Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Bayesian modelling”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,603 records · Page 89Linked to original sources
PubMed2005

Population coding of self-motion: applying bayesian analysis to a population of visual interneurons in the fly.

Coding of sensory information often involves the activity of neuronal populations. We demonstrate how the accuracy of a population code depends on integration time, the size of the population, and noise correlation between the participating neurons. The population we study consists of 10 identified visual interneurons in the blowfly Calliphora vicina involved in optic flow processing. These neurons are assumed to encode the animal's head or body rotations around horizontal axes by means of graded potential changes. From electrophysiological experiments we obtain parameters for modeling the neurons' responses. From applying a Bayesian analysis on the modeled population response we draw three major conclusions. First, integration of neuronal activities over a time period of only 5 ms after response onset is sufficient to decode accurately the rotation axis. Second, noise correlation between neurons has only little impact on the population's performance. And third, although a population of only two neurons would be sufficient to encode any horizontal rotation axis, the population of 10 vertical system neurons is advantageous if the available integration time is short. For the fly, short integration times to decode neuronal responses are important when controlling rapid flight maneuvers.

Animals↗
PubMed2006

Analysis of the renal transplant waiting list in the País Valencià (Spain).

In this paper we analyse the renal transplant waiting list of the País Valencià in Spain, using Queueing theory. The customers of this queue are patients with end-stage renal failure waiting for a kidney transplant. We set up a simplified model to represent the flow of the customers through the system, and perform Bayesian inference to estimate parameters in the model. Finally, we consider several scenarios by tuning the estimations achieved and computationally simulate the behaviour of the queue under each one. The results indicate that the system could reach equilibrium at some point in the future and the model forecasts a slow decrease in the size of the waiting list in the short and middle term.

Bayes Theorem↗
PubMed1979

Twin azygotic test for the study of hereditary qualitative traits in twin populations.

Following previous formulations of a model of qualitative analysis of twin population data independent of zygosity, a new Bayesian approach has been developed. The present model can be applied to any qualitative genetic trait in twin population data, provided no specific source of variation be introduced by the twin condition, and allows not only estimation of the frequencies of mono- and dizygosity as well as the gene frequencies, but also verification of the trait's mode of inheritance.

Bayes Theorem↗
PubMed2005

Estimates of genetic parameters for Canadian Holstein female reproduction traits.

Age at first insemination, days from calving to first insemination, number of services, first-service nonreturn rate to 56 d, days from first service to conception, calving ease, stillbirth, gestation length, and calf size of Canadian Holstein cows were jointly analyzed in a linear multiple-trait model. Traits covered a wide spectrum of aspects related to reproductive performance of dairy cows. Other frequently used fertility characteristics, like days open or calving intervals, could easily be derived from the analyzed traits. Data included 94,250 records in parities 1 to 6 on 53,158 cows from Ontario and Quebec, born in the years 1997 to 2002. Reproductive characteristics of heifers and cows were treated as different but genetically correlated traits that gave 16 total traits in the analysis. Repeated records for later parities were modeled with permanent environmental effects. Direct and maternal genetic effects were included in linear models for traits related to calving performance. Bayesian methods with Gibbs sampling were used to estimate covariance components of the model and respective genetic parameters. Estimates of heritabilities for fertility traits were low, from 3% for nonreturn rate in heifers to 13% for age at first service. Interval traits had higher heritabilities than binary or categorical traits. Service sire, sire of calf, and artificial insemination technician were important (relative to additive genetic) sources of variation for nonreturn rate and traits related to calving performance. Fertility traits in heifers and older cows were not the same genetically (genetic correlations in general were smaller than 0.9). Genetic correlations (both direct and maternal) among traits indicated that different traits measured different aspects of reproductive performance of a dairy cow. These traits could be used jointly in a fertility index to allow for selection for better fertility of dairy cattle.

Animals↗
PubMed2006

A structural equation model for describing relationships between somatic cell score and milk yield in first-lactation dairy cows.

Relationships between production and diseases may involve recursive or simultaneous effects between traits. Four structural equation models (SEqM) for somatic cell score and milk yield, with varying specifications for the effects relating the 2 traits, were compared. Data consisted of repeated records of milk yield and somatic cell score of 33,453 first-lactation daughters of 245 Norwegian Red sires that had their first progeny test in 1991 and 1992. All models included random effects of the sire and of the cow and were fitted using the LISREL software. The Bayesian information criterion clearly favored a model with a recursive effect from somatic cell score on milk yield over the 3 other models fitted (absence of recursive effects; an effect from milk yield on somatic cell score; simultaneity of effects between the 2 traits). This provides evidence that the negative association between milk yield and somatic cell score is more likely due to an effect of infection (measured indirectly by the somatic cell score) on production than to a dilution effect. Estimates indicated that a mastitis event would reduce milk yield in the following 15 d by about 900 g/d. The estimated genetic (co)variances did not change sizably when the specification of recursive or simultaneous effects was varied. However, estimates of the phenotypic covariance were altered when a recursive effect from somatic cell score on milk yield was included in the model.

Age Factors↗
PubMed2006

Segregation analysis of a complex quantitative trait: approaches for identifying influential data points.

BACKGROUND/AIMS: Complex traits pose a particular challenge to standard methods for segregation analysis (SA), and for such traits it is difficult to assess the ability of complex SA (CSA) to approximate the true mode of inheritance. Here we use an oligogenic Bayesian Markov chain Monte Carlo method for SA (OSA) to verify results from a single-locus likelihood-based CSA for data on a quantitative measure of reading ability. METHODS: We compared the profile likelihood from CSA, maximized over the trait allele frequency, to the posterior distribution of genotype effects from OSA to explore differences in the overall parameter estimates from SA on the original phenotype data and the same data Winsorized to reduce the potential influence of three outlying data points. RESULTS: Bayesian OSA revealed two modes of inheritance, one of which coincided with the QTL model from CSA. Winsorizing abolished the model originally estimated by CSA; both CSA and OSA identified only the second OSA model. CONCLUSION: Differences between the results from the two methods alerted us to the presence of influential data points, and identified the QTL model best supported by the data. Thus, the Bayesian OSA proved a valuable tool for assessing and verifying inheritance models from CSA.

Alleles↗
PubMed2004

Calcium regulation of single ryanodine receptor channel gating analyzed using HMM/MCMC statistical methods.

Type-II ryanodine receptor channels (RYRs) play a fundamental role in intracellular Ca(2+) dynamics in heart. The processes of activation, inactivation, and regulation of these channels have been the subject of intensive research and the focus of recent debates. Typically, approaches to understand these processes involve statistical analysis of single RYRs, involving signal restoration, model estimation, and selection. These tasks are usually performed by following rather phenomenological criteria that turn models into self-fulfilling prophecies. Here, a thorough statistical treatment is applied by modeling single RYRs using aggregated hidden Markov models. Inferences are made using Bayesian statistics and stochastic search methods known as Markov chain Monte Carlo. These methods allow extension of the temporal resolution of the analysis far beyond the limits of previous approaches and provide a direct measure of the uncertainties associated with every estimation step, together with a direct assessment of why and where a particular model fails. Analyses of single RYRs at several Ca(2+) concentrations are made by considering 16 models, some of them previously reported in the literature. Results clearly show that single RYRs have Ca(2+)-dependent gating modes. Moreover, our results demonstrate that single RYRs responding to a sudden change in Ca(2+) display adaptation kinetics. Interestingly, best ranked models predict microscopic reversibility when monovalent cations are used as the main permeating species. Finally, the extended bandwidth revealed the existence of novel fast buzz-mode at low Ca(2+) concentrations.

Algorithms↗
PubMed2003

A Bayesian molecular interaction library.

We describe a library of molecular fragments designed to model and predict non-bonded interactions between atoms. We apply the Bayesian approach, whereby prior knowledge and uncertainty of the mathematical model are incorporated into the estimated model and its parameters. The molecular interaction data are strengthened by narrowing the atom classification to 14 atom types, focusing on independent molecular contacts that lie within a short cutoff distance, and symmetrizing the interaction data for the molecular fragments. Furthermore, the location of atoms in contact with a molecular fragment are modeled by Gaussian mixture densities whose maximum a posteriori estimates are obtained by applying a version of the expectation-maximization algorithm that incorporates hyperparameters for the components of the Gaussian mixtures. A routine is introduced providing the hyperparameters and the initial values of the parameters of the Gaussian mixture densities. A model selection criterion, based on the concept of a 'minimum message length' is used to automatically select the optimal complexity of a mixture model and the most suitable orientation of a reference frame for a fragment in a coordinate system. The type of atom interacting with a molecular fragment is predicted by values of the posterior probability function and the accuracy of these predictions is evaluated by comparing the predicted atom type with the actual atom type seen in crystal structures. The fact that an atom will simultaneously interact with several molecular fragments forming a cohesive network of interactions is exploited by introducing two strategies that combine the predictions of atom types given by multiple fragments. The accuracy of these combined predictions is compared with those based on an individual fragment. Exhaustive validation analyses and qualitative examples (e.g., the ligand-binding domain of glutamate receptors) demonstrate that these improvements lead to effective modeling and prediction of molecular interactions.

Algorithms↗
PubMed2003

A Bayesian method for predicting 5-fluorouracil pharmacokinetic parameters following short-term infusion in patients with colorectal cancer.

The objective of this study was to develop a population pharmacokinetic model and validate it using a Bayesian approach for predicting, a priori and a posteriori, the individual volume of distribution (V(d)) and clearance (Cl) of 5-fluorouracil (5-FU) given as short-term intravenous infusion in weekly and multiple doses. Forty-four patients were divided in group A (5-FU weekly doses) including 27 patients with nonmetastatic colorectal adenocarcinoma treated with 450 mg/m(2) of 5-FU, 1 day per week for 48 doses, plus oral levamisol (50 mg/8 h) for 3 days, every 15 days and group B (5-FU multiple doses) including 17 patients with metastatic colorectal adenocarcinoma, receiving 5-FU (425 mg/m(2)) plus intravenous folinic acid (20 mg/m(2)) over 5 consecutive days, every 4 weeks for six cycles. In both groups 5-FU was administered as a 30-60-min infusion. A total of 176 plasma concentrations were analyzed using a NONMEM program according to a linear one-compartment model. In group A, 5-FU population pharmacokinetic parameters were obtained and the covariables studied were age, gender, weight, ideal body weight, height, body surface area, creatinine clearance, and hepatic function tests. A priori and a posteriori validation of this model was carried out with plasma concentrations obtained in day 1 in group B. In group B, population pharmacokinetic parameters of 5-FU following multiple doses were estimated using scale factors to identify differences in 5-FU V(d) and Cl between days 1 and 4, and the interindividual, interoccasion, and residual variabilities studied. V(d) was 0.266 L/kg of ideal body weight and Cl was 1.21 L/h. kg of total weight following weekly doses. The plasma sample obtained at 10 min gave the best accuracy and precision predictions. When 5-FU was administered in multiple doses, the Cl of the drug in day 4 is reduced by 30.14% compared to day 1. The interoccasion variability was lower than interindividual variability for both V(d) and Cl, suggesting that it could be feasible to individualise dosage of 5-FU for subsequent cycles from data obtained in a previous one in an attempt to improve the therapeutic index of colorectal cancer treatment.

Adult↗
PubMed1995

Pharmaco-informatics: more precise drug therapy from 'multiple model' (MM) adaptive control regimens: evaluation with simulated vancomycin therapy.

A multiple model (MM) stochastic control of dosage regimens permits essentially optimal use of the information contained in either a population pharmacokinetic model or in a MM Bayesian updated parameter set to achieve and maintain selected therapeutic goals with optimal precision. The regimens are visibly more precise than those achieved using mean parameter values. Feedback has now also been incorporated into the MM software. An evaluation of MM adaptive control precision versus control achieved using population mean parameter values is presented using a real population model (Vancomycin). Further feedback control was evaluated, incorporating simulated clinical errors in the preparation and administration of doses.

Bayes Theorem↗
PubMed2007

A multicompartment vascular model for inferring baseline and functional changes in cerebral oxygen metabolism and arterial dilation.

Functional hemodynamic responses are the composite results of underlying variations in cerebral oxygen consumption and the dilation of arterial vessels after neuronal activity. The development of biophysically based models of the cerebral vasculature allows the separation of the neuro-metabolic and neuro-vascular influences on measurable hemodynamic signals such as functional magnetic resonance imaging or optical imaging. We describe a multicompartment model of the vascular and oxygen transport dynamics associated with stimulus-driven neuronal activation. Our model offers several unique features compared with previous formulations such as the ability to estimate baseline blood flow, volume, and oxygen consumption from functional data. In addition, we introduce a capillary compliance model, arterial and venous oxygen permeability, and model the dynamics of extravascular tissue oxygenation. We apply this model to multimodal optical spectroscopic and laser speckle imaging of the rat somato-sensory cortex during nine conditions of whisker stimulation. By fitting the model using a psuedo-Bayesian framework to incorporate multimodal observations, we estimate baseline blood flow to be 94 (+/-15) mL/100 g min and baseline oxygen consumption to be 6.7 (+/-1.3) mL O(2)/100 g min. We calculate parametric, linear increases in arterial dilation (R(2)=0.96) and CMRO(2) (R(2)=0.87) responses over the nine conditions. Other parameters estimated by the model include vascular transit time and volume reserve, oxygen content, saturation, diffusivity rate constants, and partial pressure of oxygen in the vascular compartments and in the extravascular tissue. Finally, we compare this model to earlier work and find that the multicompartment model more accurately describes the observed oxygenation changes when compared with a single compartment version.

Arteries↗
PubMedDate not supplied

[Cancer incidence estimation in Spain: period 1993-1996].

OBJECTIVE: To estimate the number of incident cases of cancer in Spain between 1993 and 1996. METHODS: We used data on the incidence of cancer from nine Spanish population-based cancer registries published in the monograph Cancer incidence in Five Continents, vols. VI and VII (period 1983-92). The National Institute of Statistics provided mortality data (period 1983-96). Generalized linear mixed models were used to estimate the number of incident cases. The incidence/mortality ratio was modeled. To account for heterogeneity, the providence of residence was considered as a random effect. Other factors analyzed were sex, age and period. Model parameters were estimated using a Bayesian approach with BUGS software. Estimates were valdated by comparing the observed number of cases with those predicted by the model in the regions with cancer registry data. RESULTS: The average number of incident cases per annum for all cancer sites except non-melanoma skin cancer was 78,440 for men and 55,480 for women. The most frequent neoplasm in men was lung with 15,480 cases followed by bladder with 9,445 cases and colorectal with 8,876 cases. In women the most frequent cancer was breast with 13,490 cases followed by colorectal with 8,274 cases. These absolute frequencies showed an increasing time trend for all cancers and for the most frequent sites, with the exception of stomach and uterine cervix. Internal validation of the estimates allowed calculation of a relative error smaller than 10%. IMPLICATIONS: This is the first time that the number of incident cases of cancer in Spain has been estimated with methods that account for heterogeneity. These figures show the importance of cancer as a public health problem in our community.

Adult↗
PubMed2003

Combining multiple microarray studies and modeling interstudy variation.

We have established a method for systematic integration of multiple microarray datasets. The method was applied to two different sets of cancer profiling studies. The change of gene expression in cancer was expressed as 'effect size', a standardized index measuring the magnitude of a treatment or covariate effect. The effect sizes were combined to obtain the estimate of the overall mean. The statistical significance was determined by a permutation test extended to multiple datasets. It was shown that the data integration promotes the discovery of small but consistent expression changes with increased sensitivity and reliability. The effect size methods provided the efficient modeling framework for addressing interstudy variation as well. Based on the result of homogeneity tests, a fixed effects model was adopted for one set of datasets that had been created in controlled experimental conditions. By contrast, a random effects model was shown to be appropriate for the other set of datasets that had been published by independent groups. We also developed an alternative modeling procedure based on a Bayesian approach, which would offer flexibility and robustness compared to the classical procedure.

Algorithms↗
PubMed2000

A compound poisson process for relaxing the molecular clock.

The molecular clock hypothesis remains an important conceptual and analytical tool in evolutionary biology despite the repeated observation that the clock hypothesis does not perfectly explain observed DNA sequence variation. We introduce a parametric model that relaxes the molecular clock by allowing rates to vary across lineages according to a compound Poisson process. Events of substitution rate change are placed onto a phylogenetic tree according to a Poisson process. When an event of substitution rate change occurs, the current rate of substitution is modified by a gamma-distributed random variable. Parameters of the model can be estimated using Bayesian inference. We use Markov chain Monte Carlo integration to evaluate the posterior probability distribution because the posterior probability involves high dimensional integrals and summations. Specifically, we use the Metropolis-Hastings-Green algorithm with 11 different move types to evaluate the posterior distribution. We demonstrate the method by analyzing a complete mtDNA sequence data set from 23 mammals. The model presented here has several potential advantages over other models that have been proposed to relax the clock because it is parametric and does not assume that rates change only at speciation events. This model should prove useful for estimating divergence times when substitution rates vary across lineages.

Bayes Theorem↗
PubMed2007

Bayesian analysis of paired survival data using a bivariate exponential distribution.

We consider a Bayesian analysis method of paired survival data using a bivariate exponential model proposed by Moran (1967, Biometrika 54:385-394). Important features of Moran's model include that the marginal distributions are exponential and the range of the correlation coefficient is between 0 and 1. These contrast with the popular exponential model with gamma frailty. Despite these nice properties, statistical analysis with Moran's model has been hampered by lack of a closed form likelihood function. In this paper, we introduce a latent variable to circumvent the difficulty in the Bayesian computation. We also consider a model checking procedure using the predictive Bayesian P-value.

Bayes Theorem↗
PubMed2006

Segmenting eukaryotic genomes with the Generalized Gibbs Sampler.

Eukaryotic genomes display segmental patterns of variation in various properties, including GC content and degree of evolutionary conservation. DNA segmentation algorithms are aimed at identifying statistically significant boundaries between such segments. Such algorithms may provide a means of discovering new classes of functional elements in eukaryotic genomes. This paper presents a model and an algorithm for Bayesian DNA segmentation and considers the feasibility of using it to segment whole eukaryotic genomes. The algorithm is tested on a range of simulated and real DNA sequences, and the following conclusions are drawn. Firstly, the algorithm correctly identifies non-segmented sequence, and can thus be used to reject the null hypothesis of uniformity in the property of interest. Secondly, estimates of the number and locations of change-points produced by the algorithm are robust to variations in algorithm parameters and initial starting conditions and correspond to real features in the data. Thirdly, the algorithm is successfully used to segment human chromosome 1 according to GC content, thus demonstrating the feasibility of Bayesian segmentation of eukaryotic genomes. The software described in this paper is available from the author's website (www.uq.edu.au/ approximately uqjkeith/) or upon request to the author.

Algorithms↗
PubMedDate not supplied

Probabilistic analysis of cost-effectiveness models: choosing between treatment strategies for gastroesophageal reflux disease.

When choosing between mutually exclusive treatment options, it is common to construct a cost-effectiveness frontier on the cost-effectiveness plane that represents efficient points from among the treatment choices. Treatment options internal to the frontier are considered inefficient and are excluded either by strict dominance or by appealing to the principle of extended dominance. However, when uncertainty is considered, options excluded under the baseline analysis may form part of the cost-effectiveness frontier. By adopting a Bayesian approach, where distributions for model parameters are specified, uncertainty in the decision concerning which treatment option should be implemented is addressed directly. The approach is illustrated using an example from a recently published cost-effectiveness analysis of different possible treatment strategies for gastroesophageal reflux disease. It is argued that probabilistic analyses should be encouraged because they have potential to quantify the strength of evidence in favor of particular treatment choices.

Bayes Theorem↗
PubMed2005

On the correlation between composition and site-specific evolutionary rate: implications for phylogenetic inference.

Model-based phylogenetic reconstruction methods traditionally assume homogeneity of nucleotide frequencies among sequence sites and lineages. Yet, heterogeneity in base composition is a characteristic shared by most biological sequences. Compositional variation in time, reflected in the compositional biases among contemporary sequences, has already been extensively studied, and its detrimental effects on phylogenetic estimates are known. However, fewer studies have focused on the effects of spatial compositional heterogeneity within genes. We show here that different sites in an alignment do not always share a unique compositional pattern, and we provide examples where nucleotide frequency trends are correlated with the site-specific rate of evolution in RNA genes. Spatial compositional heterogeneity is shown to affect the estimation of evolutionary parameters. With standard phylogenetic methods, estimates of equilibrium frequencies are found to be biased towards the composition observed at fast-evolving sites. Conversely, the ancestral composition estimates of some time-heterogeneous but spatially homogeneous methods are found to be biased towards frequencies observed at invariant and slow-evolving sites. The latter finding challenges the result of a previous study arguing against a hyperthermophilic last universal ancestor from the low apparent G + C content of its rRNA sequences. We propose a new model to account for compositional variation across sites. A Gaussian process prior is used to allow for a smooth change in composition with evolutionary rate. The model has been implemented in the phylogenetic inference software PHASE, and Bayesian methods can be used to obtain the model parameters. The results suggest that this model can accurately capture the observed trends in present-day RNA sequences.

Evolution, Molecular↗