Computer simulation of within family selection in finite populations

Summary The relative efficiency, in terms of selection limits, between mass selection and within family selection was compared by computer simulation methods. A 20-locus additive model was used to simulate a quantitative trait under selection. It was assumed that 50–75 percent of the genetic variance in the base population was controlled by four major genes initially at low frequencies.In populations of size N=100 no loss of major genes was found when either method of selection was used. When N=50 within family selection was generally superior to mass selection but when N=10 the situation was reversed. For N=30 within family selection was more efficient only under high selection intensity or high heritability situations.     

Computer simulation of mutagenesis

A FORTRAN program is described which simulates point-substitution mutations in the DNA strands of typical organisms. Its objective is to help students to understand the significance and structure of the genetic code, and the mechanisms and effects of mutagenesis. The program is intended to be used as part of an elementary course in genetics at degree level.     

Computer simulation of the segmental neural network generating locomotion in lamprey by using populations of network interneurons

Realistic computer simulations of the experimentally established local spinal cord neural network generating swimming in the lamprey have been performed. Populations of network interneurons were used in which cellular properties, like cell size and membrane conductance including voltage dependent ion channels were randomly distributed around experimentally obtained mean values, as were synaptic conductances (kainate/AMPA, NMDA, glycine) and delays. This population model displayed more robust burst activity over a wider frequency range than the more simple subsample model used previously, and the pattern of interneuronal activity was appropriate. The strength of the reciprocal inhibition played a very important role in the regulation of burst frequency, and just by changing the inhibitory bias the entire physiological range could be covered. At the lower frequency range of bursting the segmental excitatory interneurons provide stability as does the activation of voltage dependent NMDA receptors. Spike frequency adaptation by means of summation of afterhyperpolarization (AHP) serves as a major burst terminating factor, and at lower rates the membrane properties conferred by the NMDA receptor activation. The lateral interneurons were not of critical importance for the burst termination. They may, however, be of particular importance for inducing a rapid burst termination during for instance steering and righting reactions. Several cellular factors combine to provide a secure and stable motor pattern in the entire frequency range.     

Robustness and regularity of oscillations in neuronal populations

We study a biologically plausible but computationally simplified integrate-and-fire neuronal model. Oscillatory activity is analyzed in the networks with and without self-connections. We perform a detailed scan of four major parameters that represent the properties of neurons and synapses: connection ratio, connection strengths, post-synaptic potential decay rate and soma's potential decay rate. It is observed that networks with different properties exhibit different periods and different patterns of synchrony. We find that generally these oscillations are robust against changes of parameters, meanwhile we also locate the parametric boundaries where oscillations break down.     

Computer simulation of calcium-induced myotonia

Summary In an extensive research project on myotonia, the ionic mechanisms which are at the basis of the phenomenon of calcium-induced myotonia have been taken into consideration. A mathematical model of a muscle fibre was constructed to demonstrate the possibility that anomalous values of the membrane permeability to Calcium ions have an active part in the genesis of myotonia. This work was in great part supported by Grant of Muscular Dystrophy Assoc. Inc. and by CNR, Rome.     

Computer simulation of biological systems

The current status of mathematical models of biological systems is reviewed. Advances in supercomputer hardware allows more complex models to be constructed. The new generation of microcomputers are quite adequate for many computer simulations of biological systems. A theory of modeling is being developed to improve the relationship between the real biological system and the model. Deterministic models, stochastic models and applications of control theory and optimization methods are discussed. Examples given include models of molecular structure, of experimental techniques, and of biochemical reactions. It is recommended that experimental biologists consider the use of microcomputers to model the system under study as a part of their research program.     

Computer simulation of ribosome editing

A stochastic model of protein synthesis was modified by including the process of dissociating peptidyl-tRNA from ribosomes. To simulate ribosome editing, the probability of dissociation was assumed to be high if the peptidyl-tRNA was erroneous; that is, if it resulted from transfer of a peptide to an aminoacyl-tRNA that was inappropriate relative to the mRNA codon. The effects of amino acid starvation on protein synthesis were simulated both by increasing the probability of such erring at and by reducing the conditional probability of elongation at “hungry” codons, those whose correct amino acid was in short supply. These probabilities were varied systematically to simulate tryptophan limitation during synthesis of coat protein from bacteriophage MS2.Significant reduction, during starvation, in the synthesis of complete coat protein required large reductions in the probability of elongation at hungry codons but only small increases in the probability of erring. Enhanced dissociation of peptidyl-tRNA during starvation, followed rapidly by dissociation of ribosomes from mRNA, led to reductions in mean polysome size, a result that had been interpreted by others as due to some effect of starvation on the initiation of protein synthesis.Results from experiments by Goldman (1982) on the cell-free synthesis of MS2 coat protein during tryptophan starvation could be mimicked in detail by the computer simulations. A simple competition between correct and erroneous amino acids was sufficient to explain the tryptophan dependence of complete coat protein and internal peptide syntheses. Values for the Michaelis constants were derived from the computer simulations.     

Computer simulation of DNA supercoiling

We treat supercoiled DNA within a wormlike model with excluded volume. A modified Monte Carlo approach has been used, which allowed computer statistical-mechanical simulations of moderately and highly supercoiled DNA molecules. Even highly supercoiled molecules do not have a regular shape, though with an increase in writhing the chains look more and more like branched interwound helixes. The averaged writhing (Wr) approximately 0.7 delta Lk. The superhelical free energy F is calculated as a function of the linking number. Lk. The calculations have shown that the generally accepted quadratic dependence of F on Lk is valid for a variety of conditions, though it is by no means universal. Significant deviations from the quadratic dependence are expected at high superhelical density under ionic conditions where the effective diameter of DNA is small. The results are compared with the available experimental data.     

Computer simulation of single-file transport

A stochastic model of single-file transport was developed as the Markov process in continuous time technique. The model was constructed using an EC-1060 computer. Unidirectional fluxes were investigated and populations of channels were correlated with flux fluctuations. The profiles of channel populations were shown to have nonlinear shapes even with the transport of nonelectrolyte (the classical diffusion approach gives linear profiles). The relationship between the paired correlation function F(AB) and the concentration of transported particles was examined. The F(AB) profile was shown to become flattened (or exponential for asymmetrical cases) at high concentrations. The concentration dependence jA/jA0 ratio were analyzed, where jA is a single-file unidirectional flux, jA0 is unidirectional flux for the case of free diffusion. An interesting "stack" phenomenon was observed for abnormal time correlations of single-file fluxes.     

Computer simulation of purine metabolism

A computer model of purine metabolism, including catabolism, salvage pathways and interconversion among nucleotides, is given. Steady-state rate equations corresponding to metabolic enzymes are written based on information from the literature about their kinetic behaviour. Numerical integration of this set of equations is performed employing selected parameters taken from the literature. After stabilization of purine compound concentrations is reached, simulation of enzyme deficit and enzyme overproduction is carried out. The latter is calculated by varying specified maximum velocities in the numerical integration. A pattern of intermediate metabolite concentrations is found. These results form a basis for the comparison of normal patterns or patterns reflecting the effects of inborn errors of metabolism. The aim of this paper is to demonstrate the usefulness of this computer simulation method in complex metabolism pathways.     

Computer simulation of introductory neurophysiology

A computer-assisted learning (CAL) package, NeuroLab, developed for use by first-year university students undertaking professional programs in the health area, is described and evaluated. NeuroLab is a simulation of a laboratory, in which students are able to impale neurons to measure resting membrane potentials and subsequently undertake experiments including measuring resting membrane potentials, determining threshold potentials, measuring refractory periods, and examining effects on membrane potential through altering the membrane permeability to sodium and potassium ions. Students find the package to be a worthwhile learning experience, with 81 +/- 2.2% reporting the package increased their understanding of neuron function, and 78 +/- 2.5% expressing a desire for more CAL packages. Exposure to the package resulted in significantly higher mean scores in a multiple-choice question test on measuring neuron membrane potentials compared with those who were not exposed (mean scores out of 4 of 2.42 and 2.02, respectively, P < 0.001).     

Computer simulation of aqueous biomolecular systems

Computer simulation techniques are increasingly being used to predict structural and thermodynamic properties of large heterogeneous macromolecule and solvent assemblies. We discuss, with examples from our own studies, some problems we and others have experienced in using these techniques, which were originally devised for simple liquids. In particular, we consider the problems which arise from the large size and heterogeneity of macromolecule water systems, comparisons with experimental data and equilibrium and sampling procedures.     

Computer simulation of neurone pattern processing

Physiological simulation techniques can provide a very useful additional tool with which to explore the behaviour of neurones, especially for probing those areas that are not easily accessible to experimental monitoring techniques such as activity in the dendrites. This paper explores the information processing capabilities of a cerebral cortical pyramidal neurone using a computer simulation. The computer model simulated two important aspects of pyramidal cell behaviour: the transient distribution of membrane potential over a proportion of the apical dendritic tree of the cell, and the ability of the receptors in the neurones' dendritic spines to undergo plastic changes. The simulation of receptor behaviour modelled the ability of receptor regions to increase their sensitivity if a prior input had occurred when the spine head membrane was depolarized. The model was used to explore the response of the cell to different inputs. It underlined the need for large amounts of local activity before spinal receptors changed their sensitivity. It also demonstrated the ability of pyramidal cells to both recognize patterns of input and to associate one pattern of inputs with another. It is argued that this pattern association property could be a neuronal basis for association learning.