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Results for “deterministic processes”

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PubMed2025

Pedigree Painter (pepa): a tool for the visualization of genetic inheritance in chromosomal context.

MOTIVATION: Data visualization is increasingly important in genomics, enabling researchers to uncover inheritance and recombination patterns across generations. While most existing tools focus on ancestry prediction, they lack functionality for analyzing known ancestries in controlled settings, such as determining parental contributions to offspring genomes. To address this gap, I developed pepa, a lightweight, deterministic, modular tool that visualizes and quantifies genomic inheritance, designed for beginner and advanced users. RESULTS: pepa is a program for processing VCF files, assigning ancestries to homozygous SNPs, and clustering them into biologically meaningful regions. It generates human-readable comparison tables and visualizes inheritance patterns with chromosome paintings through R. Tested on fission yeast, pepa revealed non-uniform recombination patterns, with chromosomes largely inherited from one parent and seemingly random recombination. Quantitative analyses showed differences in parental contributions at the nucleotide and gene levels, with some offspring inheriting similar percentages from parents. However, the painted chromosomes revealed that even offspring with similar percentages from one parent rarely inherit the same genomic region, highlighting the importance of this tool in drawing biologically meaningful insights. pepa provides an accessible and powerful solution for analyzing genomic inheritance, bridging experimental and computational biology. Its modular design and minimal dependencies allow adaptation to diverse organisms, facilitating intuitive visualization and quantitative insights into recombination dynamics.

Pedigree↗
PubMed1980

Population genetic basis of the evolutionary change.

Short introduction is given to population genetic treatment of the evolutionary change. The evolutionary change in the population is based upon the appearance (by mutation or immigration) of new genetic information. The proportion of this new information may increase or decrease by selection and/or random processes. The aid of population genetics is to formulate models in order to understand the essence of the evolutionary change. Some simple deterministic and stochastic single-locus models are quoted from elementary population genetic theory.

Biological Evolution↗
PubMed1986

Optimal harvesting of a logistic population in an environment with stochastic jumps.

Dynamic programming is employed to examine the effects of large, sudden changes in population size on the optimal harvest strategy of an exploited resource population. These changes are either adverse or favorable and are assumed to occur at times of events of a Poisson process. The amplitude of these jumps is assumed to be density independent. In between the jumps the population is assumed to grow logistically. The Bellman equation for the optimal discounted present value is solved numerically and the optimal feedback control computed for the random jump model. The results are compared to the corresponding results for the quasi-deterministic approximation. In addition, the sensitivity of the results to the discount rate, the total jump rate and the quadratic cost factor is investigated. The optimal results are most strongly sensitive to the rate of stochastic jumps and to the quadratic cost factor to a lesser extent when the deterministic bioeconomic parameters are taken from aggregate antarctic pelagic whaling data.

Animals↗
PubMed1990

A stochastic analysis of the repair of radiation-induced DNA double-strand breaks.

A three-state stochastic model is described for the repair of radiation-induced double-strand breaks (DSBs) in DNA. If irradiated, a site or region in DNA is assumed to be in a potentially damaged state; this site may either become permanently damaged or be repaired after a certain period of time. The result of the analysis of the available experimental data reveals that the present two-parameter model is capable of interpreting the rapid decrease in the number of DSBs in the initial period, which cannot be predicted by previously proposed models. The stochastic analysis yields not only the temporal variation of the mean of the number of DSBs but also its variance, and therefore is a generalization of the conventional deterministic models.

DNA↗
PubMed1976

A cybernetic approach to the origin of the genetic coding mechanism. I. Methodological principles.

It is postulated that some quasi-deterministic code features (universality, connectedness, systematic degeneracy, symmetry, regularity and so on) resulted from unique (and therefore universal) relization of a stochastic evolutionary process. The evolution of real genetic systems should satisfy the principle of succession; that is, loss of a feature that is necessary for a genetic system means death to its carrier. The hypothesis of unique key coincidence is proposed which indicates the mechanisms of arising of the primary correspondence between the linear structures of polynucleotides and polypeptides. If the collinear coincidence was to appear in the key positions of pra-protein with, at least, some of the primitive properties of the pra-amino-acyl-t-RNA-synthetase required for the accelerated recognition of the key positions of pra-template, the positive feed-back mechanism in the system would be most short-circuited so that the repetitive reproduction of pra-synthetase would be much accelerated.

Amino Acyl-tRNA Synthetases↗
PubMed1994

Genetic information and ecosystem health: arguments for the application of chaos theory to identify boundary conditions for ecosystem management.

To meet the demands for goods and services of an exponentially growing human population, global ecosystems will come under increasing human management. The hallmark of successful ecosystem management will be long-term ecosystem stability. Ecosystems and the genetic information and processes which underlie interactions of organisms with the environment in populations and communities exhibit behaviors which have nonlinear characteristics. Nonlinear mathematical formulations describing deterministic chaos have been used successfully to model such systems in physics, chemistry, economics, physiology, and epidemiology. This approach can be extended to ecotoxicology and can be used to investigate how changes in genetic information determine the behavior of populations and communities. This article seeks to provide the arguments for such an approach and to give initial direction to the search for the boundary conditions within which lies ecosystem stability. The identification of a theoretical framework for ecotoxicology and the parameters which drive the underlying model is a critical component in the formulation of a prioritized research agenda and appropriate ecosystem management policy and regulation.

Ecosystem↗
PubMed1991

An evaluation of sensory noise in the human visual system.

It is assumed that the activity of a visual channel may be represented as V(t) = g(t) + xi(t), where g(t) is the deterministic response of the channel due to the presentation of a stimulus and xi(t) is the trajectory of a wide-sense stationary Gauss process. The stimulus is detected if the event (V(t) greater than S for at least one t epsilon[0, T]) occurs. Two approximations for the probability of this event are proposed, and it is demonstrated how they may be employed to estimate (i) the value of the second spectral moment lambda 2 of the noise process xi t, where lambda 2 reflects the speed of the fluctuations of the trajectories xi(t), and (ii) the value of the internal threshold S. The commonly made assumption of peak--detection is shown to serve as a very good first approximation in particular if the channel is of transient type or--in case of detection by a channel of sustained type--if the stimulus durations are not too long.

Humans↗
PubMed1991

[Synergetics--a possible hypothetical approach to better understanding of pathologic processes].

Modern understanding of the human disease cannot be reduced only on the disturbed biological processes of the living organism. Disease as the consequence of the disorders of a complex system needs in the same sense a complex view. It is necessary to take in consideration the theory of systems, the concept of layers and the idea of the deterministic chaos. A helpful clamp to coordinate these different views seems to be the synergetics, the teaching of the cooperation in complex systems. Synergetics investigate the mechanisms of the self-organization, too. The self-organization is of great significance in the phylogenetic and ontogenetic morphogenesis. Especially all diseases which are characterized by the disorders in the differentiation the processes forming "Gestalten" are to understand as processes of the disturbed self-organization. These refers the malformations, the malignant tumours and the chronic diseases. Self-organization being a system-internal mechanism is to understand as a process which determines the behaviour of complex organized living systems in confrontation with their environment.

Biological Evolution↗
PubMedDate not supplied

Random drug excess.

If a patient is treated in a hospital, drugs are administered at 'deterministic', known times. However, if the patient is not supervised the times of drug intake may be less 'deterministic' and less well known. It seems therefore worthwhile to make a theoretical experiment in which one assumes that drugs are applied according to a random process. In the present article it is proposed that shot noise models could be used to represent concentration curves in such situations. By means of Monte Carlo methods different measures of random drug excess are described. An included program may encourage readers to consider these methods and to perform computer experiments.

Drug Administration Schedule↗
PubMed1989

[Dynamic computer models of xenobiotics].

On the basis of the physical substance transport in the circulatory system a dynamic pharmacokinetic model is developed. The method describes the behaviour of xenobiotics and their metabolites by direct simulation of the transport and the distribution in the bloodstream and tissues by suitable algorithms in discrete steps. The cardiovascular system represented by a 2-(or 3-)dimensional array is connected to other kinetic relevant components, likewise represented by arrays of suitable dimensions and acting as transport-, storage, distribution-, exchange- and reaction areas. (Bio-)chemical transformation is accounted for by introducing an identical new set of arrays, one set for each metabolite. The overall characterisation of a model needs a great variety of coefficients, thus creating a highly flexible tool for the study of kinetic processes. The result being a time- and position-dependent discrete distribution of substance reflects the heterogeneity and complexity of a real biological system. The compartmental (deterministic and stochastic) models are of course a subset of the DVM.

Algorithms↗
PubMedDate not supplied

Statistical methods of detection of a periodic phenomenon in a short series. Example of application: a density series of nematode eggs - II.

Using the example of the statistical treatment of a series of density of nematode eggs, we give here a survey of the main methods of detection of a periodic phenomenon in a short series. The purpose of these methods, which may be ranked into 3 groups: smoothing methods, regression methods, autocorrelations, is to study non random characteristics of the process. We detected in this series and estimated a rhythm of period 12 h. We concluded that the regression methods are the most resourceful for detecting a deterministic periodic phenomenon but that it is useful to confirm the results using the other methods.

Animals↗
PubMed1989

Saltatory transitions are a naturally occurring property of evolving systems.

On the basis of paleological evidence, it has been suggested that biological evolution need not necessarily be characterized by gradual change. Rather, evolutionary history may display saltatory periods of rapid speciation alternating with periods of relative quiescence, the whole dynamic being called punctuated equilibria. The empirical evidence that has been presented in support of this hypothesis has been the object of a vigorous dispute. Mathematical investigations of complex models of biological evolution that contain random elements have demonstrated that these systems can display saltatory behavior. In this paper we address a more abstract question: can saltations occur in the evolution of very simple, deterministic mathematical systems that function in a constant environment? The answer appears to be yes. Saltations appear as a natural dynamical behavior in the evolution of simplistic information processing networks. We stress that these networks do not constitute a model of biological evolution. However, the appearance of saltations in such simple systems suggests that their appearance in a process as complex as biological evolution is not surprising.

Animals↗
PubMed1992

Extending the stochastic two-stage model of carcinogenesis to include self-regulation of the nonmalignant cell population.

One of the challenges of introducing greater biological realism into stochastic models of cancer induction is to find a way to represent the homeostatic control of the normal cell population over its own size without complicating the analysis too much to obtain useful results. Current two-stage models of carcinogenesis typically ignore homeostatic control. Instead, a deterministic growth path is specified for the population of "normal" cells, while the population of "initiated" cells is assumed to grow randomly according to a birth-death process with random immigrations from the normal population. This paper introduces a simple model of homeostatically controlled cell division for mature tissues, in which the size of the nonmalignant population remains essentially constant over time. Growth of the nonmalignant cell population (normal and initiated cells) is restricted by allowing cells to divide only to fill the "openings" left by cells that die or differentiate, thus maintaining the constant size of the nonmalignant cell population. The fundamental technical insight from this model is that random walks, rather than birth-and-death processes, are the appropriate stochastic processes for describing the kinetics of the initiated cell population. Qualitative and analytic results are presented, drawn from the mathematical theories of random walks and diffusion processes, that describe the probability of spontaneous extinction and the size distribution of surviving initiated populations when the death/differentiation rates of normal and initiated cells are known. The constraint that the nonmalignant population size must remain approximately constant leads to much simpler analytic formulas and approximations, flowing directly from random walk theory, than in previous birth-death models.(ABSTRACT TRUNCATED AT 250 WORDS)

Cell Death↗
PubMed1985

Decision making under uncertainty: a comparison of simple scalability, fixed-sample, and sequential-sampling models.

The purpose of this article is to investigate the learning and memory processes involved in decision making under uncertainty. In two different experiments, subjects were given a choice between a certain alternative that produced a single known payoff and an uncertain alternative that produced a normal distribution of payoffs. Initially this distribution was unknown, and in the first experiment it was learned through feedback from past decisions, whereas in the second experiment it was learned by observing sample outcomes. In the first experiment, a response deadline was used to limit the amount of time available for making a decision. In the second experiment, an observation cost was used to limit the number of samples that could be purchased. The mean and variance of the uncertain alternative and the value of the certain alternative were factorially manipulated to study their joint effects on choice probability, choice response time (Experiment 1), and number of observations purchased (Experiment 2). Algebraic-deterministic theories developed for decision making with simple gambles fail to explain the present results. Two new models are developed and tested--fixed- and sequential-sampling models--that attempt to describe the learning and memory processes involved in decision making under uncertainty.

Adult↗
PubMed1977

A mechanistic model of the aerobic growth of Saccharomyces cerevisiae.

A two-stage deterministic model of the growth of Saccharomyces cerevisiae is presented. The cell cycle of this organism was used to suggest the basic model structure. The model represents the preparatory processes of substrate uptake and conversion separately from replication and division. The regulation of the fraction of the culture devoted to each of these broad areas of metabolism, and the overall growth rate, is related to the nature and availability of the energy substrate. The simulation of respiration and glycolysis is achieved by including two alternative energy producing pathways. The regulation of these pathways is described in terms of the postulated primary regulation of the proportion of the culture required for substrate uptake and conversion, and the overall kinetic constants for each pathway. This regulation is dictated primarily by the growth rate rather than the nature or concentration of the energy substrate. The model successfully describes both batch and continuous growth of S. cerevisiae under conditons of glucose limitation and oxygen excess. A preliminary assessment indicates that adjustment of the relevant parameters will allow the model to describe the growth of S. cerevisiae on other sugars and under oxygen limitation. Similarly the model could be expected to describe the growth characteristics of other yeast species.

Aerobiosis↗
PubMed1990

[The EEG and thinking].

The on-going EEG contains information on thinking strategies during cognitive and creative tasks and during listening to music. This was demonstrated by a method taking use of the fact that both the amount of local current production and the degree of electric coupling of brain regions is characteristically changed by mental tasks. In groups of volunteers the significant changes of absolute power and coherence caused by different mental tasks are computed and entered into schematic brain maps (EEG probability maps). The results indicate the existence of general brain strategies even in mental activities as specific as those referred to above. Moreover, several relationships between EEG, psychological test scores, degree of special education and intelligence were found. Studies with extreme value validation according to intelligence and creativity test scores yielded significant differences between the groups of the best and the poorest performers during a creative task in the EEG. The EEG thus can be conceived of as deterministic chaos with different degrees of organization according to its information content. In this context, the question arises as to a possible function of the EEG for the optimization of thinking processes.

Cognition↗
PubMed1991

Dynamic population epidemic models.

Most multipopulation epidemic models are of the contact distribution type, in which the locations of successive contacts are chosen independently from appropriate contact distributions. This paper is concerned with an alternative class of models, termed dynamic population epidemic models, in which infectives move among the populations and can infect only within their current population. Both the stochastic and deterministic versions of such models are considered. Their threshold behavior is analyzed in some depth, as are their final outcomes. Velocities of spread of infection are considered when the populations have a spatial structure. A criterion for finding the equivalent contact distribution epidemic for any given dynamic population epidemic is provided, enabling comparisons to be made for the velocities and final outcomes displayed by the two classes of models. The relationship between deterministic and stochastic epidemic models is also discussed briefly.

Disease Outbreaks↗