A random walk method for computing genetic location scores.

Calculation of location scores is one of the most computationally intensive tasks in modern genetics. Since these scores are crucial in placing disease loci on marker maps, there is ample incentive to pursue such calculations with large numbers of markers. However, in contrast to the simple, standardized pedigrees used in making marker maps, disease pedigrees are often graphically complex and sparsely phenotyped. These complications can present insuperable barriers to exact likelihood calculations with more than a few markers simultaneously. To overcome these barriers we introduce in the present paper a random walk method for computing approximate location scores with large numbers of biallelic markers. Sufficient mathematical theory is developed to explain the method. Feasibility is checked by small-scale simulations for two applications permitting exact calculation of location scores.     

A potential method for selecting genetic deletions in Escherichia coli

Summary A method is described for the selection of deletions in those genes of Escherichia coli that can be carried on specialized transducing phages.     

Timed surveys and transect walks as comparable methods for monitoring butterflies in small plots

Butterflies are widely used in biodiversity surveys, and several methods of relative abundance counts have been developed. The most frequently used linear transects are praised for a good replicability, but recently have been criticised for poor species detecting ability, especially for poorly visible or extremely sedentary species. As an alternative, timed surveys, based on zigzagging study sites and flexibly checking transient butterfly resources, have been proposed by some authors. We tested the utility of the two methods while studying the effect of restoration practices on butterfly assemblages in limestone quarries in the Czech Republic. Numbers of species and individuals detected per 10 min transect walk were compared with numbers of species and individuals detected during 10 min timed survey. Mobile and imperceptible species were compared in separate analyses as a measure of detection efficiency. More species and individuals per visit were recorded by timed surveys. No difference in detectability of mobile and imperceptible species between both methods used was observed. Whereas linear transects will probably remain the method of choice for long-term monitoring programs employing armies of recorders, timed surveys appear more appropriate for studies in which it is important to obtain the most comprehensive check-list of species occurring at study sites, which is often the case in conservation inventories in species rich regions with limited number of experienced researchers.     

A rapid method for selecting fermentative yeasts at high temperatures

A rapid and efficient method for isolating and selecting thermotolerant and sugar-fermenting yeasts was developed. Several samples from sugar cane by-products could be analyzed at the same time. Yeast cultures could be isolated in about 3 d, in contrast to the conventional methods, and its fermentative ability was qualitatively maintained at the desired temperature. A broad spectrum of temperatures can be tested. Yeasts of generaSaccharomyces andKluyveromyces were easily identified.     

A complexity-based method for predicting protein subcellular location

A complexity-based approach is proposed to predict subcellular location of proteins. Instead of extracting features from protein sequences as done previously, our approach is based on a complexity decomposition of symbol sequences. In the first step, distance between each pair of protein sequences is evaluated by the conditional complexity of one sequence given the other. Subcellular location of a protein is then determined using the k-nearest neighbor algorithm. Using three widely used data sets created by Reinhardt and Hubbard, Park and Kanehisa, and Gardy et al., our approach shows an improvement in prediction accuracy over those based on the amino acid composition and Markov model of protein sequences.     

A Modified-Whittaker nested vegetation sampling method

A standardized sampling technique for measuring plant diversity is needed to assist in resource inventories and for monitoring long-term trends in vascular plant species richness. The widely used Whittaker plot (Shmida 1984) collects species richness data at multiple spatial scales, using 1 m², 10 m², and 100 m² subplots within a 20 m × 50 m (1000 m²) plot, but it has three distinct design flaws involving the shape and placement of subplots. We modified and tested a comparable sampling design (Modified-Whittaker plot) that minimizes the problems encountered in the original Whittaker design, while maintaining many of its attractive attributes. We overlaid the two sampling methods in forest and prairie vegetation types in Larimer County, Colorado, USA (n=13 sites) and Wind Cave National Park, South Dakota, USA (n=19 sites) and showed that the modified design often returned significantly higher (p<0.05) species richness values in the 1 m², 10 m², and 100 m² subplots. For all plots, except seven ecotone plots, there was a significant difference (p<0.001) between the Whittaker plot and the Modified-Whittaker plot when estimating the total number of species in the 1000 m² plots based on linear regressions of the subplot data: the Whittaker plot method, on average, underestimated plant species richness by 34%. Species-area relationships, using the Modified-Whittaker design, conformed better to published semilog relationships, explaining, on average, 92% of the variation. Using the original Whittaker design, the semilog species-area relationships were not as strong, explaining only 83% of the variation, on average. The Modified-Whittaker plot design may allow for better estimates of mean species cover, analysis of plant diversity patterns at multiple spatial scales, and trend analysis from monitoring a series of strategically-placed, long-term plots.     

A frequency-controlled random mutagenesis method for GC-rich genes

A novel random mutagenesis strategy was developed by combining sodium bisulfite modification with polymerase chain reaction (PCR). This method introduced the predominant substitution of GC to AT, meaning that it was more suitable for mutagenesis of GC-rich genes and helped to decrease the GC content of target DNA. Mutation efficiency correlated with modification time and different mutation frequency could easily be obtained by controlling modification time. The results indicated that this method could yield a desired and adequate frequency of random mutation to the DNA of interest, especially GC-rich genes, and provided a powerful tool for directed molecular evolution.     

A simple statistical method for use in kinetic analysis based on Lineweaver-Burk plots

Statistical methods for the analysis of initial-velocity and/or inhibition data are described. They involve application of F tests (i) to determine goodness of fit to the first-order Michaelis-Menten equation, (ii) to predict the reaction mechanism by assessing slope and y-intercept effects in Lineweaver-Burk plots according to the inspection rules of Cleland [Cleland, W. W. (1963) Biochim. Biophys. Acta67, 188–196], (iii) to test the linearity of the replots of slopes or y-intercepts versus the reciprocal of the substrate concentration or the inhibitor concentration, and (iv) to estimate the true K_m or K_i values from these replots. The method serves to fill a gap in the kinetic analysis methodology between the antiquated graphical method and the sophisticated direct computer-fitting of data to a variety of possible rate equations. The entire theoretical and computational format is provided to allow the investigator to apply these statistical tests to his data using only a desk-top calculator.     

A comparison of Braun-Blanquet's method with sum-of-squares agglomeration for vegetation classification

Summary This paper presents the results of a comparative study in which the same collection of vegetation stands of an ombrotrophic peatland was classified firstly, by Braun-Blanquet's method by using synthesis tables, and secondly by a method of sum-of-squares agglomeration, suitable for computer processing. The classification by sum-of-squares agglomeration derived from presence data closely resembled that derived from abundance data, both of which, in turn, were statistically indistinguishable at the 0.05 probability level from the classification obtained by Braun-Blanquet's method.

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Résumé Etude comparative de classification d'une association végétale par la méthode deBraun-Blanquet (tables de synthèse) et par une méthode—qui consiste à agglomérer les sommes des carrés — facilement programmable à l'ordinateur. La classification de l'association végétale obtenue selon cette méthode-ci est presque identique à celle deBraun-Blanquet, et statistiquement parlant, il n'existe entre les deux méthodes aucune différence au niveau de probabilité de cinq pour cent.

     

A method for analyzing temporal patterns of variability of a time series from Poincare plots

The Poincaré plot is a popular two-dimensional, time series analysis tool because of its intuitive display of dynamic system behavior. Poincaré plots have been used to visualize heart rate and respiratory pattern variabilities. However, conventional quantitative analysis relies primarily on statistical measurements of the cumulative distribution of points, making it difficult to interpret irregular or complex plots. Moreover, the plots are constructed to reflect highly correlated regions of the time series, reducing the amount of nonlinear information that is presented and thereby hiding potentially relevant features. We propose temporal Poincaré variability (TPV), a novel analysis methodology that uses standard techniques to quantify the temporal distribution of points and to detect nonlinear sources responsible for physiological variability. In addition, the analysis is applied across multiple time delays, yielding a richer insight into system dynamics than the traditional circle return plot. The method is applied to data sets of R-R intervals and to synthetic point process data extracted from the Lorenz time series. The results demonstrate that TPV complements the traditional analysis and can be applied more generally, including Poincaré plots with multiple clusters, and more consistently than the conventional measures and can address questions regarding potential structure underlying the variability of a data set.     

Improved method for selecting RNA-binding activities in vivo.

RNA challenge phages are modified versions of bacteriophage P22 that allow one to select directly for a specific RNA-protein interaction in vivo. The original construction method for generating a bacteriophage that encodes a specific RNA target requires two homologous recombination reactions between plasmids and phages in bacteria. An improved method is described that enables one to readily construct RNA challenge phages through a single homologous recombination reaction in vivo. We have applied the new method to construct a derivative of P22R17, an RNA challenge phage that undergoes lysogenic development in bacterial cells that express the bacteriophage R17/MS2 coat protein.     

A two-stage random forest-based pathway analysis method

Pathway analysis provides a powerful approach for identifying the joint effect of genes grouped into biologically-based pathways on disease. Pathway analysis is also an attractive approach for a secondary analysis of genome-wide association study (GWAS) data that may still yield new results from these valuable datasets. Most of the current pathway analysis methods focused on testing the cumulative main effects of genes in a pathway. However, for complex diseases, gene-gene interactions are expected to play a critical role in disease etiology. We extended a random forest-based method for pathway analysis by incorporating a two-stage design. We used simulations to verify that the proposed method has the correct type I error rates. We also used simulations to show that the method is more powerful than the original random forest-based pathway approach and the set-based test implemented in PLINK in the presence of gene-gene interactions. Finally, we applied the method to a breast cancer GWAS dataset and a lung cancer GWAS dataset and interesting pathways were identified that have implications for breast and lung cancers.     

A general method for the analysis of random bisubstrate enzyme mechanisms

In the present communication, a general method for the kinetic analysis of random bisubstrate mechanisms is described. The method comprises a stepwise application of the following kinetic and ligand-binding experiments: determination of steady-state kinetic constants, product inhibition patterns, maximum rate relationships, application of alternate substrates, application of dead-end inhibitors, direct binding of substrates, kinetic isotope effects, and isotope exchange studies. This general method was applied to a practical example: a yeast alcohol dehydrogenase-catalyzed oxidation of 2-propanol by NAD⁺ at pH 7.0, 25°C. It was found that this fully reversible reaction proceeds by a steady-state random Bi-Bi mechanism, whereby both dead-end complexes are formed.     

A method of selecting data points for fitting the maximum biomass-density line for stands undergoing self-thinning

Abstract A problem that has always existed in self-thinning studies is the lack of objectivity in determining which data points to include when fitting the maximum biomass-density line. This paper demonstrates a more objective method of selecting data points using data from 12 even-aged Pinus radiata stands undergoing self-thinning. The method involves the division of a cluster of data points into a specified number of intervals. From each interval, that point having the maximum stand biomass is selected to contribute to the fitting process. This process is repeated a specified number of times using an increasing number of intervals. Each time an estimate of the line is obtained. From these estimates, one can be chosen to represent the maximum biomass-density line. The method may also be useful in other areas involving the definition of a boundary condition.     

A method for predicting the location of particles sedimenting in sucrose gradients

A theory was developed for the calculation of the positions of zones of particles sedimenting through a sucrose gradient. Equations were derived for particles sedimenting through gradients in which the sucrose concentration is (a) a linear function of radius, or (b) a hyperbolic function of radius. Computations were made for both swing-out and zonal rotors. The theory, which is based on direct integration of the sedimentation equation, exploits equations relating (a) the density of sucrose solutions to sucrose concentration and (b) the viscosity of sucrose solutions to sucrose concentration, and also the concept of reduced time (T/2 = S20.w integral of t to w2dt) of Fujita. The required computations may be made using a scientific calculator. Experimental support for the theory was obtained.