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PubMed2006

Bootstrapping the recognition and anaphoric linking of named entities in Drosophila articles.

This paper demonstrates how Drosophila gene name recognition and anaphoric linking of gene names and their products can be achieved using existing information in FlyBase and the Sequence Ontology. Extending an extant approach to gene name recognition we achieved a F-score of 0.8559, and we report a preliminary experiment using a baseline anaphora resolution algorithm. We also present guidelines for annotation of gene mentions in texts and outline how the resulting system is used to aid FlyBase curation.

Animals↗
PubMed1967

Operation bootstrap.

Explore the source record for details and available documents.

Dental Service, Hospital↗
PubMed1998

1998 Nova Award winners. By the bootstraps.

Social ills lead to physical ones, and sometimes it's up to hospitals to help communities turn things around. From a quiet town in southwest Georgia to the hustle and bustle of Seattle, this year's NOVA recipients are adept at promoting their vision of a healthier, safer society.

Awards and Prizes↗
PubMed1997

Stability and performance of a population pharmacokinetic model.

This study aimed to determine the stability (in terms of covariate selection) of a population pharmacokinetic model and evaluate its performance in the absence of a test data set. Data from 88 full-term infants, 11 of whom were human immunodeficiency virus (HIV)-seropositive, taking an antiinfective agent were analyzed using exploratory data analysis methods and the nonlinear mixed-effects modeling (NONMEM) program to obtain the final population pharmacokinetic model. The stability of the population pharmacokinetic model was tested using the nonparametric bootstrap approach in four steps: 1) with the base pharmacokinetic model, 100 bootstrap replicates of the original data were generated by sampling with replacement; 2) ascertainment that each bootstrap data replicate was described by the basic structural model using the NONMEM objective function; 3) generalized additive modeling (GAM) applied to empiric Bayesian estimates for covariate selection at alpha = 0.05 and a frequency (f) cutoff value of 0.50; and 4) NONMEM population model building using covariates selected in the third step with alpha = 0.005. Performance of the population pharmacokinetic model was evaluated using 200 additional bootstrap replicates of the data by fitting the model obtained in step 4 to them. Parameters obtained were compared with those obtained in the model stability step, and improved prediction error, a measure of predictive accuracy as an index of internal validation, was computed. The reciprocal of serum creatinine (RSC; f = 0.73) and HIV (f = 0.70) were selected by GAM as predictors of clearance (Cl). The population pharmacokinetic model obtained without the determination of model stability included RSC as a predictor of Cl, but the final model from the model stability step included both HIV and RSC as predictors of Cl. Final population pharmacokinetic parameters were obtained with this model fitted to the original data; however, the 95% confidence interval on the HIV status regression coefficient included zero, indicating no significance. The mean parameter estimates obtained with the additional 200 bootstrap replicates of data were within 15% of those obtained with the final model at the regression stability step. Bootstrap resampling procedure is useful for evaluating the stability and performance of a population model by repeatedly fitting it to the bootstrap samples when there is no test data set.

Adolescent↗
PubMed1998

Coverage and precision of confidence intervals for area under the curve using parametric and non-parametric methods in a toxicokinetic experimental design.

PURPOSE: The coverage and precision of parametric Bailer-type confidence intervals (CIs) for area under the curve (AUC) was compared to nonparametric bootstrap confidence intervals. METHODS: Concentration-time data was simulated using Monte Carlo simulation under a toxicokinetic paradigm with sparse (SSC) and dense sampling (DSC) conditions. AUC was calculated using the trapezoidal rule and 95% CIs were computed using various parametric and nonparametric methods. RESULTS: Under SSC, the various parametric CIs contained the true population AUC with coverage probabilities ranging from 0.77 to 0.95 with low inter-subject variation (coefficient of variation (CV) = 15%) and from 0.82 to 0.95 with high inter-subject variation (CV = 50%). The nominal value should be close to 0.95. DSC tended to increase coverage by about 0.05. Bailer's method always produced the lowest coverage of all parametric CIs examined. Under SSC, bootstrap CIs had coverage probabilities ranging from 0.62 (CV = 15%) to 0.68 (CV = 50%). DSC increased coverage to 0.77. Parametric CIs were wider than their nonparametric counterparts, often giving lower CI estimates less than zero. Bailer's method and Bailer's method using the jackknife estimate of the standard error were the worst in this respect. Bootstrap CIs never had lower CI estimates less than zero. However, SSC tends to produce bootstrap distributions that are not continuous which, if used, may produce biased CI estimates. CONCLUSIONS: Bootstrap CI estimates were judged to be the "best". However, the limitations of the bootstrap should be clearly recognized and it should not be used indiscriminately. Examination of the bootstrap distribution for its degree of discreteness must be part of the statistical process.

Area Under Curve↗
PubMed2004

Automated variable selection methods for logistic regression produced unstable models for predicting acute myocardial infarction mortality.

OBJECTIVES: Automated variable selection methods are frequently used to determine the independent predictors of an outcome. The objective of this study was to determine the reproducibility of logistic regression models developed using automated variable selection methods. STUDY DESIGN AND SETTING: An initial set of 29 candidate variables were considered for predicting mortality after acute myocardial infarction (AMI). We drew 1,000 bootstrap samples from a dataset consisting of 4,911 patients admitted to hospital with an AMI. Using each bootstrap sample, logistic regression models predicting 30-day mortality were obtained using backward elimination, forward selection, and stepwise selection. The agreement between the different model selection methods and the agreement across the 1,000 bootstrap samples were compared. RESULTS: Using 1,000 bootstrap samples, backward elimination identified 940 unique models for predicting mortality. Similar results were obtained for forward and stepwise selection. Three variables were identified as independent predictors of mortality among all bootstrap samples. Over half the candidate prognostic variables were identified as independent predictors in less than half of the bootstrap samples. CONCLUSION: Automated variable selection methods result in models that are unstable and not reproducible. The variables selected as independent predictors are sensitive to random fluctuations in the data.

Aged↗
PubMed2005

Cluster randomized trials: another problem for cost-effectiveness ratios.

OBJECTIVES: This work has investigated under what conditions cost-effectiveness data from a cluster randomized trial (CRT) are suitable for analysis using a cluster-adjusted nonparametric bootstrap. The bootstrap's main advantages are in dealing with skewed data and its ability to take correlations between costs and effects into account. However, there are known theoretical problems with a commonly used cluster bootstrap procedure, and the practical implications of these require investigation. METHODS: Simulations were used to estimate the coverage of confidence intervals around incremental cost-effectiveness ratios from CRTs using two bootstrap methods. RESULTS: The bootstrap gave excessively narrow confidence intervals, but there was evidence to suggest that, when the number of clusters per treatment arm exceeded 24, it might give acceptable results. The method that resampled individuals as well as clusters did not perform well when cost and effectiveness data were correlated. CONCLUSIONS: If economic data from such trials are to be analyzed adequately, then there is a need for further investigations of more complex bootstrap procedures. Similarly, further research is required on methods such as the net benefit approach.

Cluster Analysis↗
PubMedDate not supplied

Human mesor-hypertensive chronorisk.

Twelve endocrine variables in blood from a small number of clinically healthy adult women were sampled systematically around the clock and the seasons. Pattern discrimination methods singled out certain hormone values in certain seasons as classifiers for a high vs low risk of developing diseases associated with a high blood pressure. Further evidence in support of such classifiers is obtained on data from adolescent, menstrually cycling young adults and post-menopausal women, here analyzed as pool of series, with the scope of the data from any one age group greatly extended by a resampling procedure, namely, by bootstrapping. This mathematical approach was carried out on data series around the clock and seasons on several hormones as well as systolic and diastolic blood pressure. Classifier roles were strongly supported for plasma aldosterone and thyroid stimulating hormone, originally by an analysis of variance and, in the case of aldosterone, by circannual cosinor analysis and by numerical resampling. Circannual bootstrapping, a procedure recommended for broad routine use as a safeguard for hypothesis testing, was also done for plasma cortisol, dehydro-epi-androsterone sulfate and prolactin, variables for which (parametric) analyses of variance and cosinors did not reveal any difference between groups at high and low cardiovascular risk. In these instances, bootstrapping results are tentative and await further analyses. Results show the ability of circannual bootstrapping to detect outliers. Identification of classifiers provides cost-effective endocrine checks complementing the targeted automatic monitoring of blood pressure. Circannual indices for risk evaluation are, however, costly in several ways since it takes at least a year and quite a few samples to estimate them reliably. Accordingly, we also extended the scope of previous results by the application of an added procedure for circadian bootstrapping. With circadian as well as circannual bootstrapping, we here illustrate a major potential component of a system of chrono-engineering for health maintenance. This system should start with focus on the newborn. The results on adults here analyzed are likely to be more prominent in the neonate, to the extent that they are genetic in origin, yet amenable to modification by the extra-uterine environment.

Adolescent↗
PubMed2001

Elongation factor-2: a useful gene for arthropod phylogenetics.

Robust resolution of controversial higher-level groupings within Arthropoda requires additional sources of characters. Toward this end, elongation factor-2 sequences (1899 nucleotides) were generated from 17 arthropod taxa (5 chelicerates, 6 crustaceans, 3 hexapods, 3 myriapods) plus an onychophoran and a tardigrade as outgroups. Likelihood and parsimony analyses of nucleotide and amino acid data sets consistently recovered Myriapoda and major chelicerate groups with high bootstrap support. Crustacea + Hexapoda (= Pancrustacea) was recovered with moderate support, whereas the conflicting group Myriapoda + Hexapoda (= Atelocerata) was never recovered and bootstrap values were always <5%. With additional nonarthropod sequences included, one indel supports monophyly of Tardigrada, Onychophora, and Arthropoda relative to molluscan, annelidan, and mammalian outgroups. New and previously published sequences from RNA polymerase II (1038 nucleotides) and elongation factor-1alpha (1092 nucleotides) were analyzed for the same taxa. A comparison of bootstrap values from the three genes analyzed separately revealed widely varying values for some clades, although there was never strong support for conflicting groups. In combined analyses, there was strong bootstrap support for the generally accepted clades Arachnida, Arthropoda, Euchelicerata, Hexapoda, and Pycnogonida, and for Chelicerata, Myriapoda, and Pancrustacea, whose monophyly is more controversial. Recovery of some additional groups was fairly robust to method of analysis but bootstrap values were not high; these included Pancrustacea + Chelicerata, Hexapoda + Cephalocarida + Remipedia, Cephalocarida + Remipedia, and Malaocostraca + Cirripedia. Atelocerata (= Myriapoda + Hexapoda) was never recovered. Elongation factor-2 is now the second protein-encoding, nuclear gene (in addition to RNA polymerase II) to support Pancrustacea over Atelocerata. Atelocerata is widely cited in morphology-based analyses, and the discrepancy between results derived from molecular and morphological data deserves greater attention.

Amino Acid Sequence↗