The Contraction-Expansion Algorithm and Its Use in Fitting Nonlinear Equation

1IntroductionMostadequatenumeriMrelationshipbetweencovarlate扯dresPOnsearenonlinear．Howev·er,applicationofnonlinearequationappearedfarlessthanlinearregression．ThedifficultyInesti·mail呛theparametersIncomplicatednonllnearmodelingmaybethemainreasoninbl     

An Improved Artificial Immune Algorithm with a Dynamic Threshold

An improved artificial immune algorithm with a dynamic threshold is presented. The calculation for the affinity function in the real-valued coding artificial immune algorithm is modified through considering the antibody＇s fitness and setting the dynamic threshold value. Numerical experiments show that compared with the genetic algorithm and the originally real-valued coding artificial immune algorithm, the improved algorithm possesses high speed of convergence and good performance for preventing premature convergence.     

一种新的蛋白质结构字母序列优化算法

基于蛋白质结构字母的预测和分析方法,一个必然的步聚,是将目标蛋白质离散成结构字母序列。本文在对蛋白质结构字母序列空间,及其最小根均方偏差变化,穷举分析的基础上,提出了一种新的蛋白质结构字母序列优化算法,全局贪婪算法。全局贪婪算法避免了基本贪婪算法过度依赖候选集大小,计算量过大、以及过早收缩于局部最小等缺点。经实验分析,全局贪婪算法在性能上优于基本贪婪算法和局部最优方法。。     

ECG 信号QRS 波群检测算法的进展

QRS波群是ECG信号的重要组成部分,是心电信号分析的基础.QRS波群的检测方法已经有很多种实用有效的方法,并逐步地走向成熟,在实际应用中得到实现.本文就QRS波群的检测方法作了具体的整理与分析,较全面的阐述了实际应用中的各种算法,最后作者对检测算法的发展趋势进行了总结和展望.     

机器学习在MALDI-TOF MS鉴定微生物中的应用

基质辅助激光解吸/电离飞行时间质谱(matrix-assisted laser desorption/ionization time-of-flight mass spectrometry,MALDI-TOF MS)是一种新兴的高通量技术,已广泛应用于临床微生物、食品微生物和水产微生物的快速鉴定。如何进一步提高MALDI-TOF MS在微生物鉴定中的分辨率是该技术当前面临的一大挑战。为了高效处理大量高维微生物MALDI-TOF MS数据,各种机器学习算法得到了应用。本文综述了机器学习在微生物MALDI-TOFMS鉴定中的应用。首先,本文在介绍机器学习在微生物MALDI-TOF MS分类中的工作流程后,进一步对MALDI-TOF MS的数据特征、MALDI-TOF MS数据库、数据的预处理和模型的性能评估进行了描述。然后讨论了典型的机器学习分类算法和集成学习算法的应用。简单的机器学习算法很难满足微生物MALDI-TOF MS分类的高分辨率的需求,而组合不同机器学习算法和集成学习算法可以获得更好的微生物分类性能。在MALDI-TOF MS数据的预处理方面,小波算法和遗传算法的应用最广,它们...     

Experimental benchmarking of RayStation proton dose calculation algorithms inside and outside the target region in heterogeneous phantom geometries

PurposeThe aim of the presented study was to complement existing literature on benchmarking proton dose by comparing dose calculations with experimental measurements in heterogeneous phantom. Points of interest inside and outside the target were considered to quantify the magnitude of calculation uncertainties in current and previous proton therapy practice that might especially have an impact on the dose in organs at risk (OARs).MethodsThe RayStation treatment planning system (RaySearch Laboratories), offering two dose calculation algorithms for pencil beam scanning in proton therapy, i.e., Pencil Beam (PB) and Monte Carlo (MC), was utilized. Treatment plans for a target located behind the interface of the heterogeneous tissues were generated. Dose measurements within and behind the target were performed in a water phantom with embedded slabs of various tissue equivalent materials and 24 PinPoint ionization chambers (PTW). In total 12 test configurations encompassing two different target depths, oblique beam incidence of 30 degrees and range shifter, were considered.ResultsPB and MC calculated doses agreed equally well with the measurements for all test geometries within the target, including the range shifter (mean dose differences ± 3%). Outside the target, the maximum dose difference of 9% (19%) was observed for MC (PB) for the oblique beam incidence and inserted range shifter.ConclusionThe accuracy of MC dose algorithm was superior compared to the PB algorithm, especially outside the target volumes. MC based dose calculation should therefore be preferred in treatment scenarios with heterogeneities, especially to reduce clinically relevant uncertainties for OARs.     

An improved biclustering algorithm and its application to gene expression spectrum analysis

Cheng and Church algorithm is an important approach in biclustering algorithms. In this paper, the process of the extended space in the second stage of Cheng and Church algorithm is improved and the selections of two important parameters are discussed. The results of the improved algorithm used in the gene expression spectrum analysis show that, compared with Cheng and Church algorithm, the quality of clustering results is enhanced obviously, the mining expression models are better, and the data possess a strong consistency with fluctuation on the condition while the computational time does not increase significantly.     

The variability in type I collagen helical pitch is reflected in the D periodic fibrillar structure

The variability in amino acid axial rise per residue of the collagen helix is a potentially important parameter that is missing in many structural models of fibrillar collagen to date. The significance of this variability has been supported by evidence from collagen axial structures determined by electron microscopy and X-ray diffraction, as well as studies of the local sequence-dependent conformation of the collagen helix. Here, sequence-dependent variation of the axial rise per residue was used to improve the fit between simulated diffraction patterns derived from model structures of the axially projected microfibrillar structure and the observed X-ray diffraction pattern from hydrated rat tail tendon. Structural models were adjusted using a genetic algorithm that allowed a wide range of structures to be tested efficiently. The results show that variation of the axial rise per residue could reduce the difference metric between model and observed data by up to 50%, indicating that such a variable is a necessary part of fibril model structure building. The variation in amino acid translation was also found to be influenced by the number of proline and hydroxyproline residues in the triple helix structure.     

A model-free algorithm for the removal of baseline artifacts

Summary A novel algorithm for removing baseline distortions in NMR spectra is presented. The algorithm approximates the baseline as the median of the noise extrema. Consequently, the method does not require that NMR peaks be discriminated from noise peaks. In addition, no assumptions regarding the source or functional form of the distortion are made. The algorithm is shown to remove the baseline artifacts present in a particularly distorted NOESY spectrum and to reveal peaks which had been obscured by the artifacts. The parameters and spectral characteristics (signal-to-noise ratio, NMR peak density, peak linewidths) governing the resolution of the calculated baselines are also explored.     

Modelling zinc-binding proteins with GADGET: genetic algorithm and distance geometry for exploring topology

A novel combination of optimization methods (Genetic Algorithm with Distance Geometry) has been developed and shown to find near-optimal solutions to a set of imposed structural constraints. With this modelling tool (GADGET), the fold-space of a variety of small zinc-binding proteins was investigated under the constraints required to form a zinc-binding site (or pair of sites). Analysis of the results concentrated on the ring-finger domain as the "classic" zinc-finger domains were too constrained to provide much topological variety, whilst the TFIIH domain (which has large unstructured loops) did not behave well. The intermediate ring-finger domain, however, was found to adopt a variety of different folds, many of which had near-optimal scores under the fitness function employed in GADGET (forming good secondary structures and zinc-coordination). Although the native fold was dominant amongst the solutions, the discovery of good alternate folds shows that even the eight residues constrained to form two zinc-binding sites was not sufficient to uniquely determine the native fold. Despite this, the fold-space of 48 theoretically possible folds was greatly reduced with just six topologies found in significant numbers.     

The effect of overabundant projection directions on 3D reconstruction algorithms

The experimental process of collecting images from macromolecules in an electron microscope is such that it does not allow for prior specification of the angular distribution of the projection images. As a consequence, an uneven distribution of projection directions may occur. Concerns have been raised recently about the behavior of 3D reconstruction algorithms for the case of unevenly distributed projections. It has been illustrated on experimental data that in the case of a heavily uneven distribution of projection directions some algorithms tend to elongate the reconstructed volumes along the overloaded direction so much as to make a quantitative biological analysis impossible. In answer to these concerns we have developed a strategy for quantitative comparison and optimization of 3D reconstruction algorithms. We apply this strategy to quantitatively analyze algebraic reconstruction techniques (ART) with blobs, simultaneous iterative reconstruction techniques (SIRT) with voxels, and weighted backprojection (WBP). We show that the elongation artifacts that had been previously reported can be strongly reduced. With our specific choices for the free parameters of the three algorithms, WBP reconstructions tend to be inferior to those obtained with either SIRT or ART and the results obtained with ART are comparable to those with SIRT, but at a very small fraction of the computational cost of SIRT.     

Multi-Hop Routing Optimization Method Based on Improved Ant Algorithm for Vehicle to Roadside Network

This paper proposes a route optimization method to improve the performance of route selection in Vehicle Ad-hoc Network （VANET）. A novel bionic swarm intelligence algorithm, which is called ant colony algorithm, was introduced into a traditional ad-hoc route algorithm named AODV. Based on the analysis of movement characteristics of vehicles and according to the spatial relationship between the vehicles and the roadside units, the parameters in ant colony system were modified to enhance the performance of the route selection probability rules. When the vehicle moves into the range of several different roadsides, it could build the route by sending some route testing packets as ants, so that the route table can be built by the reply information of test ants, and then the node can establish the optimization path to send the application packets. The simulation results indicate that the proposed algorithm has better performance than the traditional AODV algorithm, especially when the vehicle is in higher speed or the number of nodes increases.     

Reconstruction of Gene Regulatory Networks Based on Two-Stage Bayesian Network Structure Learning Algorithm

In the post-genomic biology era,the reconstruction of gene regulatory networks from microarray gene expression data isvery important to understand the underlying biological system,and it has been a challenging task in bioinformatics.TheBayesian network model has been used in reconstructing the gene regulatory network for its advantages,but how to determinethe network structure and parameters is still important to be explored.This paper proposes a two-stage structure learning algorithmwhich integrates immune evolution algorithm to build a Bayesian network.The new algorithm is evaluated with the use ofboth simulated and yeast cell cycle data.The experimental results indicate that the proposed algorithm can find many of theknown real regulatory relationships from literature and predict the others unknown with high validity and accuracy.     

小波变换及滚球算法在单分子荧光能量共振转移图像分析中的应用

单分子荧光共振能量转移技术是通过检测单个分子内的荧光供体及受体间荧光能量转移的效率来研究分子构象的变化．要得到这些生物大分子的信息就需要对大量的单分子信号进行统计分析,人工分析这些信息,既费时费力又不具备客观性和可重复性,因此本文将小波变换及滚球算法应用到单分子荧光能量共振转移图像中对单分子信号进行统计分析．在保证准确检测到单分子信号的前提下,文章对滚球算法和小波变换算法处理图像后的线性进行了分析,结果表明,滚球算法和小波变换算法不但能够很好地去除单分子FRET图像的背景噪声,同时还能很好地保持单分子荧光信号的线性．最后本文还利用滚球算法处理单分子FRET图像及统计15 bp DNA的FRET效率的直方图,通过计算得到了15 bp DNA的FRET效率值．     

Applications of Genetic Algorithms in Cluster Optimisation

Abstract

Applications of Genetic Algorithms for optimisation of atomic clusters are reported. It is shown that the genetic algorithms are very useful tools for determining the minimum energy structures of clusters of atoms described by interatomic potential functions containing up to a few hundred atoms. The algorithm generally outperforms other optimisation methods for this task. A number of applications are given including covalent carbon and silicon clusters, close-packed structures such as argon and silver and the two-component C—H system.     

噬菌斑电子图像的计算机处理及其自动计数

噬菌斑平板计数是微生物学理论研究与实际应用中常用的方法之一.但由于平板上噬菌斑与背景反差小,而且往往出现几个噬菌斑相连,计算机识别时出现较大的误差,因此噬菌斑计数目前仍为人工方法.本文以λ噬菌体为材料,感染E.coli宿主细胞,获得噬菌斑.然后将噬菌斑制成电子图像.抽取图像中有代表性的区域,利用分水岭算法对图像进行分割处理,将相连的噬菌斑分割成单独的噬菌斑,然后利用基于区域生长法进行计数,结果与人工计数完全相同,表明我们建立的新方法可以用于噬菌斑计算机自动计数.     

Fast numerical methods for simulating large-scale integrate-and-fire neuronal networks

We discuss numerical methods for simulating large-scale, integrate-and-fire (I&F) neuronal networks. Important elements in our numerical methods are (i) a neurophysiologically inspired integrating factor which casts the solution as a numerically tractable integral equation, and allows us to obtain stable and accurate individual neuronal trajectories (i.e., voltage and conductance time-courses) even when the I&F neuronal equations are stiff, such as in strongly fluctuating, high-conductance states; (ii) an iterated process of spike-spike corrections within groups of strongly coupled neurons to account for spike-spike interactions within a single large numerical time-step; and (iii) a clustering procedure of firing events in the network to take advantage of localized architectures, such as spatial scales of strong local interactions, which are often present in large-scale computational models—for example, those of the primary visual cortex. (We note that the spike-spike corrections in our methods are more involved than the correction of single neuron spike-time via a polynomial interpolation as in the modified Runge-Kutta methods commonly used in simulations of I&F neuronal networks.) Our methods can evolve networks with relatively strong local interactions in an asymptotically optimal way such that each neuron fires approximately once in operations, where N is the number of neurons in the system. We note that quantifications used in computational modeling are often statistical, since measurements in a real experiment to characterize physiological systems are typically statistical, such as firing rate, interspike interval distributions, and spike-triggered voltage distributions. We emphasize that it takes much less computational effort to resolve statistical properties of certain I&F neuronal networks than to fully resolve trajectories of each and every neuron within the system. For networks operating in realistic dynamical regimes, such as strongly fluctuating, high-conductance states, our methods are designed to achieve statistical accuracy when very large time-steps are used. Moreover, our methods can also achieve trajectory-wise accuracy when small time-steps are used. Action Editor: Nicolas Brunel     

A click chemistry approach for the synthesis of cyclic ureido tethered coumarinyl and 1-aza coumarinyl 1,2,3-triazoles as inhibitors of Mycobacterium tuberculosis H37Rv and their in silico studies

Nucleoside bases like uracil, pharmacophoric triazoles and benzimidazolones have been used during the present study to design molecular matrices for antitubercular activity, employing Click Chemistry. Click triazoles 4/7/10 have been obtained by the reaction of 4-(Azidomethyl)-2H-chromen-2-ones/quinolin-2(1H)-ones 3 and propargyl ethers 2/6/9 derived from theophylline/6-methyl uracil/2-benzimidazolone respectively. In addition to spectral data structures have been confirmed by single crystal X-ray diffraction studies in case of uracil bis alkyne (6) and theophylline mono triazole (4c). Theophylline linked mono triazoles, 4(a-d) and 6-methyl uracil linked bis triazoles, 7(a-e) have been found to inhibit Mycobacterium tuberculosis H37Rv with MIC values in the range 55.62–115.62 μM. Benzimidazolone bis triazoles, 10(a-n) showed better activity with MIC in the range 2.33–18.34 μM. Molecular modeling studies using Surflex-Dock algorithm supported our results.