PCA based population generation for genetic network optimization

A gene regulatory network (GRN) represents a set of genes and its regulatory interactions. The inference of the regulatory interactions between genes is usually carried out using an appropriate mathematical model and the available gene expression profile. Among the various models proposed for GRN inference, our recently proposed Michaelis–Menten based ODE model provides a good trade-off between the computational complexity and biological relevance. This model, like other known GRN models, also uses an evolutionary algorithm for parameter estimation. Considering various issues associated with such population based stochastic optimization approaches (e.g. diversity, premature convergence due to local optima, accuracy, etc.), it becomes important to seed the initial population with good individuals which are closer to the optimal solution. In this paper, we exploit the inherent strength of principal component analysis (PCA) in a novel manner to initialize the population for GRN optimization. The benefit of the proposed method is validated by reconstructing in silico and in vivo networks of various sizes. For the same level of accuracy, the approach with PCA based initialization shows improved convergence speed.     

Kinematic quantitation of the patellar tendon reflex using a tri-axial accelerometer

We designed a simple procedure based on the angular speed of the knee joint for quantitating the patellar tendon reflex. The angular speed of the knee joint is calculated from acceleration data generated in response to the tapping force applied to the patellar tendon with a customized tendon hammer and measured using a tri-axial accelerometer placed at the ankle joint. Data were collected and processed using a signal analyzer and a notebook PC. The results obtained using standard equipment were similar to those generated by more elaborate devices. For instance, the time delay (29.6+/-6.0 ms) and the acceleration time (150.8+/-19.5 ms) of the speed response were quite constant for all participants within the range of tapping forces normally applied during physical examinations. Representative relationships between the peak tapping force and the peak angular speed also closely fit with the exponential model (the average coefficient of determination, 0.70; range, 0.43-0.97). In contrast, the mean asymptotic value of the peak angular speed (Omega(pas)) was 160+/-67 degrees/s for spastic individuals, compared with only 72+/-21 degrees/s for healthy individuals. The important features of this method are portability, ease of use, and non-constraint of solicited reflex responses.     

Research on the parameter inversion problem of prestack seismic data based on improved differential evolution algorithm

The parameter inversion technology composed by intelligent algorithm and AVO inversion for prestack seismic data provides a comparatively effective identification method for oil-gas exploration. However, traditionally intelligent iterative algorithm, such as, genetic algorithm, shows many disadvantages in solving this problem, including highly depending on initial model, fast convergence in algorithm and being easy to fall into local optimal. Therefore, an unsatisfied inversion performance is produced. In order to solve the above problems, this paper proposes a parameter inversion method based on improved differential evolution algorithm which is better in solving parameter inversion problems of prestack seismic data. In the proposed algorithm, aims at the Aki and Rechard approximation formula used specific initialization strategy, then the initialization parameter curve more smooth. Otherwise, the new algorithm has many advantages, such as, fast computing speed, simple operation, a low independence to initial model and good global convergence, this algorithm is the right choice in solving the parameter inversion problem based on pre-stack seismic data of real number encoding.     

Amplified fragment length polymorphism analysis of Mythimna separata (Lepidoptera: Noctuidae) geographic and melanic laboratory populations in China

Genetic diversity within and among three wild-type natural populations and one melanic laboratory population of Mythimna separata (Walker) (Lepidoptera: Noctuidae) were evaluated using amplified fragment length polymorphism (AFLP) analysis. Although extensive genetic diversity occurs among individuals from different geographic populations (P = 54.5%, h = 0.209, I = 0.305), the majority of the genetic diversity is within populations and not between populations (G(ST) = 0.172), indicating high gene flow (N(M) = 2.403) and suggesting that M. separata in northern China are a part of a single large metapopulation. Genetic diversity in the natural populations was significantly higher than that in the melanic laboratory population (with P = 43.4% versus P = 25.9%, h = 0.173 versus h = 0.086, and I = 0.251 versus I = 0.127), suggesting that the melanic laboratory population is narrowly genetic-based and genetically uniform. Genetic similarities based on AFLP data were calculated, and cluster analysis was preformed to graphically display groupings between individuals and populations. Individuals from the same region were not grouped together in cluster analysis of three natural populations, whereas melanic individuals from laboratory population were grouped together very well. Four subpopulations were clustered into two broad groups. Melanic laboratory population became a single group, which had apparent differentiation from the other group in which three natural subpopulations were included. These results indicated that although high genetic variability existed among the individuals of natural populations, there was little genetic differentiation among three geographic populations that could be explained by the effects of the long distance migration of the oriental armyworm in China enhanced the level of gene flow. Influences of migration on the genetic polymorphism and differentiations that make a significant contribution to evolution in this insect are reviewed.     

Effective population size,genetic diversity,and coalescence time in subdivided populations

A formula for the effective population size for the finite island model of subdivided populations is derived. The formula indicates that the effective size can be substantially greater than the actual number of individuals in the entire population when the migration rate among subpopulations is small. It is shown that the mean nucleotide diversity, coalescence time, and heterozygosity for genes sampled from the entire population can be predicted fairly well from the theory for randomly mating populations if the effective population size for the finite island model is used.     

Patterns of genetic diversity and migration in increasingly fragmented and declining orang-utan (Pongo pygmaeus) populations from Sabah, Malaysia

We investigated the genetic structure within and among Bornean orang-utans (Pongo pygmaeus) in forest fragments of the Lower Kinabatangan flood plain in Sabah, Malaysia. DNA was extracted from hair and faecal samples for 200 wild individuals collected during boat surveys on the Kinabatangan River. Fourteen microsatellite loci were used to characterize patterns of genetic diversity. We found that genetic diversity was high in the set of samples (mean H(E) = 0.74) and that genetic differentiation was significant between the samples (average F(ST) = 0.04, P < 0.001) with F(ST) values ranging from low (0.01) to moderately large (0.12) values. Pairwise F(ST) values were significantly higher across the Kinabatangan River than between samples from the same river side, thereby confirming the role of the river as a natural barrier to gene flow. The correlation between genetic and geographical distance was tested by means of a series of Mantel tests based on different measures of geographical distance. We used a Bayesian method to estimate immigration rates. The results indicate that migration is unlikely across the river but cannot be completely ruled out because of the limited F(ST) values. Assignment tests confirm the overall picture that gene flow is limited across the river. We found that migration between samples from the same side of the river had a high probability indicating that orang-utans used to move relatively freely between neighbouring areas. This strongly suggests that there is a need to maintain migration between isolated forest fragments. This could be done by restoring forest corridors alongside the river banks and between patches.     

Individual variation in migration speed of upriver-migrating sockeye salmon in the Fraser River in relation to their physiological and energetic status at marine approach

Little research has examined individual variation in migration speeds of Pacific salmon (Oncorhynchus spp.) in natural river systems or attempted to link migratory behavior with physiological and energetic status on a large spatial scale in the wild. As a model, we used three stocks of summer-run sockeye salmon (Oncorhynchus nerka) from the Fraser River watershed, British Columbia, to test the hypothesis that individual variation in migration speed is determined by a combination of environmental factors (i.e., water temperature), intrinsic biological differences (sex and population), and physiological and energetic condition. Before the freshwater portion of the migration, sockeye salmon (Quesnel, Chilcotin, and Nechako stock complexes) were captured in Johnstone Strait ( approximately 215 km from river entry), gastrically implanted with radio transmitters, and sampled for blood, gill tissue, and energetic status before release. Analyses focused solely on individuals that successfully reached natal subwatersheds. Migration speeds were assessed by an extensive radiotelemetry array. Individuals from the stock complex that migrated the longest distance (Nechako) traveled at speeds slower than those of other stock complexes. Females traveled slower than males. An elevated energetic status of fish in the ocean was negatively correlated with migration speed in most river segments. During the transition from the ocean to the river, migration speed was negatively correlated with mean maximum water temperature; however, for the majority of river segments, it was positively correlated with migration speed. Physiological status measured in the ocean did not explain among-individual variability in river migration speeds. Collectively, these findings suggest that there could be extensive variation in migration behavior among individuals, sexes, and populations and that physiological condition in the ocean explained little of this variation relative to in-river environmental conditions and energetic status. Interestingly, individual fish generally retained their rank in swimming speed across different segments, except when transiting a challenging canyon midway during the migration.     

Comment on “numerical treatment of two-center overlap integrals”

The subject paper by H. Safouhi (J Mol Model 12:213–220, 2006) presents a scheme based on a nonlinear convergence acceleration transformation for the numerical evaluation of two-center overlap integrals of Slater-type orbitals. In this comment we argue that there is no reason to adopt such an approach, as well-known methods for these integrals are substantially superior both in speed and in accuracy.     

Community differentiation on landscapes: drift, migration and speciation

Theories of the differentiation of ecological communities on landscapes have typically not considered evolutionary dynamics. Here we analytically study the expected differentiation among local communities in a large metacommunity, undergoing speciation, ecological drift and intercommunity dispersal, in the context of neutral theory. We demonstrate that heterogeneity in species diversity and abundance arises among communities when local communities are small and intercommunity migration is infrequent. We propose a new measure to describe community differentiation, defined as the average correlation or the average probability (C_st) that two randomly sampled individuals of the same species within local communities are from the same ancestor. The effects of driving forces (migration, mutation, and ecological drift) are incorporated into the two-level hierarchical community structure in a finite island model of neutral communities. Community differentiation can increase the effective metacommunity size or the Hubbell's fundamental species diversity in the metacommunity by a factor (1−C_st)⁻¹. Significant community differentiation arises when C_st≠0. Intercommunity migration promotes species diversity in local communities but reduce species diversity in the metacommunity. In either the finite or infinite island case, one can estimate the number of intercommunity migrants by using multiple local community datasets when the speciation is negligible in the neutral local communities, or by using the metacommunity dataset when the speciation is included in the local neutral communities. These results highlight the significance of the evolutionary mechanisms in generating heterogeneous communities in the absence of complicated ecological processes on large landscapes.     

A study of Y-chromosome microsatellite variation in sub-Saharan Africa: a comparison between F(ST) and R(ST) genetic distances

Seven Y-chromosome microsatellite loci (DYS19, DYS389I, DYS389II, DYS390, DYS391, DYS392, and DYS393) were analyzed in three populations from sub-Saharan Africa: the Bamileke and Ewondo populations from Cameroon and the Hutu from Rwanda. Complete typing was obtained for 112 individuals, and a total of 53 different haplotypes was observed. The single-locus gene diversity, averaged across populations, ranges from 0.100 for the DYS392 locus to 0.610 for the DYS389I locus. The haplotype diversity ranges from 0.832 (Ewondo) to 0.965 (Hutu), with an intermediate value of 0.918 in the Bamileke. The diversity among Bamileke, Ewondo, Hutu, and other sub-Saharan populations selected from the literature was analyzed using both a classical (F(ST)) and a stepwise-based (R(ST)) genetic distance method. The pattern of interpopulational diversity based on F(ST) was congruent with anthropological knowledge, while that based on R(ST) revealed unexpected and unconvincing population affinities. From a practical point of view, our study indicates that Y-chromosome microsatellite data may provide useful information for analyses of interpopulational diversity among sub-Saharan populations if an adequate number of loci and individuals along with an appropriate genetic distance method are used. On a theoretical ground, we propose that the lesser performance of R(ST) compared to F(ST) could be explained by the important role played by genetic drift in shaping the relationships among examined populations.     

基于SRAP标记的墨西哥落羽杉优良单株的遗传多样性分析

采用SRAP标记方法,分析了原产地及种植地不同的18个墨西哥落羽杉(Taxodium mucronatum Tenore)优良单株的遗传多样性,并根据遗传相似系数、采用UPGMA法对它们的遗传关系进行了聚类分析.结果显示:用7对引物组合从18个单株的总DNA中共扩增出87条带,其中多态性条带71条,多态性条带百分率为81.6％.按照原产地和种植地可将18个单株分为4组,它们的总体Nei's基因多样性指数、Shannon信息指数和基因分化系数分别为0.229、0.355和0.479 9,而基因流仅为0.542,说明各组间的基因交流较少.18个单株间的遗传相似系数为0.632 2～0.919 5,平均值为0.753 9.聚类分析结果显示:18个单株可分为3组,其中18号和14号单株分别单独成组,其余16个单株聚为1组.后者可进一步分为8个亚组:1号、7号、12号和15号单株各自单独成亚组;2号、3号、5号、9号、11号和13号单株聚为1个亚组;4号和6号单株、8号和17号单株、10号和16号单株分别聚为3个亚组.研究结果表明:18个优良单株间存在丰富的遗传变异,但它们的遗传关系与原产地及种植地明显不相关.     

Setting and situation in migration from the Isle of Lewis*

This paper examines migration from the Isle of Lewis (Scotland). Mitchell's concepts of the social setting and the social situation of migration are employed: first, to demonstrate how the economic conditions of peripherality have created the factors, or social setting, promoting extensive out‐migration. Second, to demonstrate how the particular circumstances, or social situations, of individuals result in a wide range of types and patterns of migration. The historical development of the social setting and the effect of changes in it on migration are briefly examined. A number of career histories are used to illustrate the diversity of migrant responses to the setting. It is argued that this diversity is better understood if the concepts of type and pattern of migration are introduced into the analysis.     

Hybrid Symbiotic Organisms Search Optimization Algorithm for Scheduling of Tasks on Cloud Computing Environment

Cloud computing has attracted significant attention from research community because of rapid migration rate of Information Technology services to its domain. Advances in virtualization technology has made cloud computing very popular as a result of easier deployment of application services. Tasks are submitted to cloud datacenters to be processed on pay as you go fashion. Task scheduling is one the significant research challenges in cloud computing environment. The current formulation of task scheduling problems has been shown to be NP-complete, hence finding the exact solution especially for large problem sizes is intractable. The heterogeneous and dynamic feature of cloud resources makes optimum task scheduling non-trivial. Therefore, efficient task scheduling algorithms are required for optimum resource utilization. Symbiotic Organisms Search (SOS) has been shown to perform competitively with Particle Swarm Optimization (PSO). The aim of this study is to optimize task scheduling in cloud computing environment based on a proposed Simulated Annealing (SA) based SOS (SASOS) in order to improve the convergence rate and quality of solution of SOS. The SOS algorithm has a strong global exploration capability and uses fewer parameters. The systematic reasoning ability of SA is employed to find better solutions on local solution regions, hence, adding exploration ability to SOS. Also, a fitness function is proposed which takes into account the utilization level of virtual machines (VMs) which reduced makespan and degree of imbalance among VMs. CloudSim toolkit was used to evaluate the efficiency of the proposed method using both synthetic and standard workload. Results of simulation showed that hybrid SOS performs better than SOS in terms of convergence speed, response time, degree of imbalance, and makespan.     

Particle Swarm Optimization with Scale-Free Interactions

The particle swarm optimization (PSO) algorithm, in which individuals collaborate with their interacted neighbors like bird flocking to search for the optima, has been successfully applied in a wide range of fields pertaining to searching and convergence. Here we employ the scale-free network to represent the inter-individual interactions in the population, named SF-PSO. In contrast to the traditional PSO with fully-connected topology or regular topology, the scale-free topology used in SF-PSO incorporates the diversity of individuals in searching and information dissemination ability, leading to a quite different optimization process. Systematic results with respect to several standard test functions demonstrate that SF-PSO gives rise to a better balance between the convergence speed and the optimum quality, accounting for its much better performance than that of the traditional PSO algorithms. We further explore the dynamical searching process microscopically, finding that the cooperation of hub nodes and non-hub nodes play a crucial role in optimizing the convergence process. Our work may have implications in computational intelligence and complex networks.     

Convergence to the island-model coalescent process in populations with restricted migration

In this article we apply some graph-theoretic results to the study of coalescence in a structured population with migration. The graph is the pattern of migration among subpopulations, or demes, and we use the theory of random walks on graphs to characterize the ease with which ancestral lineages can traverse the habitat in a series of migration events. We identify conditions under which the coalescent process in populations with restricted migration, such that individuals cannot traverse the habitat freely in a single migration event, nonetheless becomes identical to the coalescent process in the island migration model in the limit as the number of demes tends to infinity. Specifically, we first note that a sequence of symmetric graphs with Diaconis-Stroock constant bounded above has an unstructured Kingman-type coalescent in the limit for a sample of size two from two different demes. We then show that circular and toroidal models with long-range but restricted migration have an upper bound on this constant and so have an unstructured-migration coalescent in the limit. We investigate the rate of convergence to this limit using simulations.     

Genetic diversity and relationships among germplasm of Jatropha curcas L. revealed by RAPDs

Variation is the phenomenon where individuals of a population differ from each other. The variation or diversity can have morphological manifestation or genetic basis. Individual identification based on morphological record is the most common practice in Jatropha. Therefore, in order to find a proper method for estimation of genetic diversity and genetic relationships among different germplasm of Jatropha curcas L., random amplified polymorphic DNA (RAPD) technique based on polymerase chain reaction (PCR) was used for described purpose. Out of 55 decamer primers tested, 26 primers produced good amplification products. A total of 6,011 amplification products were scored from which only 1,859 bands (30.92%) were found to be polymorphic and the size of bands ranged from 300 to 2,500 bp. Unweighted pair group method using arithmetic average cluster analysis revealed clear genetic difference among J. curcas germplasm. The scientific data presented in this study suggests that RAPD-PCR could be used as a valuable tool for estimation of genetic diversity and genetic relationship among germplasm of J. curcas L.     

Finish with a sprint: Evidence for time‐selected last leg of migration in a long‐distance migratory songbird

Under time‐selected migration, birds should choose a strategy for outcompeting rivals over securing access to prime resources at the final destination. Thus, migration can be viewed as a race among individuals where winners are arriving first when conditions are suitable. The sprint migration hypothesis predicts that individuals shift from maximum sustained speed to a final burst of sprint to shorten the transition from migration to breeding (Alerstam, 2006). In this study, we test the hypothesis of a final sprint migration in a long‐distance Afro‐Palearctic migrant, the collared flycatcher Ficedula albicollis, during autumn and spring, and compare migration strategies between the seasons. In both seasons, collared flycatchers evidently exhibited sprint migration by increasing their overall speed over the last leg of migration after the Sahara crossing. This phenomenon was more pronounced in spring, contributing to overall faster spring migration and possibly highlighting higher importance for early arrival at the breeding grounds. In both seasons and particularly in spring, late departing individuals flew at a faster rate, partially being able to catch up with their early departing conspecifics. Differential fueling strategies may play an important role in determining migration speed, especially during the early stages of the migration, and might explain the observed differences in migration speeds between late and early departing individuals. Our findings suggest competition for early arrival at the breeding and at the nonbreeding destinations alike. Sprint migration might be an appropriate strategy to gain advantage over conspecifics and settle in prime territories as well as to cope with the increasingly earlier springs at high latitudes.     

Using Social Network Methods to Test for Assortment of Prosociality among Korean High School Students

Assortative interaction among altruistic individuals is a necessary condition for the evolution of cooperation. The requirement for assortment holds regardless of whether a meta-population is subdivided into distinct and isolated subgroups or has ephemeral boundaries with a high migration rate. The assumption, however, is rarely tested directly. In this paper, we develop a method to test for assortment of prosociality in network-structured data. The method is applied to a friendship network collected from 238 Korean students attending the same high school. A mixing matrix was used to explore the presence of assortative friendship among more prosocial individuals. An exponential random graph model of network structure that accounts for additional observed relational propensities (higher-than-expected number of people nominating no friends) and sampling constraints (upper bound on friendship nominations) found that individual prosociality predicted friendship propensity, and that individuals with higher prosocial scores had a higher probability of befriending other more prosocial individuals. The results reveal that a considerable level of assortment of prosociality characterizes this population.