Evaluation of algorithms used to order markers on genetic maps

When building genetic maps, it is necessary to choose from several marker ordering algorithms and criteria, and the choice is not always simple. In this study, we evaluate the efficiency of algorithms try (TRY), seriation (SER), rapid chain delineation (RCD), recombination counting and ordering (RECORD) and unidirectional growth (UG), as well as the criteria PARF (product of adjacent recombination fractions), SARF (sum of adjacent recombination fractions), SALOD (sum of adjacent LOD scores) and LHMC (likelihood through hidden Markov chains), used with the RIPPLE algorithm for error verification, in the construction of genetic linkage maps. A linkage map of a hypothetical diploid and monoecious plant species was simulated containing one linkage group and 21 markers with fixed distance of 3 cM between them. In all, 700 F(2) populations were randomly simulated with and 400 individuals with different combinations of dominant and co-dominant markers, as well as 10 and 20% of missing data. The simulations showed that, in the presence of co-dominant markers only, any combination of algorithm and criteria may be used, even for a reduced population size. In the case of a smaller proportion of dominant markers, any of the algorithms and criteria (except SALOD) investigated may be used. In the presence of high proportions of dominant markers and smaller samples (around 100), the probability of repulsion linkage increases between them and, in this case, use of the algorithms TRY and SER associated to RIPPLE with criterion LHMC would provide better results. Heredity (2009) 103, 494-502; doi:10.1038/hdy.2009.96; published online 29 July 2009

Combined heuristic with fuzzy system to transmission system expansion planning

A heuristic algorithm that employs fuzzy logic is proposed to the power system transmission expansion planning problem. The algorithm is based on the divide to conquer strategy, which is controlled by the fuzzy system. The algorithm provides high quality solutions with the use of fuzzy decision making, which is based on nondeterministic criteria to guide the search. The fuzzy system provides a self-adjusting mechanism that eliminates the manual adjustment of parameters to each system being solved. (C) 2010 Elsevier B.V. All rights reserved.

A Constructive Genetic Algorithm for permutation flowshop scheduling

The general flowshop scheduling problem is a production problem where a set of n jobs have to be processed with identical flow pattern on in machines. In permutation flowshops the sequence of jobs is the same on all machines. A significant research effort has been devoted for sequencing jobs in a flowshop minimizing the makespan. This paper describes the application of a Constructive Genetic Algorithm (CGA) to makespan minimization on flowshop scheduling. The CGA was proposed recently as an alternative to traditional GA approaches, particularly, for evaluating schemata directly. The population initially formed only by schemata, evolves controlled by recombination to a population of well-adapted structures (schemata instantiation). The CGA implemented is based on the NEH classic heuristic and a local search heuristic used to define the fitness functions. The parameters of the CGA are calibrated using a Design of Experiments (DOE) approach. The computational results are compared against some other successful algorithms from the literature on Taillard`s well-known standard benchmark. The computational experience shows that this innovative CGA approach provides competitive results for flowshop scheduling; problems. (C) 2007 Elsevier Ltd. All rights reserved.

Fuzzy computational control for real Chua circuit

We preserit a computational procedure to control art experimental chaotic system by applying the occasional proportional feedback (OPF) method. The method implementation uses the fuzzy theory to relate the variable correction to the necessary adjustment in the control parameter. As an application We control the chaotic attractors of the Chua circuit. We present file developed circuits and algorithms to implement this control in real time. To simplify the used procedure, we use it low resolution analog to digital converter compensated for a lowpass filter that facilitates similar applications to control other systems. (C) 2007 Elsevier Ltd. All rights reserved.

Jointly multi-user detection and channel estimation with genetic algorithm

This work aims at proposing the use of the evolutionary computation methodology in order to jointly solve the multiuser channel estimation (MuChE) and detection problems at its maximum-likelihood, both related to the direct sequence code division multiple access (DS/CDMA). The effectiveness of the proposed heuristic approach is proven by comparing performance and complexity merit figures with that obtained by traditional methods found in literature. Simulation results considering genetic algorithm (GA) applied to multipath, DS/CDMA and MuChE and multi-user detection (MuD) show that the proposed genetic algorithm multi-user channel estimation (GAMuChE) yields a normalized mean square error estimation (nMSE) inferior to 11%, under slowly varying multipath fading channels, large range of Doppler frequencies and medium system load, it exhibits lower complexity when compared to both maximum likelihood multi-user channel estimation (MLMuChE) and gradient descent method (GrdDsc). A near-optimum multi-user detector (MuD) based on the genetic algorithm (GAMuD), also proposed in this work, provides a significant reduction in the computational complexity when compared to the optimum multi-user detector (OMuD). In addition, the complexity of the GAMuChE and GAMuD algorithms were (jointly) analyzed in terms of number of operations necessary to reach the convergence, and compared to other jointly MuChE and MuD strategies. The joint GAMuChE-GAMuD scheme can be regarded as a promising alternative for implementing third-generation (3G) and fourth-generation (4G) wireless systems in the near future. Copyright (C) 2010 John Wiley & Sons, Ltd.

On the efficiency of evolutionary fuzzy clustering

This paper tackles the problem of showing that evolutionary algorithms for fuzzy clustering can be more efficient than systematic (i.e. repetitive) approaches when the number of clusters in a data set is unknown. To do so, a fuzzy version of an Evolutionary Algorithm for Clustering (EAC) is introduced. A fuzzy cluster validity criterion and a fuzzy local search algorithm are used instead of their hard counterparts employed by EAC. Theoretical complexity analyses for both the systematic and evolutionary algorithms under interest are provided. Examples with computational experiments and statistical analyses are also presented.

Grid job scheduling using Route with Genetic Algorithm support

In 2006 the Route load balancing algorithm was proposed and compared to other techniques aiming at optimizing the process allocation in grid environments. This algorithm schedules tasks of parallel applications considering computer neighborhoods (where the distance is defined by the network latency). Route presents good results for large environments, although there are cases where neighbors do not have an enough computational capacity nor communication system capable of serving the application. In those situations the Route migrates tasks until they stabilize in a grid area with enough resources. This migration may take long time what reduces the overall performance. In order to improve such stabilization time, this paper proposes RouteGA (Route with Genetic Algorithm support) which considers historical information on parallel application behavior and also the computer capacities and load to optimize the scheduling. This information is extracted by using monitors and summarized in a knowledge base used to quantify the occupation of tasks. Afterwards, such information is used to parameterize a genetic algorithm responsible for optimizing the task allocation. Results confirm that RouteGA outperforms the load balancing carried out by the original Route, which had previously outperformed others scheduling algorithms from literature.

Inteligência artificial aplicada à Zootecnia

Os sistemas biológicos são surpreendentemente flexíveis pra processar informação proveniente do mundo real. Alguns organismos biológicos possuem uma unidade central de processamento denominada de cérebro. O cérebro humano consiste de 10(11) neurônios e realiza processamento inteligente de forma exata e subjetiva. A Inteligência Artificial (IA) tenta trazer para o mundo da computação digital a heurística dos sistemas biológicos de várias maneiras, mas, ainda resta muito para que isso seja concretizado. No entanto, algumas técnicas como Redes neurais artificiais e lógica fuzzy tem mostrado efetivas para resolver problemas complexos usando a heurística dos sistemas biológicos. Recentemente o numero de aplicação dos métodos da IA em sistemas zootécnicos tem aumentado significativamente. O objetivo deste artigo é explicar os princípios básicos da resolução de problemas usando heurística e demonstrar como a IA pode ser aplicada para construir um sistema especialista para resolver problemas na área de zootecnia.

Inbreeding levels in Northeast Brazil: strategies for the prospecting of new genetic disorders

A new autosomal recessive genetic condition, the SPOAN syndrome (an acronym for spastic paraplegia, optic atrophy and neuropathy syndrome), was recently discovered in an isolated region of the State of Rio Grande do Norte in Northeast Brazil, in a population that was identified by the IBGE (Brazilian Institute of Geography and Statistics) as belonging to the Brazilian communities with the highest rates of "deficiencies" (Neri, 2003), a term used to describe diseases, malformations, and handicaps in general. This prompted us to conduct a study of consanguinity levels in five of its municipal districts by directly interviewing their inhabitants. Information on 7,639 couples (corresponding to about 40% of the whole population of the studied districts) was obtained. The research disclosed the existence of very high frequencies of consanguineous marriages, which varied from about 9% to 32%, suggesting the presence of a direct association between genetic diseases such as the SPOAN syndrome, genetic drift and inbreeding levels. This fact calls for the introduction of educational programs for the local populations, as well as for further studies aiming to identify and characterize other genetic conditions. Epidemiological strategies developed to collect inbreeding data, with the collaboration of health systems available in the region, might be very successful in the prospecting of genetic disorders.

Genetic evaluation of the mating system in the blue-and-yellow macaw (Ara ararauna, Aves, Psittacidae) by DNA fingerprinting

More than 90% of birds are socially monogamous, although genetic studies indicate that many are often not sexually monogamous. In the present study, DNA fingerprinting was used to estimate the genetic relationships between nestlings belonging to the same broods to evaluate the mating system in the socially monogamous macaw, Ara ararauna. We found that in 10 of 11 broods investigated, the nestlings showed genetic similarity levels congruent with values expected among full-sibs, suggesting that they shared the same parents. However, in one brood, the low genetic similarity observed between nestlings could be a result of intraspecific brood parasitism, intraspecific nest competition or extra-pair paternity. These results, along with available behavioral and life-history data, imply that the blue-and-yellow macaw is not only socially, but also genetically monogamous. However, the occurrence of eventual cases of extra-pair paternity cannot be excluded.

Population genetic structuring in pacu (Piaractus mesopotamicus) across the Paraná-Paraguay basin: evidence from microsatellites

The Paraná-Paraguay basin encompasses central western Brazil, northeastern Paraguay, eastern Bolivia and northern Argentina. The Pantanal is a flooded plain with marked dry and rainy seasons that, due to its soil characteristics and low declivity, has a great water holding capacity supporting abundant fish fauna. Piaractus mesopotamicus, or pacu, endemic of the Paraná-Paraguay basin, is a migratory species economically important in fisheries and ecologically as a potential seed disperser. In this paper we employ eight microsatellite loci to assess the population structure of 120 pacu sampled inside and outside the Pantanal of Mato Grosso. Our main objective was to test the null hypothesis of panmixia and to verify if there was a different structuring pattern between the Pantanal were there were no physical barriers to fish movement and the heavily impounded Paraná and Paranapanema rivers. All loci had moderate to high levels of polymorphism, the number of alleles varied from three to 18. The average observed heterozygosity varied from 0.068 to 0.911. After the Bonferroni correction three loci remained significant for deviations from Hardy-Weinberg, and for those the frequency of null alleles was estimated. F ST and R ST pairwise comparisons detected low divergence among sampling sites, and differentiation was significant only between Paranapanema and Cuiabá and Paranapanema and Taquari. No correlation between genetic distance and the natural logarithm of the geographic distance was detected. Results indicate that for conservation purposes and for restoration programs small genetic differences detected in the Cuiabá and Paranapanema rivers should be taken in consideration.

Molecular markers and genetic diversity of Plasmodium vivax

Enhanced understanding of the transmission dynamics and population genetics for Plasmodium vivax is crucial in predicting the emergence and spread of novel parasite phenotypes with major public health implications, such as new relapsing patterns, drug resistance and increased virulence. Suitable molecular markers are required for these population genetic studies. Here, we focus on two groups of molecular markers that are commonly used to analyse natural populations of P. vivax. We use markers under selective pressure, for instance, antigen-coding polymorphic genes, and markers that are not under strong natural selection, such as most minisatellite and microsatellite loci. First, we review data obtained using genes encoding for P. vivax antigens: circumsporozoite protein, merozoite surface proteins 1 and 3α, apical membrane antigen 1 and Duffy binding antigen. We next address neutral or nearly neutral molecular markers, especially microsatellite loci, providing a complete list of markers that have already been used in P. vivax populations studies. We also analyse the microsatellite loci identified in the P. vivax genome project. Finally, we discuss some practical uses for P. vivax genotyping, for example, detecting multiple-clone infections and tracking the geographic origin of isolates.

Rare earth element and yttrium geochemistry applied to the genetic study of cryolite ore at the Pitinga Mine (Amazon, Brazil)

This work aims at the geochemical study of Pitinga cryolite mineralization through REE and Y analyses in disseminated and massive cryolite ore deposits, as well as in fluorite occurrences. REE signatures in fluorite and cryolite are similar to those in the Madeira albite granite. The highest ΣREE values are found in magmatic cryolite (677 to 1345 ppm); ΣREE is lower in massive cryolite. Average values for the different cryolite types are 10.3 ppm, 6.66 ppm and 8.38 ppm (for nucleated, caramel and white types, respectively). Disseminated fluorite displays higher ΣREE values (1708 and 1526ppm) than fluorite in late veins(34.81ppm). Yttrium concentration is higher in disseminated fluorite and in magmatic cryolite. The evolution of several parameters (REEtotal, LREE/HREE, Y) was followed throughout successive stages of evolution in albite granites and associated mineralization. At the end of the process, late cryolite was formed with low REEtotal content. REE data indicate that the MCD was formed by, and the disseminated ore enriched by (additional formation of hydrothermal disseminated cryolite), hydrothermal fluids, residual from albite granite. The presence of tetrads is poorly defined, although nucleated, caramel and white cryolite types show evidence for tetrad effect.

Molecular phylogeny of the Myzorhynchella Section of Anopheles (Nyssorhynchus) (Diptera: Culicidae): genetic support for recently described and resurrected species

Phylogenetic relationships among species of the Myzorhynchella Section of Anopheles (Nyssorhynchus) were investigated using the nuclear ribosomal DNA second internal transcribed spacer (ITS2), the nuclear whitegene and mitochondrial cytochrome oxidase subunit I (COI) regions. The recently described Anopheles pristinus and resurrected Anopheles guarani were also included in the study. Bayesian phylogenetic analyses found Anopheles parvus to be the most distantly related species within the Section, a finding that is consistent with morphology. An. pristinus and An. guarani were clearly resolved from Anopheles antunesi and Anopheles lutzii, respectively. An. lutzii collected in the same mountain range as the type locality were found within a strongly supported clade, whereas individuals from the southern state of Rio Grande do Sul, tentatively identified as An. lutzii based on adult female external morphology, were distinct from An. lutzii, An. antunesi and from each other, and may therefore represent two new sympatric species. A more detailed examination of An. lutzii sensu latoalong its known geographic range is recommended to resolve these anomalous relationships.

A fuzzy reed-frost model for epidemic spreading

In this paper, we present a fuzzy approach to the Reed-Frost model for epidemic spreading taking into account uncertainties in the diagnostic of the infection. The heterogeneities in the infected group is based on the clinical signals of the individuals (symptoms, laboratorial exams, medical findings, etc.), which are incorporated into the dynamic of the epidemic. The infectivity level is time-varying and the classification of the individuals is performed through fuzzy relations. Simulations considering a real problem with data of the viral epidemic in a children daycare are performed and the results are compared with a stochastic Reed-Frost generalization