Functional restraints on the patterns of amino acid substitutions: application to sequence-structure homology recognition

Amino acid residues that are involved in functional interactions in proteins have strong evolutionary pressure to remain unchanged and consequently their substitution patterns are different from those that are noninteracting. To characterize and quantify the differences between amino acid substitution patterns due to structural restraints and those under functional restraints, we have made a comparative analysis of families of homologous proteins. Residues classified as having the same amino acid type, secondary structure, accessibility, and side-chain hydrogen bonds are shown to be better conserved if they are close to the active site. We have focused on enzyme families for this analysis since they have functional sites that are easily defined by their catalytic residues. We have derived new sets of environment-specific substitution tables, which we term function-dependent environment-specific substitution tables, where amino acid residues are classified according to their distance from the functional sites. The residues that are within a distance of 9 A from the active site have distinct amino acid substitution patterns when compared to the other sites. The function-dependent environment-specific substitution tables have been tested using the sequence-structure homology recognition program FUGUE and the results compared with the recognition performance obtained using the standard environment-specific substitution tables. Significant improvements are obtained in both recognition performance and alignment accuracy using the function-dependent environment-specific substitution tables (P-value = 0.02, according to the Wilcoxon signed rank test for alignment accuracy). The alignments near the active site are greatly improved with pronounced improvements at lower percentage identities (less than 30%).     

A Monte Carlo Study to Evaluate the Performance of Selected Tests of Homogeneity in Sparse Contingency Tables

We address the problem of tests of homogeneity in two-way contingency tables in case-control studies when the case category is subdivided into k subcategories. In this situation, we have two cells with large frequencies and 2 X k cells with frequencies that become small as k increases. We propose two ad hoc statistics in which a statistic for the sparse cells is combined with a statistic for the cells with large frequencies. We will study these tests along with the Pearson test (using a chi-square approximation) in a Monte Carlo simulation study. Two sets of null hypothesis models and two sets of alternative hypothesis models are considered. The best test for the models considered is the usual Pearson test (using an approximate chi-square distribution) although the ad hoc models are more powerful under one alternative model considered.     

The Waste Input-Output Approach to Materials Flow Analysis

Abstract: A general analytical model of materials flow analysis (MFA) incorporating physical waste input-output is proposed that is fully consistent with the mass balance principle. Exploiting the triangular nature of the matrix of input coefficients, which is obtained by rearranging the ordering of sectors according to degrees of fabrication, the material composition matrix is derived, which gives the material composition of products. A formal mathematical definition of materials (or the objects, the flow of which is to be accounted for by MFA) is also introduced, which excludes the occurrence of double accounting in economy-wide MFAs involving diverse inputs. By using the model, monetary input-output (IO) tables can easily be converted into a physical material flow account (or physical input-output tables [PIOT]) of an arbitrary number of materials, and the material composition of a product can be decomposed into its input origin. The first point represents substantial saving in the otherwise prohibitive cost that is associated with independent compilation of PIOT. The proposed methodology is applied to Japanese IO data for the flow of 11 base metals and their scrap (available as e-supplement on the JIE Web site).     

Decomposition and Model Selection for Large Contingency Tables

Large contingency tables summarizing categorical variables arise in many areas. One example is in biology, where large numbers of biomarkers are cross‐tabulated according to their discrete expression level. Interactions of the variables are of great interest and are generally studied with log–linear models. The structure of a log–linear model can be visually represented by a graph from which the conditional independence structure can then be easily read off. However, since the number of parameters in a saturated model grows exponentially in the number of variables, this generally comes with a heavy computational burden. Even if we restrict ourselves to models of lower‐order interactions or other sparse structures, we are faced with the problem of a large number of cells which play the role of sample size. This is in sharp contrast to high‐dimensional regression or classification procedures because, in addition to a high‐dimensional parameter, we also have to deal with the analogue of a huge sample size. Furthermore, high‐dimensional tables naturally feature a large number of sampling zeros which often leads to the nonexistence of the maximum likelihood estimate. We therefore present a decomposition approach, where we first divide the problem into several lower‐dimensional problems and then combine these to form a global solution. Our methodology is computationally feasible for log–linear interaction models with many categorical variables each or some of them having many levels. We demonstrate the proposed method on simulated data and apply it to a bio‐medical problem in cancer research.     

A More Powerful Simultaneous Test Procedure in Configural Frequency Analysis

In the Configural Frequency Analysis (CFA) of KRAUTH and LIENERT (1973 a, b), overfrequented (or underfrequented) cells in multivariate contingency tables are identified by simultaneous binomial tests. As an alternative, finite and asymptotic tests are proposed, which are derived from the (exact conditional) generalized hypergeometrical distribution of the cell frequencies. These tests allow for considerably more powerful decisions than do the conservative binomial tests.     

On the Analysis of Special Incomplete Three-dimensional Contingency Tables

Incomplete contingency tables, i.e. tables with structurally caused empty cells, are analysed by means of so-called quasilog-linear models. In general the expected values can be calculated by means of iterative cyclic adaption to corresponding marginals of the empirical contingency tables (in the same way as in complete tables) under different hierarchical hypotheses concerning the parameters of the models. For important cases of 2-dimensional contingency tables it is possible to demonstrate that expected values and test statistics are to find in a closed form. If all 2-dimensional sub or partial tables of a 3-dimensional table can be assigned to such cases then the hypotheses of classes (AB×C) (??), (B×C)/A(??), (A??B)/A(??) etc. are testable in closed form. But the expected values to (A×B×C) (×) have to be calculated iteratively. An example shows that some definite additive decompositions of the test statistic 2 I are no longer valid while some others remain valid in spite of incompleteness of the tables.     

Closed Form Estimators of Latent Cell Frequencies

One-stage and two-stage closed form estimators of latent cell frequencies in multidimensional contingency tables are derived from the weighted least squares criterion. The first stage estimator is asymptotically equivalent to the conditional maximum likelihood estimator and does not necessarily have minimum asymptotic variance. The second stage estimator does have minimum asymptotic variance relative to any other existing estimator. The closed form estimators are defined for any number of latent cells in contingency tables of any order under exact general linear constraints on the logarithms of the nonlatent and latent cell frequencies.     

A censored quantile regression approach for relative survival analysis: Relative survival quantile regression

We propose a censored quantile regression model for the analysis of relative survival data. We create a hybrid data set consisting of the study observations and counterpart randomly sampled pseudopopulation observations imputed from population life tables that adjust for expected mortality. We then fit a censored quantile regression model to the hybrid data incorporating demographic variables (e.g., age, biologic sex, calendar time) corresponding to the population life tables of demographically-similar individuals, a population versus study covariate, and its interactions with the variables of interest. These latter variables can be interpreted as relative survival parameters that depict the differences in failure quantiles between the study participants and their population counterparts.     

THE POWER OF SENSORY DISCRIMINATION METHODS

Difference testing methods are extensively used in a variety of applications from small sensory evaluation tests to large scale consumer tests. A central issue in the use of these tests is their statistical power, or the probability that if a specified difference exists it will be demonstrated as a significant difference in a difference test. A general equation for the power of any discrimination method is given. A general equation for the sample size required to meet Type I and Type II error specifications is also given. Sample size tables for the 2-alternative forced choice (2-AFC), 3-AFC, the duo-trio and the triangular methods are given. Tables of the psychometric functions for the 2-AFC, 3-AFC, triangular and duo-trio methods are also given.     

A new mathematical evaluation of smoking problem based of algebraic statistical method

Smoking problem is considered as one of the hot topics for many years. In spite of overpowering facts about the dangers, smoking is still a bad habit widely spread and socially accepted. Many people start smoking during their gymnasium period. The discovery of the dangers of smoking gave a warning sign of danger for individuals. There are different statistical methods used to analyze the dangers of smoking. In this study, we apply an algebraic statistical method to analyze and classify real data using Markov basis for the independent model on the contingency table. Results show that the Markov basis based classification is able to distinguish different date elements. Moreover, we check our proposed method via information theory by utilizing the Shannon formula to illustrate which one of these alternative tables is the best in term of independent.     

Population size estimation with interval censored counts and external information: Prevalence of multiple sclerosis in Rome

We discuss Bayesian log-linear models for incomplete contingency tables with both missing and interval censored cells, with the aim of obtaining reliable population size estimates. We also discuss use of external information on the censoring probability, which may substantially reduce uncertainty. We show in simulation that information on lower bounds and external information can each improve the mean squared error of population size estimates, even when the external information is not completely accurate. We conclude with an original example on estimation of prevalence of multiple sclerosis in the metropolitan area of Rome, where five out of six lists have interval censored counts. External information comes from mortality rates of multiple sclerosis patients.     

Influence of ground predators and water levels on Lapwing Vanellus vanellus breeding success in two continental wetlands

Insufficient productivity has driven population declines in grassland breeding waders with high levels of predation limiting productivity in many wetland reserves. We studied hatching and fledging success of Lapwings Vanellus vanellus in two continental river floodplains (Havel and Oder) differing in water regime and density of Red Foxes Vulpes vulpes to assess the effects of increased water tables as a management option. Nest predation rates were high on dry sites as well as on flooded grasslands in all areas irrespective of fox litter density. Carnivores formed the majority of the predators identified and eggshell remains suggested that mustelids took proportionally more nests at low fox densities. At unsuccessful nests on flooded grassland, an increasing incidence of nocturnal disturbances prior to predation indicated an influx of carnivores as the sites dried out. Brood survival depended on the availability of wet features, and productivity was thus linked to water tables in June in one area (Havel). Productivity was insufficient to maintain local populations in all areas and years except for two occasions related to increased water tables. Retaining high water tables throughout the breeding season therefore remains an important management option for waders on continental wet grasslands.     

Association,Symmetry and Diagonal Models for Occupational Mobility and Other Similar Square Contingency Tables Having Ordered Categorical Variables

This paper examines various association, symmetry and “diagonal band” class models for both the British and Danish social mobility data. Composite models are also fitted to these data and the variety of models considered ensures that for most square tables, parsimonious models within the class of models examined in this study can always be found that will adequately describe such tables. The models considered in this study, which have been described in various forms by Goodman (1984), Upton (1985) and Tomizawa (1986) can suit most square tables having ordered classificatory variables. A model selection procedure is also examined.     

赤爱胜蚯蚓(Eisenia Foetida Sarigny)纤溶酶的研究 Ⅶ.纤溶酶片释放度的研究

本文采用紫外分光光度法对纤溶酶片的释放度进行了测定研究,释放T5O为45分钟,释放时间80分钟,释放量不少于70％。本测定方法快速简便,适宜生产中控制药品质量,进一步指导生产。     

HOW TO ESTIMATE AND USE THE VARIANCE OF d' FROM DIFFERENCE TESTS

d' is an estimate of δ, a measure of the degree of sensory difference between two products, that can be obtained easily using tables, from the proportion of difference tests performed correctly. Tables of δ are available for the 2-AFC, 3-AFC, triangular and duo-trio tests. Tables for calculating the variance of d' for these tests are provided in this paper. They can be used for comparison of d's, especially for those obtained from different difference tests. A simple procedure is described here for computing values for the variance of d'. Having obtained the variance, confidence intervals for d' can be obtained, tests of significance for d' can be made as well as tests of whether two or more d's are significantly different. The formula and tables for the number of judgments required for the estimation of δ are given also in this paper.     

Tables of Bonferroni-limits for Simultaneous F-Tests

Bonferroni adjusted F-tables are given for α=0.10 and α = 0.001 with degrees of freedom following classical tables of Fisher and Yates. The tables may be used in simultaneous analysis of variances or in evaluating binomial tests by means of F-tables in configural frequency testing.     

ADVANTAGES OF THE SAME-DIFFERENT METHOD OVER THE TRIANGULAR METHOD FOR THE MEASUREMENT OF TASTE DISCRIMINATION

The triangular method, the same-different rating method, and the standard same-different method were each used with 10 tasters to obtain estimates of the discriminability of two concentrations of a colorless beverage. There were no significant differences in d', an index of discriminability, among the three tasks. In the light of this parity, a choice amongst the methods should be driven by practical considerations. When receiver operating characteristics (ROCs) were fitted to the rating data, the model underlying published tables of d' was strongly supported, so that discriminability can be assessed from same-different data either by entering tables or by fitting ROC curves. Same-different methods appear more acceptable to tasters than the triangular method.     

Components of the cellular defense and detoxification system of the common cuttlefish Sepia officinalis (Mollusca,Cephalopoda)

Endocytotic-active cells in the branchial heart complex of Sepia officinalis were studied by in situ injection of different types of xenobiotics and by in vitro perfusion of the organ complex with a bacterial suspension. The rhogocytes (ovoid cells) ingest particles of all tested sizes by endocytosis and phagocytosis. The hemocytes of the circulating blood and the adhesive hemocytes in the wall of the branchial heart incorporate all tested kinds of foreign materials, including bacterial cells due to phagocytosis achieved by the triangular mesenchymatic cells. The ultrastructural findings also give strong evidence that the triangular mesenchymatic cells are fixed hemocytes that have migrated into the branchial heart tissue. The ingestion and digestion of allogeneic substances and bacteria or their debris by rhogocytes and/or all (forms of) hemocytes suggests the involvement of these either fixed or mobile endocytotic-active cells in the defense and detoxification system of cephalopods.     

Distinguishing structural and functional restraints in evolution in order to identify interaction sites

Structural genomics projects are producing many three-dimensional structures of proteins that have been identified only from their gene sequences. It is therefore important to develop computational methods that will predict sites involved in productive intermolecular interactions that might give clues about functions. Techniques based on evolutionary conservation of amino acids have the advantage over physiochemical methods in that they are more general. However, the majority of techniques neither use all available structural and sequence information, nor are able to distinguish between evolutionary restraints that arise from the need to maintain structure and those that arise from function. Three methods to identify evolutionary restraints on protein sequence and structure are described here. The first identifies those residues that have a higher degree of conservation than expected: this is achieved by comparing for each amino acid position the sequence conservation observed in the homologous family of proteins with the degree of conservation predicted on the basis of amino acid type and local environment. The second uses information theory to identify those positions where environment-specific substitution tables make poor predictions of the overall amino acid substitution pattern. The third method identifies those residues that have highly conserved positions when three-dimensional structures of proteins in a homologous family are superposed. The scores derived from these methods are mapped onto the protein three-dimensional structures and contoured, allowing identification clusters of residues with strong evolutionary restraints that are sites of interaction in proteins involved in a variety of functions. Our method differs from other published techniques by making use of structural information to identify restraints that arise from the structure of the protein and differentiating these restraints from others that derive from intermolecular interactions that mediate functions in the whole organism.     

A Note on Binary Contingency Tables

This paper considers contingency tables in which the marginal frequencies for one variable are all 1. This could occur with two-category binary data or when a continuous variable is treated in categorical fashion. Some results concerning the expectation of goodness-of-fit statistics are reported. In particular it is noted that the expectation of the Pearson statistic is independent of the model being fitted.