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PubMed1992

The tricarboxylic acid cycle in Dictyostelium discoideum. II. Evaluation of model consistency and robustness.

When kinetic models of complex biochemical systems are reconstructed from knowledge of the component reactions that have been characterized in vitro, or when values must be assumed for some of the parameters, errors are invariably encountered, and, as a consequence, the resulting model is frequently internally inconsistent. The simplest and most basic manifestations of such logical inconsistency are the failure of the model to exhibit a steady state or to yield a steady state that is in agreement with the actual steady state of the integrated system, or to yield a steady state that is dynamically stable. Models that are consistent may nonetheless be lacking in robustness, which is manifested as a pathological sensitivity to small changes in the values of their parameters. In this paper, we examine the current model of the tricarboxylic acid cycle in Dictyostelium discoideum (see Shiraishi, F., and Savageau, M. A. (1992) J. Biol. Chem. 267, 22912-22918) with regard to these basic indicators of model quality. This may be viewed as a preliminary analysis; the object is to determine whether or not the model is reasonable and worthy of a more refined analysis and, if not, to diagnose the areas in need of modification before further analysis is undertaken. The results demonstrate that the current model of the tricarboxylic acid cycle is self-consistent and possesses a steady state that is in agreement with experimental evidence. However, the results also suggest that this model is not very robust. The high sensitivities of parameters influencing pyruvate metabolism indicate that the experimental characterization of these reactions might be fruitfully re-examined. These high sensitivities lead us to predict that this model of the tricarboxylic acid cycle should be accurate only over a very narrow range in variation of the independent variables. This is verified by the results presented in the following paper (Shiraishi, F., and Savageau, M. A. (1992) J. Biol. Chem. 267, 22926-22933).

Animals↗
PubMed2004

Using agent-based simulation to examine the robustness of up-or-out promotion systems in universities.

One of the dominant features of the American higher education system is the use of up-or-out promotion for junior faculty followed by life-long tenure. For organizational economists, the widespread use of up-or-out promotion over a long period of time represents prima facie evidence of its efficiency. What is well less known is the robustness of the system to various changes in labor patterns. The following paper uses an agent-based simulation to examine the robustness of an up-or-out system to contingencies such as heightened turnover, undersupply and oversupply of tenure-track candidates, and retirement policies. In each case a comparison is made with alternative promotion systems, such as seniority and merit based promotion. It is concluded that up-or-out promotion is not optimal in all cases.

Career Mobility↗
PubMed2004

Robust reasoning with agent-based modeling.

Agent-based modeling (ABM) is a powerful representational formalism that has wide utility for modeling nonlinear systems. For ABM to achieve its potential as a scientific tool, our ability to build models that embody our knowledge must be complemented by rigorous means for making inferences using such models. Due to nonlinearity, this rigor cannot in general be based solely on demonstrating that a model reliably predicts the outcomes of available physical measurements. In this paper we describe an alternative approach to robust reasoning based on the concept of ensembles of alternative models. Ensembles of models can be defined that plausibly span classes of systems including the system of interest. Research methodologies for searching and sampling from such ensembles can be used to support plausible conclusions about invariant properties of ensembles of ABMs and hence of the classes of systems they represent. Notable among these are approaches that implement a competition between ensembles of problem formulations or challenges and conclusions robust to these challenges. This approach is demonstrated using examples drawn from our research.

Journal Article↗
PubMed2004

Model reduction and analysis of robustness for the Wnt/beta-catenin signal transduction pathway.

We present a framework for model reduction of signal transduction networks. The methods are explained by considering a recent model for Wnt/beta-catenin signalling which plays an important regulatory role in cell development and oncogenesis. The procedure results in a reduction of system variables and parameters while maintaining the ability of the model to describe experimental data and to predict the in-vivo behaviour of the pathway. Using metabolic control analysis we quantified the response of the pathway towards random fluctuations of model parameters. This allows to characterise the robustness of the pathway against perturbations in stimulated and unstimulated states. We show that robustness depends on structural as well as kinetic properties of the pathway.

Animals↗
PubMed2005

Improving model robustness with bootstrapping -- application to optimal discriminant analysis for ordinal responses (ODAO).

OBJECTIVE: Recent results published by Coste et al. in discriminant analysis with ordinal responses showed the superiority of optimal discriminating analysis for ordinal responses (ODAO) both in terms of classification and simplicity of implementation compared to classic methods (Fisher's discrimination, logistic regression) applied to medical data (prognostics of burns) and to simulated data. Nevertheless, the solutions obtained by ODAO may be sensitive to re-sampling (i.e the estimated coefficients by ODAO may show excessive sensitivity to the training sample). This study proposes some solutions to control the fluctuations of sampling and to ensure model stability. METHODS: We used intensive computational methods and bootstrapping, at the outset of model building in order to reduce the sampling variability of estimated coefficients. Thus, the estimation of the coefficients was not based on the minimization of a classification criterion of the training sample, but on the minimization of an aggregate criterion of bootstrapped replications of a classification criterion. Five aggregate criteria were studied. RESULTS: The improvement in terms of robustness appeared in 30% of the test cases with moderate training sample size and 55% of those with small training sample size. CONCLUSION: Simulated test cases showed that bootstrapping can help construct more robust models in difficult classification situations and small training samples which are particularly frequent.

Burns↗
PubMed2003

CTSS: a robust and efficient method for protein structure alignment based on local geometrical and biological features.

We present a new method for conducting protein structure similarity searches, which improves on the accuracy, robustness, and efficiency of some existing techniques. Our method is grounded in the theory of differential geometry on 3D space curve matching. We generate shape signatures for proteins that are invariant, localized, robust, compact, and biologically meaningful. To improve matching accuracy, we smooth the noisy raw atomic coordinate data with spline fitting. To improve matching efficiency, we adopt a hierarchical coarse-to-fine strategy. We use an efficient hashing-based technique to screen out unlikely candidates and perform detailed pairwise alignments only for a small number of candidates that survive the screening process. Contrary to other hashing based techniques, our technique employs domain specific information (not just geometric information) in constructing the hash key, and hence, is more tuned to the domain of biology. Furthermore, the invariancy, localization, and compactness of the shape signatures allow us to utilize a well-known local sequence alignment algorithm for aligning two protein structures. One measure of the efficacy of the proposed technique is that we were able to discover new, meaningful motifs that were not reported by other structure alignment methods.

Algorithms↗
PubMed2006

Robustness of a computer-assisted diabetes self-management intervention across patient characteristics, healthcare settings, and intervention staff.

BACKGROUND: A major problem in the dissemination of most interventions found to be efficacious is that they are of limited or unknown generalizability. OBJECTIVE: To document the "robustness," or external validity, of a computer-assisted diabetes self-management program across different patient characteristics, healthcare settings (mixed payer vs health maintenance organization), intervention staff, and outcomes. STUDY DESIGN: A randomized controlled trial evaluating a computer-assisted behavior change program for adult patients with type 2 diabetes mellitus (n = 217) vs a computerized health risk assessment. METHODS: Outcomes were identified using the RE-AIM framework and included program adoption among physicians, reach across patient groups, implementation, and behavioral (fat intake and physical activity) and biological (glycosylated hemoglobin and lipid levels) effectiveness measures. RESULTS: The program achieved 41% patient participation, variable adoption across healthcare settings (76% of health maintenance organization physicians vs 18% of non-health maintenance organization physicians participated), good implementation, and improvement in behavioral outcomes. There were few significant interactions between treatment condition and patient characteristics, type of healthcare setting, or interventionist experience on effectiveness measures. CONCLUSIONS: Patients and physicians were willing to participate in a computer-assisted dietary and physical activity goal-setting intervention, although participation varied by healthcare setting. Interventionists from different backgrounds successfully delivered the intervention, and the results appear robust across various patient and delivery characteristics.

Aged↗
PubMed2006

[A robust approach to independent component analysis and its application in the analysis of magnetoencephalographic data].

Independent component analysis (ICA) is a new method of signal statistical processing and widely used in many fields. We face several problems such as the different nature of source signals (e.g. both super-Gaussian and sub-Gaussian sources exist), unknown number of sources and contamination of the sensor signals with a high level of additive noise in the analysis of signal. A robust approach was proposed to solve these problems in this paper. Firstly, observations (noisy data) possessing high dimensionality were preprocessed and decomposed into a source signal subspace and a noise subspace. Then the number of sources was got through the cross-validation method, and this solved the problem that ICA could not confirm the number of sources. At last the transformed low-dimensional source signals were further separated with the fast and stable ICA algorithm. Through the analysis of artificially synthesized data and the real-world Magnetoencephalographic data, the efficacy of this robust approach was illustrated.

Algorithms↗
PubMed2006

[Research on testing the robustness of DICOM-e-mail secure teleradiology systems].

DICOM-e-mail is a secure teleradiology protocol released by German Radiology Society and has already been applied clinically. To improve the robustness of the system, the protocol has been upgraded by adding some mechanisms such as system feedback. Moreover, a test method is also implemented by sending erroneous mails to application software that supports DICOM-e-mail. Through the tests for two different DICOM-e-mail teleradiology application, the validity of the new protocol is proved and at the same time some bugs are found. The implementation of the latest protocol and the general error tests can help to make the whole teleradiology system a better robustness. The implementation of DICOM-e-mail protocol in our country is also discussed in this paper.

Computer Communication Networks↗
PubMed2006

[Acquired tumor "robustness" in the case of prostate cancer].

Tumors are highly robust and maintain their proliferative potential against both a wide range of host-defense mechanisms and anticancer therapies. In this study, we investigated the levels of human leukocyte antigen (HLA) class I, multi-drug resistance 1 (MDR1), and androgen receptor (AR) expressions in untreated prostate cancers harvested by radical prostectomy. The mean percentages of cancer cells expressing HLA class I, MDR1, and AR among the 10 cancer samples were 41, 35, and 74%, respectively. In addition, double-staining of HLA class I and MDR1 revealed the four definite populations (HLA class I(+)/MDR(+), HLA class I(+)/MDR(-), HLA class I (-)/MDR(+), and HLA class I(-)/MDR(-)) in cancer tissues from the majority of cancer patients tested, and the mean percentages of cells expressing these combinations were 13, 29, 22, and 38%, respectively. Similar results were obtained by double staining of HLA class I and AR, except for 2 cases in which HLA class I(-)/AR (+) cancer cells predominated. These results indicated that untreated prostate cancer cells acquired a wide range of genomic mutation, which may have been caused by internal host pressure to eliminate malignant cells, and would provide evidence of the robustness of untreated prostate cancer.

Aged↗
PubMed1991

Use of the robust sib-pair method to screen for single-locus, multiple-locus, and pleiotropic effects: application to traits related to hypertension.

Robust sib-pair linkage analysis can be used as a screening tool in the search for the potential involvement of single-loci, multiple-loci, and pleiotropic effects of single loci underlying phenotypic variation. Four large families were each ascertained through one adult white male with essential hypertension. The robust sib-pair method was used to screen these families for evidence of linkage between 39 quantitative traits related to hypertension and 25 genetic marker loci. All traits were analyzed on the untransformed, square-root and log-transformed scales. Among other findings, there is a suggestion of linkage between the 6-phosphogluconate dehydrogenase locus on chromosome 1p36 and mean fifth-phase diastolic blood pressure. There may also be linkage between the following markers and traits: the adenylate kinase-1 marker and/or the Lewis blood group marker and the traits height, weight, and biacromial breadth; the glyoxylase I marker and the traits upper-arm circumference and suprailiac skinfold thickness; the ABO blood group and adenylate kinase-1 markers on chromosome 9q34 and the third component of complement marker on chromosome 19p13 and dopamine-beta-hydroxylase; and the P1 blood group and the traits weight and 1-h postload serum glucose level.

Alleles↗
PubMed1991

Robustness and balance in the mixed model.

When balanced data are analyzed by a robust method, different weights are applied to data points depending on their apparent status as outliers. This results in the effective unbalancing of the data. Concepts developed for the analysis of unbalanced data can help to suggest robust methods of analysis for balanced data.

Analysis of Variance↗
PubMed1988

[Possibility of the current segregation analysis to discriminate between monogenic and multifactorial types of inheritance of traits. The effect of the structure of family data on model robustness and power of the analysis].

The influence of sampling designs for robustness of the autosomal major locus model and the multifactorial model as well as possibility of segregation analysis to discriminate these models was studied. Nuclear families and 3-generation pedigrees were considered. It was found that robustness of models increased, when the size of sibships in nuclear families grows and when configuration of pedigrees is complicated. The resolution power of the analysis is always increased with size elevation of sibships, the highest effect of the analysis being observed for sibships of the size 3 or 4. Consideration of new generations is only advisable, if attracting sibs of these generations, the resolution power being increased, provided that the parameters of models are of high value.

Genetics, Population↗
PubMed1982

Robustness in real life: a study of clinical laboratory data.

Previous studies have evaluated the performance of robust estimators of location using computer-generated distributions. This paper describes how distributions commonly seen in biomedical research differ from the simulated distributions, and compares the performance of six families of estimators using samples from four biomedical distributions. The biomedical distributions can be asymmetric, and have shorter tails and other anomalies, such as digit preferences, which are not modeled in simulation studies. The four biomedical distributions studied differ markedly from the models previously studied, and these differences strongly affect the robust estimators. In such situations the trimmed mean provides an improvement over the sample mean, and its performance is more stable than that of estimators whose psi functions have steeply-descending tails. The central value and dispersion of each of the estimators are evaluated.

Adult↗
PubMed1995

A likelihood-based approach to capture-recapture estimation of demographic parameters under the robust design.

The Jolly-Seber method has been the traditional approach to the estimation of demographic parameters in long-term capture-recapture studies of wildlife and fish species. This method involves restrictive assumptions about capture probabilities that can lead to biased estimates, especially of population size and recruitment. Pollock (1982, Journal of Wildlife Management 46, 752-757) proposed a sampling scheme in which a series of closely spaced samples were separated by longer intervals such as a year. For this "robust design," Pollock suggested a flexible ad hoc approach that combines the Jolly-Seber estimators with closed population estimators, to reduce bias caused by unequal catchability, and to provide estimates for parameters that are unidentifiable by the Jolly-Seber method alone. In this paper we provide a formal modelling framework for analysis of data obtained using the robust design. We develop likelihood functions for the complete data structure under a variety of models and examine the relationship among the models. We compute maximum likelihood estimates for the parameters by applying a conditional argument, and compare their performance against those of ad hoc and Jolly-Seber approaches using simulation.

Animals↗
PubMed1994

Robust variance estimation for the case-cohort design.

Large cohort studies of rare outcomes require extensive data collection, often for many relatively uninformative subjects. Sampling schemes have been proposed that oversample certain groups. For example, the case-cohort design of Prentice (1986, Biometrika 73, 1-11) provides an efficient method of analysis of failure time data. However, the variance estimate must explicitly correct for correlated score contributions. A simple robust variance estimator is proposed that allows for more complicated sampling mechanisms. The variance estimate uses a jackknife estimate of the variance of the individual influence function and is shown to be equivalent to a robust variance estimator proposed by Lin and Wei (1989, Journal of the American Statistical Association 84, 1074-1078) for the standard Cox model. Simulation results indicate excellent agreement with corrected asymptotic estimates and appropriate test size. The technique is illustrated with data evaluating the efficacy of mammography screening in reducing breast cancer mortality.

Analysis of Variance↗
PubMed1996

Application of robust data processing methods to the analysis of eye movements.

We have developed a robust, nonlinear differentiating digital filter for the estimation of eye velocity from an eye-position signal. This filter is equally applicable to a large variety of other biomedical signals. The filter is implemented by taking an odd number of two-point differences around the point of interest and then selecting the median difference. Dividing the median difference by the time interval yields the derivative of the input signal. The Robust Differentiator (RD) is a classic order-statistic filter consisting of a bank of linear filters (the two-point differences) followed by the median operation to select one difference for the derivative calculation. The RD has no impulse response function and eliminates the "ringing" that is typical of all linear filters. The RD not only performs better than the FIR differentiating filters for impulse noise but is equally effective for both broad-band and narrow-band Gaussian noise. The RD "bandwidth" is adjustable by selecting the interval for the two-point differences.

Eye Movements↗
PubMed1996

Robust tests for treatment comparisons based on recurrent event responses.

Robust nonparametric tests are considered for use in longitudinal studies in which the response of interest is a recurrent event. The tests are robust in the sense that they do not rely on distributional assumptions regarding the processes generating the events. The methods we describe are presented in the context of a clinical trial with attention initially directed at the two-sample problem in which a single experimental treatment is compared to a control. We investigate a family of generalized pseudo-score statistics (Lawless and Nadeau, 1995, Technometrics 37, 158-168) in which weight functions may be chosen to generate tests sensitive to various types of departure from the null hypothesis that the mean functions for the treatment and control groups are identical. All tests we consider are evaluated by simulation with respect to the type I error rate and power under a variety of practical scenarios. An application involving data from a kidney transplant study illustrates these procedures. For trials with multiple treatment arms, we generalize these approaches and indicate test statistics appropriate for unstructured alternatives and tests based on linear contrasts of the treatment-specific mean functions. Extensions of this methodology for stratified designs are also indicated.

Antibodies↗