基于图论模型的蛋白质结构类型的研究

提出了基于图论模型的H系数分类蛋白质结构为H结型和NH结型的方法.论述了蛋白质结构中序列不相邻的C_α原子之间的空间距离与序列相邻的C_α原子之间空间距离的关系.用此方法对PDB的66个单链蛋白质结构进行分类,结果显示H结型占18.2%.H结在全α型中出现比例较高,在全β型中出现比例较小,所以H结倾向出现在含有α螺旋的蛋白质结构中.     

A Class of Pairwise Models for Epidemic Dynamics on Weighted Networks

In this paper, we study the SIS (susceptible–infected–susceptible) and SIR (susceptible–infected–removed) epidemic models on undirected, weighted networks by deriving pairwise-type approximate models coupled with individual-based network simulation. Two different types of theoretical/synthetic weighted network models are considered. Both start from non-weighted networks with fixed topology followed by the allocation of link weights in either (i) random or (ii) fixed/deterministic way. The pairwise models are formulated for a general discrete distribution of weights, and these models are then used in conjunction with stochastic network simulations to evaluate the impact of different weight distributions on epidemic thresholds and dynamics in general. For the SIR model, the basic reproductive ratio R ₀ is computed, and we show that (i) for both network models R ₀ is maximised if all weights are equal, and (ii) when the two models are ‘equally-matched’, the networks with a random weight distribution give rise to a higher R ₀ value. The models with different weight distributions are also used to explore the agreement between the pairwise and simulation models for different parameter combinations.     

Untangling the Interplay between Epidemic Spread and Transmission Network Dynamics

The epidemic spread of infectious diseases is ubiquitous and often has a considerable impact on public health and economic wealth. The large variability in the spatio-temporal patterns of epidemics prohibits simple interventions and requires a detailed analysis of each epidemic with respect to its infectious agent and the corresponding routes of transmission. To facilitate this analysis, we introduce a mathematical framework which links epidemic patterns to the topology and dynamics of the underlying transmission network. The evolution, both in disease prevalence and transmission network topology, is derived from a closed set of partial differential equations for infections without allowing for recovery. The predictions are in excellent agreement with complementarily conducted agent-based simulations. The capacity of this new method is demonstrated in several case studies on HIV epidemics in synthetic populations: it allows us to monitor the evolution of contact behavior among healthy and infected individuals and the contributions of different disease stages to the spreading of the epidemic. This gives both direction to and a test bed for targeted intervention strategies for epidemic control. In conclusion, this mathematical framework provides a capable toolbox for the analysis of epidemics from first principles. This allows for fast, in silico modeling--and manipulation--of epidemics and is especially powerful if complemented with adequate empirical data for parameterization.     

A Tutorial on Analysis and Simulation of Boolean Gene Regulatory Network Models

Driven by the desire to understand genomic functions through the interactions among genes and gene products, the research in gene regulatory networks has become a heated area in genomic signal processing. Among the most studied mathematical models are Boolean networks and probabilistic Boolean networks, which are rule-based dynamic systems. This tutorial provides an introduction to the essential concepts of these two Boolean models, and presents the up-to-date analysis and simulation methods developed for them. In the Analysis section, we will show that Boolean models are Markov chains, based on which we present a Markovian steady-state analysis on attractors, and also reveal the relationship between probabilistic Boolean networks and dynamic Bayesian networks (another popular genetic network model), again via Markov analysis; we dedicate the last subsection to structural analysis, which opens a door to other topics such as network control. The Simulation section will start from the basic tasks of creating state transition diagrams and finding attractors, proceed to the simulation of network dynamics and obtaining the steady-state distributions, and finally come to an algorithm of generating artificial Boolean networks with prescribed attractors. The contents are arranged in a roughly logical order, such that the Markov chain analysis lays the basis for the most part of Analysis section, and also prepares the readers to the topics in Simulation section.     

A Coarse-Grained Elastic Network Atom Contact Model and Its Use in the Simulation of Protein Dynamics and the Prediction of the Effect of Mutations

Normal mode analysis (NMA) methods are widely used to study dynamic aspects of protein structures. Two critical components of NMA methods are coarse-graining in the level of simplification used to represent protein structures and the choice of potential energy functional form. There is a trade-off between speed and accuracy in different choices. In one extreme one finds accurate but slow molecular-dynamics based methods with all-atom representations and detailed atom potentials. On the other extreme, fast elastic network model (ENM) methods with C_α−only representations and simplified potentials that based on geometry alone, thus oblivious to protein sequence. Here we present ENCoM, an Elastic Network Contact Model that employs a potential energy function that includes a pairwise atom-type non-bonded interaction term and thus makes it possible to consider the effect of the specific nature of amino-acids on dynamics within the context of NMA. ENCoM is as fast as existing ENM methods and outperforms such methods in the generation of conformational ensembles. Here we introduce a new application for NMA methods with the use of ENCoM in the prediction of the effect of mutations on protein stability. While existing methods are based on machine learning or enthalpic considerations, the use of ENCoM, based on vibrational normal modes, is based on entropic considerations. This represents a novel area of application for NMA methods and a novel approach for the prediction of the effect of mutations. We compare ENCoM to a large number of methods in terms of accuracy and self-consistency. We show that the accuracy of ENCoM is comparable to that of the best existing methods. We show that existing methods are biased towards the prediction of destabilizing mutations and that ENCoM is less biased at predicting stabilizing mutations.     

玉米粗缩病(MRDV)的季节流行动态和经济损失的定量研究

采用系统调查方法研究田间玉米粗缩病(MRDV)的自然发展动态和经济损失规律,其结果表明,MRDV在玉米生长季中的进展曲线遵循对数抛物线函数(y=a·e~bx ex~2)规律,从而建立了中单2#和丹玉13#玉米上MRDV(病指数和发病率)的流行模型(α<0.05,估计病情符合率75—100％),同时认为此函数为生长后期表现“隐症”的一类植物病毒病发展动态的通用拟合模型。MRDV对玉米成穗率、穗粒数、穗粒和干粒重诸产量因子都显著影响,相关分析发现玉米损失率与拔节,抽雄和吐丝期的MRDV严重度密切相关(r≥0.89,α<0.05),因此建立了这些时期病指数和病株率与经济损失率间的线性关系模型,并用相应的模型估计了南充地区1988—1989年MRDV引起的玉米产量和经济损失。     

加性-显性-母体效应及GE互作效应遗传模型的模拟比较

运用蒙特卡罗方法比较了8个亲本正反应的加性－显性－母体效应的全模型及缩减模型,当σ^2M和σ^2ME存在时,检测各项遗传方差分量的功效高达97％以上,如何存在σ^2M和σ^2ME而缩减模型未包括这两项效应时,除显性效应以外的各项方差分量都被高估。对于加性－显性模型,如果忽略了基因型与环境互作,σ^2ε和σ^2A将被高估。当母体效应和基因型与环境互作被忽略时,将显著地增加遗传效应预测值的方差。     

具垂直传染和连续预防接种的SIRS传染病模型的研究

研究了具有垂直传染的两类连续预防接种传染病模型,分别给出了SIRS传染病模型基本再生数并利用广义Dulac函数方法和LaSalle不变原理证明了无病平衡点和正平衡点的全局稳定性.最后对两种结果进行了比较.     

A Molecular Dynamics Simulation Study of Rigid and Non-rigid Hard Dumb-bells

Abstract

We present a comparative study, using molecular dynamics, of systems of diatomic, hard dumb-bell, molecules in which the interatomic distance is either constrained to a fixed value or is allowed to vary freely between preset limits. A significant improvement in simulation effciency can be attained by allowing the bond length to vary. We find that thermodynamic properties, and some time correlation functions, are only slightly affected by the removal of the rigid bond-length constraint. The atomic velocity correlation function responds dramatically at short times to changes in the degree of non-rigidity, but at long times these differences are much less important.     

A Molecular Dynamics Simulation Study of Coaxial Stacking in RNA

Abstract

We report on unrestrained molecular dynamics simulations of an RNA tetramer binding to a tetra-nucleotide overhang at the 5′-end of an RNA hairpin (nicked structure) and of the corresponding continuous hairpin with Na⁺ as counterions. The simulations lead to stable structures and in this way a structural model for the coaxially stacked RNA hairpin is generated. The stacking interface in the coaxially stacked nicked hairpin structure is characterized by a reduced twist and shift and a slightly increased propeller twist as compared to the continuous system. This leads to an increased overlap between C22 and G23 in the stacking interface of the nicked structure. In the simulations the continuous RNA hairpin has an almost straight helical axis. On the other hand, the corresponding axis for the nicked structure exhibits a marked kink of 39°. The stacking interface exhibits no increased flexibility as compared to the corresponding base pair step in the continuous structure.     

H3N2v and Other Influenza Epidemic Risk Based on Age-Specific Estimates of Sero-Protection and Contact Network Interactions

Cases of a novel swine-origin influenza A(H3N2) variant (H3N2v) have recently been identified in the US, primarily among children. We estimated potential epidemic attack rates (ARs) based on age-specific estimates of sero-susceptibility and social interactions. A contact network model previously established for the Greater Vancouver Area (GVA), Canada was used to estimate average epidemic (infection) ARs for the emerging H3N2v and comparator viruses (H1N1pdm09 and an extinguished H3N2 seasonal strain) based on typical influenza characteristics, basic reproduction number (R₀), and effective contacts taking into account age-specific sero-protection rates (SPRs). SPRs were assessed in sera collected from the GVA in 2009 or earlier (pre-H1N1pdm09) and fall 2010 (post-H1N1pdm09, seasonal A/Brisbane/10/2007(H3N2), and H3N2v) by hemagglutination inhibition (HI) assay. SPR was assigned per convention based on proportion with HI antibody titre ≥40 (SPR40). Recognizing that the HI titre ≥40 was established as the 50%sero-protective threshold we also explored for ½SPR40, SPR80 and a blended gradient defined as: ¼SPR20, ½SPR40, ¾SPR80, SPR160. Base case analysis assumed R₀ = 1.40, but we also explored R₀ as high as 1.80. With R₀ = 1.40 and SPR40, simulated ARs were well aligned with field observations for H1N1pdm09 incidence (AR: 32%), sporadic detections without a third epidemic wave post-H1N1pdm09 (negligible AR<0.1%) as well as A/Brisbane/10/2007(H3N2) seasonal strain extinction and antigenic drift replacement (negligible AR<0.1%). Simulated AR for the novel swine-origin H3N2v was 6%, highest in children 6–11years (16%). However, with modification to SPR thresholds per above, H3N2v AR ≥20% became possible. At SPR40, H3N2v AR ≥10%, ≥15% or ≥30%, occur if R₀≥1.48, ≥1.56 or ≥1.86, respectively. Based on conventional assumptions, the novel swine-origin H3N2v does not currently pose a substantial pandemic threat. If H3N2v epidemics do occur, overall community ARs are unlikely to exceed typical seasonal influenza experience. However risk assessment may change with time and depends crucially upon the validation of epidemiological features of influenza, notably the serologic correlate of protection and R₀.     

当代森林动态的计算机模型述评

一、引言森林动态这一广义语,包括森林生态系统随时间的任何变化。要想经营好森林,使其为人类创造出最大的财富,必须深刻认识森林的动态规律。在过去的一个多世纪里,森林生态学家们对森林动态规律进行了广泛而深入的研究,现已形成各种动态学说。随着科学的发展以及森林经营水平的提高,人们逐渐用各种方     

The Structure of Liquid Methanol: A Molecular Dynamics Study Using Three-Site Models

Abstract

The structure of liquid methanol at 298.15 K is investigated by performing molecular dynamics (MD) simulations in NVE ensemble using two 3-site force field models. The simulated structural results are compared with the recent neutron diffraction (ND) results obtained at the partial pair distribution function (pdf) level by employing H/D substitution on the hydroxyl hydrogen, Ho. Overall agreement is found between the simulated and experimental total intermolecular radial distribution functions (rdfs). The ability of the 3-site model simulations to satisfactorily reproduce experimental X—X (X = C, O or H- a methyl hydrogen) intermolecular partial distribution function, dominated by contributions from the methyl group. demonstrates that the methyl group does not participate in any bonding in the liquid. However, a comparison between the simulated and experimental Ho—Ho and X—Ho functions reveals that discrepancies still exist at a quantitative level.     

New Moment Closures Based on A Priori Distributions with Applications to Epidemic Dynamics

Recently, research that focuses on the rigorous understanding of the relation between simulation and/or exact models on graphs and approximate counterparts has gained lots of momentum. This includes revisiting the performance of classic pairwise models with closures at the level of pairs and/or triples as well as effective-degree-type models and those based on the probability generating function formalism. In this paper, for a fully connected graph and the simple SIS (susceptible-infected-susceptible) epidemic model, a novel closure is introduced. This is done via using the equations for the moments of the distribution describing the number of infecteds at all times combined with the empirical observations that this is well described/approximated by a binomial distribution with time dependent parameters. This assumption allows us to express higher order moments in terms of lower order ones and this leads to a new closure. The significant feature of the new closure is that the difference of the exact system, given by the Kolmogorov equations, from the solution of the newly defined approximate system is of order 1/N(2). This is in contrast with the O(1/N) difference corresponding to the approximate system obtained via the classic triple closure. The fully connected nature of the graph also allows us to interpret pairwise equations in terms of the moments and thus treat closures and the two approximate models within the same framework. Finally, the applicability and limitations of the new methodology is discussed in detail.     

Selecting Optimal Random Forest Predictive Models: A Case Study on Predicting the Spatial Distribution of Seabed Hardness

Spatially continuous predictions of seabed hardness are important baseline environmental information for sustainable management of Australia’s marine jurisdiction. Seabed hardness is often inferred from multibeam backscatter data with unknown accuracy and can be inferred from underwater video footage at limited locations. In this study, we classified the seabed into four classes based on two new seabed hardness classification schemes (i.e., hard90 and hard70). We developed optimal predictive models to predict seabed hardness using random forest (RF) based on the point data of hardness classes and spatially continuous multibeam data. Five feature selection (FS) methods that are variable importance (VI), averaged variable importance (AVI), knowledge informed AVI (KIAVI), Boruta and regularized RF (RRF) were tested based on predictive accuracy. Effects of highly correlated, important and unimportant predictors on the accuracy of RF predictive models were examined. Finally, spatial predictions generated using the most accurate models were visually examined and analysed. This study confirmed that: 1) hard90 and hard70 are effective seabed hardness classification schemes; 2) seabed hardness of four classes can be predicted with a high degree of accuracy; 3) the typical approach used to pre-select predictive variables by excluding highly correlated variables needs to be re-examined; 4) the identification of the important and unimportant predictors provides useful guidelines for further improving predictive models; 5) FS methods select the most accurate predictive model(s) instead of the most parsimonious ones, and AVI and Boruta are recommended for future studies; and 6) RF is an effective modelling method with high predictive accuracy for multi-level categorical data and can be applied to ‘small p and large n’ problems in environmental sciences. Additionally, automated computational programs for AVI need to be developed to increase its computational efficiency and caution should be taken when applying filter FS methods in selecting predictive models.     

A Molecular Dynamics Simulation Study of Nanomechanical Properties of Asymmetric Lipid Bilayer

A very important part of the living cells of biological systems is the lipid membrane. The mechanical properties of this membrane play an important role in biophysical studies. Investigation as to how the insertion of additional phospholipids in one leaflet of a bilayer affects the physical properties of the obtained asymmetric lipid membrane is of recent practical interest. In this work a coarse-grained molecular dynamics simulation was carried out in order to compute the pressure tensor, the lateral pressure, the surface tension and the first moment of lateral pressure in each leaflet of such a bilayer. Our simulations indicate that adding more phospholipids into one monolayer results in asymmetrical changes in the lateral pressure of the individual bilayer leaflets. Interestingly, it has been observed that a change in phospholipid density in one leaflet affects the physical properties of unperturbed leaflet as well. The asymmetric behavior of the physical properties of the two leaflets as a result of a change in the contribution of the various intermolecular forces in the presence of additional phospholipids may be expressed formally.     

构建基于患者个体化的Stanford B型主动脉夹层计算流体力学数值模拟分析模型

目的:探索简便、高效、精确的构建基于真实人体解剖形态结构的Stanford B型主动脉夹层计算流体力学数值模拟分析模型的方法.方法:利用Siemens Sensation Cardiac 64层螺旋CT薄层扫描技术,基于1mm层厚获取6例Stanford B型主动脉夹层连续断层DICOM格式图像,导入Materialise MIMICS v12.11软件,界定目标区域后生成三维动脉模型,经网格优化处理去除低质量及相交面网格,保存结果输出,导入TGrid 5.0软件,对主动脉面网格模型进行几何修复,使面网格扭曲率<0.75,采用自由分网方式生成Stanford B型主动脉夹层计算流体力学分析体网格模型,并对所构建模型进行血流属性、流场边界等界定,初步验证模型的有效性.结果:通过初步计算求解,确定所构建的6例Stanford B型主动脉夹层计算流体力学分析模型分别包含1857030,1820501,1844181,1849651,1858246及1814914个四面体单元.结论:利用64层螺旋CT薄层扫描技术获取DICOM格式连续断层CT图像可快速、准确地构建Stanford B型主动脉夹层计算流体力学数值模拟分析模型,为进一步的计算流体力学分析奠定了良好的基础.     

Comparing the Performance of Cluster Random Sampling and Integrated Threshold Mapping for Targeting Trachoma Control,Using Computer Simulation

Background

Implementation of trachoma control strategies requires reliable district-level estimates of trachomatous inflammation–follicular (TF), generally collected using the recommended gold-standard cluster randomized surveys (CRS). Integrated Threshold Mapping (ITM) has been proposed as an integrated and cost-effective means of rapidly surveying trachoma in order to classify districts according to treatment thresholds. ITM differs from CRS in a number of important ways, including the use of a school-based sampling platform for children aged 1–9 and a different age distribution of participants. This study uses computerised sampling simulations to compare the performance of these survey designs and evaluate the impact of varying key parameters.

Methodology/Principal Findings

Realistic pseudo gold standard data for 100 districts were generated that maintained the relative risk of disease between important sub-groups and incorporated empirical estimates of disease clustering at the household, village and district level. To simulate the different sampling approaches, 20 clusters were selected from each district, with individuals sampled according to the protocol for ITM and CRS. Results showed that ITM generally under-estimated the true prevalence of TF over a range of epidemiological settings and introduced more district misclassification according to treatment thresholds than did CRS. However, the extent of underestimation and resulting misclassification was found to be dependent on three main factors: (i) the district prevalence of TF; (ii) the relative risk of TF between enrolled and non-enrolled children within clusters; and (iii) the enrollment rate in schools.

Conclusions/Significance

Although in some contexts the two methodologies may be equivalent, ITM can introduce a bias-dependent shift as prevalence of TF increases, resulting in a greater risk of misclassification around treatment thresholds. In addition to strengthening the evidence base around choice of trachoma survey methodologies, this study illustrates the use of a simulated approach in addressing operational research questions for trachoma but also other NTDs.     

The Ca2+ Influence on Calmodulin Unfolding Pathway: A Steered Molecular Dynamics Simulation Study

The force-induced unfolding of calmodulin (CaM) was investigated at atomistic details with steered molecular dynamics. The two isolated CaM domains as well as the full-length CaM were simulated in N-C-terminal pulling scheme, and the isolated N-lobe of CaM was studied specially in two other pulling schemes to test the effect of pulling direction and compare with relevant experiments. Both Ca²⁺-loaded CaM and Ca²⁺-free CaM were considered in order to define the Ca²⁺ influence to the CaM unfolding. The results reveal that the Ca²⁺ significantly affects the stability and unfolding behaviors of both the isolated CaM domains and the full-length CaM. In Ca²⁺-loaded CaM, N-terminal domain unfolds in priori to the C-terminal domain. But in Ca²⁺-free CaM, the unfolding order changes, and C-terminal domain unfolds first. The force-extension curves of CaM unfolding indicate that the major unfolding barrier comes from conquering the interaction of two EF-hand motifs in both N- and C- terminal domains. Our results provide the atomistic-level insights in the force-induced CaM unfolding and explain the observation in recent AFM experiments.