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PubMed1986

A computer program for enzyme kinetics that combines model discrimination, parameter refinement and sequential experimental design.

A method of model discrimination and parameter estimation in enzyme kinetics is proposed. The experimental design and analysis of the model are carried out simultaneously and the stopping rule for experimentation is deduced by the experimenter when the probabilities a posteriori indicate that one model is clearly superior to the rest. A FORTRAN77 program specifically developed for joint designs is given. The method is very powerful, as indicated by its usefulness in the discrimination between models. For example, it has been successfully applied to three cases of enzyme kinetics (a single-substrate Michaelian reaction with product inhibition, a single-substrate complex reaction and a two-substrate reaction). By using this method the most probable model and the estimates of the parameters can be obtained in one experimental session. The FORTRAN77 program is deposited as Supplementary Publication SUP 50134 (19 pages) at the British Library (Lending Division), Boston Spa, Wetherby, West Yorkshire LS23 7BQ, U.K., from whom copies can be obtained on the terms indicated in Biochem. J. (1986) 233, 5.

Computers↗

PubMed1999

Photogrammetric calibration of a stereo light microscope.

Quantitative stereo light microscopy has been used in very rare cases to obtain geometric representations of microscopic objects. Although the instrument itself has limitations, most of them efficiently overcome by other 3D microscopes, it bears considerable advantages in observing and measuring dynamic scenes with multiple objects. The biggest asset of the stereo method is that the full 3D work space is imaged in one shot - a property which distinguishes stereo from all the scanning techniques in 3D microscopy. With the work presented in this paper, we contribute to making the stereo technique applicable to the numerous mensuration tasks in the microscopic domain, where its potential would be invaluable.We report the photogrammetric calibration of a common main objective lens type stereo light microscope. Such a calibration is the initial step in ensuring accurate measurements with this instrument. First, we derive a mathematical formulation of the imaging function and discuss the estimation of the parameters involved. Then, three main problems of the practical implementation of the framework are addressed: the finding of a calibration standard, the automatic measuring of the many image coordinates required, and the stabilization of the parameter estimation. Finally, results of various calibration runs are presented and analysed under different aspects. Among these, the most important is the accuracy of the calibrated instrument in measuring 3D positions and positional relationships. With a Zeiss Stemi 11, Achromat 1.6 x we achieve accuracies of 1 per thousand laterally and 1-2% axially relative to the volume of the work space. On the highest magnification level this corresponds to 700 nm and 1.8 &mgr;m, respectively.

Journal Article↗

PubMed2002

Treating allergic rhinitis in patients with comorbid asthma: the risk of asthma-related hospitalizations and emergency department visits.

BACKGROUND: Although asthma and allergic rhinitis commonly occur together, the nature of the association has yet to be determined. Treatments for one condition could potentially alleviate the coexisting condition. OBJECTIVE: Patients with both allergic rhinitis and asthma were studied to test the hypothesis that treating allergic rhinitis reduces health care utilization for co-morbid asthma. METHODS: A retrospective cohort study was carried out with 1994-1995 MarketScan claims data. The cohort was limited to patients with both allergic rhinitis and asthma, aged 12 to 60 years, who were continuously enrolled and had no evidence of chronic obstructive pulmonary disease. Allergic rhinitis treatment and asthma-related events (hospitalizations and emergency department visits) were identified. An incidence density ratio (IDR) associated with exposure to allergic rhinitis treatment was calculated. A multivariate Poisson regression was estimated, and the parameter estimates were transformed into IDRs for each explanatory variable. An allergic rhinitis treatment indicator was included in all regressions. RESULTS: The study sample population consisted of 4944 patients with allergic asthma, approximately 73% of whom were treated for their allergic rhinitis. Asthma-related events occurred more often for the untreated group compared with the treated group, 6.6% compared with 1.3%. An IDR of 0.49 for the treatment group (P =.001) indicates that the risk of an asthma-related event for the treated group was about half that for the untreated group. CONCLUSION: In summary, those who were treated for allergic rhinitis have a significantly lower risk of subsequent asthma-related events (emergency department visits or hospitalizations) than those who were not treated.

Adolescent↗

PubMed1997

A descriptive model for the kinetics of a homogeneous fluorometric immunoassay.

A descriptive mathematical model was chosen to fit the antigen-antibody association kinetics of a new homogeneous immunometric assay for prolactin, involving time-resolved fluorescence detection (TRACE technology, Time Resolved Amplified Cryptate Emission). We paid special attention to the methodology and criteria applied, to yield a convenient and statistically valid model, designed to allow potential exploitation of kinetic information in the data processing of the assay. We compared specific parameterizations of an hyperbolic model, the Gompertz, and the monomolecular models on the basis of morphological considerations, a statistical analysis of fit, and an assessment of the parameters estimation quality, over a wide range of antigen concentrations. The monomolecular model gave the best fit, and the most precise and stable estimation of its parameters. The study of parameter properties confirmed this choice.

Antigens↗

PubMed2005

Systems Biology Toolbox for MATLAB: a computational platform for research in systems biology.

We present a Systems Biology Toolbox for the widely used general purpose mathematical software MATLAB. The toolbox offers systems biologists an open and extensible environment, in which to explore ideas, prototype and share new algorithms, and build applications for the analysis and simulation of biological and biochemical systems. Additionally it is well suited for educational purposes. The toolbox supports the Systems Biology Markup Language (SBML) by providing an interface for import and export of SBML models. In this way the toolbox connects nicely to other SBML-enabled modelling packages. Models are represented in an internal model format and can be described either by entering ordinary differential equations or, more intuitively, by entering biochemical reaction equations. The toolbox contains a large number of analysis methods, such as deterministic and stochastic simulation, parameter estimation, network identification, parameter sensitivity analysis and bifurcation analysis.

Database Management Systems↗

PubMed1977

Simulation of quantitative characters by genes with biochemically definable action. VI. Modifications of a simple model.

Investigations on metric characters of defined genotypes of Matthiola incana, and application of different linear models for the estimation of genetic parameters, indicate that the use of midparental value as a reference point results in parameter estimates that do not correspond to the actual biological situation. Use of the most recessive genotype as a reference point causes all of the contributions of single loci to be undirectional and positive, and all the allelic and nonallelic interactions to be unidirectional and negative, in accord with our Model 2.2. The results indicate that the phenotypic response to allelic substitutions follows the characteristics of a saturation curve. The possibility is discussed that the saturation character results from regulating processes, whereas deviations of single measurements from the response curve, or response surface, reflect real interactions between allelic and nonallelic genes.

Genes, Recessive↗

PubMed2006

Comparison of Gompertz and neural network models of broiler growth.

Neural networks offer an alternative to regression analysis for biological growth modeling. Very little research has been conducted to model animal growth using artificial neural networks. Twenty-five male chicks (Ross x Ross 308) were raised in an environmental chamber. Body weights were determined daily and feed and water were provided ad libitum. The birds were fed a starter diet (23% CP and 3,200 kcal of ME/kg) from 0 to 21 d, and a grower diet (20% CP and 3,200 kcal of ME/ kg) from 22 to 70 d. Dead and female birds were not included in the study. Average BW of 18 birds were used as the data points for the growth curve to be modeled. Training data consisted of alternate-day weights starting with the first day. Validation data consisted of BW at all other age periods. Comparison was made between the modeling by the Gompertz nonlinear regression equation and neural network modeling. Neural network models were developed with the Neuroshell Predictor. Accuracy of the models was determined by mean square error (MSE), mean absolute deviation (MAD), mean absolute percentage error (MAPE), and bias. The Gompertz equation was fit for the data. Forecasting error measurements were based on the difference between the model and the observed values. For the training data, the lowest MSE, MAD, MAPE, and bias were noted for the neural-developed neural network. For the validation data, the lowest MSE and MAD were noted with the genetic algorithm-developed neural network. Lowest bias was for the neural-developed network. As measured by bias, the Gompertz equation underestimated the values whereas the neural- and genetic-developed neural networks produced little or no overestimation of the observed BW responses. Past studies have attempted to interpret the biological significance of the estimates of the parameters of an equation. However, it may be more practical to ignore the relevance of parameter estimates and focus on the ability to predict responses.

Animals↗

PubMed1994

Evaluation of a Bayesian approach to the pharmacokinetic interpretation of cyclosporin concentrations in renal allograft recipients.

The utility of a Bayesian parameter estimation program in the interpretation of cyclosporin concentrations was investigated in a group of 32 patients following renal transplantation. The program was evaluated by comparing concentrations predicted from individual estimates of pharmacokinetic parameters with measured concentrations. A one-compartment model incorporating an exponential, time-related change in clearance was used for data collected in the first 4 weeks after transplantation, and predictions of concentrations measured during weeks 5-14 were made using three schemes: a changing clearance model using all data from week 1 onward; a changing clearance model using data from week 4 onward; and a nonchanging clearance model using data from week 4 onward. Results demonstrated that predictions made by the Bayesian program were unreliable during the first 4 weeks of therapy, but that there was a progressive improvement as time after transplantation increased. The changing clearance model was superior to the constant clearance model and its performance was not compromised by including data from the first 4 weeks of therapy. Although the Bayesian approach may help with the interpretation of blood cyclosporin concentrations during maintenance therapy, the large variability in the pharmacokinetics of orally administered cyclosporin limits the usefulness of the approach in the early weeks following transplantation.

Adult↗

PubMed2006

Inferring the distribution of mutational effects on fitness in Drosophila.

The properties of the distribution of deleterious mutational effects on fitness (DDME) are of fundamental importance for evolutionary genetics. Since it is extremely difficult to determine the nature of this distribution, several methods using various assumptions about the DDME have been developed, for the purpose of parameter estimation. We apply a newly developed method to DNA sequence polymorphism data from two Drosophila species and compare estimates of the parameters of the distribution of the heterozygous fitness effects of amino acid mutations for several different distribution functions. The results exclude normal and gamma distributions, since these predict too few effectively lethal mutations and power-law distributions as a result of predicting too many lethals. Only the lognormal distribution appears to fit both the diversity data and the frequency of lethals. This DDME arises naturally in complex systems when independent factors contribute multiplicatively to an increase in fitness-reducing damage. Several important parameters, such as the fraction of effectively neutral non-synonymous mutations and the harmonic mean of non-neutral selection coefficients, are robust to the form of the DDME. Our results suggest that the majority of non-synonymous mutations in Drosophila are under effective purifying selection.

Animals↗

PubMed2004

Correct estimation of preferential chromosome pairing in autotetraploids.

In recent work, a statistical model was proposed for the purpose of estimating parameters associated with quantitative trait locus (QTL) mapping and preferential pairing within a polyploidy framework. The statistical model contained several parameters that, when estimated from experimental data, supplied information about QTL, including a preferential pairing factor. Among the results reported were estimates of preferential pairing, many of which indicated high levels of preferential pairing (p = 0.60) that were inconsistent with biological expectations. By using the biological inconsistencies as our motivation, we present a reformulated statistical method for estimating preferential pairing, and use this method to reanalyze the same autotetraploid alfalfa data and to conduct a simulation study. Our results directly contradict the current findings of significant preferential pairing and affirm the traditional view of random chromosome segregation in alfalfa.

Chromosome Pairing↗

PubMed2005

Insulin kinetics in type-I diabetes: continuous and bolus delivery of rapid acting insulin.

We investigated insulin lispro kinetics with bolus and continuous subcutaneous insulin infusion (CSII) modes of insulin delivery. Seven subjects with type-1 diabetes treated by CSII with insulin lispro have been studied during prandial and postprandial conditions over 12 hours. Eleven alternative models of insulin kinetics have been proposed implementing a number of putative characteristics. We assessed 1) the effect of insulin delivery mode, i.e., bolus or basal, on the insulin absorption rate, the effects of 2) insulin association state and 3) insulin dose on the rate of insulin absorption, 4) the remote insulin effect on its volume of distribution, 5) the effect of insulin dose on insulin disappearance, 6) the presence of insulin degradation at the injection site, and finally 7) the existence of two pathways, fast and slow, of insulin absorption. An iterative two-stage parameter estimation technique was used. Models were validated through assessing physiological feasibility of parameter estimates, posterior identifiability, and distribution of residuals. Based on the principle of parsimony, best model to fit our data combined the slow and fast absorption channels and included local insulin degradation. The model estimated that 67(53-82)% [mean (interquartile range)] of delivered insulin passed through the slow absorption channel [absorption rate 0.011(0.004-0.029) min(-1)] with the remaining 33% passed through the fast channel [absorption rate 0.021(0.011-0.040) min(-1)]. Local degradation rate was described as a saturable process with Michaelis-Menten characteristics [VMAX = 1.93(0.62 - 6.03) mU min(-1), KM = 62.6(62.6 - 62.6) mU]. Models representing the dependence of insulin absorption rate on insulin disappearance and the remote insulin effect on its volume of distribution could not be validated suggesting that these effects are not present or cannot be detected during physiological conditions.

Adult↗

PubMed2005

Estimation of genetic parameters for the prevalence of osseous fragments in limb joints of Hanoverian Warmblood horses.

Genetic parameters were estimated for the prevalence of osseous fragments in distal (DIJ) and proximal interphalangeal (PIJ), fetlock (FJ) and hock joints (HJ) of Hanoverian Warmblood horses by using residual maximum likelihood (REML) with linear animal models. The analyses were based on the results of 10 standardized radiographs of all four limbs of 3725 young riding horses selected for sale at auction. Transformation factors onto the underlying liability scale were verified by a simulation study. The heritability estimates of osseous fragments on the liability scale were in the range of h2 = 0.19-0.60. Further analyses of osseous fragments in FJ and HJ were performed separately in males and females. In both sexes, the heritabilities of osseous fragments in HJ were higher (h2 = 0.41 in males, h2 = 0.25 in females) than those of osseous fragments in FJ (h2 = 0.21 in males, h2 = 0.23 in females). Osseous fragments in the phalangeal joints (DIJ, PIJ, FJ) were genetically correlated moderately positive (r(g) = 0.19-0.41). The genetic correlations between osseous fragments in the phalangeal joints and in HJ were negative (r(g) = -0.27 to -0.67). Particularly, this applied to osseous fragments in FJ in both sexes, to those in front FJ in males and to osseous fragments in front and hind FJ of females (up to r(g) = -1). The heritability of height at withers was estimated at h2 = 0.27-0.28. Genetic correlations between height at withers and osseous fragments in equine limb joints were mostly moderately positive (up to r(g) = 0.75). We conclude from our results that osseous fragments in phalangeal and hock joints are genetically different traits but sex-specific expression of osseous fragments was unlikely.

Animals↗

PubMed2006

Modeling distortion product otoacoustic emission input/output functions using segmented regression.

Distortion product otoacoustic emissions (DPOAEs) are low-level acoustic signals, the detection of which involves extraction from a background of noise. Boege and Janssen [J. Acoust. Soc. Am. 111, 1810-1818 (2002)] described a method for modeling the presence and growth of these responses. While improving growth function parameter estimation, this technique excludes a significant fraction of the data (especially low-level responses), and relies on ad hoc model fit acceptance criteria. The statistical difficulties associated with these limitations are described, and a weighted segmented linear regression model that avoids them is proposed. A simple test is presented for the presence of DPOAE growth. This technique is compared to that of Boege and Janssen in a dataset of 9 556 input/output (I/O) functions collected over 4 years on 866 ears from 379 construction apprentices and 63 age-matched controls. Comparisons are made on the entire dataset and within audiometric hearing loss categories. Segmented regression avoids the statistical pitfalls of the previous method, allows estimation of the threshold and slope of auditory response on a far greater number of I/O functions, and improves estimation of these parameters in this dataset. The potential for this method to yield more sensitive metrics of hearing function and compromise is discussed.

Acoustic Impedance Tests↗

PubMed2006

Pose estimation in automated visual inspection using genetic algorithm.

In this paper, we propose a genetic algorithm based approach to determine the pose of an object in Automated Visual Inspection having three degrees of freedom. We have investigated the effect of noise at 20 dB SNR and also mismatch resulting from incorrect correspondences between the object space points and the image space points, on the estimation of pose parameters. The maximum error in translation parameters is less than 0.45 cm and rotational error is less than 0.2 degree at 20 dB SNR. The error in parameter estimation is insignificant upto 7 pairs of mismatched points out of 24 points in object space and the results skyrockets when 8 or more pairs of points are mismatched. We have compared our result with that obtained by least square technique and it shows that GA based method outperform the gradient based technique when the number of vertices of the object to be inspected is small. These results have clearly established the robustness of GA in estimating the pose of an object with small number of vertices in automated visual inspection.

Algorithms↗

PubMed1987

An evaluation of the two-dimensional Gabor filter model of simple receptive fields in cat striate cortex.

1. Using the two-dimensional (2D) spatial and spectral response profiles described in the previous two reports, we test Daugman's generalization of Marcelja's hypothesis that simple receptive fields belong to a class of linear spatial filters analogous to those described by Gabor and referred to here as 2D Gabor filters. 2. In the space domain, we found 2D Gabor filters that fit the 2D spatial response profile of each simple cell in the least-squared error sense (with a simplex algorithm), and we show that the residual error is devoid of spatial structure and statistically indistinguishable from random error. 3. Although a rigorous statistical approach was not possible with our spectral data, we also found a Gabor function that fit the 2D spectral response profile of each simple cell and observed that the residual errors are everywhere small and unstructured. 4. As an assay of spatial linearity in two dimensions, on which the applicability of Gabor theory is dependent, we compare the filter parameters estimated from the independent 2D spatial and spectral measurements described above. Estimates of most parameters from the two domains are highly correlated, indicating that assumptions about spatial linearity are valid. 5. Finally, we show that the functional form of the 2D Gabor filter provides a concise mathematical expression, which incorporates the important spatial characteristics of simple receptive fields demonstrated in the previous two reports. Prominent here are 1) Cartesian separable spatial response profiles, 2) spatial receptive fields with staggered subregion placement, 3) Cartesian separable spectral response profiles, 4) spectral response profiles with axes of symmetry not including the origin, and 5) the uniform distribution of spatial phase angles. 6. We conclude that the Gabor function provides a useful and reasonably accurate description of most spatial aspects of simple receptive fields. Thus it seems that an optimal strategy has evolved for sampling images simultaneously in the 2D spatial and spatial frequency domains.

Animals↗

PubMed1983

Evaluating pedigree data. II. Identifying the cause of error in families with inconsistencies.

Pedigree data can be evaluated, and subsequently corrected, by analysis of the distribution of genetic markers, taking account of the possibility of mistyping . Using a model of pedigree error developed previously, we obtained the maximum likelihood estimates of error parameters in pedigree data from Tokelau. Posterior probabilities for the possible true relationships in each family are conditional on the putative relationships and the marker data are calculated using the parameter estimates. These probabilities are used as a basis for discriminating between pedigree error and genetic marker errors in families where inconsistencies have been observed. When applied to the Tokelau data and compared with the results of retyping inconsistent families, these statistical procedures are able to discriminate between pedigree and marker error, with approximately 90% accuracy, for families with two or more offspring. The large proportion of inconsistencies inferred to be due to marker error (61%) indicates the importance of discriminating between error sources when judging the reliability of putative relationship data. Application of our model of pedigree error has proved to be an efficient way of determining and subsequently correcting sources of error in extensive pedigree data collected in large surveys.

Female↗

PubMed1987

Robustness of path analysis of family resemblance against deviations from multivariate normality.

Path analysis is one of several methods available for quantitative genetic analysis, providing for both tests of hypotheses and estimates of relevant parameters. Central to the theory is the assumption that the observations follow a multivariate normal distribution within families. The purpose of the present investigation is to assess the effects of a certain type of departures from multivariate normality using quantitative family data on lipid and lipoprotein levels. The results show that even large departures produce reasonably unbiased parameter estimates. Whereas moderate departures lead to few inferential errors in hypothesis testing, gross departures from multivariate normality may have considerable effects on likelihood ratio tests.

Environment↗

PubMed2003

Segregation analysis comparing liability and quantitative trait models for hypertension using the Genetic Analysis Workshop 13 simulated data.

Discrete (qualitative) data segregation analysis may be performed assuming the liability model, which involves an underlying normally distributed quantitative phenotype. The appropriateness of the liability model for complex traits is unclear. The Genetic Analysis Workshop 13 simulated data provides measures on systolic blood pressure, a highly complex trait, which may be dichotomized into a discrete trait (hypertension). We perform segregation analysis under the liability model of hypertensive status as a qualitative trait and compare this with results using systolic blood pressure as a quantitative trait (without prior knowledge at that stage of the true underlying simulation model) using 1050 pedigrees ascertained from four replicates on the basis of at least one affected member. Both analyses identify models with major genes and polygenic components to explain the family aggregation of systolic blood pressure. Neither of the methods estimates the true parameters well (as the true model is considerably more complicated than those considered for the analysis), but both identified the most complicated model evaluated as the preferred model. Segregation analysis of complex diseases using relatively simple models is unlikely to provide accurate parameter estimates but is able to indicate major gene and/or polygenic components in familial aggregation of complex diseases.

Adult↗