Estimation of the Size Distribution of Spherical Grains in the Boolean Model

A method of strong consistent estimation of the radius' distribution of spherical grains in the Boolean model in R^d, d ≦3, is proposed. It is based on the evaluation of the empirical capacity functional and application of the Glivenko-Cantelli theorem for random closed sets.     

Judgement post-stratification with imprecise rankings

Judgement post-stratification, which is based on ideas similar to those in ranked set sampling, relies on the ability of a ranker to forecast the ranks of potential observations on a set of units. In practice, the authors sometimes find it difficult to assign these ranks. This note shows how one can borrow techniques from the literature on finite population sampling to allow a probabilistic ranking of the units in a set, thus facilitating use of these sampling plans and improving estimation. The same techniques provide one approach to estimation using a judgement post-stratified sample with multiple rankers. The technique is illustrated on allometric data relating brain weight to body weight in different species of mammals, and on a study of student performance in graduate school.     

Classification of pathogenic microbes using a minimal set of single nucleotide polymorphisms derived from whole genome sequences

In a context specific manner, Intra-species genomic variation plays an important role in phenotypic diversity observed among pathogenic microbes. Efficient classification of these pathogens is important for diagnosis and treatment of several infectious diseases. NGS technologies have provided access to wealth of data that can be utilized to discover important markers for pathogen classification. In this paper, we described three different approaches (Jensen-Shannon divergence, random forest and Shewhart control chart) for identification of a minimal set of SNPs that can be used for classification of organisms. These methods are generic and can be implemented for analysis of any organism. We have shown usefulness of these approaches for analysis of Mycobacterium tuberculosis and Escherichia coli isolates. We were able to identify a minimal set of 18 SNPs that can be used as molecular markers for phylogroup based classification and 8 SNPs for pathogroup based classification of E. coli.     

Random median sampling to enhance the precision of population estimates

We describe the characteristics of a sampling procedure called random median sampling that was proposed to enhance the precision of population estimates. In performing random median sampling, we first select a sampling item at random from the sampling area. We roughly compare the abundance of individuals in the selected item with that of the adjacent two items in order to identify the item that has median abundance, i.e., the item that has the second largest abundance among the three items. We count the number of individuals of the item having the median abundance. This procedure is repeated n times in the sampling area (i = 1, 2, ..., n). Let m _i be the ith median abundance. The estimates of the mean abundance per sampling item and the variance of estimates are given by Σm _i /n and Σ(m _i –Σm _i /n)²/n(n – 1), respectively. This method is a local application of the median ranked set sampling that was proposed by Muttlak (J Appl Stat Sci 6:245–255, 1997). Random median sampling is effective when the correlation coefficient between adjacent items is small. If the correlation coefficient is close to zero, random median sampling reduces the variance of estimates to 45 or 32% of that in simple random sampling when the distribution follows a normal distribution or a Laplace distribution, respectively. The sample size required to achieve a given precision of estimate decreases accordingly. The effectiveness of random median sampling, however, is small if the correlation coefficient is large. The condition in which random median sampling is superior to simple random sampling is also discussed.     

On statistical inference for the random set generated Cox process with set-marking

Cox point process is a process class for hierarchical modelling of systems of non-interacting points in Rd under environmental heterogeneity which is modelled through a random intensity function. In this work a class of Cox processes is suggested where the random intensity is generated by a random closed set. Such heterogeneity appears for example in forestry where silvicultural treatments like harvesting and site-preparation create geometrical patterns for tree density variation in two different phases. In this paper the second order property, important both in data analysis and in the context of spatial sampling, is derived. The usefulness of the random set generated Cox process is highly increased, if for each point it is observed whether it is included in the random set or not. This additional information is easy and economical to obtain in many cases and is hence of practical value; it leads to marks for the points. The resulting random set marked Cox process is a marked point process where the marks are intensity-dependent. The problem with set-marking is that the marks are not a representative sample from the random set. This paper derives the second order property of the random set marked Cox process and suggests a practical estimation method for area fraction and covariance of the random set and for the point densities within and outside the random set. A simulated example and a forestry example are given.     

ASpediaFI: Functional Interaction Analysis of Alternative Splicing Events

Alternative splicing (AS) regulates biological processes governing phenotypes and diseases. Differential AS (DAS) gene test methods have been developed to investigate important exonic expression from high-throughput datasets. However, the DAS events extracted using statistical tests are insufficient to delineate relevant biological processes. In this study, we developed a novel application, Alternative Splicing Encyclopedia: Functional Interaction (ASpediaFI), to systemically identify DAS events and co-regulated genes and pathways. ASpediaFI establishes a heterogeneous interaction network of genes and their feature nodes (i.e., AS events and pathways) connected by co-expression or pathway gene set knowledge. Next, ASpediaFI explores the interaction network using the random walk with restart algorithm and interrogates the proximity from a query gene set. Finally, ASpediaFI extracts significant AS events, genes, and pathways. To evaluate the performance of our method, we simulated RNA sequencing (RNA-seq) datasets to consider various conditions of sequencing depth and sample size. The performance was compared with that of other methods. Additionally, we analyzed three public datasets of cancer patients or cell lines to evaluate how well ASpediaFI detects biologically relevant candidates. ASpediaFI exhibits strong performance in both simulated and public datasets. Our integrative approach reveals that DAS events that recognize a global co-expression network and relevant pathways determine the functional importance of spliced genes in the subnetwork. ASpediaFI is publicly available at https://bioconductor.org/packages/ASpediaFI.     

Confidence Intervals and Tests of Hypotheses on Variance Components in an Unbalanced Two-fold Nested Design

Confidence intervals and tests of hypotheses on variance components are required in studies that employ a random effects design. The unbalanced random two-fold nested design is considered in this paper and confidence intervals are proposed for the variance components σ2/A and σ2/B. Computer simulation is used to show that even in very unbalanced designs, these intervals generally maintain the stated confidence coefficient. The hypothesis test for σ2/A based on the lower bound of the recommended confidence interval is shown to be better than previously proposed approximate tests.     

一类具有随机周期移民扰动的非线性人口发展方程随机周期解的存在唯一性

本文给出了一类具有随机周期移民扰动的非线性m增生人口发展方程随机周期解的存在性和唯一性结论。     

应用随机PCR方法鉴定一株真养产碱杆菌

采用随机引物PCR技术从新建细胞培养室空气中获得一段长414bp的片段,通过克隆测序及序列分析,结果表明所测序列与真养产碱杆菌主要参考菌株的同源性分别高达79%-83%,由其推导的氨基酸序列与真养产碱杆菌主要参考菌株的同源性高达86.4%-89.1%,从而确定所分离菌株为真养产碱杆菌。     

Mean Figures and Mean Shapes Applied to Biological Figure and Shape Distributions in the Plane

Fundamental propositions for mean figures and mean shapes in the plane are proved by using complex numbers. A test of equality of two figure or shape distributions is introduced and applied to data from larvae of mussels and from saurian heads.     

Hadamard randomization: a valid restriction of random permuted blocks

Random permuted blocks can result in treatment imbalance if entry to the trial stops in mid‐block. This paper presents a restriction of this method of randomization. The restriction avoids severe treatment imbalance but gives unbiased estimators of the treatment difference and its variance.     

应用抗病毒抗体表位筛选的多肽文库的构建

1985年,Sndth在《科学》杂志上提出构建"融合噬菌体",即在这种丝状病毒的包膜蛋白上表达融合蛋白[1]．1990年,Scott和Smith山利用这种表面表达载体建立了随机多肽文库,可以很方便地筛选出抗体及其他功能蛋白的强结合配基[2]．我们建立了十二肽的随机多肽库,将从中筛选出抗HIV-gP160抗体的抗独特型多肽．1材料和方法1．1质粒、菌株和培养墓噬菌粒成h血四、大肠杆菌XLI-Blue和辅助噬菌体VCSM13由军事医学科学院微生物流行病研究所王海涛教授惠赠．SB液体培养基：30gtmptone,20g酵母膏,10gMops溶于IL去离子水中,调pH7．0．枝…     

Prediction of multi-locus inbreeding coefficients and relation to linkage disequilibrium in random mating populations

An algorithm to predict the level of identity by descent simultaneously at multiple loci is presented, which can in principle be extended to any number of loci. The model assumes a random mating population, with random association of haplotypes. The relationship is shown between coefficients of multi-locus identity or non-identity by descent and moments of multi-locus linkage disequilibrium. Thus, these moments can be computed from the multilocus identity or, using algorithms derived previously to predict the disequilibria moments, vice-versa. The results can be applied to predict multi-locus identity in, for example, gene mapping.     

Spatial distributions and clutch sizes of Drosophila species ovipositing on cherry fruits of different stages

In the aggregation theory, aggregation of eggs is one of important conditions for the coexistence of species. However, aggregation of eggs by clutch laying does not always promote coexistence, whereas aggregation of eggs by aggregated distributions of ovipositing females always has a significant contribution to the coexistence. In this study, spatial distributions of three Drosophila species across naturally occurring cherry fruits were studied with relation to their clutch sizes. Drosophila suzukii oviposited eggs mainly on fresh fruits on trees, and its eggs were randomly distributed across cherry fruits. The emergence data also indicated random spatial distributions of this species. Random egg distributions of this species are explained by random visits of females to fruits and the production of clutches of mostly single eggs. On the other hand, D. lutescens and D. rufa oviposited on fallen fruits, showed aggregated distributions in the emergence data, and frequently produced clutches of a few eggs. In these species, the degree of aggregation was usually significantly lower than the expectation based on random visits of females to fruits and their clutch sizes observed in the present experiments, indicating that their aggregation is unlikely to arise from aggregated distributions of ovipositing females. Thus, the spatial aggregation of these species does not necessarily lead to their coexistence.     

On analytical approaches to epidemics on networks

One way to describe the spread of an infection on a network is by approximating the network by a random graph. However, the usual way of constructing a random graph does not give any control over the number of triangles in the graph, while these triangles will naturally arise in many networks (e.g. in social networks). In this paper, random graphs with a given degree distribution and a given expected number of triangles are constructed. By using these random graphs we analyze the spread of two types of infection on a network: infections with a fixed infectious period and infections for which an infective individual will infect all of its susceptible neighbors or none. These two types of infection can be used to give upper and lower bounds for R(0), the probability of extinction and other measures of dynamics of infections with more general infectious periods.