Genomic Object Net: I. A platform for modelling and simulating biopathways

Genomic Object Net (GON) 1.0 is a software package for creating models and simulations of biopathways. Its core architecture employs the notion of a hybrid functional Petri net with extension (HFPNe). HFPNe can seamlessly handle discrete and continuous objects and events while keeping the model components themselves simple. With the feature and graphical model editor, biopathways can be modelled intuitively and simulated on GON. The subsequent output of the simulation results can be evaluated in customised views on GON Visualizer by writing an XML file. Additionally, GON provides a tool to transform biopathway models in KEGG and BioCyc to the GON XML files for modelling and simulation. The tool avoids a lot of tedious work by users, enabling them to focus on the biological model.     

Online model checking approach based parameter estimation to a neuronal fate decision simulation model in Caenorhabditis elegans with hybrid functional Petri net with extension

Mathematical modeling and simulation studies are playing an increasingly important role in helping researchers elucidate how living organisms function in cells. In systems biology, researchers typically tune many parameters manually to achieve simulation results that are consistent with biological knowledge. This severely limits the size and complexity of simulation models built. In order to break this limitation, we propose a computational framework to automatically estimate kinetic parameters for a given network structure. We utilized an online (on-the-fly) model checking technique (which saves resources compared to the offline approach), with a quantitative modeling and simulation architecture named hybrid functional Petri net with extension (HFPNe). We demonstrate the applicability of this framework by the analysis of the underlying model for the neuronal cell fate decision model (ASE fate model) in Caenorhabditis elegans. First, we built a quantitative ASE fate model containing 3327 components emulating nine genetic conditions. Then, using our developed efficient online model checker, MIRACH 1.0, together with parameter estimation, we ran 20-million simulation runs, and were able to locate 57 parameter sets for 23 parameters in the model that are consistent with 45 biological rules extracted from published biological articles without much manual intervention. To evaluate the robustness of these 57 parameter sets, we run another 20 million simulation runs using different magnitudes of noise. Our simulation results concluded that among these models, one model is the most reasonable and robust simulation model owing to the high stability against these stochastic noises. Our simulation results provide interesting biological findings which could be used for future wet-lab experiments.     

The systems approach to the prespore-specific activation of sigma factor SigF in Bacillus subtilis

The prespore-specific activation of sigma factor SigF (σ^F) in Bacillus subtilis has been explained mainly by two factors, i.e., the transient genetic asymmetry and the volume difference between the mother cell and the prespore. Here, we systematically surveyed the effect of these two factors on sporulation using a quantitative modeling and simulation architecture named hybrid functional Petri net with extension (HFPNe). Considering the fact that the transient genetic asymmetry and the volume difference in sporulation of B. subtilis finally bring about the concentration difference in two proteins SpoIIAB (AB) and SpoIIAA (AA) between the mother cell and the prespore, we have surveyed the effect of AB and AA concentration on the prespore-specific activation of σ^F occurring in the early stage of sporulation. Our results show that the prespore-specific activation of σ^F could be governed by the ratio of AA to AB rather than their concentrations themselves. Our model also suggests that B. subtilis could maximize the ratio of AA to AB in the prespore and minimize it in the mother cell by employing both the transient genetic asymmetry and the volume difference simultaneously. This might give a good explanation to the co-occurrence of the transient asymmetry and the volume difference during sporulation of B. subtilis. In addition, we suggest for the first time that the σ^F activation in the prespore might be switched off by the decrease in the ratio of AA to AB after the transient genetic asymmetry is to an end by completion of DNA translocation into the prespore.     

The resource-constrained project scheduling model of Bianco and Caramia: clarifications and an alternative model formulation

Recently, Bianco and Caramia (Flex Serv Manuf J 25(1–2), 6–24, 2013) proposed a new model for the resource-constrained project scheduling problem. Despite its potential, the presentation of the mixed-integer programming model contains some ambiguity which may create misunderstanding in the implementation phase. Here, we clarify the definitions of the decision variables and illustrate their corresponding values using a numerical example. Furthermore, we propose a different interpretation of two decision variables which gives rise to an alternative model formulation also presented using the same numerical example.     

多时滞三种群捕食模型的持久性和全局渐近性

研究了一类多时滞非自治三种群捕食模型的持久性和全局渐近稳定性,分别利用比较原理和构造Lyapunov函数方法得到了模型持久生存与全局渐近稳定性的充分条件,并举例说明定理的可行性且利用Matlab绘出图像.     

A Linear Model with Plot Effects

It is a common practice to analyze the data from agricultural experiments using randomized block design where each block has homogeneous experimental units (plots). However, many times, during the period of study, due to unavoidable circumstances such as natural calamities, say floods, for example, plots are no longer homogeneous. Thus, it is desirable to consider the plot effects also in the model. An appropriate model and an example of the analysis of data with plot effects is provided here.     

流行病免疫规律的随机模型研究

本文提出了流行病免疫规律的随机过程模型,给出了一定条件下个体从不具有免疫力向具有免疫力转移或相反方向转移的转移概率表达式,并给出了各年龄组人群中获得抗性的个体比例．以广州市正常人群甲型病毒性肝炎为例研究模型的具体应用．     

Spatio‐temporal Modelling of Weeds by Shot‐noise G Cox processes

Tractable space‐time point processes models are needed in various fields. For example in weed science for gaining biological knowledge, for prediction of weed development in order to optimize local treatments with herbicides or in epidemiology for prediction of the risk of a disease. Motivated by the spatio‐temporal point patterns for two weed species, we propose a spatio‐temporal Cox model with intensity based on gamma random fields. The model is an extension of Neyman–Scott and shot‐noise Cox processes to the space‐time domain and it allows spatial and temporal inhomogeneity. We use the weed example to give a first intuitive interpretation of the model and then show how the model is constructed more rigorously and how to estimate the parameters. The weed data are analysed using the proposed model, and both spatially and temporally the model shows a good fit to the data using classical goodness‐of‐fit tests.     

Modernization of the Kadomtsev corrugated trap

Various modifications of the Kadomtsev corrugated trap intended for model experiments on studying turbulent plasma dynamics are discussed. The possibility of using the existing magnetic system of the TO-2 tokamak for this purpose is considered as an example.     

Strategies for the development of a peptide computer

MOTIVATION: We devise a computational model using protein-protein interactions. RESULTS: Peptide-antibody interactions can be used to perform a large number of small logical operations in parallel. We show for example how a sequence of operations can be used to compare the number of occurrences of an element in two sets and how to estimate the number of occurrences of an element in a set. Similar to DNA-computing, these techniques could in principle be extended to solve instances of NP-complete problems. We give as an example a procedure to solve examples of the satisfiability problem.     

Effect of activation energy microheterogeneity on first-order enzyme deactivation

The influence of microheterogeneity on enzyme inactivation kinetics is examined. A continuous normal distribution of the thermal activation energy is assumed, and using this, a simple mathematical model is developed to find the activity-time trajectories for a microheterogeneous enzyme. Using an example, the model is used to show the quantitative effects of microheterogeneity such as increased order and stability observed during an enzyme inactivation. Experimental measurement of the extent of microheterogeneity in an enzyme sample is also discussed.     

害虫防治决策的复序贯分析方法及抽样技术研究

复序贯抽样决策技术实际应用的受限 ,原因在于截止限序贯抽样模型的缺乏。本文在检验昆虫种群空间格局回归模型的基础上 ,推导出了目前国内常用检验回归模型的截止限序贯抽样模型 ,并将其运用于复序贯分析决策过程中。实例分析表明 ,对于同一种生物种群 ,在一定的精度 (D)和置信水平(tα)要求下 ,复序贯抽样决策技术可以大幅度地节约抽样成本     

A kinetic study of analyte-receptor binding and dissociation for biosensor applications: a fractal analysis for two different DNA systems

A fractal analysis of DNA binding and dissociation kinetics on biosensor surfaces is presented. The fractal approach provides an attractive, convenient method to model the kinetic data taking into account the effects of surface heterogeneity brought about by ligand immobilization. The fractal technique can be used in conjunction or as an alternate approach to conventional modeling techniques, such as the Langmuir model, saturation model, etc. Examples analyzed include a DNA molecular beacon biosensor and a plasmid DNA-(cationic polymer) interaction biosensor. The molecular beacon example provides some insights into the nature of the surface and how it influences the binding rate coefficients. The DNA-cationic polymer interaction example provides some quantitative results on the binding and dissociation rate coefficients. Data taken from the literature may be modeled, in the case of binding, using a single-fractal analysis or a dual-fractal analysis. The dual-fractal analysis results indicate a change in the binding mechanism as the reaction progresses on the surface. A single-fractal analysis is adequate to model the dissociation kinetics in the example presented. Relationships are presented for the binding rate coefficients as a function of their corresponding fractal dimension, D(f), which is an indication of the degree of heterogeneity that exists on the surface. When analyte-receptor binding is involved, an increase in the heterogeneity of the surface (increase in D(f)) leads to an increase in the binding rate coefficient.     

An evolutionary computing approach for parameter estimation investigation of a model for cholera

We consider the problem of using time-series data to inform a corresponding deterministic model and introduce the concept of genetic algorithms (GA) as a tool for parameter estimation, providing instructions for an implementation of the method that does not require access to special toolboxes or software. We give as an example a model for cholera, a disease for which there is much mechanistic uncertainty in the literature. We use GA to find parameter sets using available time-series data from the introduction of cholera in Haiti and we discuss the value of comparing multiple parameter sets with similar performances in describing the data.     

Use of an experimental model of mixed chlamydial-gonococcal infection in ovo for evaluating the etiotropic action of chemopreparations

The detection of the differentiated chemotherapeutic activity of tetracyclin and penicillin has been used as an example for demonstrating the possibility of using the experimental in ovo model of mixed chlamydial and gonococcal infection for the detection and primary selection of effective etiotropic preparations, simultaneously affecting Chlamydia trachomatis and Neisseria gonorrhoeae.     

Distinguishing Migration from Isolation Using the Variance of Pairwise Differences

Two demographic scenarios are considered: two populations with migration and two populations that have been completely isolated from each other for some period of time. The variance of the number of differences between pairs of sequences in a single sample is studied and forms the basis of a test of the isolation model. The migration model is one possible alternative to isolation. The isolation model is rejected when the proposed test statistic, which involves the variances of pairwise difference within and between populations, is larger than some critical value. The power and realized significance of the test are investigated using simulations, and an example using mitochondrial DNA illustrates its application.     

Integrate-and-fire models with nonlinear leakage

Can we express biophysical neuronal models as integrate-and-fire (IF) models with leakage coefficients which are no longer constant, as in the conventional leaky IF model, but functions of membrane potential and other biophysical variables? We illustrate the answer to this question using the FitzHugh-Nagumo (FHN) model as an example. A novel IF type model, the IF-FHN model, which approximates to the FHN model, is obtained. The leakage coefficient derived in the IF-FHN model has nonmonotonic relationship with membrane potential, revealing at least in part the intrinsic mechanisms underlying the FHN models. The IF-FHN model correspondingly exhibits more complex behaviour than the standard IF model. For example, in some parameter regions, the IF-FHN model has a coefficient of variation of the output interspike interval which is independent of the number of inhibitory inputs, being close to unity over the whole range, comparable to the FHN model as we noted previously (Brown et al., 1999).     

Effect of geographical factors on the biological productivity of Lake ecosystems: Modeling and forecast

The correlation between the lake ecosystem productivity and geographical and climatic factors and the production of terrestrial vegetation in the catchment area has been described in the form of a dynamic mass-balance model using Lake Krivoe (North Karelia) as an example. A model algorithm has been presented. It is concluded that, with natural year-to-year fluctuations of the biogenic load and the absence of anthropogenic impacts, Lake Krivoe has been preserving the status of an oligotrophic water body for more than 40 years (1968–2013).     

Modeling shifts in microbial populations associated with health or disease

Stable microbial communities associated with health can be disrupted by altered environmental conditions. Periodontal diseases are associated with changes in the resident oral microflora. For example, as gingivitis develops, a key change in the microbial composition of dental plaque is the ascendancy of Actinomyces spp. and gram-negative rods at the expense of Streptococcus spp. We describe the use of an in vitro model to replicate this population shift, first with a dual-species model (Actinomyces naeslundii and Streptococcus sobrinus) and then using a microcosm model of dental plaque. The population shift was induced by environmental changes associated with gingivitis, first by the addition of artificial gingival crevicular fluid and then by a switch to a microaerophilic atmosphere. In addition to the observed population shifts, confocal laser scanning microscopy also revealed structural changes and differences in the distribution of viable and nonviable bacteria associated with the change in environmental conditions. This model provides an appropriate system for the further understanding of microbial population shifts associated with gingivitis and for the testing of, for example, antimicrobial agents.