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Results for “Monte Carlo Method”

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PubMed2003

Summary of Group 8: Development and extension of linkage methods.

The diverse contributions to Group 8 focus on the development and extension of linkage methods, and share themes that are organized around approaches to analysis. The themes discussed include issues of the accuracy of estimates of marker identity-by-descent (IBD) information, the influence of such IBD information on linkage detection, and methods for dealing with genetic heterogeneity and multiple testing. In addition, challenges were identified and solutions were offered for coping with some of the common problems of complex trait analysis, including trait model selection and computational compromises. Analytic approaches based on Bayesian and Monte Carlo methods were prominent, and provided optimistic results.

Bayes Theorem↗

PubMed1989

[A procedure for determining the dose distribution behind block shields. I. A computational method of determining the scatter distribution of a 60Co pencil beam].

The energy dose distribution of a photon pencil beam ray for photons with the primary energy of 1.25 MeV is determined using the Monte-Carlo-method. The found energy dose distribution underlies the calculation of spreading additive-air-ratio for extended 60Co-irradiation fields. The spreading additive-air-ratios, found by the model, show good correspondence with known values from literature.

Cobalt Radioisotopes↗

PubMed1999

Analysis of PBPK models for risk characterization.

Adoption of a Bayesian framework for risk characterization permits the seamless integration of different kinds of information available in order to choose and parameterize risk models. It also becomes easy to disentangle uncertainty from variability, through hierarchical statistical modeling. Appropriate numerical techniques can be found, for example, in the recently developed arsenal of Markov chain, Monte Carlo simulations. The developments in this area can actually be viewed as extensions of the traditional or standard Monte Carlo methods for uncertainty analysis. Following a brief review of the techniques, examples of Bayesian analyses of physiologically-based pharmacokinetic models are presented for tetrachloroethylene and dichloromethane. The discussion touches on some open problems and perspectives for the proposed methods.

Bayes Theorem↗

PubMed2001

Waiting times to appearance and dominance of advantageous mutants: estimation based on the likelihood.

The germinal center reaction (GCR) of vertebrate immunity provides a remarkable example of evolutionary succession, in which an advantageous phenotype arises as a spontaneous mutation from the parental type and eventually displaces the parental type altogether. In the case of the immune response to the hapten (4-hydroxy-3-nitrophenyl)acetyl (NP), as with several other designed immunogens, the process is dominated by a single key mutation, which greatly simplifies the modeling of and analysis of data. We developed a two-stage model of this process in which the primary stage represents the appearance and establishment of the mutant population as a stochastic process while the second stage represents the growth and dominance of the clone as a deterministic process, conditional on its time of establishment from stage one. We applied this model to the analysis of population samples from several germinal center (GC) reactions and used maximum-likelihood methods to estimate the waiting times to arrival and to dominance of the mutant clone. We determined the sampling properties of the maximum-likelihood estimates using Monte Carlo methods and compared them to their asymptotic distributions. The methods we present here are well-suited for use in the analysis of other systems, such as tumor growth and the experimental evolution of bacteria.

Animals↗

PubMed1999

Method revealing latent periodicity of the nucleotide sequences modified for a case of small samples.

An earlier reported method for revealing latent periodicity of the nucleotide sequences has been considerably modified in a case of small samples, by applying a Monte Carlo method. This improved method has been used to search for the latent periodicity of some nucleotide sequences of the EMBL data bank. The existence of the nucleotide sequences' latent periodicity has been shown for some genes. The results obtained have implied that periodicity of gene structure is projected onto the periodicity of primary amino acid sequences and, further, onto spatial protein conformation. Even though the periodic structure of gene sequences has been eroded, it is still retained in primary and/or spatial structures of corresponding proteins. Furthermore, in a few cases the study of genes' periodicity has suggested their possible evolutionary origin by multifold duplications of some gene's fragments.

Base Sequence↗

PubMed2006

[Three-dimensional dose calculation of 153Sm-EDTMP in treating bone metastasis--comparison of Monte Carlo and S value calculation methods].

BACKGROUND & OBJECTIVE: Three-dimensional (3D) dose calculation of radionuclide therapy for specified patients is a research interest in nuclear medicine, of which the main methods include S value calculation method, dose point kernel calculation method, and Monte Carlo (MC) simulation method. This study was to compare 3D absorbed dose calculation of 153Sm-EDTMP in treating a specified patient with bone metastasis between MC and S value methods. METHODS: A 3D dose calculation program was built based on the MC program EGS4, and the S value of nuclide 153Sm was calculated. For the specified patient with bone metastasis, 153Sm activity in excreted urine was measured at 0, 0.5, 2, 3.5, 5 and 6 h after injection of 153Sm-EDTMP. The accumulative activity is calculated by fitting measurement data. Based on the fusion SPECT/CT images of the patient, 3D absorbed dose is calculated by MC and S value methods. RESULTS: The iso-dose distribution curves of MC and S value calculation results were similar, and the dose was mainly collected in the bone. According to the 2 methods, the maximum doses were 3.92 Gy and 3.71 Gy with a difference of 5%. On the dose-volume histogram of the calculation volume, D10 (the highest dose of the 10% volume) were 2.14 Gy and 2.00 Gy with a difference of 7%; D20 (the highest dose of the 20% volume) were 0.58 Gy and 0.51 Gy with a difference of 14%. In general, the data of S value calculation were smaller than the data of MC calculation. CONCLUSIONS: MC and S value could be used to calculate the 3D dose of radionuclide therapy based on nuclear medical image. S value is a fast and simple method for the dose evaluation although the error of the calculation is relatively bigger.

Bone Neoplasms↗

PubMed2002

Comparison of two random-effects methods of meta-analysis.

Two studies compared the Schmidt-Hunter method of meta-analysis (J. E. Hunter & F. L. Schmidt, 1990) with the method described by L. V. Hedges and J. L. Vevea (1998). Study 1 evaluated estimates of rho, sigmarho, and resulting credibility intervals for both models through Monte Carlo methods. Results showed slight differences between the 2 methods. In Study 2, a reanalysis of published meta-analyses using both methods with several artifact distributions showed that although both choice of technique and type of correction could matter, the technique of meta-analysis used is less influential on the study outcome than is the choice of artifact correction.

Bias↗

PubMed2000

Bayesian analysis of discrete survival data with a hidden Markov chain.

This paper considers the discrete survival data from a Bayesian point of view. A sequence of the baseline hazard functions, which plays an important role in the discrete hazard function, is modeled with a hidden Markov chain. It is explained how the resultant model is implemented via Markov chain Monte Carlo methods. The model is illustrated by an application of real data.

Bayes Theorem↗

PubMed2001

Computer simulations for biological aging and sexual reproduction.

The sexual version of the Penna model of biological aging, simulated since 1996, is compared here with alternative forms of reproduction as well as with models not involving aging. In particular we want to check how sexual forms of life could have evolved and won over earlier asexual forms hundreds of million years ago. This computer model is based on the mutation-accumulation theory of aging, using bits-strings to represent the genome. Its population dynamics is studied by Monte Carlo methods.

Aging↗

PubMedDate not supplied

[Energetics of hydration of nucleic acids with various nucleotide composition].

The energetics of hydration of natural DNA of different AT/GC content and model double-helical polyribonucleotides was studied. The results obtained by a new approach, which is based on calorimetric measurements of hydration-dehydration energy of nucleic acid-water systems at different relative humidities are presented. A correlation between the dehydration energy and the nucleotide composition of native DNA was found. The energetic characteristics of systems containing deoxynucleoside monophosphates and water clusters of different dimensions were obtained by the Monte Carlo method. The results of computer simulation correlate with the experimental calorimetric data.

Calorimetry↗

PubMed1988

Image interpretation of metal shadowed specimens with the aid of Monte Carlo simulation of the shadowing process.

Rotary shadowing is investigated by means of an adapted shadowing model, which has been used for relief reconstruction of unidirectionally shadowed specimens. The metal layer geometry is calculated for a simple geometric object. In order to elucidate the metal accumulation process on the surface, a Monte Carlo simulation of shadowing is applied to synthetic reliefs and to experimental relief reconstruction data of a paracrystalline membrane. For rotary shadowed specimens, no linear relationship between local metal thickness and surface height can be established as in the unidirectional case. Low spatial frequencies of the surface relief contribute very little to the information content of the observed metal film. Contrast produced by rotary shadowed films is lower compared to unidirectionally shadowed ones. The main effects are due to the steep slopes which give rise to the considerable amount of metal viewed in the normal projection, and due to the shadow casts. A further contrast enhancing effect is self-shadowing, an artifact introduced primarily by rotating the specimen during evaporation. The Monte Carlo simulation shows that low elevation angles favor self-shadowing effects. This results in a pronounced granularity that is caused by the random incidence of the atoms and the accumulation at previously deposited atoms or grown clusters. On real surfaces, small decorating clusters can be enlarged by self-shadowing. This explains the increased decoration tendency of rotary shadowed specimens. The Monte Carlo method can be used as a means to differentiate shadowing information from these effects.

Image Processing, Computer-Assisted↗

PubMed2005

Experiment and analyses for 14 MeV neutron streaming through a dogleg duct.

There are several vacant channels for diagnosis, RF heating and so on through the shielding structure in fusion reactors. Some of them consist of dogleg ducts, through which neutrons stream in a complex manner. An experiment was conducted with the Fusion Neutronics Source (FNS) facility at JAERI to study the behaviour of neutrons in the duct and assess the reliability of calculation methods for the design of fusion reactors such as ITER. The assembly was an iron slab 180 cm in thickness with a doubly bent duct 30 x 30 cm2 in cross section. The experiment was analysed using a simple design code for radiation streaming, DUCT-III, and the Monte Carlo code MCNP. The results indicate that the simple design code is reliable enough to be used for shielding design analyses as well as the Monte Carlo method, which showed excellent agreement between calculated and measured values.

Algorithms↗

PubMed2006

Monte Carlo algorithms for Hardy-Weinberg proportions.

The Hardy-Weinberg law is among the most important principles in the study of biological systems. Given its importance, many tests have been devised to determine whether a finite population follows Hardy-Weinberg proportions. Because asymptotic tests can fail, Guo and Thompson developed an exact test; unfortunately, the Monte Carlo method they proposed to evaluate their test has a running time that grows linearly in the size of the population N. Here, we propose a new algorithm whose expected running time is linear in the size of the table produced, and completely independent of N. In practice, this new algorithm can be considerably faster than the original method.

Algorithms↗

PubMed2004

Predicting meningococcal disease outbreaks in structured populations.

Rational decision making on whether some form of intervention would be necessary to control the spread of a meningococcal epidemic is based on predictions concerning its potential natural progression. Unfortunately, reliable predictions are difficult to make during the early stages of an outbreak. A stochastic discrete time epidemic model was applied to adaptively predict the development of outbreaks of meningococcal disease in 'closed' populations such as military garrisons or boarding schools, which are further divided into subgroups called 'units'. The performance of the adaptive method was assessed by using 3 simulated epidemics representing substantially different realizations in a 'garrison' of 20 units, with 68 men in each. Predictions of the weekly number of disease cases, of the number of carriers, and of the number of new infections were computed. Simulations suggest that predictions based only on the observed numbers of disease cases are generally inaccurate. These predictions can be improved if temporal observations on asymptomatic carriers in different units are utilized together with observed time series of the disease. A sample of 15 per cent from all units can be sufficient for a major improvement if the alternative is to obtain a full sample of only some units. Exploiting fully such information requires computer intensive Markov chain Monte Carlo methods.

Disease Outbreaks↗

PubMed2006

Online updating of space-time disease surveillance models via particle filters.

Online surveillance of disease has become an important issue in public health. In particular, the space-time monitoring of disease plays an important part in any syndromic system. However, methodology for these systems is generally lacking. One approach to space-time monitoring of health data is to consider the space-time model parameters as the focus and to monitor their changes as multivariate time series (Lawson AB. Some considerations in spatial-temporal analysis of public health surveillance data. In Brookmeyer R, Stroup DF eds. Monitoring the Health of Populations. Oxford University Press, 2004; Vidal Rodeiro CL, Lawson AB. Monitoring changes in spatio-temporal maps of disease. Biometrical Journal 2006; to appear). However with complex space-time models, this becomes very time consuming. Some simplifications may be necessary and these can be made in a number of ways. In this article, the focus is on particle filters that can be used to resample the history of the process and thereby reduce computation time. This article describes a particular case of particle filters, the resample-move algorithm, proposed by Gilks and Berzuini (Gilks WR, Berzuini C. Following a moving target--Monte Carlo inference for dynamic Bayesian models. Journal of the Royal Statistical Society, Series B 2001; 63: 127-46), in the context of disease map surveillance. This is followed by an application to a real data set in which a comparison between the use of Markov chain Monte Carlo methods and the resample-move algorithm is carried out.

Algorithms↗

PubMed2002

An ensemble method for identifying regulatory circuits with special reference to the qa gene cluster of Neurospora crassa.

A chemical reaction network for the regulation of the quinic acid (qa) gene cluster of Neurospora crassa is proposed. An efficient Monte Carlo method for walking through the parameter space of possible chemical reaction networks is developed to identify an ensemble of deterministic kinetics models with rate constants consistent with RNA and protein profiling data. This method was successful in identifying a model ensemble fitting available RNA profiling data on the qa gene cluster.

Genes, Fungal↗

PubMed1998

Complexity of Monte Carlo and deterministic dose-calculation methods.

Grid-based deterministic dose-calculation methods for radiotherapy planning require the use of six-dimensional phase space grids. Because of the large number of phase space dimensions, a growing number of medical physicists appear to believe that grid-based deterministic dose-calculation methods are not competitive with Monte Carlo methods. We argue that this conclusion may be premature. Our results do suggest, however, that finite difference or finite element schemes with orders of accuracy greater than one will probably be needed if such methods are to compete well with Monte Carlo methods for dose calculations.

Biometry↗

PubMed2002

[Modeling light distribution in nasal tissue structures].

There are different applications in the field of optical diagnostics in which the theories explaining the light transport in tissue do not lead to simple solutions for complicate geometric conditions. In these cases the Monte Carlo method provides a powerful tool to solve this problem statistically. In order to simulate the light transport in the nasal region a model was created which includes the structure depending on the swelling of the mucous membrane as well as the Monte Carlo model. Using this model it is possible to evaluate the measured values qualitatively. However, due to the long distance between light source and detector the statistical error becomes a major problem for reliable statements.

Humans↗