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At least 343 records · Page 19Linked to original sources

PubMed2005

Selection of optimal oligonucleotide probes for microarrays using multiple criteria, global alignment and parameter estimation.

The oligonucleotide specificity for microarray hybridization can be predicted by its sequence identity to non-targets, continuous stretch to non-targets, and/or binding free energy to non-targets. Most currently available programs only use one or two of these criteria, which may choose 'false' specific oligonucleotides or miss 'true' optimal probes in a considerable proportion. We have developed a software tool, called CommOligo using new algorithms and all three criteria for selection of optimal oligonucleotide probes. A series of filters, including sequence identity, free energy, continuous stretch, GC content, self-annealing, distance to the 3'-untranslated region (3'-UTR) and melting temperature (T(m)), are used to check each possible oligonucleotide. A sequence identity is calculated based on gapped global alignments. A traversal algorithm is used to generate alignments for free energy calculation. The optimal T(m) interval is determined based on probe candidates that have passed all other filters. Final probes are picked using a combination of user-configurable piece-wise linear functions and an iterative process. The thresholds for identity, stretch and free energy filters are automatically determined from experimental data by an accessory software tool, CommOligo_PE (CommOligo Parameter Estimator). The program was used to design probes for both whole-genome and highly homologous sequence data. CommOligo and CommOligo_PE are freely available to academic users upon request.

Algorithms↗

PubMed1985

Parameter estimation and sensitivity analysis of a nonlinearly elastic static lung model.

A model for the static pressure-volume behavior of the lung parenchyma based on a pseudo-elastic strain energy function was tested. Values of the model parameters and their variances were estimated by an optimal least-squares fit of the model-predicted pressures to the corresponding data from excised, saline-filled dog lungs. Although the model fit data from twelve lungs very well, the coefficients of variation for parameter values differed greatly. To analyze the sensitivity of the model output to its parameters, we examined an approximate Hessian, H, of the least-squares objective function. Based on the determinant and condition number of H, we were able to set formal criteria for choosing the most reliable estimates of parameter values and their variances. This in turn allowed us to specify a normal range of parameter values for these dog lungs. Thus the model not only describes static pressure-volume data, but also uses the data to estimate parameters from a fundamental constitutive equation. The optimal parameter estimation and sensitivity analysis developed here can be widely applied to other physiologic systems.

Animals↗

PubMed2001

Genetic parameter estimates for pre-weaning weight traits in Dorper sheep.

Genetic parameters were estimated for birth-, 42-day, and 100-day (weaning) weight in the Dorper flock of the Glen Agricultural Institute in South Africa. Direct heritability estimates of 0.11, 0.28 and 0.20 and maternal heritability estimates of 0.10, 0.10 and 0.10 were obtained for body weights at birth, 42 and 100 days, respectively. The corresponding genetic correlation estimates between direct and maternal effects were 0.35, -0.63 and -0.58, respectively. Both direct and maternal genetic correlation estimates among the traits were of moderate to high magnitude and positive. It is concluded that the traits can be improved by selection with no serious antagonisms among traits studied.

Journal Article↗

PubMed2005

Genetic and phenotypic parameter estimates of total and partial lifetime traits for dairy ewes.

A data file with 11,547 lactations for 2602 Spanish Churra ewes, daughters of 100 sires and 2179 dams, was used to estimate genetic and phenotypic parameters of total and partial lifetime traits with a multiple-trait animal model using REML. These ewes first lambed between 1992 and 1998 and belonged to 27 flocks enrolled in the nucleus scheme of the breed. The study took into account 4 life span traits, 2 productive traits, and 2 reproductive traits. Lifetime revenues from milk and lambs were calculated. Daily traits for both milk and revenues of lifetime, productive life, and useful life were also calculated. Partial lifetime traits were considered for the first 3 parities. The model included flock and birth year within flock as fixed effects and animal as a random effect. Both fixed effects contributed significantly to variation of all total lifetime traits. Milk production level was included in the model as a covariable to adjust life span traits. Heritability estimates for life span traits were low (0.02 to 0.06), indicating few possibilities for direct genetic selection. Genetic and phenotypic correlations among life span traits averaged 0.90 and 0.87, respectively. Heritabilities for daily milk and revenue traits were always higher than those for their corresponding lifetime traits. Heritability for milk yield per day of useful life was 0.25 (+/-0.04). Heritability estimates for partial lifetime performance traits increased notably when more parities were included (from the first parity to the first 3 parities). Their genetic and phenotypic correlations with total lifetime traits also increased gradually when more information was considered. These results indicate that possibilities for early genetic selection for some lifetime traits are not totally excluded.

Animals↗

PubMed1989

Sensitivity analysis of the systemic circulation with a view to computer simulation and parameter estimation.

A sensitivity analysis study has been performed on a seven-parameter model of the systemic vascular bed in order to obtain structure reductions appropriate for simulation and estimation. This analysis considers separately the systolic and diastolic transfer functions between arterial and venous pressures in order to divide a non-linear problem in two distinct linear problems. The results obtained refer to nominal parameter values corresponding to normal circulatory conditions in man and supply guide-lines for an application-oriented selection of reduced models. Simple resistance-compliance models are preferred because the inertial effects appear to have only slight influence. In particular, the choice of a five-parameter model seems to be convenient for simulation purposes. An additional structure reduction is suggested to reach reliable results in parameter estimation problems. The resulting model is characterized by three elements: peripheral resistance, arterial compliance and venous compliance.

Blood Circulation↗

PubMed1985

Parameter estimates for a QALY utility model.

This paper discusses a utility model for quality adjusted life years (QALY). According to this model, the utility of Y years of survival in health state Q is bYrH(Q), where b is a scaling constant and r and H(Q) are parameters. The parameter r is shown to be interpretable as a representation of a patient's risk attitude with respect to survival duration. The parameter H(Q) represents the proportionate reduction in the utility of survival when health state Q prevails. Methods are described for estimating these parameters from the results of an individual patient utility assessment. Results are then reported for empirical estimation of parameters r and H(Q) from the preference judgments of a sample of 46 coronary artery disease patients. In this empirical study, health state Q takes on two values--survival with angina pectoris and survival free from angina pectoris. Estimated values of parameters r and H(Q) are discussed in relation to the decision analysis of coronary artery bypass graft surgery. Finally, it is argued that the model deserves consideration as a medical utility model, despite some preliminary evidence that assumptions of the model are descriptively false, because it provides a simple representation of the utility of survival duration and health quality. These aspects of health outcomes are known to be critically important in the expected utility analysis of health decisions.

Angina Pectoris↗

PubMed1995

Misclassification of a prognostic dichotomous variable: sample size and parameter estimate adjustment.

Under general conditions, Lagakos showed that for an explanatory variable observed with error, the asymptotic relative efficiency (ARE) when using the observed rather than the true values in linear models, logistic models and proportional hazards models for survival is the square of the correlation between the true and observed variables. The result is useful for sample size adjustment when this correlation is estimable. Often, one cannot observe correct values of the explanatory variable under any circumstances. We show, however, that under the models considered by Lagakos for a dichotomous explanatory variable, the ARE equals the kappa statistic in a read-reread protocol. Consequently, one need not know 'truth' in this situation to estimate the ARE and to adjust sample size to maintain desired power; divide the estimated sample size obtained with the assumption of no measurement error by the consistent estimate of the kappa statistic (which is unlikely to be zero or negative). We then develop heuristically an adjusted estimate of the beta parameter in a proportional hazards survival model. The work was motivated by analyses of the Childhood Brain Tumour Consortium database. Examples from this database illustrate the method.

Brain Neoplasms↗

PubMed1997

Multiple Parameter Estimation in an Adaptive Psychometric Method: MUEST, an Extension of the QUEST Method

An extension of the so-called QUEST method of Watson and Pelli (1979, 1983) is proposed. In contrast to the traditional QUEST method, the new method, the MUEST method, offers the possibility of simultaneously estimating more than one parameter of a parametric representation of the psychometric function. Knowledge about more parameters gives a higher guarantee of obtaining correct threshold values. The basic extension itself is analytically quite modest and can be explained in a few sentences. However, the involved additional techniques, like the placing of stimulus levels, require a more extensive description, which is presented here. Copyright 1997 Academic Press. Copyright 1997 Academic Press

Journal Article↗

PubMed1992

A relation between the Akaike criterion and reliability of parameter estimates, with application to nonlinear autoregressive modelling of ictal EEG.

The Akaike minimum information criterion provides a means to determine the appropriate number of lags in a linear autoregressive model of a time series. We show that the Akaike criterion is closely related to the reliability estimates of successively determined parameters of a linear autoregressive (LAR) model. A similar criterion may be applied to determine whether the addition of a nonlinear term to an LAR model provides a statistically significant improvement in the description of the time series. As an example, we use this method to identify quadratic contributions to a nonlinear autoregressive characterization of a typical 3/s spike and wave seizure discharge.

Data Interpretation, Statistical↗

PubMed2000

Nonlinear regression in parameter estimation from polarographic signals

In this work we describe a detailed treatment of polarographic data curves, including error analysis, by means of nonlinear least-squares in its standard form (or resorting to the errors in variables model). Error estimates for the related parameters are additionally verified by Monte-Carlo simulation and resampling techniques.

Journal Article↗

PubMed1998

A Metropolis Monte Carlo implementation of bayesian time-domain parameter estimation: application to coupling constant estimation from antiphase multiplets.

The Bayesian perspective on statistics asserts that it makes sense to speak of a probability of an unknown parameter having a particular value. Given a model for an observed, noise-corrupted signal, we may use Bayesian methods to estimate not only the most probable value for each parameter but also their distributions. We present an implementation of the Bayesian parameter estimation formalism developed by G. L. Bretthorst (1990, J. Magn. Reson. 88, 533) using the Metropolis Monte Carlo sampling algorithm to perform the parameter and error estimation. This allows us to make very few assumptions about the shape of the posterior distribution, and allows the easy introduction of prior knowledge about constraints among the model parameters. We present evidence that the error estimates obtained in this manner are realistic, and that the Monte Carlo approach can be used to accurately estimate coupling constants from antiphase doublets in synthetic and experimental data.

Algorithms↗

PubMedDate not supplied

Arterial windkessel parameter estimation: a new time-domain method.

We developed and validated a new, more accurate, and easily applied method for calculating the parameters of the three-element Windkessel to quantitate arterial properties and to investigate ventriculoarterial coupling. This method is based on integrating the governing differential equation of the three-element Windkessel and solving for arterial compliance. It accounts for the interaction between characteristic impedance and compliance, an important phenomenon that has been ignored by previously implemented methods. The new integral method was compared with four previously published methods as well as a new independent linear least-squares analysis, using ascending aortic micromanometric and volumetric flow measurements from eight dogs. The parameters calculated by the new integral method were found to be significantly different from those obtained by the previous methods but did not differ significantly from maximum likelihood estimators obtained by a linear least-squares approach. To assess the accuracy of parameter estimation, pressure and flow waveforms were reconstructed in the time domain by numerically solving the governing differential equation of the three-element Windkessel model. Standard deviations of reconstructed waveforms from the experimental ensemble-averaged waveforms, which solely reflect the relative accuracy of the Windkessel parameters given by the various methods, were calculated. The new integral method invariably yielded the smallest error. These results demonstrate the improved accuracy of our new integral method in estimating arterial parameters of the three-element Windkessel.

Animals↗

PubMed2006

Parameter estimate of signal transduction pathways.

BACKGROUND: The "inverse" problem is related to the determination of unknown causes on the bases of the observation of their effects. This is the opposite of the corresponding "direct" problem, which relates to the prediction of the effects generated by a complete description of some agencies. The solution of an inverse problem entails the construction of a mathematical model and takes the moves from a number of experimental data. In this respect, inverse problems are often ill-conditioned as the amount of experimental conditions available are often insufficient to unambiguously solve the mathematical model. Several approaches to solving inverse problems are possible, both computational and experimental, some of which are mentioned in this article. In this work, we will describe in details the attempt to solve an inverse problem which arose in the study of an intracellular signaling pathway. RESULTS: Using the Genetic Algorithm to find the sub-optimal solution to the optimization problem, we have estimated a set of unknown parameters describing a kinetic model of a signaling pathway in the neuronal cell. The model is composed of mass action ordinary differential equations, where the kinetic parameters describe protein-protein interactions, protein synthesis and degradation. The algorithm has been implemented on a parallel platform. Several potential solutions of the problem have been computed, each solution being a set of model parameters. A sub-set of parameters has been selected on the basis on their small coefficient of variation across the ensemble of solutions. CONCLUSION: Despite the lack of sufficiently reliable and homogeneous experimental data, the genetic algorithm approach has allowed to estimate the approximate value of a number of model parameters in a kinetic model of a signaling pathway: these parameters have been assessed to be relevant for the reproduction of the available experimental data.

Algorithms↗

PubMed1978

Program to estimate parameters of linear systems without numerical differentiation.

This paper describes a computer program for estimating the parameters of a linear differential equation systen with constant coefficients by use of a nonlinear least-squares method. For minimization the sum of squares of an existing standard program, the Gauss-Newton gradient procedure, is employed. The differential equation system is solved by the Taylor expansion method. The advantage of this approach is that the derivatives with respect to the parameters are available without numerical differentiation. Therefore the inaccuracy inherent in numerical differentiation and the problem of choosing the modification of the parameters are eliminated. The given procedure is applicable for all the first order gradient methods. The presented method was tested with generated data from a four-compartmental model.

Computers↗

PubMed2005

Parameter estimation in a stochastic model of the tubuloglomerular feedback mechanism in a rat nephron.

A key parameter in the understanding of renal hemodynamics is the gain of the feedback function in the tubuloglomerular feedback mechanism. A dynamic model of autoregulation of renal blood flow and glomerular filtration rate has been extended to include a stochastic differential equations model of one of the main parameters that determines feedback gain. The model reproduces fluctuations and irregularities in the tubular pressure oscillations that the former deterministic models failed to describe. This approach assumes that the gain exhibits spontaneous erratic variations that can be explained by a variety of influences, which change over time (blood pressure, hormone levels, etc.). To estimate the key parameters of the model we have developed a new estimation method based on the oscillatory behavior of the data. The dynamics is characterized by the spectral density, which has been estimated for the observed time series, and numerically approximated for the model. The parameters have then been estimated by the least squares distance between data and model spectral densities. To evaluate the estimation procedure measurements of the proximal tubular pressure from 35 nephrons in 16 rat kidneys have been analyzed, and the parameters characterizing the gain and the delay have been estimated. There was good agreement between the estimated values, and the values obtained for the same parameters in independent, previously published experiments.

Animals↗

PubMed1981

Twin-family studies of perceptual speed ability. II. Parameter estimation.

Offspring of monozygotic (MZ) twins form half-ships that permit a direct test of maternal effects and differentiate several sources of between-family environmental variance. Combined with conventional twin data, these genetic half-sibships provide a unique data set for estimating sources of variation in quantitative traits. To illustrate, genetic and environmental parameters were estimated for Identical Pictures Test data obtained from children of MZ twin parents and an (approximate) age-matched cohort of like-sex twins. Analyses of variance of the data, standardized for age and sex, yield 12 mean squares to which gene-environment models were fit. Maximum-likelihood estimation revealed a complete absence of maternal influences and shared environmental effects; a simple two-parameter model, assuming random mating and attributing variation in test scores to additive genes and within-family environment, adequately accounts for the familial data.

Adolescent↗

PubMedDate not supplied

Parameter estimation for a prosthetic ankle.

The mechanical parameters of a model of an energy storage and return ankle prosthesis are estimated for normal level walking by means of an optimization procedure. The walking cycle is divided into six fields, such that the power does not change sign within each field; the transition between successive fields occurs at zero power. The optimal spring stiffness as a function of time, is found by optimizing a quadratic cost function to minimize the difference between the estimated ankle moments and the moments in normal walking. The optimization is subjected to four continuous constraints within each field and to two continuity constraints for the transitions between successive fields. The time-varying spring stiffness and the implications of additional external energy are discussed and are presented as recommendations for the designer.

Ankle Joint↗

PubMed2004

The impact of model misfit on partial credit model parameter estimates.

The partial credit model (PCM) is commonly employed to parameterize items and individuals using responses to a set of polytomous items. Because the PCM does not include a discrimination parameter, it may encounter substantial lack of fit to the data in certain situations. To determine the impact of model misfit on the estimation of person and item parameters using the PCM, a simulation study was conducted in which data were generated according to the generalized partial credit model, and the bias and efficiency of the resulting person and item parameter estimates were assessed. The results suggest that small amounts of unsystematic misfit do not lead to dramatic levels of bias or loss of efficiency of the estimators, but large levels of unsystematic misfit and moderate levels of systematic misfit result in substantial loss of efficiency and bias of the estimators.

Humans↗