Software control of sensing and stimulation for cardiac electrophysiological study

A software-controlled cardiac stimulator for clinical investigations is described. The stimulator is programmed by the user at a keyboard, while current status and values of parameters are presented on a visual display screen. A menu of predefined cardiac electrophysiological tests is available for user selection. Validity checks on data keyed in by the user and internal checks on safe pacing limits are incorporated in case of malfunction or user error. The system consists of a separate relatively simple isolated sensing and stimulation unit which communicates, via a standard digital input output interface, with a controlling microcomputer. All timing and control functions are performed in software by the computer. The use of high-level FORTRAN as the main programming language provides the system with a high degree of adaptability.     

ALC: automated reduction of rule-based models

Background

Combinatorial complexity is a challenging problem for the modeling of cellular signal transduction since the association of a few proteins can give rise to an enormous amount of feasible protein complexes. The layer-based approach is an approximative, but accurate method for the mathematical modeling of signaling systems with inherent combinatorial complexity. The number of variables in the simulation equations is highly reduced and the resulting dynamic models show a pronounced modularity. Layer-based modeling allows for the modeling of systems not accessible previously.

Results

ALC (Automated Layer Construction) is a computer program that highly simplifies the building of reduced modular models, according to the layer-based approach. The model is defined using a simple but powerful rule-based syntax that supports the concepts of modularity and macrostates. ALC performs consistency checks on the model definition and provides the model output in different formats (C MEX, MATLAB, Mathematica and SBML) as ready-to-run simulation files. ALC also provides additional documentation files that simplify the publication or presentation of the models. The tool can be used offline or via a form on the ALC website.

Conclusion

ALC allows for a simple rule-based generation of layer-based reduced models. The model files are given in different formats as ready-to-run simulation files.     

New stochastic simulation capability applied to the GREET model

Background, Aims and Scope

In 1995, the Center for Transportation Research (CTR) of Argonne National Laboratory (ANL) began to develop a model, called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation), for estimating the full fuel-cycle energy and emissions impacts of alternative transportation fuels and advanced vehicle technologies. The parametric assumptions used in the GREET model involve uncertainties. A new stochastic simulation tool, developed by Vishwamitra Research Institute (VRI), is built into the GREET model to address uncertainties. This paper presents the methodology and features of this new stochastic simulation tool and evaluates the performance of the sampling techniques in the tool.

Methods

The new tool is interfaced through the graphical user interface (GUI) to perform the stochastic simulation. In general, five steps need to be followed to run a complete simulation: 1) Specify probability distribution functions; 2) Indicate the number of samples and the sampling technique; 3) Define the forecast variables; 4) Delete distribution functions (if necessary); and 5) Propagate the uncertainties and statistically analyze the outputs. The GREET model contains more than 700 default distribution functions for a wide variety of key parameters and as many as 3000 forecast variables. The stochastic simulation tool has been developed to incorporate 11 probability distribution function types for representing uncertain parameters and four sampling techniques (Monte Carlo sampling [MCS], Hammersley Sequence sampling [HSS], Latin Hypercube sampling [LHS] and Latin Hypercube Hammersley sampling [LHHS]) for stochastic simulation. To evaluate the performance of the four sampling techniques, 16 independent stochastic simulation runs were conducted in GREET and the output results were analyzed and compared.

Results and Discussion

With the same number of samples, the output distribution curve simulated by HSS is the smoothest corresponding to the highest level of uniformity. To achieve the same level of smoothness as HSS with 1,000 samples, LHHS needs to be simulated with ～1500 samples and LHS and MCS with ～3,000 samples. As a result, HSS can achieve more than 200% reduction in running time compared to LHS or MCS without compromising the accuracy and quality of the prediction curves. The simulated mean values are close enough to the actual mean value (within ±1%) despite the selection of sampling technique and the number of samples (between 1,000 and 4,000). The standard deviation values from each other are close enough as well (within ±5%). It shows the trend that the increasing number of samples makes the simulated mean value marginally closer to the actual mean value; however, the improvement effect is negligible. The simulation time is strictly positive-correlated with the number of samples; therefore, the trade-off between extending simulation time and improving the smoothness of the output distribution curve needs to be carefully assessed.

Conclusion

A new stochastic simulation tool has been developed to be built into Argonne’s GREET model to enhance its capability for addressing uncertainty. This new tool guides the user in each step of the process through the user-friendly GUI windows. According to the performance comparison among the four sampling techniques, HSS was found to be the most efficient technique. Therefore, HSS was set as the default technique in GREET.     

Interactive computer graphics in the study of human body planar motion under free fall conditions

A computer program utilizing interactive graphics was developed in order to study the planar motion of a five-segment model of the human body. By providing instantaneous feedback and convenient graphical representation of the body, the program allows the user to quickly simulate and study body motions of interest. Consequently, the model is a useful tool for the researcher and may be readily employed for student instructional purposes.The configuration of the model, and the derivation and validation of the equations of motion, are included. Several options provided by the simulation are described.     

bioTk: Componentry for genome informatics graphical user interfaces

bioTk is a collection of graphical “widgets” and utilities that support application programming in the domain of bioinformatics. It is intended to establish a framework that encourages the development of communicating window-based applications and flexible, non-modal user interaction. The current release to bioTk has domain-specific widgets for chromosome ideogram displays, genome maps, and scrolling sequence windows.     

Chemical synthesis of [32P]pyrophosphate with high specific activity

Graphical methods have traditionally been the principal means for estimation of parameters (e.g., affinity constants, cooperativity parameters, and concentrations of receptor sites) in enzymology and ligand-binding problems. The present report provides a review of these methods as well as new results, as applied to three coordinate systems popularly used in ligand-binding studies: $\text{B}\text{F}$ vs [Bound]. $\text{B}\text{F}$ vs [Free], and $\text{B}\text{F}$ vs [Total]. We consider two extremely general models, the statistical mechanical model and the Adair model for equilibrium ligand binding. We also consider a very specialized case of receptor interaction wherein the equilibrium constannt of dissociation is linearly related to receptor occupancy. We collect previously described equations and derive new ones, to enable the user to estimate the parameters of the models in terms of relatively easily measurable graphical characteristics. We have evaluated the performance of these methods in representative cases using Monte Carlo studies. The results indicate the kind of precision and accuracy which can be obtained with typical experimental designs. Depending upon the magnitude of experimental error, the graphical methods can provide dependable values for the binding parameters. However, in general, the results obtained by the graphical methods should be regarded as reasonable initial estimates for further refinement by weighted nonlinear least-squares curve fitting.     

A graphical user interface for BIOEQS: a program for simulating and analyzing complex biomolecular interactions

BIOEQS is a global analysis and simulation program for complex biomolecular interaction data developed during the 1990s. Its continued usefulness derives from the fact that it is based on a numerical solver for complex coupled biological equilibria rather than on closed-form analytical equations for the binding isotherms. Therefore, it is quite versatile, allowing easy testing of multiple binding models and analysis of systems too complex for closed-form solutions. However, a major drawback to a generalized use of this program has been the lack of a graphical user interface (GUI) for setting up the binding models and experimental conditions as well as for visualizing the results. We present here a new GUI for BIOEQS that should be useful in both research and teaching applications.     

A FORTRAN computer program for storage and retrieval of personal journal references

A FORTRAN program is described for interactive maintenance of a personal library of journal references and reprints. The program queries the user for category (author, journal, year, title, and keyword) information during entry of new documents. Retrieval of documents in the set is accomplished by entering as many search words as desired, in any order, and in any category. The program returns documents that match for all entered words. Other functions include terminal display of the information stored for a given document and the ability to generate an alphabetized bibliographic listing from among the document set. A correction routine and a routine for listing the contents of the search word files are also included.     

Boolink: a graphical interface for open access Boolean network simulations and use in guard cell CO2 signaling

Signaling networks are at the heart of almost all biological processes. Most of these networks contain large number of components, and often either the connections between these components are not known or the rate equations that govern the dynamics of soluble signaling components are not quantified. This uncertainty in network topology and parameters can make it challenging to formulate detailed mathematical models. Boolean networks, in which all components are either on or off, have emerged as viable alternatives to detailed mathematical models that contain rate constants and other parameters. Therefore, open-source platforms of Boolean models for community use are desirable. Here, we present Boolink, a freely available graphical user interface that allows users to easily construct and analyze existing Boolean networks. Boolink can be applied to any Boolean network. We demonstrate its application using a previously published network for abscisic acid (ABA)-driven stomatal closure in Arabidopsis spp. (Arabidopsis thaliana). We also show how Boolink can be used to generate testable predictions by extending the network to include CO₂ regulation of stomatal movements. Predictions of the model were experimentally tested, and the model was iteratively modified based on experiments showing that ABA effectively closes Arabidopsis stomata at near-zero CO₂ concentrations (1.5-ppm CO₂). Thus, Boolink enables public generation and the use of existing Boolean models, including the prior developed ABA signaling model with added CO₂ signaling components.

An open-source, graphical interface for the simulation of Boolean networks is presented, applied to an abscisic acid signaling network in guard cells, and extended to include input from CO₂.     

Adaptive on-line simulation of bioreactors: Fermentation monitoring and modeling system

Summary In order to study and control fermentation processes, indirect on-line measurements and mathematical models can be used. Here an on-line model for fermentation processes is presented. The model is based on atom and partial mass balances as well as on stability equations for the protolytes. The model is given an adaptive form by including transport equations for mass transfer and expressions for the fermentation kinetics. The state of the process can be estimated on-line using the balance component of the model completed with measurement equations for the input and the output flows of the process. Adaptivity is realized by means of on-line estimation of the parameters in the transport and kinetic expressions using recursive regression analysis. On-line estimation of the kinetic and mass transfer parameters makes model-based predictions possible and enables intelligent process control while facilitating testing of the validity of the measurement variables. A practical MS-Windows 3.1 model implementation called FMMS—Fermentation Monitoring and Modeling System is shown. The system makes it easy to configure the operating conditions for a run. It uses Windows dialogs for all set-ups, model configuration parameters, elemental compositions, on-line measurement devices and signal conditioning. Advanced on-line data analysis makes it possible to plot variables against each other for easy comparison. FMMS keeps track of over 100 variables per run. These variables are either measured or estimated by the model. Assay results can also be entered and plotted during fermentation. Thus the model can be verified almost instantly. Historical fermentation runs can be re-analyzed in simulation mode. This makes it possible to examine different signal conditining filters as well as the sensitivity of the model. Combined, the data analysis and the simulation mode make it easy to test and develop model theories and new ideas.     

Mathematical approach to the stimulation of the competence development in Bacillus subtilis.

The stimulation of competence development by culture fluids of B. subtilis has been studied at very short intervals. In these conditions, successive competence waves as well as changes in the level of competence stimulating activity are observed. A mathematical model for the explanation of the phenomenon is developed. Two methods have been followed to study the model: construction of a simulation by using a computer system and analytic study of the equations.     

MEGA11: Molecular Evolutionary Genetics Analysis Version 11

The Molecular Evolutionary Genetics Analysis (MEGA) software has matured to contain a large collection of methods and tools of computational molecular evolution. Here, we describe new additions that make MEGA a more comprehensive tool for building timetrees of species, pathogens, and gene families using rapid relaxed-clock methods. Methods for estimating divergence times and confidence intervals are implemented to use probability densities for calibration constraints for node-dating and sequence sampling dates for tip-dating analyses. They are supported by new options for tagging sequences with spatiotemporal sampling information, an expanded interactive Node Calibrations Editor, and an extended Tree Explorer to display timetrees. Also added is a Bayesian method for estimating neutral evolutionary probabilities of alleles in a species using multispecies sequence alignments and a machine learning method to test for the autocorrelation of evolutionary rates in phylogenies. The computer memory requirements for the maximum likelihood analysis are reduced significantly through reprogramming, and the graphical user interface has been made more responsive and interactive for very big data sets. These enhancements will improve the user experience, quality of results, and the pace of biological discovery. Natively compiled graphical user interface and command-line versions of MEGA11 are available for Microsoft Windows, Linux, and macOS from www.megasoftware.net.     

A-Cell: graphical user interface for the construction of biochemical reaction models

SUMMARY: A-Cell is a tool for constructing models of complex and complicated biochemical reactions. An important feature of A-Cell is its graphical user interface for constructing biochemical reactions. In addition, it has a capability of importing previously constructed models, combining them, and constructing a comprehensive model. The simulation program for the model is automatically generated by A-cell.     

Stability of cyclic gene models for systems involving repression

We ccnsider a Goodwin-type model for cyclic gene systems involving endproduct repression. The model is described by a very general system of functic nal differential equations which include as special cases continuous analogues of cyclic models studied previously via computer simulation by other investigators (Fraser & Tiwari, 1974). We establish global stability of equilibrium solutions with arguments which are valid for any number (odd or even) of genes in the cyclic loop.     

Marine systems analysis and modeling

Oceanography and marine ecology have a considerable history in the use of computers for modeling both physical and ecological processes. With increasing stress on the marine environment due to human activities such as fisheries and numerous forms of pollution, the analysis of marine problems must increasingly and jointly consider physical, ecological and socio-economic aspects in a broader systems framework that transcends more traditional disciplinary boundaries. This often introduces difficult-to-quantify, “soft” elements, such as values and perceptions, into formal analysis. Thus, the problem domain combines a solid foundation in the physical sciences, with strong elements of ecological, socio-economic and political considerations. At the same time, the domain is also characterized by both a very large volume of some data, and an extremely datapoor situation for other variables, as well as a very high degree of uncertainty, partly due to the temporal and spatial heterogeneity of the marine environment. Consequently, marine systems analysis and management require tools that can integrate these diverse aspects into efficient information systems that can support research as well as planning and also policy- and decisionmaking processes. Supporting scientific research, as well as decision-making processes and the diverse groups and actors involved, requires better access and direct understanding of the information basis as well as easy-to-use, but powerful tools for analysis. Advanced information technology provides the tools to design and implement smart software where, in a broad sense, the emphasis is on the man-machine interface. Symbolic and analogous, graphical interaction, visual representation of problems, integrated data sources, and built-in domain knowledge can effectively support users of complex and complicated software systems. Integration, interaction, visualization and intelligence are key concepts that are discussed in detail, using an operational software example of a coastal water quality model. The model comprises components of a geographical information and mapping system, data bases, dynamic simulation models, and an integrated expert system. An interactive graphical user interface, dynamic visualization of model results, and a hyper-text-based help-and-explain system illustrate some of the features of new and powerful software tools for marine systems analysis and modeling.     

What <Emphasis Type="BoldItalic">in silico</Emphasis> molecular docking can do for the ‘bench-working biologists’

Required by an increasing amount of scientists, the in silico docking field is in full expansion, new algorithms and methods appearing at an exponential rate. The sheer range of available programs is overwhelming for the bench-working biologist, which is often discouraging by the lack of a graphical user interface, good user manual or literature to validate a given program. This mini-review attempts to present the docking problem and available solutions from a non-bioinformatician point of view and makes a selection of the available servers and programs. These tools are evaluated from several points of view, as numbers of citations, ease of usage and computer requirements. Finally, the capabilities and limitations as well as specific applications of in silico docking techniques are presented.     

Nomograms Aid Interpretation of Complex Regression Models

ABSTRACT Ecologists often develop complex regression models that include multiple categorical and continuous variables, interactions among predictors, and nonlinear relationships between the response and predictor variables. Nomograms, which are graphical devices for presenting mathematical functions and calculating output values, can aid biologists in interpreting and presenting these complex models. To illustrate benefits of nomograms, we developed a logistic regression model of elk (Cervus elaphus) resource selection. With this model, we demonstrated how a nomogram helps scientists and managers interpret interactions among variables, compare the relative biological importance of variables, and examine predicted shapes of relationships (e.g., linear vs. nonlinear) between response and predictor variables. Although our example focused on logistic regression, nomograms are equally useful for other linear and nonlinear models. Regardless of the approach used for model development, nomograms and other graphical summaries can help scientists and managers develop, interpret, and apply statistical models.     

A minicomputer program for rapid graphical and statistical analysis of laboratory data

The utility of a FORTRAN program package, which enables the scientific investigator to make a rapid assessment of laboratory data is described. Data are submitted from the keyboard or specified disk files in the form of coordinate pairs. The program includes routines for plotting values as a series of X-Y pairs on the computer video monitor or for comparing the X and Y arrays via paired differences and Student's t-test. A least squares linear regression of plotted data may also be called. Data modification, curve fitting, and I/O are easily handled in either single pair or column format. Examples of both statistical and graphical data analysis are presented.     

动态神经元的网络模型 Ⅰ.模型和算法

从生物神经元接收和处理信息的基本实验事实出发,提出了一种新的神经网络模型。这个模型修改了大多数现有人工神经网络中关于输出函数只反映静态特性的假设,而强调了神经元发放脉冲的动态过程。模型方程分别对应于突触后电位、感受器电位、始段分级电位和轴突上的的脉冲系列,每个方程都具有明确的生理意义。还给出了计算此非线性方程组解的递推算法和程序框图。因此不仅可对本模型作进一步的理论分析,也可在计算机上仿真,并和相应的生物学实验资料进行对照比较。