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At least 595 records · Page 33Linked to original sources
PubMed2004

FunnyBase: a systems level functional annotation of Fundulus ESTs for the analysis of gene expression.

BACKGROUND: While studies of non-model organisms are critical for many research areas, such as evolution, development, and environmental biology, they present particular challenges for both experimental and computational genomic level research. Resources such as mass-produced microarrays and the computational tools linking these data to functional annotation at the system and pathway level are rarely available for non-model species. This type of "systems-level" analysis is critical to the understanding of patterns of gene expression that underlie biological processes. RESULTS: We describe a bioinformatics pipeline known as FunnyBase that has been used to store, annotate, and analyze 40,363 expressed sequence tags (ESTs) from the heart and liver of the fish, Fundulus heteroclitus. Primary annotations based on sequence similarity are linked to networks of systematic annotation in Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) and can be queried and computationally utilized in downstream analyses. Steps are taken to ensure that the annotation is self-consistent and that the structure of GO is used to identify higher level functions that may not be annotated directly. An integrated framework for cDNA library production, sequencing, quality control, expression data generation, and systems-level analysis is presented and utilized. In a case study, a set of genes, that had statistically significant regression between gene expression levels and environmental temperature along the Atlantic Coast, shows a statistically significant (P < 0.001) enrichment in genes associated with amine metabolism. CONCLUSION: The methods described have application for functional genomics studies, particularly among non-model organisms. The web interface for FunnyBase can be accessed at http://genomics.rsmas.miami.edu/funnybase/super_craw4/. Data and source code are available by request at jpaschall@bioinfobase.umkc.edu.

Animals↗
PubMed1996

Cross-over trials with censored data.

Cross-over trials assign two or more treatments sequentially to the same subject; groups of subjects receive different treatment sequences. Both parametric and non-parametric methods of inference are available for cross-over trials with complete data. In this paper we develop methods for estimation and testing in cross-over trials with censored data, based partly on methods used for complete data. Our estimator is consistent for the true effects. Simulation results show that both of our proposed tests have approximately nominal size. We compare our procedures to a method for cross-over designs based on Cox regression proposed by France, Lewis and Kay. We demonstrate that our method of estimation is superior to the Cox-based method, which has considerable bias. Both of the tests presented here have more power than the Cox-based tests in all of the situations we investigated. The estimation and test procedures apply to other designs, such as parallel trials and repeated measures designs.

Bias↗
PubMed1996

Specific and total carotenoid intakes among oral contraceptive and estrogen hormone users in the United States.

OBJECTIVE: To compare carotenoid intakes between hormone users and nonusers in a nationally representative sample of US women by demographic and lifestyle characteristics and to identify those with potentially greater risk for disease. DESIGN: Data from the 1987 National Health Interview Survey's-Epidemiology Supplement food frequency questionnaire were linked to the USDA-NCI Carotenoid database to estimate mean total and specific carotenoid intakes. SUBJECTS: Women (n = 8,962) were grouped by menopausal status and classified by hormone use into premenopausal oral contraceptive users/nonusers (n = 5,918) and postmenopausal estrogen replacement hormone users/nonusers (n = 3,044). STATISTICAL ANALYSES PERFORMED: Mean carotenoid intakes and standard errors were weighted using SUDAAN and adjusted for potential confounding factors using multiple linear regression analysis. Statistically significant differences were at p values < 0.01. RESULTS: Compared to nonusers, oral contraceptive users had lower specific carotenoid intakes. Demographic and lifestyle characteristics differed between oral contraceptive users/nonusers and were examined in relation to carotenoid intakes. More oral contraceptive users than nonusers were married, highly educated, drank alcoholic beverages, and smoked. After adjustment for these factors in a multiple linear regression model, the associations between oral contraceptive use and carotenoid intake remained statistically significant. Mean carotenoid intakes were not significantly different among estrogen hormone replacement users versus nonusers. CONCLUSIONS: Oral contraceptive users have lower dietary carotenoid intakes than nonusers. Since oral contraceptive users smoke and drink more than nonusers, and both factors are associated with lower carotenoid intakes, oral contraceptive users form a potential high risk group for disease.

Alcohol Drinking↗
PubMed2001

The use of neural networks and logistic regression analysis for predicting pathological stage in men undergoing radical prostatectomy: a population based study.

PURPOSE: Clinical under staging occurs in 40% to 60% of patients who undergo radical prostatectomy for prostate cancer. To decrease under staging several methods of predicting pathological stage preoperatively have been developed based on statistical logistic regression analysis and neural networks. To our knowledge none has been validated in our homogeneous regional patient population to date. We created logistic regression and neural network models, and implemented and adapted them into our practice. We also compared the 2 methods to determine their value and practicality in daily clinical practice. We present the results of our novel approach for predicting pathological staging of prostate adenocarcinoma. MATERIALS AND METHODS: Between 1986 and 1999, 600 white men from the Aragon region of Spain underwent surgery for prostate cancer; of whom 468 were selected for study. Predictive study variables included patient age, clinical stage, biopsy Gleason score and preoperative prostate specific antigen (PSA). The predicted result included in analysis was organ confined or nonorgan confined disease. Data were analyzed by multivariate logistic regression and a supervised neural network (multilayer perceptron and radial basis function). Results were compared by comparing the areas under the receiver operating characteristics curves. RESULTS: We generated 5 logistic regression models. The model created with clinical staging, Gleason biopsy score and PSA distributed in 5 categories (p <0.001) with an area under the receiver operating characteristics curve of 0.840 proved to be most predictive of pathological stage. Similarly of the 6 neural network models evaluated the radial basis function model, which included age, clinical stage, Gleason biopsy score and preoperative PSA distributed in 5 categories with an area under the curve of 0.882, proved the most predictive but not superior to the logistic regression model. The difference in the area under the curves in the 2 chosen models was 0.042 (p = 0.1). CONCLUSIONS: It is possible to generate useful predictive models of organ confined disease using logistic regression or neural networks with high indexes of clinical and statistical validity. However, using these variables neural networks did not prove to be better than logistic regression analysis. Therefore, better predictive variables must be identified, preferably nonlinear characteristics with respect to the probability of organ confined tumor, to generate better predictive models using neural networks.

Aged↗
PubMed1997

[Abnormally broad confidence intervals in logistic regression: interpretation of results of statistical programs].

This study describes the behavior of eight statistical programs (BMDP, EGRET, JMP, SAS, SPSS, STATA, STATISTIX, and SYSTAT) when performing a logistic regression with a simulated data set that contains a numerical problem created by the presence of a cell value equal to zero. The programs respond in different ways to this problem. Most of them give a warning, although many simultaneously present incorrect results, among which are confidence intervals that tend toward infinity. Such results can mislead the user. Various guidelines are offered for detecting these problems in actual analyses, and users are reminded of the importance of critical interpretation of the results of statistical programs.

Confidence Intervals↗
PubMed1998

Four-quadrant assessment of gestational age-specific values of amniotic fluid volume in uncomplicated pregnancies.

BACKGROUND: The purpose of this study was to establish a normative scale of amniotic fluid index (AFI) throughout gestation in uncomplicated singleton pregnancies, and to identify the lower and upper limits for each gestational week. METHODS: Four-quadrant assessment of amniotic fluid volume (AFV) was performed prospectively in 750 uncomplicated pregnancies between 16 and 43 weeks. The logarithmic transformations were used to get the data in Gaussian distribution. The means, and the 90%, 95% and 98% confidence intervals at each week of gestation were calculated from polynomial regression equation. Statistical differences in AFIs among gestational age groups were tested. RESULTS: The amniotic fluid index observations from regression equation curve were stratified in week-specific normative curve. The variations between mean AFI of the total population and the means of the preterm, term and postdate pregnancies were statistically significant (p<0.0001). The 90%, 95% and 98% confidence limits about the mean (12.5 cm) were 5.4 to 20.6, 4.2 to 22.3, 1.8 to 25.8 cm, respectively in term gestation. The 5th and 95th percentile serves as lower and upper limits of normal, respectively. CONCLUSIONS: Gestational age-specific values of AFI were established, determining the significant trends of changes in the AFV with gestation. The normogram may have a clinical benefit to accurate, reliable and semiquantitative diagnosis of oligohydramnios and polyhydramnios.

Amniotic Fluid↗
PubMed2000

Comparing the agreement among alternative models in evaluating HMO efficiency.

OBJECTIVE: To describe the efficiency of HMOs and to test the robustness of these findings across alternative models of efficiency. This study examines whether these models, when constructed in parallel to use the same information, provide researchers with the same insights and identify the same trends. DATA SOURCES: A data set containing 585 HMOs operating from 1985 through 1994. Variables include enrollment, utilization, and financial information compiled primarily from Health Care Investment Analysts, InterStudy HMO Census, and Group Health Association of America. STUDY DESIGN: We compute three estimates of efficiency for each HMO and compare the results in terms of individual performance and industry-wide trends. The estimates are then regressed against measures of case mix, quality, and other factors that may be related to the model estimates. PRINCIPAL FINDINGS: The three models identify similar trends for the HMO industry as a whole; however, they assess the relative technical efficiency of individual firms differently. Thus, these techniques are limited for either benchmarking or setting rates because the firms identified as efficient may be a consequence of model selection rather than actual performance. CONCLUSIONS: The estimation technique to evaluate efficient firms can affect the findings themselves. The implications are relevant not only for HMOs, but for efficiency analyses in general. Concurrence among techniques is no guarantee of accuracy, but it is reassuring; conversely, radically distinct inferences across models can be a warning to temper research conclusions.

Efficiency, Organizational↗
PubMed2003

Massachusetts registered dietitians' knowledge, attitudes, opinions, personal use, and recommendations to clients about herbal supplements.

OBJECTIVE: To assess the knowledge, personal use and recommendations of herbal supplements among registered dietitians (RDs) in Massachusetts. DESIGN: A descriptive, cross-sectional study conducted by a self-administered survey. SUBJECTS: One hundred and fifty-eight RDs from active members of the Massachusetts Dietetic Association (MDA). STATISTICAL ANALYSIS: One-way analysis of variance (ANOVA), Kruskal-Wallis tests, and multivariate regression identified statistical significance and examined the association between the dietitians' test scores from eight herbal knowledge questions with their personal herbal use and recommendations to clients and their age, education, work experience, and work status. RESULTS: We obtained a 53% response rate. The dietitians scored an average of 5.4 of a possible 8 on the herbal knowledge questions. Seventy-three percent (73%) perceived themselves to have little or no knowledge of herbal supplements. Only 37% reported using herbs and 22% recommending herbs to clients in the past year. A significant positive association was observed between herbal supplement knowledge score and frequency of personal use (p = 0.004), and recommendation to clients (p = 0.001). Eighty-nine percent (89%) agreed that herbal supplement education should be incorporated into dietetic curricula. DISCUSSION: The majority of the dietitians may lack herbal supplement familiarity. Therefore, these dietitians may be reluctant to personally use or recommend herbs to clients, even though the majority believe herbs can be effective for specific illness and health maintenance. These results may indicate a need to include more extensive education in the dietetic curricula and to continue education regarding herbal supplements in response to the increasing consumer herbal supplement use.

Adult↗
PubMed2003

Application of ultrasound-based velocity estimate statistics to strain-rate estimation.

Quantification of the relative myocardial deformation rate, or strain rate, is an emerging capability to aid a cardiologist in assessing myocardial function. Ultrasound Doppler techniques can be used to compute tissue motion relative to a transducer. The myocardial strain rate can be computed as the localized spatial derivative of the tissue velocity. Such a strain-rate estimate is typically numerically noisy. We present the relevant speckle statistics to faciliate the computation of the strain rate based on a weighted least squares regression, with statistically appropriate weights.

Child↗
PubMed2004

Sparse kernel density construction using orthogonal forward regression with leave-one-out test score and local regularization.

This paper presents an efficient construction algorithm for obtaining sparse kernel density estimates based on a regression approach that directly optimizes model generalization capability. Computational efficiency of the density construction is ensured using an orthogonal forward regression, and the algorithm incrementally minimizes the leave-one-out test score. A local regularization method is incorporated naturally into the density construction process to further enforce sparsity. An additional advantage of the proposed algorithm is that it is fully automatic and the user is not required to specify any criterion to terminate the density construction procedure. This is in contrast to an existing state-of-art kernel density estimation method using the support vector machine (SVM), where the user is required to specify some critical algorithm parameter. Several examples are included to demonstrate the ability of the proposed algorithm to effectively construct a very sparse kernel density estimate with comparable accuracy to that of the full sample optimized Parzen window density estimate. Our experimental results also demonstrate that the proposed algorithm compares favorably with the SVM method, in terms of both test accuracy and sparsity, for constructing kernel density estimates.

Algorithms↗
PubMed2004

Dynamic analysis of multivariate failure time data.

We present an approach for analyzing internal dependencies in counting processes. This covers the case with repeated events on each of a number of individuals, and more generally, the situation where several processes are observed for each individual. We define dynamic covariates, i.e., covariates depending on the past of the processes. The statistical analysis is performed mainly by the nonparametric additive approach. This yields a method for analyzing multivariate survival data, which is an alternative to the frailty approach. We present cumulative regression plots, statistical tests, residual plots, and a hat matrix plot for studying outliers. A program in R and S-PLUS for analyzing survival data with the additive regression model is available on the web site http://www.med.uio.no/imb/stat/addreg. The program has been developed to fit the counting process framework.

Biometry↗