Comparison of bacterial and phage display peptide libraries in search of target-binding motif

Genetic engineering allows modification of bacterial and bacteriophage genes, which code for surface proteins, enabling display of random peptides on the surface of these microbial vectors. Biologic peptide libraries thus formed are used for high-throughput screening of clones bearing peptides with high affinity for target proteins. There are reports of many successful affinity selections performed with phage display libraries and substantially fewer cases describing the use of bacterial display systems. In theory, bacterial display has some advantages over phage display, but the two systems have never been experimentally compared. We tested both techniques in selecting streptavidin-binding peptides from two commercially available libraries. Under similar conditions, selection of phage-displayed peptides to model protein streptavidin proved convincingly better.     

Computer comparisons of variables in capillary gas chromatography

A series of computer-constructed van Deemter curves that permits evaluation of a number of variables in capillary gas chromatography is presented. The graphs permit the comparison of inter-related parameters, including the choice of carrier gas (hydrogen vs helium vs nitrogen), column length (10-100 m), column diameter (0.20, 0.25, 0.32, 0.4 mm), solute partition ratios (0-10), and liquid phase film thickness (0.1, 0.25, 0.5, 1.0 μm). The curves are evaluated, both in terms of the relative magnitude of the optimum average linear carrier gas velocity, and in terms of the significance of the sharpness of the curve.     

Resolution of mixtures of three nonsteroidal anti-inflammatory drugs by fluorescence using partial least squares multivariate calibration with previous wavelength selection by Kohonen artificial neural networks

A spectrofluorometric method for the quantitative determination of flufenamic, mefenamic and meclofenamic acids in mixtures has been developed by recording emission fluorescence spectra between 370 and 550 nm with an excitation wavelength of 352 nm. The excitation–emission spectra of these compounds are deeply overlapped which does not allow their direct determination without previous separation. The proposed method applies partial least squares (PLS) multivariate calibration to the resolution of this mixture using a set of wavelengths previously selected by Kohonen artificial neural networks (K-ANN). The linear calibration graphs used to construct the calibration matrix were selected in the ranges from 0.25 to 1.00 μg ml⁻¹ for flufenamic and meclofenamic acids, and from 1.00 to 4.00 μg ml⁻¹ for mefenamic acid. A cross-validation procedure was used to select the number of factors. The selected calibration model has been applied to the determination of these compounds in synthetic mixtures and pharmaceutical formulations.     

Maintaining the positive definiteness of the matrices in reduced secant methods for equality constrained optimization

We propose an algorithm for minimizing a functionf on ⁿ in the presence ofm equality constraintsc that locally is a reduced secant method. The local method is globalized using a nondifferentiable augmented Lagrangian whose decrease is obtained by both a longitudinal search that decreases mainlyf and a transversal search that decreases mainly c. Our main objective is to show that the longitudinal path can be designed to maintain the positive definiteness of the reduced matrices by means of the positivity of _k ^T _k , where _k is the change in the reduced gradient and _k is the reduced longitudinal displacement.Work supported by the FNRS (Fonds National de la Recherche Scientifique) of Belgium.     

Representative subset selection

Fast development of analytical techniques enable to acquire huge amount of data. Large data sets are difficult to handle and therefore, there is a big interest in designing a subset of the original data set, which preserves the information of the original data set and facilitates the computations. There are many subset selection methods and their choice depends on the problem at hand. The two most popular groups of subset selection methods are uniform designs and cluster-based designs. Among the methods considered in this paper there are uniform designs, such as those proposed by Kennard and Stone, OptiSim, and cluster-based designs applying K-means technique and density based spatial clustering of applications with noise (DBSCAN). Additionally, a new concept of the subset selection with K-means is introduced.     

In vitro selection of self-cleaving DNAs

Background: Ribozymes catalyze an important set of chemical transformations in metabolism, and ‘engineered’ ribozymes have been made that catalyze a variety of additional reactions. The possibility that catalytic DNAs or ‘deoxyribozymes’ can be made has only recently been addressed. Specifically, it is unclear whether the absence of the 2′ hydroxyl renders DNA incapable of exhibiting efficient enzyme-like activity, making it impossible to discover natural or create artificial DNA biocatalysts.Results: We report the isolation by in vitro selection of two distinct classes of self-cleaving DNAs from a pool of random-sequence oligonucleotides. Individual catalysts from ‘class I’ require both Cu²⁺ and ascorbate to mediate oxidative self-cleavage. Individual catalysts from class II use Cu²⁺ as the sole cofactor. Further optimization of a class II individual by in vitro selection yielded new catalytic DNAs that facilitate Cu²⁺-dependent self-cleavage with rate enhancements exceeding 1000 000-fold relative to the uncatalyzed rate of DNA cleavage.Conclusions: Despite the absence of 2′ hydroxyls, single-stranded DNA can adopt structures that promote divalent-metal-dependent self-cleavage via an oxidative mechanism. These results suggest that an efficient DNA enzyme might be made to cleave DNA in a biological context.     

Counterexamples to parsimony and BIC

Suppose that the log-likelihood-ratio sequence of two models with different numbers of estimated parameters is bounded in probability, without necessarily having a chi-square limiting distribution. Then BIC and all other related consistent model selection criteria, meaning those which penalize the number of estimated parameters with a weight which becomes infinite with the sample size, will, with asymptotic probability 1, select the model having fewer parameters. This note presents examples of nested and non-nested regression model pairs for which the likelihood-ratio sequence is bounded in probability and which have the property that the model in each pair with more estimated parameters has better predictive properties, for an independent replicate of the observed data, than the model with fewer parameters. Our second example also shows how a one-dimensional regressor can overfit the data used for estimation in comparison to the fit of a two-dimensional regressor.An earlier version of this article was presented at the Symposium on the Analysis of Statistical Information held in the Institute of Statistical Mathematics, Tokyo during December 5–8, 1989.     

Computational study of propagating fronts in a Lattice-gas model

Velocities and other features of propagating fronts in the lattice-gas model analyzed by Bramsonet al. are computed by Monte Carlo simulation. The propagation velocity() is found to converge slowly to its asymptotic dependence on the exchange-rate parameter. The number density of occupied sites in the interaction zone (extending from the forwardmost occupied to the rearmost unoccupied site) appears to converge to 2/3 for large. Spatial profiles of site occupancy and interface number density for finite are compared to the profiles originally computed by Fisher using the differential equation obeyed in the large- limit. Several significant features inferred from the computations have not yet been explained analytically.     

A model of natural selection that exhibits a dynamic phase transition

A simple, stochastic model is developed of an asexual biological population that is undergoing natural selection. It is then observed that the size of the population, like the temperature parameter in the simulated annealing algorithm, is a measure of the amount of randomness to be allowed in the system. Exploiting the formal analogy between the two processes, it is shown that the distribution of different types of organisms in the population model converges to a stationary distribution if the population is growing more slowly thanO(lnt) (annealing), but can fail to converge at all if the population is growing faster thanO(lnt) (quenching). The results may be related to the historical accidents that permeate biological structures.     

波长优选对土壤有机质含量可见光/近红外光谱模型的优化

可见光/近红外光谱模型是土壤属性预测的有效工具。波长优选在光谱建模过程中起着重要作用。文中首先利用从安徽省涡阳县采集的130个砂姜黑土土壤样本获得可见光/近红外光谱,然后利用平滑与多重散射校正联合的光谱预处理方式消除光谱中的无关变量和冗余信息以提高模型预测结果的相关性,再利用SPXY方法挑选建模集样本,分别利用连续投影算法和遗传算法进行波长优选,最后利用留一法进行交互验证建立有机质含量的主成分回归模型。研究结果显示：连续投影算法和遗传算法都可以有效地减少参与建模的波长数并提高模型的准确度,尤其是遗传算法能够更好地提高土壤有机质含量预测精度,其相关系数、预测均方根误差和相对分析误差分别达到0.9316,0.2142和2.3195。通过合适的特征波长选取,不仅计算量可以大大减少,预测精度也会有效提高。