetics classrooms we need to take into account domain-specific features of the epistemology of genetics, in particular issues about determinism and underdetermination. I suggest that certain difficulties may be related to the specific nature of causality in genetics, and in particular to the correspondence between a given set of factors and a range of potential effects, rather than a single one. The paper seeks to bring together recent developments in the epistemology of biology and of genetics, on the one hand, with science education approaches about epistemic practices, on the other. The implications of these perspectives for current challenges in learning genetics are examined, focusing on students' engagement in epistemic practices, as argumentation, understood as using evidence to evaluate knowledge claims. Engaging in argumentation in genetics classrooms is intertwined with practices such as using genetics models to build explanations, or framing genetics issues in their social context. These challenges are illustrated with studies making part of our research program in the USC.

Determinants of children's eating behavior.

PubMed

Scaglioni, Silvia; Arrizza, Chiara; Vecchi, Fiammetta; Tedeschi, Sabrina

2011-12-01

Parents have a high degree of control over the environments and experiences of their children. Food preferences are shaped by a combination of genetic and environmental factors. This article is a review of current data on effective determinants of children's eating habits. The development of children's food preferences involves a complex interplay of genetic, familial, and environmental factors. There is evidence of a strong genetic influence on appetite traits in children, but environment plays an important role in modeling children's eating behaviors. Parents use a variety of strategies to influence children's eating habits, some of which are counterproductive. Overcontrol, restriction, pressure to eat, and a promise of rewards have negative effects on children's food acceptance. Parents' food preferences and eating behaviors provide an opportunity to model good eating habits. Satiety is closely related to diet composition, and foods with low energy density contribute to prevent overeating. Parents should be informed about the consequences of an unhealthy diet and lifestyle and motivated to change their nutritional habits. Parents should be the target of prevention programs because children model themselves on their parents' eating behaviors, lifestyles, eating-related attitudes, and dissatisfaction regarding body image. Pediatricians can have an important role in the prevention of diet-related diseases. Informed and motivated parents can become a model for children by offering a healthy, high-satiety, low-energy-dense diet and promoting self-regulation from the first years of life.

Novel applications of multitask learning and multiple output regression to multiple genetic trait prediction.

PubMed

He, Dan; Kuhn, David; Parida, Laxmi

2016-06-15

Given a set of biallelic molecular markers, such as SNPs, with genotype values encoded numerically on a collection of plant, animal or human samples, the goal of genetic trait prediction is to predict the quantitative trait values by simultaneously modeling all marker effects. Genetic trait prediction is usually represented as linear regression models. In many cases, for the same set of samples and markers, multiple traits are observed. Some of these traits might be correlated with each other. Therefore, modeling all the multiple traits together may improve the prediction accuracy. In this work, we view the multitrait prediction problem from a machine learning angle: as either a multitask learning problem or a multiple output regression problem, depending on whether different traits share the same genotype matrix or not. We then adapted multitask learning algorithms and multiple output regression algorithms to solve the multitrait prediction problem. We proposed a few strategies to improve the least square error of the prediction from these algorithms. Our experiments show that modeling multiple traits together could improve the prediction accuracy for correlated traits. The programs we used are either public or directly from the referred authors, such as MALSAR (http://www.public.asu.edu/~jye02/Software/MALSAR/) package. The Avocado data set has not been published yet and is available upon request. dhe@us.ibm.com. © The Author 2016. Published by Oxford University Press.

Psychosocially influenced cancer: diverse early-life stress experiences and links to breast cancer.

PubMed

Schuler, Linda A; Auger, Anthony P

2010-11-01

This perspective on Boyd et al. (beginning on page 1398 in this issue of the journal) discusses recent published research examining the interplay between social stress and breast cancer. Cross-disciplinary studies using genetically defined mouse models and established neonatal and peripubertal paradigms of social stress are illuminating biological programming by diverse early-life experiences for the risk of breast cancer. Understanding the mechanisms underlying this programming can lead to the identification of risk factors and sensitive developmental windows, enabling improved prevention and treatment strategies for this devastating disease. ©2010 AACR.

Testcross additive and dominance effects in best linear unbiased prediction of maize single-cross performance.

PubMed

Bernardo, R

1996-11-01

Best linear unbiased prediction (BLUP) has been found to be useful in maize (Zea mays L.) breeding. The advantage of including both testcross additive and dominance effects (Intralocus Model) in BLUP, rather than only testcross additive effects (Additive Model), has not been clearly demonstrated. The objective of this study was to compare the usefulness of Intralocus and Additive Models for BLUP of maize single-cross performance. Multilocation data from 1990 to 1995 were obtained from the hybrid testing program of Limagrain Genetics. Grain yield, moisture, stalk lodging, and root lodging of untested single crosses were predicted from (1) the performance of tested single crosses and (2) known genetic relationships among the parental inbreds. Correlations between predicted and observed performance were obtained with a delete-one cross-validation procedure. For the Intralocus Model, the correlations ranged from 0.50 to 0.66 for yield, 0.88 to 0.94 for moisture, 0.47 to 0.69 for stalk lodging, and 0.31 to 0.45 for root lodging. The BLUP procedure was consistently more effective with the Intralocus Model than with the Additive Model. When the Additive Model was used instead of the Intralocus Model, the reductions in the correlation were largest for root lodging (0.06-0.35), smallest for moisture (0.00-0.02), and intermediate for yield (0.02-0.06) and stalk lodging (0.02-0.08). The ratio of dominance variance (v D) to total genetic variance (v G) was highest for root lodging (0.47) and lowest for moisture (0.10). The Additive Model may be used if prior information indicates that VD for a given trait has little contribution to VG. Otherwise, the continued use of the Intralocus Model for BLUP of single-cross performance is recommended.

Epistasis analysis using artificial intelligence.

PubMed

Moore, Jason H; Hill, Doug P

2015-01-01

Here we introduce artificial intelligence (AI) methodology for detecting and characterizing epistasis in genetic association studies. The ultimate goal of our AI strategy is to analyze genome-wide genetics data as a human would using sources of expert knowledge as a guide. The methodology presented here is based on computational evolution, which is a type of genetic programming. The ability to generate interesting solutions while at the same time learning how to solve the problem at hand distinguishes computational evolution from other genetic programming approaches. We provide a general overview of this approach and then present a few examples of its application to real data.

Nurses' knowledge and educational needs regarding genetics.

PubMed

Seven, Memnun; Akyüz, Aygül; Elbüken, Burcu; Skirton, Heather; Öztürk, Hatice

2015-03-01

Nurses now require a basic knowledge of genetics to provide patient care in a range of settings. To determine Turkish registered nurses' current knowledge and educational needs in relation to genetics. A descriptive, cross-sectional study. Turkish registered nurses working in a university hospital in Turkey were recruited. All registered nurses were invited to participate and 175 completed the study. The survey instrument, basic knowledge of health genetics, confidence in knowledge and the nurses' need for genetics education were used to collect data. The majority (81.1%, n=142) of participants indicated that genetics was not taught during their degree program, although 53.1% to 96% of respondents felt confident in defining different genetic concepts. The average genetics knowledge score was 6.89±1.99 of a possible 11 (range 0-11). The majority (70.3%) expressed a strong wish to attend a continuing nursing education program in genetics. The study shows that although Turkish nurses are not sufficiently knowledgeable to apply genetics in practice, they are willing to have more education to support their care of patients. Nurses need to have more education related to genetics in accordance with advances in human genetics to optimize health care. Copyright © 2014 Elsevier Ltd. All rights reserved.

Multi-period response management to contaminated water distribution networks: dynamic programming versus genetic algorithms

NASA Astrophysics Data System (ADS)

Bashi-Azghadi, Seyyed Nasser; Afshar, Abbas; Afshar, Mohammad Hadi

2018-03-01

Previous studies on consequence management assume that the selected response action including valve closure and/or hydrant opening remains unchanged during the entire management period. This study presents a new embedded simulation-optimization methodology for deriving time-varying operational response actions in which the network topology may change from one stage to another. Dynamic programming (DP) and genetic algorithm (GA) are used in order to minimize selected objective functions. Two networks of small and large sizes are used in order to illustrate the performance of the proposed modelling schemes if a time-dependent consequence management strategy is to be implemented. The results show that for a small number of decision variables even in large-scale networks, DP is superior in terms of accuracy and computer runtime. However, as the number of potential actions grows, DP loses its merit over the GA approach. This study clearly proves the priority of the proposed dynamic operation strategy over the commonly used static strategy.

Web application for automatic prediction of gene translation elongation efficiency.

PubMed

Sokolov, Vladimir; Zuraev, Bulat; Lashin, Sergei; Matushkin, Yury

2015-09-03

Expression efficiency is one of the major characteristics describing genes in various modern investigations. Expression efficiency of genes is regulated at various stages: transcription, translation, posttranslational protein modification and others. In this study, a special EloE (Elongation Efficiency) web application is described. The EloE sorts the organism's genes in a descend order on their theoretical rate of the elongation stage of translation based on the analysis of their nucleotide sequences. Obtained theoretical data have a significant correlation with available experimental data of gene expression in various organisms. In addition, the program identifies preferential codons in organism's genes and defines distribution of potential secondary structures energy in 5´ and 3´ regions of mRNA. The EloE can be useful in preliminary estimation of translation elongation efficiency for genes for which experimental data are not available yet. Some results can be used, for instance, in other programs modeling artificial genetic structures in genetically engineered experiments.

The use of genetically modified mice in cancer risk assessment: challenges and limitations.

PubMed

Eastmond, David A; Vulimiri, Suryanarayana V; French, John E; Sonawane, Babasaheb

2013-09-01

The use of genetically modified (GM) mice to assess carcinogenicity is playing an increasingly important role in the safety evaluation of chemicals. While progress has been made in developing and evaluating mouse models such as the Trp53⁺/⁻, Tg.AC and the rasH2, the suitability of these models as replacements for the conventional rodent cancer bioassay and for assessing human health risks remains uncertain. The objective of this research was to evaluate the use of accelerated cancer bioassays with GM mice for assessing the potential health risks associated with exposure to carcinogenic agents. We compared the published results from the GM bioassays to those obtained in the National Toxicology Program's conventional chronic mouse bioassay for their potential use in risk assessment. Our analysis indicates that the GM models are less efficient in detecting carcinogenic agents but more consistent in identifying non-carcinogenic agents. We identified several issues of concern related to the design of the accelerated bioassays (e.g., sample size, study duration, genetic stability and reproducibility) as well as pathway-dependency of effects, and different carcinogenic mechanisms operable in GM and non-GM mice. The use of the GM models for dose-response assessment is particularly problematic as these models are, at times, much more or less sensitive than the conventional rodent cancer bioassays. Thus, the existing GM mouse models may be useful for hazard identification, but will be of limited use for dose-response assessment. Hence, caution should be exercised when using GM mouse models to assess the carcinogenic risks of chemicals.

Progress, challenges and perspectives on fish gamete cryopreservation: A mini-review.

PubMed

Asturiano, Juan F; Cabrita, Elsa; Horváth, Ákos

2017-05-01

Protocols for the cryopreservation of fish gametes have been developed for many different fish species, in special, freshwater salmonids and cyprinids. Methods for sperm freezing have progressed during the last decades due to the increasing number of potential applications: aquaculture (genetic improvement programs, broodstock management, helping with species having reproductive problems), biotechnology studies using model fish species (preservation of transgenic or mutant lines), cryobanking of genetic resources from endangered species, etc. This mini-review tries to give an overview of the present situation of this area of research, identifying the main challenges and perspectives, redirecting the reader to more in-depth reviews and papers. Copyright © 2016 Elsevier Inc. All rights reserved.

[Programmed mouse genome modifications].

PubMed

Babinet, C

1998-02-01

The availability, in the mouse, of embryonic stem cells (ES cells) which have the ability to colonize the germ line of a developing embryo, has opened entirely new avenues to the genetic approach of embryonic development, physiology and pathology of this animal. Indeed, it is now possible, using homologous recombination in ES cells, to introduce mutations in any gene as long as it has been cloned. Thus, null as well as more subtle mutations can be created. Furthermore, scenarios are currently being derived which will allow one to generate conditional mutations. Taken together, these methods offer a tremendous tool to study gene function in vivo; they also open the way to creating murine models of human genetic diseases.

Hypoxia as a therapy for mitochondrial disease.

PubMed

Jain, Isha H; Zazzeron, Luca; Goli, Rahul; Alexa, Kristen; Schatzman-Bone, Stephanie; Dhillon, Harveen; Goldberger, Olga; Peng, Jun; Shalem, Ophir; Sanjana, Neville E; Zhang, Feng; Goessling, Wolfram; Zapol, Warren M; Mootha, Vamsi K

2016-04-01

Defects in the mitochondrial respiratory chain (RC) underlie a spectrum of human conditions, ranging from devastating inborn errors of metabolism to aging. We performed a genome-wide Cas9-mediated screen to identify factors that are protective during RC inhibition. Our results highlight the hypoxia response, an endogenous program evolved to adapt to limited oxygen availability. Genetic or small-molecule activation of the hypoxia response is protective against mitochondrial toxicity in cultured cells and zebrafish models. Chronic hypoxia leads to a marked improvement in survival, body weight, body temperature, behavior, neuropathology, and disease biomarkers in a genetic mouse model of Leigh syndrome, the most common pediatric manifestation of mitochondrial disease. Further preclinical studies are required to assess whether hypoxic exposure can be developed into a safe and effective treatment for human diseases associated with mitochondrial dysfunction. Copyright © 2016, American Association for the Advancement of Science.

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

PubMed

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.

Influence of Genetic Counseling Graduate Program Websites on Student Application Decisions.

PubMed

Ivan, Kristina M; Hassed, Susan; Darden, Alix G; Aston, Christopher E; Guy, Carrie

2017-12-01

This study investigated how genetic counseling educational program websites affect application decisions via an online survey sent to current students and recent graduates. Program leadership: directors, assistant directors, associate directors, were also surveyed to determine where their opinions coincided or differed from those reported by students and recent graduates. Chi square analysis and t-tests were used to determine significance of results. A two-sample t-test was used to compare factors students identified as important on a 5-point Likert scale with those identified by directors. Thematic analysis revealed three major themes students consider important for program websites: easy navigation, website content, and website impression. Directors were interested in how prospective students use their program website and what information they found most useful. Students indicated there were specific programs they chose not to apply to due to the difficulty of using the website for that program. Directors significantly underestimated how important information about application requirements was to students in making application decisions. The information reported herein will help individual genetic counseling graduate programs improve website functionality and retain interested applicants.

Algorithmic Trading with Developmental and Linear Genetic Programming

NASA Astrophysics Data System (ADS)

Wilson, Garnett; Banzhaf, Wolfgang

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

Programming languages for circuit design.

PubMed

Pedersen, Michael; Yordanov, Boyan

2015-01-01

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

Genetic parameters for milk production traits and breeding goals for Gir dairy cattle in Brazil.

PubMed

Prata, M A; Faro, L E; Moreira, H L; Verneque, R S; Vercesi Filho, A E; Peixoto, M G C D; Cardoso, V L

2015-10-19

To implement an animal breeding program, it is important to define the production circumstances of the animals of interest to determine which traits of economic interest will be selected for the breeding goal. The present study defined breeding goals and proposed selection indices for milk production and quality traits of Gir dairy cattle. First, a bioeconomic model was developed to calculate economic values. The genetic and phenotypic parameters were estimated based on records from 22,468 first-lactation Gir dairy cows and their crosses for which calving occurred between 1970 and 2011. Statistical analyses were carried out for the animal model, with multitrait analyses using the restricted maximum likelihood method. Two situations were created in the present study to define the breeding goals: 1) including only milk yield in the breeding goal (HGL1) and 2) including fat and protein in addition to the milk yield (HGL2). The heritability estimates for milk, protein, and fat production were 0.33 ± 0.02, 0.26 ± 0.02, and 0.24 ± 0.02, respectively. All phenotypic and genetic correlations were highly positive. The economic values for milk, fat, and protein were US$0.18, US$0.27, and US$7.04, respectively. The expected economic responses for HGL2 and for HGL1 were US$126.30 and US$79.82, respectively. These results indicate that milk component traits should be included in a selection index to rank animals evaluated in the National Gir Dairy Breeding Program developed in Brazil.

Teaching Molecular Biology with Microcomputers.

ERIC Educational Resources Information Center

Reiss, Rebecca; Jameson, David

1984-01-01

Describes a series of computer programs that use simulation and gaming techniques to present the basic principles of the central dogma of molecular genetics, mutation, and the genetic code. A history of discoveries in molecular biology is presented and the evolution of these computer assisted instructional programs is described. (MBR)

Harnessing quantitative genetics and genomics for understanding and improving complex traits in crops

USDA-ARS?s Scientific Manuscript database

Classical quantitative genetics aids crop improvement by providing the means to estimate heritability, genetic correlations, and predicted responses to various selection schemes. Genomics has the potential to aid quantitative genetics and applied crop improvement programs via large-scale, high-thro...

Quality assurance and quality improvement in U.S. clinical molecular genetic laboratories.

PubMed

Chen, Bin; Richards, C Sue; Wilson, Jean Amos; Lyon, Elaine

2011-04-01

A robust quality-assurance program is essential for laboratories that perform molecular genetic testing to maintain high-quality testing and be able to address challenges associated with performance or delivery of testing services as the use of molecular genetic tests continues to expand in clinical and public health practice. This unit discusses quality-assurance and quality-improvement considerations that are critical for molecular genetic testing performed for heritable diseases and conditions. Specific discussion is provided on applying regulatory standards and best practices in establishing/verifying test performance, ensuring quality of the total testing process, monitoring and maintaining personnel competency, and continuing quality improvement. The unit provides a practical reference for laboratory professionals to use in recognizing and addressing essential quality-assurance issues in human molecular genetic testing. It should also provide useful information for genetics researchers, trainees, and fellows in human genetics training programs, as well as others who are interested in quality assurance and quality improvement for molecular genetic testing. 2011 by John Wiley & Sons, Inc.

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

PubMed

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

2015-11-13

The development of quantitative structure-retention relationships (QSRR) aims at constructing an appropriate linear/nonlinear model for the prediction of the retention behavior (such as Kovats retention index) of a solute on a chromatographic column. Commonly, multi-linear regression and artificial neural networks are used in the QSRR development in the gas chromatography (GC). In this study, an artificial intelligence based data-driven modeling formalism, namely genetic programming (GP), has been introduced for the development of quantitative structure based models predicting Kovats retention indices (KRI). The novelty of the GP formalism is that given an example dataset, it searches and optimizes both the form (structure) and the parameters of an appropriate linear/nonlinear data-fitting model. Thus, it is not necessary to pre-specify the form of the data-fitting model in the GP-based modeling. These models are also less complex, simple to understand, and easy to deploy. The effectiveness of GP in constructing QSRRs has been demonstrated by developing models predicting KRIs of light hydrocarbons (case study-I) and adamantane derivatives (case study-II). In each case study, two-, three- and four-descriptor models have been developed using the KRI data available in the literature. The results of these studies clearly indicate that the GP-based models possess an excellent KRI prediction accuracy and generalization capability. Specifically, the best performing four-descriptor models in both the case studies have yielded high (>0.9) values of the coefficient of determination (R(2)) and low values of root mean squared error (RMSE) and mean absolute percent error (MAPE) for training, test and validation set data. The characteristic feature of this study is that it introduces a practical and an effective GP-based method for developing QSRRs in gas chromatography that can be gainfully utilized for developing other types of data-driven models in chromatography science. Copyright © 2015 Elsevier B.V. All rights reserved.

The cold war context of the golden jubilee, or, why we think of mendel as the father of genetics.

PubMed

Wolfe, Audra J

2012-01-01

In September 1950, the Genetics Society of America (GSA) dedicated its annual meeting to a "Golden Jubilee of Genetics" that celebrated the 50th anniversary of the rediscovery of Mendel's work. This program, originally intended as a small ceremony attached to the coattails of the American Institute of Biological Sciences (AIBS) meeting, turned into a publicity juggernaut that generated coverage on Mendel and the accomplishments of Western genetics in countless newspapers and radio broadcasts. The Golden Jubilee merits historical attention as both an intriguing instance of scientific commemoration and as an early example of Cold War political theatre. Instead of condemning either Lysenko or Soviet genetics, the Golden Jubilee would celebrate Mendel - and, not coincidentally, the practical achievements in plant and animal breeding his work had made possible. The American geneticists' focus on the achievements of Western genetics as both practical and theoretical, international, and, above all, non-ideological and non-controversial, was fully intended to demonstrate the success of the Western model of science to both the American public and scientists abroad at a key transition point in the Cold War. An implicit part of this article's argument, therefore, is the pervasive impact of the Cold War in unanticipated corners of postwar scientific culture.

A comparison of machine learning techniques for survival prediction in breast cancer

PubMed Central

2011-01-01

Background The ability to accurately classify cancer patients into risk classes, i.e. to predict the outcome of the pathology on an individual basis, is a key ingredient in making therapeutic decisions. In recent years gene expression data have been successfully used to complement the clinical and histological criteria traditionally used in such prediction. Many "gene expression signatures" have been developed, i.e. sets of genes whose expression values in a tumor can be used to predict the outcome of the pathology. Here we investigate the use of several machine learning techniques to classify breast cancer patients using one of such signatures, the well established 70-gene signature. Results We show that Genetic Programming performs significantly better than Support Vector Machines, Multilayered Perceptrons and Random Forests in classifying patients from the NKI breast cancer dataset, and comparably to the scoring-based method originally proposed by the authors of the 70-gene signature. Furthermore, Genetic Programming is able to perform an automatic feature selection. Conclusions Since the performance of Genetic Programming is likely to be improvable compared to the out-of-the-box approach used here, and given the biological insight potentially provided by the Genetic Programming solutions, we conclude that Genetic Programming methods are worth further investigation as a tool for cancer patient classification based on gene expression data. PMID:21569330

Genetic parameters for natural antibody isotype titers in milk of Dutch Holstein-Friesians.

PubMed

Wijga, S; Bovenhuis, H; Bastiaansen, J W M; van Arendonk, J A M; Ploegaert, T C W; Tijhaar, E; van der Poel, J J

2013-08-01

The objective of the present study was to estimate genetic parameters for natural antibody isotypes immunoglobulin (Ig) A, IgG1 and IgM titers binding the bacterial antigens lipopolysaccharide, peptidoglycan and the model antigen keyhole limpet hemocyanin in Dutch Holstein-Friesian cows (n = 1695). Further, this study included total natural antibody titers binding the antigens mentioned above, making no isotype distinction, as well as total natural antibody titers and natural antibody isotypes IgA, IgG1 and IgM binding lipoteichoic acid. The study showed that natural antibody isotype titers are heritable, ranging from 0.06 to 0.55, and that these heritabilities were generally higher than heritabilities for total natural antibody titers. Genetic correlations, the combinations of total natural antibody titers and natural antibody isotype titers, were nearly all positive and ranged from -0.23 to 0.99. Strong genetic correlations were found between IgA and IgM. Genetic correlations were substantially weaker when they involved an IgG1 titer, indicating that IgA and IgM have a common genetic basis, but that the genetic basis for IgG1 differs from that for IgA or IgM. Results from this study indicate that natural antibody isotype titers show the potential for effective genetic selection. Further, natural antibody isotypes may provide a better characterization of different elements of the immune response or immune competence. As such, natural antibody isotypes may enable more effective decisions when breeding programs start to include innate immune parameters. © 2013 The Authors, Animal Genetics © 2013 Stichting International Foundation for Animal Genetics.

A Chromosome-Scale Assembly of the Bactrocera cucurbitae Genome Provides Insight to the Genetic Basis of white pupae

PubMed Central

Sim, Sheina B.; Geib, Scott M.

2017-01-01

Genetic sexing strains (GSS) used in sterile insect technique (SIT) programs are textbook examples of how classical Mendelian genetics can be directly implemented in the management of agricultural insect pests. Although the foundation of traditionally developed GSS are single locus, autosomal recessive traits, their genetic basis are largely unknown. With the advent of modern genomic techniques, the genetic basis of sexing traits in GSS can now be further investigated. This study is the first of its kind to integrate traditional genetic techniques with emerging genomics to characterize a GSS using the tephritid fruit fly pest Bactrocera cucurbitae as a model. These techniques include whole-genome sequencing, the development of a mapping population and linkage map, and quantitative trait analysis. The experiment designed to map the genetic sexing trait in B. cucurbitae, white pupae (wp), also enabled the generation of a chromosome-scale genome assembly by integrating the linkage map with the assembly. Quantitative trait loci analysis revealed SNP loci near position 42 MB on chromosome 3 to be tightly linked to wp. Gene annotation and synteny analysis show a near perfect relationship between chromosomes in B. cucurbitae and Muller elements A–E in Drosophila melanogaster. This chromosome-scale genome assembly is complete, has high contiguity, was generated using a minimal input DNA, and will be used to further characterize the genetic mechanisms underlying wp. Knowledge of the genetic basis of genetic sexing traits can be used to improve SIT in this species and expand it to other economically important Diptera. PMID:28450369

Factors influencing the efficiency of generating genetically engineered pigs by nuclear transfer: multi-factorial analysis of a large data set.

PubMed

Kurome, Mayuko; Geistlinger, Ludwig; Kessler, Barbara; Zakhartchenko, Valeri; Klymiuk, Nikolai; Wuensch, Annegret; Richter, Anne; Baehr, Andrea; Kraehe, Katrin; Burkhardt, Katinka; Flisikowski, Krzysztof; Flisikowska, Tatiana; Merkl, Claudia; Landmann, Martina; Durkovic, Marina; Tschukes, Alexander; Kraner, Simone; Schindelhauer, Dirk; Petri, Tobias; Kind, Alexander; Nagashima, Hiroshi; Schnieke, Angelika; Zimmer, Ralf; Wolf, Eckhard

2013-05-20

Somatic cell nuclear transfer (SCNT) using genetically engineered donor cells is currently the most widely used strategy to generate tailored pig models for biomedical research. Although this approach facilitates a similar spectrum of genetic modifications as in rodent models, the outcome in terms of live cloned piglets is quite variable. In this study, we aimed at a comprehensive analysis of environmental and experimental factors that are substantially influencing the efficiency of generating genetically engineered pigs. Based on a considerably large data set from 274 SCNT experiments (in total 18,649 reconstructed embryos transferred into 193 recipients), performed over a period of three years, we assessed the relative contribution of season, type of genetic modification, donor cell source, number of cloning rounds, and pre-selection of cloned embryos for early development to the cloning efficiency. 109 (56%) recipients became pregnant and 85 (78%) of them gave birth to offspring. Out of 318 cloned piglets, 243 (76%) were alive, but only 97 (40%) were clinically healthy and showed normal development. The proportion of stillborn piglets was 24% (75/318), and another 31% (100/318) of the cloned piglets died soon after birth. The overall cloning efficiency, defined as the number of offspring born per SCNT embryos transferred, including only recipients that delivered, was 3.95%. SCNT experiments performed during winter using fetal fibroblasts or kidney cells after additive gene transfer resulted in the highest number of live and healthy offspring, while two or more rounds of cloning and nuclear transfer experiments performed during summer decreased the number of healthy offspring. Although the effects of individual factors may be different between various laboratories, our results and analysis strategy will help to identify and optimize the factors, which are most critical to cloning success in programs aiming at the generation of genetically engineered pig models.

Genetic parameters for image analysis traits on M. longissimus thoracis and M. trapezius of carcass cross section in Japanese Black steers.

PubMed

Osawa, T; Kuchida, K; Hidaka, S; Kato, T

2008-01-01

In Japan, the degree of marbling in ribeye (M. longissimus thoracis) is evaluated in the beef meat grading process. However, other muscles (e.g., M. trapezius) are also important in determining the meat quality and carcass market prices. The purpose of this study was to estimate genetic parameters for M. longissimus thoracis (M-LONG) and M. trapezius (M-TRAP) of carcass cross section of Japanese Black steers by computer image analysis. The number of records of Japanese Black steers and the number of pedigree records were 2,925 and 10,889, respectively. Digital images of the carcass cross section were taken between the sixth and seventh ribs by photographing equipment. Muscle area (MA), fat area ratio (FAR), overall coarseness of marbling particles (OCM), and coarseness of maximum marbling particle (MMC) in M-LONG and M-TRAP were calculated by image analysis. Genetic parameters for these traits were estimated using the AIREMLF90 program with an animal model. Fixed effects that were included in the model were dates of arrival at the carcass market and slaughter age (mo), and random effects of fattening farms, additive genetic effects and residuals were included in the model. For M-LONG, heritability estimates (+/-SE) were 0.46 +/- 0.06, 0.59 +/- 0.06, 0.47 +/- 0.06, and 0.20 +/- 0.05 for MA, FAR, OCM, and MMC, respectively. Heritability estimates (+/-SE) in M-TRAP were 0.47 +/- 0.06, 0.57 +/- 0.07, 0.49 +/- 0.07, and 0.13 +/- 0.04 for the same traits. Genetic correlations between subcutaneous fat thickness and FAR for M-LONG and M-TRAP were negative (-0.21 and -0.19, respectively). Those correlations between M-LONG and M-TRAP were moderate to high for MA, FAR, OCM, and MMC (0.38, 0.52, 0.39, and 0.60, respectively). These results indicate that other muscles including M-LONG should be evaluated for more efficient genetic improvement.

Comparison of two non-convex mixed-integer nonlinear programming algorithms applied to autoregressive moving average model structure and parameter estimation

NASA Astrophysics Data System (ADS)

Uilhoorn, F. E.

2016-10-01

In this article, the stochastic modelling approach proposed by Box and Jenkins is treated as a mixed-integer nonlinear programming (MINLP) problem solved with a mesh adaptive direct search and a real-coded genetic class of algorithms. The aim is to estimate the real-valued parameters and non-negative integer, correlated structure of stationary autoregressive moving average (ARMA) processes. The maximum likelihood function of the stationary ARMA process is embedded in Akaike's information criterion and the Bayesian information criterion, whereas the estimation procedure is based on Kalman filter recursions. The constraints imposed on the objective function enforce stability and invertibility. The best ARMA model is regarded as the global minimum of the non-convex MINLP problem. The robustness and computational performance of the MINLP solvers are compared with brute-force enumeration. Numerical experiments are done for existing time series and one new data set.

The genetic basis of pectoralis major myopathies in modern broiler chicken lines.

PubMed

Bailey, Richard A; Watson, Kellie A; Bilgili, S F; Avendano, Santiago

2015-12-01

This is the first report providing estimates of the genetic basis of breast muscle myopathies (BMM) and their relationship with growth and yield in broiler chickens. In addition, this paper addresses the hypothesis that genetic selection for increase breast yield has contributed to the onset of BMM. Data were analyzed from ongoing recording of BMM within the Aviagen breeding program. This study focused on three BMM: deep pectoral myopathy (DPM; binary trait), white striping (WS; 4 categories) and wooden breast (WB; 3 categories). Data from two purebred commercial broiler lines (A and B) were utilized providing greater than 40,000 meat quality records per line. The difference in selection history between these two lines has resulted in contrasting breast yield (BY): 29% for Line A and 21% for Line B. Data were analyzed to estimate genetic parameters using a multivariate animal model including six traits: body weight (BW), processing body weight (PW), BY, DPM, WB, and WS, in addition to the appropriate fixed effects and permanent environmental effect of the dam. Results indicate similar patterns of heritability and genetic correlations for the two lines. Heritabilities (h2) of BW, PW and BY ranged from 0.271-0.418; for DPM and WB h2<0.1; and for WS h2≤0.338. Genetic correlations between the BMM and BW, PW, or BY were ≤0.132 in Line A and ≤0.248 in Line B. This paper demonstrates the polygenic nature of these traits and the low genetic relationships with BW, PW, and BY, which facilitates genetic improvement across all traits in a balanced breeding program. It also highlights the importance of understanding the environmental and/or management factors that contribute greater than 65% of the variance in the incidence of white striping of breast muscle and more than 90% of the variance of the incidence of wooden breast and deep pectoral myopathy in broiler chickens. © The Author 2015. Published by Oxford University Press on behalf of Poultry Science Association.

Use of gene-expression programming to estimate Manning’s roughness coefficient for high gradient streams

USGS Publications Warehouse

Azamathulla, H. Md.; Jarrett, Robert D.

2013-01-01

Manning’s roughness coefficient (n) has been widely used in the estimation of flood discharges or depths of flow in natural channels. Therefore, the selection of appropriate Manning’s nvalues is of paramount importance for hydraulic engineers and hydrologists and requires considerable experience, although extensive guidelines are available. Generally, the largest source of error in post-flood estimates (termed indirect measurements) is due to estimates of Manning’s n values, particularly when there has been minimal field verification of flow resistance. This emphasizes the need to improve methods for estimating n values. The objective of this study was to develop a soft computing model in the estimation of the Manning’s n values using 75 discharge measurements on 21 high gradient streams in Colorado, USA. The data are from high gradient (S > 0.002 m/m), cobble- and boulder-bed streams for within bank flows. This study presents Gene-Expression Programming (GEP), an extension of Genetic Programming (GP), as an improved approach to estimate Manning’s roughness coefficient for high gradient streams. This study uses field data and assessed the potential of gene-expression programming (GEP) to estimate Manning’s n values. GEP is a search technique that automatically simplifies genetic programs during an evolutionary processes (or evolves) to obtain the most robust computer program (e.g., simplify mathematical expressions, decision trees, polynomial constructs, and logical expressions). Field measurements collected by Jarrett (J Hydraulic Eng ASCE 110: 1519–1539, 1984) were used to train the GEP network and evolve programs. The developed network and evolved programs were validated by using observations that were not involved in training. GEP and ANN-RBF (artificial neural network-radial basis function) models were found to be substantially more effective (e.g., R2 for testing/validation of GEP and RBF-ANN is 0.745 and 0.65, respectively) than Jarrett’s (J Hydraulic Eng ASCE 110: 1519–1539, 1984) equation (R2 for testing/validation equals 0.58) in predicting the Manning’s n.

Bioinformatics education in high school: implications for promoting science, technology, engineering, and mathematics careers.

PubMed

Kovarik, Dina N; Patterson, Davis G; Cohen, Carolyn; Sanders, Elizabeth A; Peterson, Karen A; Porter, Sandra G; Chowning, Jeanne Ting

2013-01-01

We investigated the effects of our Bio-ITEST teacher professional development model and bioinformatics curricula on cognitive traits (awareness, engagement, self-efficacy, and relevance) in high school teachers and students that are known to accompany a developing interest in science, technology, engineering, and mathematics (STEM) careers. The program included best practices in adult education and diverse resources to empower teachers to integrate STEM career information into their classrooms. The introductory unit, Using Bioinformatics: Genetic Testing, uses bioinformatics to teach basic concepts in genetics and molecular biology, and the advanced unit, Using Bioinformatics: Genetic Research, utilizes bioinformatics to study evolution and support student research with DNA barcoding. Pre-post surveys demonstrated significant growth (n = 24) among teachers in their preparation to teach the curricula and infuse career awareness into their classes, and these gains were sustained through the end of the academic year. Introductory unit students (n = 289) showed significant gains in awareness, relevance, and self-efficacy. While these students did not show significant gains in engagement, advanced unit students (n = 41) showed gains in all four cognitive areas. Lessons learned during Bio-ITEST are explored in the context of recommendations for other programs that wish to increase student interest in STEM careers.

Intelligent modelling of bioprocesses: a comparison of structured and unstructured approaches.

PubMed

Hodgson, Benjamin J; Taylor, Christopher N; Ushio, Misti; Leigh, J R; Kalganova, Tatiana; Baganz, Frank

2004-12-01

This contribution moves in the direction of answering some general questions about the most effective and useful ways of modelling bioprocesses. We investigate the characteristics of models that are good at extrapolating. We trained three fully predictive models with different representational structures (differential equations, differential equations with inheritance of rates and a network of reactions) on Saccharopolyspora erythraea shake flask fermentation data using genetic programming. The models were then tested on unseen data outside the range of the training data and the resulting performances were compared. It was found that constrained models with mathematical forms analogous to internal mass balancing and stoichiometric relations were superior to flexible unconstrained models, even though no a priori knowledge of this fermentation was used.

Introduction to the Arizona Sky Island Arthropod Project (ASAP): Systematics, Biogeography, Ecology, and Population Genetics of Arthropods of the Madrean Sky Islands

PubMed Central

Moore, Wendy; Meyer, Wallace M.; Eble, Jeffrey A.; Franklin, Kimberly; Wiens, John F.; Brusca, Richard C.

2014-01-01

The Arizona Sky Island Arthropod Project (ASAP) is a new multi-disciplinary research program at the University of Arizona that combines systematics, biogeography, ecology, and population genetics to study origins and patterns of arthropod diversity along elevation gradients and among mountain ranges in the Madrean Sky Island Region. Arthropods represent taxonomically and ecologically diverse organisms that drive key ecosystem processes in this mountain archipelago. Using data from museum specimens and specimens we obtain during long-term collecting and monitoring programs, ASAP will document arthropod species across Arizona's Sky Islands to address a number of fundamental questions about arthropods of this region. Baseline data will be used to determine climatic boundaries for target species, which will then be integrated with climatological models to predict future changes in arthropod communities and distributions in the wake of rapid climate change. ASAP also makes use of the natural laboratory provided by the Sky Islands to investigate ecological and genetic factors that influence diversification and patterns of community assembly. Here, we introduce the project, outline overarching goals, and describe preliminary data from the first year of sampling ground-dwelling beetles and ants in the Santa Catalina Mountains. PMID:25505938

Bioinformatics Education in High School: Implications for Promoting Science, Technology, Engineering, and Mathematics Careers

PubMed Central

Kovarik, Dina N.; Patterson, Davis G.; Cohen, Carolyn; Sanders, Elizabeth A.; Peterson, Karen A.; Porter, Sandra G.; Chowning, Jeanne Ting

2013-01-01

We investigated the effects of our Bio-ITEST teacher professional development model and bioinformatics curricula on cognitive traits (awareness, engagement, self-efficacy, and relevance) in high school teachers and students that are known to accompany a developing interest in science, technology, engineering, and mathematics (STEM) careers. The program included best practices in adult education and diverse resources to empower teachers to integrate STEM career information into their classrooms. The introductory unit, Using Bioinformatics: Genetic Testing, uses bioinformatics to teach basic concepts in genetics and molecular biology, and the advanced unit, Using Bioinformatics: Genetic Research, utilizes bioinformatics to study evolution and support student research with DNA barcoding. Pre–post surveys demonstrated significant growth (n = 24) among teachers in their preparation to teach the curricula and infuse career awareness into their classes, and these gains were sustained through the end of the academic year. Introductory unit students (n = 289) showed significant gains in awareness, relevance, and self-efficacy. While these students did not show significant gains in engagement, advanced unit students (n = 41) showed gains in all four cognitive areas. Lessons learned during Bio-ITEST are explored in the context of recommendations for other programs that wish to increase student interest in STEM careers. PMID:24006393

Cell differentiation defines acute and chronic infection cell types in Staphylococcus aureus.

PubMed

García-Betancur, Juan-Carlos; Goñi-Moreno, Angel; Horger, Thomas; Schott, Melanie; Sharan, Malvika; Eikmeier, Julian; Wohlmuth, Barbara; Zernecke, Alma; Ohlsen, Knut; Kuttler, Christina; Lopez, Daniel

2017-09-12

A central question to biology is how pathogenic bacteria initiate acute or chronic infections. Here we describe a genetic program for cell-fate decision in the opportunistic human pathogen Staphylococcus aureus , which generates the phenotypic bifurcation of the cells into two genetically identical but different cell types during the course of an infection. Whereas one cell type promotes the formation of biofilms that contribute to chronic infections, the second type is planktonic and produces the toxins that contribute to acute bacteremia. We identified a bimodal switch in the agr quorum sensing system that antagonistically regulates the differentiation of these two physiologically distinct cell types. We found that extracellular signals affect the behavior of the agr bimodal switch and modify the size of the specialized subpopulations in specific colonization niches. For instance, magnesium-enriched colonization niches causes magnesium binding to S. aureus teichoic acids and increases bacterial cell wall rigidity. This signal triggers a genetic program that ultimately downregulates the agr bimodal switch. Colonization niches with different magnesium concentrations influence the bimodal system activity, which defines a distinct ratio between these subpopulations; this in turn leads to distinct infection outcomes in vitro and in an in vivo murine infection model. Cell differentiation generates physiological heterogeneity in clonal bacterial infections and helps to determine the distinct infection types.

Cell differentiation defines acute and chronic infection cell types in Staphylococcus aureus

PubMed Central

García-Betancur, Juan-Carlos; Goñi-Moreno, Angel; Horger, Thomas; Schott, Melanie; Sharan, Malvika; Eikmeier, Julian; Wohlmuth, Barbara; Zernecke, Alma; Ohlsen, Knut; Kuttler, Christina

2017-01-01

A central question to biology is how pathogenic bacteria initiate acute or chronic infections. Here we describe a genetic program for cell-fate decision in the opportunistic human pathogen Staphylococcus aureus, which generates the phenotypic bifurcation of the cells into two genetically identical but different cell types during the course of an infection. Whereas one cell type promotes the formation of biofilms that contribute to chronic infections, the second type is planktonic and produces the toxins that contribute to acute bacteremia. We identified a bimodal switch in the agr quorum sensing system that antagonistically regulates the differentiation of these two physiologically distinct cell types. We found that extracellular signals affect the behavior of the agr bimodal switch and modify the size of the specialized subpopulations in specific colonization niches. For instance, magnesium-enriched colonization niches causes magnesium binding to S. aureusteichoic acids and increases bacterial cell wall rigidity. This signal triggers a genetic program that ultimately downregulates the agr bimodal switch. Colonization niches with different magnesium concentrations influence the bimodal system activity, which defines a distinct ratio between these subpopulations; this in turn leads to distinct infection outcomes in vitro and in an in vivo murine infection model. Cell differentiation generates physiological heterogeneity in clonal bacterial infections and helps to determine the distinct infection types. PMID:28893374

Demography and genetic structure of a recovering grizzly bear population

USGS Publications Warehouse

Kendall, K.C.; Stetz, J.B.; Boulanger, J.; Macleod, A.C.; Paetkau, David; White, Gary C.

2009-01-01

Grizzly bears (brown bears; Ursus arctos) are imperiled in the southern extent of their range worldwide. The threatened population in northwestern Montana, USA, has been managed for recovery since 1975; yet, no rigorous data were available to monitor program success. We used data from a large noninvasive genetic sampling effort conducted in 2004 and 33 years of physical captures to assess abundance, distribution, and genetic health of this population. We combined data from our 3 sampling methods (hair trap, bear rub, and physical capture) to construct individual bear encounter histories for use in Huggins-Pledger closed mark-recapture models. Our population estimate, N?? = 765 (95% CI = 715-831) was more than double the existing estimate derived from sightings of females with young. Based on our results, the estimated known, human-caused mortality rate in 2004 was 4.6% (95% CI = 4.2-4.9%), slightly above the 4% considered sustainable; however, the high proportion of female mortalities raises concern. We used location data from telemetry, confirmed sightings, and genetic sampling to estimate occupied habitat. We found that grizzly bears occupied 33,480 km2 in the Northern Continental Divide Ecosystem (NCDE) during 1994-2007, including 10,340 km beyond the Recovery Zone. We used factorial correspondence analysis to identify potential barriers to gene flow within this population. Our results suggested that genetic interchange recently increased in areas with low gene flow in the past; however, we also detected evidence of incipient fragmentation across the major transportation corridor in this ecosystem. Our results suggest that the NCDE population is faring better than previously thought, and they highlight the need for a more rigorous monitoring program.

Single-Step BLUP with Varying Genotyping Effort in Open-Pollinated Picea glauca.

PubMed

Ratcliffe, Blaise; El-Dien, Omnia Gamal; Cappa, Eduardo P; Porth, Ilga; Klápště, Jaroslav; Chen, Charles; El-Kassaby, Yousry A

2017-03-10

Maximization of genetic gain in forest tree breeding programs is contingent on the accuracy of the predicted breeding values and precision of the estimated genetic parameters. We investigated the effect of the combined use of contemporary pedigree information and genomic relatedness estimates on the accuracy of predicted breeding values and precision of estimated genetic parameters, as well as rankings of selection candidates, using single-step genomic evaluation (HBLUP). In this study, two traits with diverse heritabilities [tree height (HT) and wood density (WD)] were assessed at various levels of family genotyping efforts (0, 25, 50, 75, and 100%) from a population of white spruce ( Picea glauca ) consisting of 1694 trees from 214 open-pollinated families, representing 43 provenances in Québec, Canada. The results revealed that HBLUP bivariate analysis is effective in reducing the known bias in heritability estimates of open-pollinated populations, as it exposes hidden relatedness, potential pedigree errors, and inbreeding. The addition of genomic information in the analysis considerably improved the accuracy in breeding value estimates by accounting for both Mendelian sampling and historical coancestry that were not captured by the contemporary pedigree alone. Increasing family genotyping efforts were associated with continuous improvement in model fit, precision of genetic parameters, and breeding value accuracy. Yet, improvements were observed even at minimal genotyping effort, indicating that even modest genotyping effort is effective in improving genetic evaluation. The combined utilization of both pedigree and genomic information may be a cost-effective approach to increase the accuracy of breeding values in forest tree breeding programs where shallow pedigrees and large testing populations are the norm. Copyright © 2017 Ratcliffe et al.

Twenty years of artificial directional selection have shaped the genome of the Italian Large White pig breed.

PubMed

Schiavo, G; Galimberti, G; Calò, D G; Samorè, A B; Bertolini, F; Russo, V; Gallo, M; Buttazzoni, L; Fontanesi, L

2016-04-01

In this study, we investigated at the genome-wide level if 20 years of artificial directional selection based on boar genetic evaluation obtained with a classical BLUP animal model shaped the genome of the Italian Large White pig breed. The most influential boars of this breed (n = 192), born from 1992 (the beginning of the selection program of this breed) to 2012, with an estimated breeding value reliability of >0.85, were genotyped with the Illumina Porcine SNP60 BeadChip. After grouping the boars in eight classes according to their year of birth, filtered single nucleotide polymorphisms (SNPs) were used to evaluate the effects of time on genotype frequency changes using multinomial logistic regression models. Of these markers, 493 had a PBonferroni  < 0.10. However, there was an increasing number of SNPs with a decreasing level of allele frequency changes over time, representing a continuous profile across the genome. The largest proportion of the 493 SNPs was on porcine chromosome (SSC) 7, SSC2, SSC8 and SSC18 for a total of 204 haploblocks. Functional annotations of genomic regions, including the 493 shifted SNPs, reported a few Gene Ontology terms that might underly the biological processes that contributed to increase performances of the pigs over the 20 years of the selection program. The obtained results indicated that the genome of the Italian Large White pigs was shaped by a directional selection program derived by the application of methodologies assuming the infinitesimal model that captured a continuous trend of allele frequency changes in the boar population. © 2015 Stichting International Foundation for Animal Genetics.

Genetic diversity and differentiation of exotic and American commercial cattle breeds raised in Brazil.

PubMed

Brasil, B S A F; Coelho, E G A; Drummond, M G; Oliveira, D A A

2013-11-18

The Brazilian cattle population is mainly composed of breeds of zebuine origin and their American derivatives. Comprehensive knowledge about the genetic diversity of these populations is fundamental for animal breeding programs and the conservation of genetic resources. This study aimed to assess the phylogenetic relationships, levels of genetic diversity, and patterns of taurine/zebuine admixture among 9 commercial cattle breeds raised in Brazil. Analysis of DNA polymorphisms was performed on 2965 animals using the 11 microsatellite markers recommended by the International Society of Animal Genetics. High genetic diversity was detected in all breeds, even though significant inbreeding was observed within some. Differences among the breeds accounted for 14.72% of the total genetic variability, and genetic differentiation was higher among taurine than among zebuine cattle. Of note, Nelore cattle presented with high levels of admixture, which is consistent with the history of frequent gene flow during the establishment of this breed in Brazil. Furthermore, significant genetic variability was partitioned within the commercial cattle breeds formed in America, which, therefore, comprise important resources of genetic diversity in the tropics. The genetic characterization of these important Brazilian breeds may now facilitate the development of management and breeding programs for these populations.

Inducing Somatic Pkd1 Mutations in Vivo in a Mouse Model of Autosomal-Dominant Polycystic Kidney Disease

DTIC Science & Technology

2016-10-01

AWARD NUMBER: W81XWH-15-1-0237 TITLE: Inducing Somatic Pkd1 Mutations in Vivo in a Mouse Model of Autosomal-Dominant Polycystic Kidney ... Kidney Disease 5b. GRANT NUMBER W81XWH-15-1-0237 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Cristina Cebrian-Ligero 5d. PROJECT NUMBER 5e. TASK...Autosomal Dominant Polycystic Kidney Disease (ADPKD) is one of the world’s most common life-threatening genetic diseases. Over 95% of diagnosed cases of

USDA forest service southern region – It’s all about GRITS

Treesearch

Barbara S. Crane; Kevin M. Potter

2017-01-01

Genetic resource management programs across the U.S. Department of Agriculture Forest Service (USDA FS) play a key role in supporting successful land management activities. The programs are responsible for developing and providing plant material for revegetation, seed management guidelines, emergency fire recovery assistance, genetic conservation strategies, climate...

A Microcomputer Exercise on Genetic Transcription and Translation.

ERIC Educational Resources Information Center

Meisenheimer, John L.

1985-01-01

Describes a microcomputer program (written for the Apple II+) which can serve as a lecture demonstration aid in explaining genetic transcription and translation. The program provides unemotional information on student errors, thus serving as a review drill to supplement the classroom. Student participation and instructor options are discussed. (DH)

Initial experiences utilizing exotic landrace germplasm in an upland cotton breeding program

USDA-ARS?s Scientific Manuscript database

A critical objective of plant breeding programs is accessing new sources of genetic variation. In upland cotton, one of the relatively untapped sources of genetic variation is maintained in the USDA-ARS cotton germplasm collection and is the exotic landrace collection. Photoperiod sensitivity is a m...

Genetics in Relation to Biology.

ERIC Educational Resources Information Center

Stewart, J. Bird

1987-01-01

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

Mathematical Modeling of Intestinal Iron Absorption Using Genetic Programming

PubMed Central

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

2017-01-01

Iron is a trace metal, key for the development of living organisms. Its absorption process is complex and highly regulated at the transcriptional, translational and systemic levels. Recently, the internalization of the DMT1 transporter has been proposed as an additional regulatory mechanism at the intestinal level, associated to the mucosal block phenomenon. The short-term effect of iron exposure in apical uptake and initial absorption rates was studied in Caco-2 cells at different apical iron concentrations, using both an experimental approach and a mathematical modeling framework. This is the first report of short-term studies for this system. A non-linear behavior in the apical uptake dynamics was observed, which does not follow the classic saturation dynamics of traditional biochemical models. We propose a method for developing mathematical models for complex systems, based on a genetic programming algorithm. The algorithm is aimed at obtaining models with a high predictive capacity, and considers an additional parameter fitting stage and an additional Jackknife stage for estimating the generalization error. We developed a model for the iron uptake system with a higher predictive capacity than classic biochemical models. This was observed both with the apical uptake dataset used for generating the model and with an independent initial rates dataset used to test the predictive capacity of the model. The model obtained is a function of time and the initial apical iron concentration, with a linear component that captures the global tendency of the system, and a non-linear component that can be associated to the movement of DMT1 transporters. The model presented in this paper allows the detailed analysis, interpretation of experimental data, and identification of key relevant components for this complex biological process. This general method holds great potential for application to the elucidation of biological mechanisms and their key components in other complex systems. PMID:28072870

Improving Search Properties in Genetic Programming

NASA Technical Reports Server (NTRS)

Janikow, Cezary Z.; DeWeese, Scott

1997-01-01

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

Integrating Genetics and Social Science: Genetic Risk Scores

PubMed Central

Belsky, Daniel W.; Israel, Salomon

2014-01-01

The sequencing of the human genome and the advent of low-cost genome-wide assays that generate millions of observations of individual genomes in a matter of hours constitute a disruptive innovation for social science. Many public-use social science datasets have or will soon add genome-wide genetic data. With these new data come technical challenges, but also new possibilities. Among these, the lowest hanging fruit and the most potentially disruptive to existing research programs is the ability to measure previously invisible contours of health and disease risk within populations. In this article, we outline why now is the time for social scientists to bring genetics into their research programs. We discuss how to select genetic variants to study. We explain how the polygenic architecture of complex traits and the low penetrance of individual genetic loci pose challenges to research integrating genetics and social science. We introduce genetic risk scores as a method of addressing these challenges and provide guidance on how genetic risk scores can be constructed. We conclude by outlining research questions that are ripe for social science inquiry. PMID:25343363

Conservative strategy-based ensemble surrogate model for optimal groundwater remediation design at DNAPLs-contaminated sites

NASA Astrophysics Data System (ADS)

Ouyang, Qi; Lu, Wenxi; Lin, Jin; Deng, Wenbing; Cheng, Weiguo

2017-08-01

The surrogate-based simulation-optimization techniques are frequently used for optimal groundwater remediation design. When this technique is used, surrogate errors caused by surrogate-modeling uncertainty may lead to generation of infeasible designs. In this paper, a conservative strategy that pushes the optimal design into the feasible region was used to address surrogate-modeling uncertainty. In addition, chance-constrained programming (CCP) was adopted to compare with the conservative strategy in addressing this uncertainty. Three methods, multi-gene genetic programming (MGGP), Kriging (KRG) and support vector regression (SVR), were used to construct surrogate models for a time-consuming multi-phase flow model. To improve the performance of the surrogate model, ensemble surrogates were constructed based on combinations of different stand-alone surrogate models. The results show that: (1) the surrogate-modeling uncertainty was successfully addressed by the conservative strategy, which means that this method is promising for addressing surrogate-modeling uncertainty. (2) The ensemble surrogate model that combines MGGP with KRG showed the most favorable performance, which indicates that this ensemble surrogate can utilize both stand-alone surrogate models to improve the performance of the surrogate model.

Development of program package for investigation and modeling of carbon nanostructures in diamond like carbon films with the help of Raman scattering and infrared absorption spectra line resolving

NASA Astrophysics Data System (ADS)

Hayrapetyan, David B.; Hovhannisyan, Levon; Mantashyan, Paytsar A.

2013-04-01

The analysis of complex spectra is an actual problem for modern science. The work is devoted to the creation of a software package, which analyzes spectrum in the different formats, possesses by dynamic knowledge database and self-study mechanism, performs automated analysis of the spectra compound based on knowledge database by application of certain algorithms. In the software package as searching systems, hyper-spherical random search algorithms, gradient algorithms and genetic searching algorithms were used. The analysis of Raman and IR spectrum of diamond-like carbon (DLC) samples were performed by elaborated program. After processing the data, the program immediately displays all the calculated parameters of DLC.

Contrasting results from molecular and pedigree-based population diversity measures in captive zebra highlight challenges facing genetic management of zoo populations.

PubMed

Ito, Hideyuki; Ogden, Rob; Langenhorst, Tanya; Inoue-Murayama, Miho

2017-01-01

Zoo conservation breeding programs manage the retention of population genetic diversity through analysis of pedigree records. The range of demographic and genetic indices determined through pedigree analysis programs allows the conservation of diversity to be monitored relative to the particular founder population for a species. Such approaches are based on a number of well-documented founder assumptions, however without knowledge of actual molecular genetic diversity there is a risk that pedigree-based measures will be misinterpreted and population genetic diversity misunderstood. We examined the genetic diversity of the captive populations of Grevy's zebra, Hartmann's mountain zebra and plains zebra in Japan and the United Kingdom through analysis of mitochondrial DNA sequences. Very low nucleotide variability was observed in Grevy's zebra. The results were evaluated with respect to current and historic diversity in the wild, and indicate that low genetic diversity in the captive population is likely a result of low founder diversity, which in turn suggests relatively low wild genetic diversity prior to recent population declines. Comparison of molecular genetic diversity measures with analogous diversity indices generated from the studbook data for Grevy's zebra and Hartmann's mountain zebra show contrasting patterns, with Grevy's zebra displaying markedly less molecular diversity than mountain zebra, despite studbook analysis indicating that the Grevy's zebra population has substantially more founders, greater effective population size, lower mean kinship, and has suffered less loss of gene diversity. These findings emphasize the need to validate theoretical estimates of genetic diversity in captive breeding programs with empirical molecular genetic data. Zoo Biol. 36:87-94, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A first generation BAC-based physical map of the rainbow trout genome

PubMed Central

Palti, Yniv; Luo, Ming-Cheng; Hu, Yuqin; Genet, Carine; You, Frank M; Vallejo, Roger L; Thorgaard, Gary H; Wheeler, Paul A; Rexroad, Caird E

2009-01-01

Background Rainbow trout (Oncorhynchus mykiss) are the most-widely cultivated cold freshwater fish in the world and an important model species for many research areas. Coupling great interest in this species as a research model with the need for genetic improvement of aquaculture production efficiency traits justifies the continued development of genomics research resources. Many quantitative trait loci (QTL) have been identified for production and life-history traits in rainbow trout. A bacterial artificial chromosome (BAC) physical map is needed to facilitate fine mapping of QTL and the selection of positional candidate genes for incorporation in marker-assisted selection (MAS) for improving rainbow trout aquaculture production. This resource will also facilitate efforts to obtain and assemble a whole-genome reference sequence for this species. Results The physical map was constructed from DNA fingerprinting of 192,096 BAC clones using the 4-color high-information content fingerprinting (HICF) method. The clones were assembled into physical map contigs using the finger-printing contig (FPC) program. The map is composed of 4,173 contigs and 9,379 singletons. The total number of unique fingerprinting fragments (consensus bands) in contigs is 1,185,157, which corresponds to an estimated physical length of 2.0 Gb. The map assembly was validated by 1) comparison with probe hybridization results and agarose gel fingerprinting contigs; and 2) anchoring large contigs to the microsatellite-based genetic linkage map. Conclusion The production and validation of the first BAC physical map of the rainbow trout genome is described in this paper. We are currently integrating this map with the NCCCWA genetic map using more than 200 microsatellites isolated from BAC end sequences and by identifying BACs that harbor more than 300 previously mapped markers. The availability of an integrated physical and genetic map will enable detailed comparative genome analyses, fine mapping of QTL, positional cloning, selection of positional candidate genes for economically important traits and the incorporation of MAS into rainbow trout breeding programs. PMID:19814815

Hierarchical maintenance of MLL myeloid leukemia stem cells employs a transcriptional program shared with embryonic rather than adult stem cells

PubMed Central

Somervaille, Tim C. P.; Matheny, Christina J.; Spencer, Gary J.; Iwasaki, Masayuki; Rinn, John L.; Witten, Daniela M.; Chang, Howard Y.; Shurtleff, Sheila A.; Downing, James R.; Cleary, Michael L.

2009-01-01

Summary The genetic programs that promote retention of self-renewing leukemia stem cells (LSCs) at the apex of cellular hierarchies in acute myeloid leukemia (AML) are not known. In a mouse model of human AML, LSCs exhibit variable frequencies that correlate with the initiating MLL oncogene and are maintained in a self-renewing state by a transcriptional sub-program more akin to that of embryonic stem cells (ESCs) than adult stem cells. The transcription/chromatin regulatory factors Myb, Hmgb3 and Cbx5 are critical components of the program and suffice for Hoxa/Meis-independent immortalization of myeloid progenitors when co-expressed, establishing the cooperative and essential role of an ESC-like LSC maintenance program ancillary to the leukemia initiating MLL/Hox/Meis program. Enriched expression of LSC maintenance and ESC-like program genes in normal myeloid progenitors and poor prognosis human malignancies links the frequency of aberrantly self-renewing progenitor-like cancer stem cells to prognosis in human cancer. PMID:19200802

A recoding scheme for X-linked and pseudoautosomal loci to be used with computer programs for autosomal LOD-score analysis.

PubMed

Strauch, Konstantin; Baur, Max P; Wienker, Thomas F

2004-01-01

We present a recoding scheme that allows for a parametric multipoint X-chromosomal linkage analysis of dichotomous traits in the context of a computer program for autosomes that can use trait models with imprinting. Furthermore, with this scheme, it is possible to perform a joint multipoint analysis of X-linked and pseudoautosomal loci. It is required that (1) the marker genotypes of all female nonfounders are available and that (2) there are no male nonfounders who have daughters in the pedigree. The second requirement does not apply if the trait locus is pseudoautosomal. The X-linked marker loci are recorded by adding a dummy allele to the males' hemizygous genotypes. For modelling an X-linked trait locus, five different liability classes are defined, in conjunction with a paternal imprinting model for male nonfounders. The formulation aims at the mapping of a diallelic trait locus relative to an arbitrary number of codominant markers with known genetic distances, in cases where a program for a genuine X-chromosomal analysis is not available. 2004 S. Karger AG, Basel.

Contribution of Large Animals to Translational Research on Prenatal Programming of Obesity and Associated Diseases.

PubMed

Gonzalez-Bulnes, Antonio; Chavatte-Palmer, Pascale

2017-01-01

The awareness of factors causing obesity and associated disorders has grown up in the last years from genome to a more complicated concept (developmental programming) in which prenatal and early-postnatal conditions markedly modify the phenotype and homeostasis of the individuals and determine juvenile growth, life-time fitness/obesity and disease risks. Experimentation in human beings is impeded by ethical issues plus inherent high variability and confounding factors (genetics, lifestyle and socioeconomic heterogeneity) and preclinical studies in adequate translational animal models are therefore decisive. Most of the studies have been performed in rodents, whilst the use of large animals is scarce. Having in mind body-size, handlingeasiness and cost-efficiency, the main large animal species for use in biomedical research are rabbits, sheep and swine. The choice of the model depends on the research objectives. To outline the main features of the use of rabbits, sheep and swine and their contributions as translational models in prenatal programming of obesity and associated disorders. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Gene-expression programming for flip-bucket spillway scour.

PubMed

Guven, Aytac; Azamathulla, H Md

2012-01-01

During the last two decades, researchers have noticed that the use of soft computing techniques as an alternative to conventional statistical methods based on controlled laboratory or field data, gave significantly better results. Gene-expression programming (GEP), which is an extension to genetic programming (GP), has nowadays attracted the attention of researchers in prediction of hydraulic data. This study presents GEP as an alternative tool in the prediction of scour downstream of a flip-bucket spillway. Actual field measurements were used to develop GEP models. The proposed GEP models are compared with the earlier conventional GP results of others (Azamathulla et al. 2008b; RMSE = 2.347, δ = 0.377, R = 0.842) and those of commonly used regression-based formulae. The predictions of GEP models were observed to be in strictly good agreement with measured ones, and quite a bit better than conventional GP and the regression-based formulae. The results are tabulated in terms of statistical error measures (GEP1; RMSE = 1.596, δ = 0.109, R = 0.917) and illustrated via scatter plots.

Family conflict interacts with genetic liability in predicting childhood and adolescent depression.

PubMed

Rice, Frances; Harold, Gordon T; Shelton, Katherine H; Thapar, Anita

2006-07-01

To test for gene-environment interaction with depressive symptoms and family conflict. Specifically, to first examine whether the influence of family conflict in predicting depressive symptoms is increased in individuals at genetic risk of depression. Second, to test whether the genetic component of variance in depressive symptoms increases as levels of family conflict increase. A longitudinal twin design was used. Children ages 5 to 16 were reassessed approximately 3 years later to test whether the influence of family conflict in predicting depressive symptoms varied according to genetic liability. The conflict subscale of the Family Environment Scale was used to assess family conflict and the Mood and Feelings Questionnaire was used to assess depressive symptoms. The response rate to the questionnaire at time 1 was 73% and 65% at time 2. Controlling for initial symptoms levels (i.e., internalizing at time 1), primary analyses were conducted using ordinary least-squares multiple regression. Structural equation models, using raw score maximum likelihood estimation, were also fit to the data for the purpose of model fit comparison. Results suggested significant gene-environment interaction specifically with depressive symptoms and family conflict. Genetic factors were of greater importance in the etiology of depressive symptoms where levels of family conflict were high. The effects of family conflict on depressive symptoms were greater in children and adolescents at genetic risk of depression. The present results suggest that children with a family history of depression may be at an increased risk of developing depressive symptoms in response to family conflict. Intervention programs that incorporate one or more family systems may be of benefit in alleviating the adverse effect of negative family factors on children.

Genetically-Based Biologic Technologies. Biology and Human Welfare.

ERIC Educational Resources Information Center

Mayer, William V.; McInerney, Joseph D.

The purpose of this six-part booklet is to review the current status of genetically-based biologic technologies and to suggest how information about these technologies can be inserted into existing educational programs. Topic areas included in the six parts are: (1) genetically-based technologies in the curriculum; (2) genetic technologies…

Effects of genetic distance on heterosis in a Drosophila melanogaster model system.

PubMed

Jensen, Charlotte; Ørsted, Michael; Kristensen, Torsten Nygaard

2018-05-14

Habitat fragmentation and small population sizes can lead to inbreeding and loss of genetic variation, which can potentially cause inbreeding depression and decrease the ability of populations to adapt to altered environmental conditions. One solution to these genetic problems is the implementation of genetic rescue, which re-establishes gene flow between separated populations. Similar techniques are being used in animal and plant breeding to produce superior production animals and plants. To optimize fitness benefits in genetic rescue programs and to secure high yielding domestic varieties in animal and plant breeding, knowledge on the genetic relatedness of populations being crossed is imperative. In this study, we conducted replicated crosses between isogenic Drosophila melanogaster lines from the Drosophila Genetic Reference Panel. We grouped lines in two genetic distance groups to study the effect of genetic divergence between populations on the expression of heterosis in two fitness components; starvation resistance and reproductive output. We further investigated the transgenerational effects of outcrossing by investigating the fitness consequences in both the F 1 - and the F 3 -generations. High fitness enhancements were observed in hybrid offspring compared to parental lines, especially for reproductive output. However, the level of heterosis declined from the F 1 - to the F 3 -generation. Generally, genetic distance did not have strong impact on the level of heterosis detected, although there were exceptions to this pattern. The best predictor of heterosis was performance of parental lines with poorly performing parental lines showing higher hybrid vigour when crossed, i.e. the potential for heterosis was proportional to the level of inbreeding depression. Overall, our results show that outcrossing can have very strong positive fitness consequences for genetically depauperate populations.

A motif detection and classification method for peptide sequences using genetic programming.

PubMed

Tomita, Yasuyuki; Kato, Ryuji; Okochi, Mina; Honda, Hiroyuki

2008-08-01

An exploration of common rules (property motifs) in amino acid sequences has been required for the design of novel sequences and elucidation of the interactions between molecules controlled by the structural or physical environment. In the present study, we developed a new method to search property motifs that are common in peptide sequence data. Our method comprises the following two characteristics: (i) the automatic determination of the position and length of common property motifs by calculating the physicochemical similarity of amino acids, and (ii) the quick and effective exploration of motif candidates that discriminates the positives and negatives by the introduction of genetic programming (GP). Our method was evaluated by two types of model data sets. First, the intentionally buried property motifs were searched in the artificially derived peptide data containing intentionally buried property motifs. As a result, the expected property motifs were correctly extracted by our algorithm. Second, the peptide data that interact with MHC class II molecules were analyzed as one of the models of biologically active peptides with buried motifs in various lengths. Twofold MHC class II binding peptides were identified with the rule using our method, compared to the existing scoring matrix method. In conclusion, our GP based motif searching approach enabled to obtain knowledge of functional aspects of the peptides without any prior knowledge.

Molecular Marker Systems for Oenothera Genetics

PubMed Central

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

2008-01-01

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. PMID:18791241

Molecular marker systems for Oenothera genetics.

PubMed

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.

Risk factor meta-analysis and Bayesian estimation of genetic parameters and breeding values for hypersensibility to cutaneous habronematidosis in donkeys.

PubMed

Navas González, Francisco Javier; Jordana Vidal, Jordi; Camacho Vallejo, María Esperanza; León Jurado, Jose Manuel; de la Haba Giraldo, Manuel Rafael; Barba Capote, Cecilio; Delgado Bermejo, Juan Vicente

2018-03-15

Cutaneous habronematidosis (CH) is a highly prevalent seasonally recurrent skin disease that affects donkeys as a result from the action of spirurid stomach worm larvae. Carrier flies mistakenly deposit these larvae on previous skin lesions or on the moisture of natural orifices, causing distress and inflicting relapsing wounds to the animals. First, we carried out a meta-analysis of the predisposing factors that could condition the development of CH in Andalusian donkeys. Second, basing on the empirical existence of an inter and intrafamilial variation previously addressed by owners, we isolated the genetic background behind the hypersensibility to this parasitological disease. To this aim, we designed a Bayesian linear model (BLM) to estimate the breeding values and genetic parameters for the hypersensibility to CH as a way to infer the potential selection suitability of this trait, seeking the improvement of donkey conservation programs. We studied the historical record of the cases of CH of 765 donkeys from 1984 to 2017. Fixed effects included birth year, birth season, sex, farm/owner, and husbandry system. Age was included as a linear and quadratic covariate. Although the effects of birth season and birth year were statistically non-significant (P > 0.05), their respective interactions with sex and farm/owner were statistically significant (P < 0.01), what translated into an increase of 40.5% in the specificity and of 0.6% of the sensibility of the model designed, when such interactions were included. Our BLM reported highly accurate genetic parameters as suggested by the low error of around 0.005, and the 95% credible interval for the heritability of ±0.0012. The CH hypersensibility heritability was 0.0346. The value of 0.1232 for additive genetic variance addresses a relatively low genetic variation in the Andalusian donkey breed. Our results suggest that farms managed under extensive husbandry conditions are the most protective ones against developing CH. Furthermore, these results provide evidence of the lack of repercussion of other factors such as age or sex. Potentially considering CH hypersensibility as a negative selection aimed goal in donkey breeding programs, may turn into a measure to improve animal welfare indirectly. However, the low heritability value makes it compulsory to control environmental factors to ensure the effectiveness of the breeding measures implemented to obtain individuals that may genetically be less prone to develop the condition. Copyright © 2018 Elsevier B.V. All rights reserved.

Population Structure, Genetic Diversity and Molecular Marker-Trait Association Analysis for High Temperature Stress Tolerance in Rice

PubMed Central

Barik, Saumya Ranjan; Sahoo, Ambika; Mohapatra, Sudipti; Nayak, Deepak Kumar; Mahender, Anumalla; Meher, Jitandriya; Anandan, Annamalai

2016-01-01

Rice exhibits enormous genetic diversity, population structure and molecular marker-traits associated with abiotic stress tolerance to high temperature stress. A set of breeding lines and landraces representing 240 germplasm lines were studied. Based on spikelet fertility percent under high temperature, tolerant genotypes were broadly classified into four classes. Genetic diversity indicated a moderate level of genetic base of the population for the trait studied. Wright’s F statistic estimates showed a deviation of Hardy-Weinberg expectation in the population. The analysis of molecular variance revealed 25 percent variation between population, 61 percent among individuals and 14 percent within individuals in the set. The STRUCTURE analysis categorized the entire population into three sub-populations and suggested that most of the landraces in each sub-population had a common primary ancestor with few admix individuals. The composition of materials in the panel showed the presence of many QTLs representing the entire genome for the expression of tolerance. The strongly associated marker RM547 tagged with spikelet fertility under stress and the markers like RM228, RM205, RM247, RM242, INDEL3 and RM314 indirectly controlling the high temperature stress tolerance were detected through both mixed linear model and general linear model TASSEL analysis. These markers can be deployed as a resource for marker-assisted breeding program of high temperature stress tolerance. PMID:27494320

Systematic analysis of Ca2+ homeostasis in Saccharomyces cerevisiae based on chemical-genetic interaction profiles

PubMed Central

Ghanegolmohammadi, Farzan; Yoshida, Mitsunori; Ohnuki, Shinsuke; Sukegawa, Yuko; Okada, Hiroki; Obara, Keisuke; Kihara, Akio; Suzuki, Kuninori; Kojima, Tetsuya; Yachie, Nozomu; Hirata, Dai; Ohya, Yoshikazu

2017-01-01

We investigated the global landscape of Ca2+ homeostasis in budding yeast based on high-dimensional chemical-genetic interaction profiles. The morphological responses of 62 Ca2+-sensitive (cls) mutants were quantitatively analyzed with the image processing program CalMorph after exposure to a high concentration of Ca2+. After a generalized linear model was applied, an analysis of covariance model was used to detect significant Ca2+–cls interactions. We found that high-dimensional, morphological Ca2+–cls interactions were mixed with positive (86%) and negative (14%) chemical-genetic interactions, whereas one-dimensional fitness Ca2+–cls interactions were all negative in principle. Clustering analysis with the interaction profiles revealed nine distinct gene groups, six of which were functionally associated. In addition, characterization of Ca2+–cls interactions revealed that morphology-based negative interactions are unique signatures of sensitized cellular processes and pathways. Principal component analysis was used to discriminate between suppression and enhancement of the Ca2+-sensitive phenotypes triggered by inactivation of calcineurin, a Ca2+-dependent phosphatase. Finally, similarity of the interaction profiles was used to reveal a connected network among the Ca2+ homeostasis units acting in different cellular compartments. Our analyses of high-dimensional chemical-genetic interaction profiles provide novel insights into the intracellular network of yeast Ca2+ homeostasis. PMID:28566553

Population Structure, Genetic Diversity and Molecular Marker-Trait Association Analysis for High Temperature Stress Tolerance in Rice.

PubMed

Pradhan, Sharat Kumar; Barik, Saumya Ranjan; Sahoo, Ambika; Mohapatra, Sudipti; Nayak, Deepak Kumar; Mahender, Anumalla; Meher, Jitandriya; Anandan, Annamalai; Pandit, Elssa

2016-01-01

Rice exhibits enormous genetic diversity, population structure and molecular marker-traits associated with abiotic stress tolerance to high temperature stress. A set of breeding lines and landraces representing 240 germplasm lines were studied. Based on spikelet fertility percent under high temperature, tolerant genotypes were broadly classified into four classes. Genetic diversity indicated a moderate level of genetic base of the population for the trait studied. Wright's F statistic estimates showed a deviation of Hardy-Weinberg expectation in the population. The analysis of molecular variance revealed 25 percent variation between population, 61 percent among individuals and 14 percent within individuals in the set. The STRUCTURE analysis categorized the entire population into three sub-populations and suggested that most of the landraces in each sub-population had a common primary ancestor with few admix individuals. The composition of materials in the panel showed the presence of many QTLs representing the entire genome for the expression of tolerance. The strongly associated marker RM547 tagged with spikelet fertility under stress and the markers like RM228, RM205, RM247, RM242, INDEL3 and RM314 indirectly controlling the high temperature stress tolerance were detected through both mixed linear model and general linear model TASSEL analysis. These markers can be deployed as a resource for marker-assisted breeding program of high temperature stress tolerance.

Evaluation of an ensemble of genetic models for prediction of a quantitative trait.

PubMed

Milton, Jacqueline N; Steinberg, Martin H; Sebastiani, Paola

2014-01-01

Many genetic markers have been shown to be associated with common quantitative traits in genome-wide association studies. Typically these associated genetic markers have small to modest effect sizes and individually they explain only a small amount of the variability of the phenotype. In order to build a genetic prediction model without fitting a multiple linear regression model with possibly hundreds of genetic markers as predictors, researchers often summarize the joint effect of risk alleles into a genetic score that is used as a covariate in the genetic prediction model. However, the prediction accuracy can be highly variable and selecting the optimal number of markers to be included in the genetic score is challenging. In this manuscript we present a strategy to build an ensemble of genetic prediction models from data and we show that the ensemble-based method makes the challenge of choosing the number of genetic markers more amenable. Using simulated data with varying heritability and number of genetic markers, we compare the predictive accuracy and inclusion of true positive and false positive markers of a single genetic prediction model and our proposed ensemble method. The results show that the ensemble of genetic models tends to include a larger number of genetic variants than a single genetic model and it is more likely to include all of the true genetic markers. This increased sensitivity is obtained at the price of a lower specificity that appears to minimally affect the predictive accuracy of the ensemble.

HpQTL: a geometric morphometric platform to compute the genetic architecture of heterophylly.

PubMed

Sun, Lidan; Wang, Jing; Zhu, Xuli; Jiang, Libo; Gosik, Kirk; Sang, Mengmeng; Sun, Fengsuo; Cheng, Tangren; Zhang, Qixiang; Wu, Rongling

2017-02-15

Heterophylly, i.e. morphological changes in leaves along the axis of an individual plant, is regarded as a strategy used by plants to cope with environmental change. However, little is known of the extent to which heterophylly is controlled by genes and how each underlying gene exerts its effect on heterophyllous variation. We described a geometric morphometric model that can quantify heterophylly in plants and further constructed an R-based computing platform by integrating this model into a genetic mapping and association setting. The platform, named HpQTL, allows specific quantitative trait loci mediating heterophyllous variation to be mapped throughout the genome. The statistical properties of HpQTL were examined and validated via computer simulation. Its biological relevance was demonstrated by results from a real data analysis of heterophylly in a wood plant, mei (Prunus mume). HpQTL provides a powerful tool to analyze heterophylly and its underlying genetic architecture in a quantitative manner. It also contributes a new approach for genome-wide association studies aimed to dissect the programmed regulation of plant development and evolution. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Mapping Heart Development in Flies: Src42A Acts Non-Autonomously to Promote Heart Tube Formation in Drosophila

PubMed Central

Vanderploeg, Jessica; Jacobs, J. Roger

2017-01-01

Congenital heart defects, clinically identified in both small and large animals, are multifactorial and complex. Although heritable factors are known to have a role in cardiovascular disease, the full genetic aetiology remains unclear. Model organism research has proven valuable in providing a deeper understanding of the essential factors in heart development. For example, mouse knock-out studies reveal a role for the Integrin adhesion receptor in cardiac tissue. Recent research in Drosophila melanogaster (the fruit fly), a powerful experimental model, has demonstrated that the link between the extracellular matrix and the cell, mediated by Integrins, is required for multiple aspects of cardiogenesis. Here we test the hypothesis that Integrins signal to the heart cells through Src42A kinase. Using the powerful genetics and cell biology analysis possible in Drosophila, we demonstrate that Src42A acts in early events of heart tube development. Careful examination of mutant heart tissue and genetic interaction data suggests that Src42A’s role is independent of Integrin and the Integrin-related Focal Adhesion Kinase. Rather, Src42A acts non-autonomously by promoting programmed cell death of the amnioserosa, a transient tissue that neighbors the developing heart. PMID:29056682

Initialization Method for Grammar-Guided Genetic Programming

NASA Astrophysics Data System (ADS)

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

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

Genetic conservation and paddlefish propagation

USGS Publications Warehouse

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

2009-01-01

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

The collaborative African genomics network training program: a trainee perspective on training the next generation of African scientists.

PubMed

Mlotshwa, Busisiwe C; Mwesigwa, Savannah; Mboowa, Gerald; Williams, Lesedi; Retshabile, Gaone; Kekitiinwa, Adeodata; Wayengera, Misaki; Kyobe, Samuel; Brown, Chester W; Hanchard, Neil A; Mardon, Graeme; Joloba, Moses; Anabwani, Gabriel; Mpoloka, Sununguko W

2017-07-01

The Collaborative African Genomics Network (CAfGEN) aims to establish sustainable genomics research programs in Botswana and Uganda through long-term training of PhD students from these countries at Baylor College of Medicine. Here, we present an overview of the CAfGEN PhD training program alongside trainees' perspectives on their involvement. Historically, collaborations between high-income countries (HICs) and low- and middle-income countries (LMICs), or North-South collaborations, have been criticized for the lack of a mutually beneficial distribution of resources and research findings, often undermining LMICs. CAfGEN plans to address this imbalance in the genomics field through a program of technology and expertise transfer to the participating LMICs. An overview of the training program is presented. Trainees from the CAfGEN project summarized their experiences, looking specifically at the training model, benefits of the program, challenges encountered relating to the cultural transition, and program outcomes after the first 2 years. Collaborative training programs like CAfGEN will not only help establish sustainable long-term research initiatives in LMICs but also foster stronger North-South and South-South networks. The CAfGEN model offers a framework for the development of training programs aimed at genomics education for those for whom genomics is not their "first language." Genet Med advance online publication 06 April 2017.

The collaborative African genomics network training program: a trainee perspective on training the next generation of African scientists

PubMed Central

Mlotshwa, Busisiwe C.; Mwesigwa, Savannah; Mboowa, Gerald; Williams, Lesedi; Retshabile, Gaone; Kekitiinwa, Adeodata; Wayengera, Misaki; Kyobe, Samuel; Brown, Chester W.; Hanchard, Neil A.; Mardon, Graeme; Joloba, Moses; Anabwani, Gabriel; Mpoloka, Sununguko W.

2017-01-01

Purpose: The Collaborative African Genomics Network (CAfGEN) aims to establish sustainable genomics research programs in Botswana and Uganda through long-term training of PhD students from these countries at Baylor College of Medicine. Here, we present an overview of the CAfGEN PhD training program alongside trainees’ perspectives on their involvement. Background: Historically, collaborations between high-income countries (HICs) and low- and middle-income countries (LMICs), or North–South collaborations, have been criticized for the lack of a mutually beneficial distribution of resources and research findings, often undermining LMICs. CAfGEN plans to address this imbalance in the genomics field through a program of technology and expertise transfer to the participating LMICs. Methods: An overview of the training program is presented. Trainees from the CAfGEN project summarized their experiences, looking specifically at the training model, benefits of the program, challenges encountered relating to the cultural transition, and program outcomes after the first 2 years. Conclusion: Collaborative training programs like CAfGEN will not only help establish sustainable long-term research initiatives in LMICs but also foster stronger North–South and South–South networks. The CAfGEN model offers a framework for the development of training programs aimed at genomics education for those for whom genomics is not their “first language.” Genet Med advance online publication 06 April 2017 PMID:28383545

Genetic characterization of Russian honey bee stock selected for improved resistance to Varroa destructor.

PubMed

Bourgeois, A Lelania; Rinderer, Thomas E

2009-06-01

Maintenance of genetic diversity among breeding lines is important in selective breeding and stock management. The Russian Honey Bee Breeding Program has strived to maintain high levels of heterozygosity among its breeding lines since its inception in 1997. After numerous rounds of selection for resistance to tracheal and varroa mites and improved honey production, 18 lines were selected as the core of the program. These lines were grouped into three breeding blocks that were crossbred to improve overall heterozygosity levels of the population. Microsatellite DNA data demonstrated that the program has been successful. Heterozygosity and allelic richness values are high and there are no indications of inbreeding among the three blocks. There were significant levels of genetic structure measured among the three blocks. Block C was genetically distinct from both blocks A and B (F(ST) = 0.0238), whereas blocks A and B did not differ from each other (F(ST) = 0.0074). The same pattern was seen for genic (based on numbers of alleles) differentiation. Genetic distance, as measured by chord distance, indicates that all of the 18 lines are equally distant, with minimal clustering. The data indicate that the overall design of the breeding program has been successful in maintaining high levels of diversity and avoiding problems associated with inbreeding.

Genetic Counseling Graduate Student Debt: Impact on Program, Career and Life Choices

PubMed Central

Kuhl, Ashley; Reiser, Catherine; Eickhoff, Jens; Petty, Elizabeth M

2015-01-01

The cost of education is rising, increasing student financial aid and debt for students pursuing higher education. A few studies have assessed the impact of student debt in medicine, physical therapy and social work, but little is known about the impact of student debt on genetic counseling students and graduates. To address this gap in knowledge, a web-based study of 408 recent alumni of genetic counseling programs in North America was conducted to assess the impact of student debt on program, career and life choices. Over half (63%; n=256/408) of the participants reported that loans were extremely important in their ability to attend their training program, with most using subsidized loans no longer available to current graduate students. While participants were generally satisfied with their genetic counseling education, 83% (n=282/342) of participants with student debt reported feeling burdened by their debt, which had a median of $40,000-$50,000. This debt is relatively close to the median starting salary reported by survey participants ($45,000-$50,000), breaching the “20-10 rule” that states student debt should not exceed 20% of annual net income. In response to this critical issue, we propose recommendations for the genetic counseling field that may help alleviate student debt impact and burden. PMID:24578121

A stepwise model to predict monthly streamflow

NASA Astrophysics Data System (ADS)

Mahmood Al-Juboori, Anas; Guven, Aytac

2016-12-01

In this study, a stepwise model empowered with genetic programming is developed to predict the monthly flows of Hurman River in Turkey and Diyalah and Lesser Zab Rivers in Iraq. The model divides the monthly flow data to twelve intervals representing the number of months in a year. The flow of a month, t is considered as a function of the antecedent month's flow (t - 1) and it is predicted by multiplying the antecedent monthly flow by a constant value called K. The optimum value of K is obtained by a stepwise procedure which employs Gene Expression Programming (GEP) and Nonlinear Generalized Reduced Gradient Optimization (NGRGO) as alternative to traditional nonlinear regression technique. The degree of determination and root mean squared error are used to evaluate the performance of the proposed models. The results of the proposed model are compared with the conventional Markovian and Auto Regressive Integrated Moving Average (ARIMA) models based on observed monthly flow data. The comparison results based on five different statistic measures show that the proposed stepwise model performed better than Markovian model and ARIMA model. The R2 values of the proposed model range between 0.81 and 0.92 for the three rivers in this study.

Genome-wide association study (GWAS) for growth rate and age at sexual maturation in Atlantic salmon (Salmo salar).

PubMed

Gutierrez, Alejandro P; Yáñez, José M; Fukui, Steve; Swift, Bruce; Davidson, William S

2015-01-01

Early sexual maturation is considered a serious drawback for Atlantic salmon aquaculture as it retards growth, increases production times and affects flesh quality. Although both growth and sexual maturation are thought to be complex processes controlled by several genetic and environmental factors, selection for these traits has been continuously accomplished since the beginning of Atlantic salmon selective breeding programs. In this genome-wide association study (GWAS) we used a 6.5K single-nucleotide polymorphism (SNP) array to genotype ∼ 480 individuals from the Cermaq Canada broodstock program and search for SNPs associated with growth and age at sexual maturation. Using a mixed model approach we identified markers showing a significant association with growth, grilsing (early sexual maturation) and late sexual maturation. The most significant associations were found for grilsing, with markers located in Ssa10, Ssa02, Ssa13, Ssa25 and Ssa12, and for late maturation with markers located in Ssa28, Ssa01 and Ssa21. A lower level of association was detected with growth on Ssa13. Candidate genes, which were linked to these genetic markers, were identified and some of them show a direct relationship with developmental processes, especially for those in association with sexual maturation. However, the relatively low power to detect genetic markers associated with growth (days to 5 kg) in this GWAS indicates the need to use a higher density SNP array in order to overcome the low levels of linkage disequilibrium observed in Atlantic salmon before the information can be incorporated into a selective breeding program.

Presenting a new kinetic model for methanol to light olefins reactions over a hierarchical SAPO-34 catalyst using the Langmuir-Hinshelwood-Hougen-Watson mechanism

NASA Astrophysics Data System (ADS)

Javad Azarhoosh, Mohammad; Halladj, Rouein; Askari, Sima

2017-10-01

In this study, a new kinetic model for methanol to light olefins (MTO) reactions over a hierarchical SAPO-34 catalyst using the Langmuir-Hinshelwood-Hougen-Watson (LHHW) mechanism was presented and the kinetic parameters was obtained using a genetic algorithm (GA) and genetic programming (GP). Several kinetic models for the MTO reactions have been presented. However, due to the complexity of the reactions, most reactions are considered lumped and elementary, which cannot be deemed a completely accurate kinetic model of the process. Therefore, in this study, the LHHW mechanism is presented as kinetic models of MTO reactions. Because of the non-linearity of the kinetic models and existence of many local optimal points, evolutionary algorithms (GA and GP) are used in this study to estimate the kinetic parameters in the rate equations. Via the simultaneous connection of the code related to modelling the reactor and the GA and GP codes in the MATLAB R2013a software, optimization of the kinetic models parameters was performed such that the least difference between the results from the kinetic models and experiential results was obtained and the best kinetic parameters of MTO process reactions were achieved. A comparison of the results from the model with experiential results showed that the present model possesses good accuracy.

Combinatorial structures to modeling simple games and applications

NASA Astrophysics Data System (ADS)

Molinero, Xavier

2017-09-01

We connect three different topics: combinatorial structures, game theory and chemistry. In particular, we establish the bases to represent some simple games, defined as influence games, and molecules, defined from atoms, by using combinatorial structures. First, we characterize simple games as influence games using influence graphs. It let us to modeling simple games as combinatorial structures (from the viewpoint of structures or graphs). Second, we formally define molecules as combinations of atoms. It let us to modeling molecules as combinatorial structures (from the viewpoint of combinations). It is open to generate such combinatorial structures using some specific techniques as genetic algorithms, (meta-)heuristics algorithms and parallel programming, among others.

Molecular characterization of high performance inbred lines of Brazilian common beans.

PubMed

Cardoso, P C B; Veiga, M M; de Menezes, I P P; Valdisser, P A M R; Borba, T C O; Melo, L C; Del Peloso, M J; Brondani, C; Vianello, R P

2013-02-06

The identification of germplasm genetic variability in breeding programs of the common bean (Phaseolus vulgaris) is essential for determining the potential of each combination of parent plants to obtain superior genotypes. The present study aimed to estimated the extent of genetic diversity in 172 lineages and cultivars of the common bean by integrating five tests of value for cultivation and use (VCU) that were conducted over the last eight years by the breeding program of Embrapa Arroz e Feijão in Brazil. Nine multilocus genotyping systems composed of 36 fluorescent microsatellite markers distributed across 11 different chromosomes of the common bean were used, of which 24 were polymorphic in all trials. One hundred and eighty-seven alleles were identified, with an average of 7.79 alleles per locus and an average gene diversity of 0.65. The combined probability of identity for all loci was 1.32 x 10(-16). Lineages that are more genetically divergent between the selection cycles were identified, allowing the breeding program to develop a crossbreed between elite genotypes with a low degree of genetic relatedness. HE values ranged from 0.31 to 0.63, with a large reduction in the genetic base over successive selection cycles. The test showed a significant degree of differentiation (FST = 0.159). Private alleles (26%) were identified and can be directly incorporated into the gene pool of cultivated germplasm, thereby contributing effectively to the expansion of genetic diversity in this bean-breeding program.

Ancient deuterostome origins of vertebrate brain signalling centres.

PubMed

Pani, Ariel M; Mullarkey, Erin E; Aronowicz, Jochanan; Assimacopoulos, Stavroula; Grove, Elizabeth A; Lowe, Christopher J

2012-03-14

Neuroectodermal signalling centres induce and pattern many novel vertebrate brain structures but are absent, or divergent, in invertebrate chordates. This has led to the idea that signalling-centre genetic programs were first assembled in stem vertebrates and potentially drove morphological innovations of the brain. However, this scenario presumes that extant cephalochordates accurately represent ancestral chordate characters, which has not been tested using close chordate outgroups. Here we report that genetic programs homologous to three vertebrate signalling centres-the anterior neural ridge, zona limitans intrathalamica and isthmic organizer-are present in the hemichordate Saccoglossus kowalevskii. Fgf8/17/18 (a single gene homologous to vertebrate Fgf8, Fgf17 and Fgf18), sfrp1/5, hh and wnt1 are expressed in vertebrate-like arrangements in hemichordate ectoderm, and homologous genetic mechanisms regulate ectodermal patterning in both animals. We propose that these genetic programs were components of an unexpectedly complex, ancient genetic regulatory scaffold for deuterostome body patterning that degenerated in amphioxus and ascidians, but was retained to pattern divergent structures in hemichordates and vertebrates. © 2012 Macmillan Publishers Limited. All rights reserved

Heritabilities of measured and mid-infrared predicted milk fat globule size, milk fat and protein percentages, and their genetic correlations.

PubMed

Fleming, A; Schenkel, F S; Koeck, A; Malchiodi, F; Ali, R A; Corredig, M; Mallard, B; Sargolzaei, M; Miglior, F

2017-05-01

The objective of this study was to estimate the heritability of milk fat globule (MFG) size and mid-infrared (MIR) predicted MFG size in Holstein cattle. The genetic correlations between measured and predicted MFG size with milk fat and protein percentage were also investigated. Average MFG size was measured in 1,583 milk samples taken from 254 Holstein cows from 29 herds across Canada. Size was expressed as volume moment mean (D[4,3]) and surface moment mean (D[3,2]). Analyzed milk samples also had average MFG size predicted from their MIR spectral records. Fat and protein percentages were obtained for all test-day milk samples in the cow's lactation. Univariate and bivariate repeatability animal models were used to estimate heritability and genetic correlations. Moderate heritabilities of 0.364 and 0.466 were found for D[4,3] and D[3,2], respectively, and a strong genetic correlation was found between the 2 traits (0.98). The heritabilities for the MIR-predicted MFG size were lower than those estimated for the measured MFG size at 0.300 for predicted D[4,3] and 0.239 for predicted D[3,2]. The genetic correlation between measured and predicted D[4,3] was 0.685; the correlation was slightly higher between measured and predicted D[3,2] at 0.764, likely due to the better prediction accuracy of D[3,2]. Milk fat percentage had moderate genetic correlations with both D[4,3] and D[3,2] (0.538 and 0.681, respectively). The genetic correlation between predicted MFG size and fat percentage was much stronger (greater than 0.97 for both predicted D[4,3] and D[3,2]). The stronger correlation suggests a limitation for the use of the predicted values of MFG size as indicator traits for true average MFG size in milk in selection programs. Larger samples sizes are required to provide better evidence of the estimated genetic parameters. A genetic component appears to exist for the average MFG size in bovine milk, and the variation could be exploited in selection programs. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Expert and Advocacy Group Consensus Findings on the Horizon of Public Health Genetic Testing

PubMed Central

Modell, Stephen M.; Greendale, Karen; Citrin, Toby; Kardia, Sharon L. R.

2016-01-01

Description: Among the two leading causes of death in the United States, each responsible for one in every four deaths, heart disease costs Americans $300 billion, while cancer costs Americans $216 billion per year. They also rank among the top three causes of death in Europe and Asia. In 2012 the University of Michigan Center for Public Health and Community Genomics and Genetic Alliance, with the support of the Centers for Disease Control and Prevention Office of Public Health Genomics, hosted a conference in Atlanta, Georgia to consider related action strategies based on public health genomics. The aim of the conference was consensus building on recommendations to implement genetic screening for three major heritable contributors to these mortality and cost figures: hereditary breast and ovarian cancer (HBOC), familial hypercholesterolemia (FH), and Lynch syndrome (LS). Genetic applications for these three conditions are labeled with a “Tier 1” designation by the U.S. Centers for Disease Control and Prevention because they have been fully validated and clinical practice guidelines based on systematic review support them. Methodology: The conference followed a deliberative sequence starting with nationally recognized clinical and public health presenters for each condition, followed by a Patient and Community Perspectives Panel, working group sessions for each of the conditions, and a final plenary session. The 74 conference participants represented disease research and advocacy, public health, medicine and nursing, genetics, governmental health agencies, and industry. Participants drew on a public health framework interconnecting policy, clinical intervention, surveillance, and educational functions for their deliberations. Results: Participants emphasized the importance of collaboration between clinical, public health, and advocacy groups in implementing Tier 1 genetic screening. Advocacy groups could help with individual and institutional buy-in of Tier 1 programs. Groups differed on funding strategies, with alternative options such as large-scale federal funding and smaller scale, incremental funding solutions proposed. Piggybacking on existing federal breast and colorectal cancer control programs was suggested. Public health departments need to assess what information is now being collected by their state cancer registries. The groups advised that information on cascade screening of relatives be included in toolkits for use by states. Participants stressed incorporation of family history into health department breast cancer screening programs, and clinical HBOC data into state surveillance systems. The carrying out of universal LS screening of tumors in those with colorectal cancer was reviewed. Expansion of universal screening to include endometrial tumors was discussed, as was the application of guidelines recommending cholesterol screening of children 9–11 years old. States more advanced in terms of Tier 1 testing could serve as models and partners with other states launching screening and surveillance programs. A multidisciplinary team of screening program champions was suggested as a means of raising awareness among the consumer and health care communities. Participants offered multiple recommendations regarding use of electronic health records, including flagging of at-risk family members and utilization of state-level health information exchanges. The paper contains an update of policy developments and happenings for all three Tier 1 conditions, as well as identified gaps. Conclusions: Implementation of cascade screening of family members for HBOC and FH, and universal screening for LS in CRC tumors has reached a point of readiness within the U.S., with creative solutions at hand. Facilitating factors such as screening coverage through the Patient Protection and Affordable Care Act, and state health information exchanges can be tapped. Collaboration is needed between public health departments, health care systems, disease advocacy groups, and industry to fully realize Tier 1 genetic screening. State health department and disease networks currently engaged in Tier 1 screening can serve as models for the launch of new initiatives. PMID:27417602

Genome stability of programmed stem cell products.

PubMed

Martin, Ulrich

2017-10-01

Inherited and acquired genomic abnormalities are known to cause genetic diseases and contribute to cancer formation. Recent studies demonstrated a substantial mutational load in mouse and human embryonic and induced pluripotent stem cells (ESCs and iPSCs). Single nucleotide variants, copy number variations, and larger chromosomal abnormalities may influence the differentiation capacity of pluripotent stem cells and the functionality of their derivatives in disease modeling and drug screening, and are considered a serious risk for cellular therapies based on ESC or iPSC derivatives. This review discusses the types and origins of different genetic abnormalities in pluripotent stem cells, methods for their detection, and the mechanisms of development and enrichment during reprogramming and culture expansion. Copyright © 2017 Elsevier B.V. All rights reserved.

Space Research Program on Planarian Schmidtea Mediterranea's Establishment of the Anterior-Posterior Axis in Altered Gravity Conditions

NASA Astrophysics Data System (ADS)

Auletta, G.; Adell, T.; Colagè, I.; D'Ambrosio, P.; Salò, E.

2012-12-01

Planarians of the species Schmidtea mediterranea are a well-established model for regeneration studies. In this paper, we first recall the morphological characters and the molecular mechanisms involved in the regeneration process, especially focussing on the Wnt pathway and the establishment of the antero-posterior axial polarity. Then, after an assessment of a space-experiment (run in 2006 on the Russian Segment of the International Space Station) on planarians of the species Girardia tigrina, we present our experimental program to ascertain the effects that altered-gravity conditions may have on regeneration processes in S. mediterrnea at the molecular and genetic level.

The GP problem: quantifying gene-to-phenotype relationships.

PubMed

Cooper, Mark; Chapman, Scott C; Podlich, Dean W; Hammer, Graeme L

2002-01-01

In this paper we refer to the gene-to-phenotype modeling challenge as the GP problem. Integrating information across levels of organization within a genotype-environment system is a major challenge in computational biology. However, resolving the GP problem is a fundamental requirement if we are to understand and predict phenotypes given knowledge of the genome and model dynamic properties of biological systems. Organisms are consequences of this integration, and it is a major property of biological systems that underlies the responses we observe. We discuss the E(NK) model as a framework for investigation of the GP problem and the prediction of system properties at different levels of organization. We apply this quantitative framework to an investigation of the processes involved in genetic improvement of plants for agriculture. In our analysis, N genes determine the genetic variation for a set of traits that are responsible for plant adaptation to E environment-types within a target population of environments. The N genes can interact in epistatic NK gene-networks through the way that they influence plant growth and development processes within a dynamic crop growth model. We use a sorghum crop growth model, available within the APSIM agricultural production systems simulation model, to integrate the gene-environment interactions that occur during growth and development and to predict genotype-to-phenotype relationships for a given E(NK) model. Directional selection is then applied to the population of genotypes, based on their predicted phenotypes, to simulate the dynamic aspects of genetic improvement by a plant-breeding program. The outcomes of the simulated breeding are evaluated across cycles of selection in terms of the changes in allele frequencies for the N genes and the genotypic and phenotypic values of the populations of genotypes.

Potential demographic and genetic effects of a sterilant applied to wild horse mares

USGS Publications Warehouse

Roelle, James E.; Oyler-McCance, Sara J.

2015-01-01

Wild horse populations on western ranges can increase rapidly, resulting in the need for the Bureau of Land Management (BLM) to remove animals in order to protect the habitat that horses share with numerous other species. As an alternative to removals, BLM has sought to develop a long-term, perhaps even permanent, contraceptive to aid in reducing population growth rates. With long-term (perhaps even permanent) efficacy of contraception, however, comes increased concern about the genetic health of populations and about the potential for local extirpation. We used simulation modeling to examine the potential demographic and genetic consequences of applying a mare sterilant to wild horse populations. Using the VORTEX software package, we modeled the potential effects of a sterilant on 70 simulated populations having different initial sizes (7 values), growth rates (5 values), and genetic diversity (2 values). For each population, we varied the treatment rate of mares from 0 to 100 percent in increments of 10 percent. For each combination of these treatment levels, we ran 100 stochastic simulations, and we present the results in the form of tables and graphs showing mean population size after 20 years, mean number of removals after 20 years, mean probability of extirpation after 50 years, and mean heterozygosity after 50 years. By choosing one or two combinations of initial population size, population growth rate, and genetic diversity that best represent a herd of interest, a manager can assess the likely effects of a contraceptive program by examining the output tables and graphs representing the selected conditions.

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

PubMed Central

Lathrop, G M; Lalouel, J M

1984-01-01

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

Proceedings of the symposium on isozymes of North American forest trees and forest insects; July 27, 1979; Berkeley, California

Treesearch

M. Thompson Conkle

1981-01-01

These 10 symposium papers discuss gene resource management, basic genetics, genetic variation between and within tree species, genetic variability and growth, comparisons of tree life history characteristics, genetic variation in forest insects, breeding systems, and applied uses of isozymes in breeding programs.

Genetic Variation Among Open-Pollinated Progeny of Eastern Cottonwood

Treesearch

R. E. Farmer

1970-01-01

Improvement programs in eastern cottonwood (Populus deltoides Bartr.) are most frequently designed to produce genetically superior clones for direct commercial use. This paper describes a progeny test to assess genetic variability on which selection might be based.

Maternal nutrition, intrauterine programming and consequential risks in the offspring.

PubMed

Yajnik, Chittaranjan S; Deshmukh, Urmila S

2008-09-01

It is traditionally believed that genetic susceptibility and adult faulty lifestyle lead to type 2 diabetes, a chronic non-communicable disease. The "Developmental Origins of Health and Disease" (DOHaD) model proposes that the susceptibility to type 2 diabetes originates in the intrauterine life by environmental fetal programming, further exaggerated by rapid childhood growth, i.e. a biphasic nutritional insult. Both fetal under nutrition (sometimes manifested as low birth weight) and over nutrition (the baby of a diabetic mother) increase the risk of future diabetes. The common characteristic of these two types of babies is their high adiposity. An imbalance in nutrition seems to play an important role, and micronutrients seem particularly important. Normal to high maternal folate status coupled with low vitamin B(12) status predicted higher adiposity and insulin resistance in Indian babies. Thus, 1-C (methyl) metabolism seems to play a key role in fetal programming. DOHaD represents a paradigm shift in the model for prevention of the chronic non-communicable diseases.

Estimation of soil cation exchange capacity using Genetic Expression Programming (GEP) and Multivariate Adaptive Regression Splines (MARS)

NASA Astrophysics Data System (ADS)

Emamgolizadeh, S.; Bateni, S. M.; Shahsavani, D.; Ashrafi, T.; Ghorbani, H.

2015-10-01

The soil cation exchange capacity (CEC) is one of the main soil chemical properties, which is required in various fields such as environmental and agricultural engineering as well as soil science. In situ measurement of CEC is time consuming and costly. Hence, numerous studies have used traditional regression-based techniques to estimate CEC from more easily measurable soil parameters (e.g., soil texture, organic matter (OM), and pH). However, these models may not be able to adequately capture the complex and highly nonlinear relationship between CEC and its influential soil variables. In this study, Genetic Expression Programming (GEP) and Multivariate Adaptive Regression Splines (MARS) were employed to estimate CEC from more readily measurable soil physical and chemical variables (e.g., OM, clay, and pH) by developing functional relations. The GEP- and MARS-based functional relations were tested at two field sites in Iran. Results showed that GEP and MARS can provide reliable estimates of CEC. Also, it was found that the MARS model (with root-mean-square-error (RMSE) of 0.318 Cmol+ kg-1 and correlation coefficient (R2) of 0.864) generated slightly better results than the GEP model (with RMSE of 0.270 Cmol+ kg-1 and R2 of 0.807). The performance of GEP and MARS models was compared with two existing approaches, namely artificial neural network (ANN) and multiple linear regression (MLR). The comparison indicated that MARS and GEP outperformed the MLP model, but they did not perform as good as ANN. Finally, a sensitivity analysis was conducted to determine the most and the least influential variables affecting CEC. It was found that OM and pH have the most and least significant effect on CEC, respectively.