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At least 73 records · Page 4Linked to original sources
PubMed2002

Resampling methods for variance estimation of singular value decomposition analyses from microarray experiments.

Microarray experiments offer the ability to generate gene expression measurements for thousands of genes simultaneously. Work has begun recently on attempting to reconstruct genetic networks based on analyses of microarray experiments in time-course studies. An important tool in these analyses has been the singular value decomposition method. However, little work has been done on assessing the variability associated with singular value decomposition analyses. In this report, we discuss use of the bootstrap as a method of obtaining standard errors for singular value decomposition analyses. We consider use of this method both when there are replicates and when no replicates exist. The proposed methods are illustrated with an application to two datasets: one involving a human foreskin study, the other involving yeast.

Algorithms↗
PubMed2005

CiteSpace II: visualization and knowledge discovery in bibliographic databases.

This article presents a description and case study of CiteSpace II, a Java application which supports visual exploration with knowledge discovery in bibliographic databases. Highly cited and pivotal documents, areas of specialization within a knowledge domain, and emergence of research topics are visually mapped through a progressive knowledge domain visualization approach to detecting and visualizing trends and patterns in scientific literature. The test case in this study is progressive knowledge domain visualization of the field of medical informatics. Datasets based on publications from twelve journals in the medical informatics field covering the time period from 1964-2004 were extracted from PubMed and Web of Science (WOS) and developed as testbeds for evaluation of the CiteSpace system. Two resulting document-term co-citation and MeSH term co-occurrence visualizations are qualitatively evaluated for identification of pivotal documents, areas of specialization, and research trends. Practical applications in bio-medical research settings are discussed.

Algorithms↗
PubMed2005

Summary receiver operating characteristic curve analysis techniques in the evaluation of diagnostic tests.

The number of studies in the literature using summary receiver operating characteristic (SROC) analysis of diagnostic accuracy is rising. The SROC is useful in many such meta-analyses, but is often poorly understood by clinicians, and its use can be inappropriate. The academic literature on this topic is not always easy to comprehend. Interpretation is therefore difficult. This report aims to explain the concept of SROC analysis, its advantages, disadvantages, indications, and interpretation for the cardiothoracic surgeon. We use a practical approach to show how SROC analysis can be applied to meta-analysis of diagnostic accuracy by using a contrived dataset of studies on virtual bronchoscopy in the diagnosis of airway lesions.

Airway Obstruction↗
PubMed1996

Population dynamics and global change: the need for new conceptual maps.

The author criticizes current approaches to the study of global population problems as typified by the discussions at the International Conference on Population and Development, held in Cairo, Egypt, in 1994. "Current approaches to population: (1) focus too much on humans and not on their interactions over time with populations of other species; (2) focus too much on the number of humans and not on their differential resource use and environmental impact; (3) accept uncritically the assumptions and concepts of industrial society regarding the nature of progress and the neutrality of technologies, markets, and trade. Broader and more integrated approaches are needed to address current international and global realities and trends." Some conceptual datasets that would illustrate a more effective approach to population problems are introduced.

Data Collection↗
PubMed2006

The experience is CLEAR.

Conventional amphotericin B has been the 'gold standard' for antifungal efficacy, but nephrotoxicity problems limit its clinical utility. In the late 1990s, three lipid-based formulations of amphotericin B were introduced, all of which offered comparable efficacy and reduced renal complications. However, to date, robust safety and comparative efficacy data have been sparse. This paper briefly reviews the available clinical data on amphotericin B lipid complex (ABLC). Also, in detail, it reviews the findings of Collaborative Exchange of Antifungal Research (CLEAR), the most extensive dataset on systemic antifungal treatment with the lipid-based agent ABLC.

Amphotericin B↗
PubMed1998

Random or rational design? Evaluation of diverse compound subsets from chemical structure databases.

The performance of rational design to maximize the structural diversity of databases for lead finding and lead refinement was investigated. Rational methods such as maximum dissimilarity methods or hierarchical cluster analysis for designing compound subsets were compared to a random approach to study their efficiency for an enhancement of the diversity of three different databases. All investigations were done based on 2D fingerprints as a validated molecular descriptor. To compare the performance of the rational selection methods to a random approach, we additionally used probability calculations. When using maximum dissimilarity-based selections, a single compound can be a member of different neighborhoods as defined by the similarity threshold value, while in hierarchical clustering each compound is assigned to only a single cluster. Therefore the relationship between the similarity threshold of the maximum diversity selection method and a 2D similarity search threshold was studied. In contrast to hierarchical clustering analysis, maximum dissimilarity selections allow to use a similarity threshold for adding a new compound to an already selected compound list. Reasonable values for this similarity threshold are presented here. More diverse subsets were designed using maximum dissimilarity selections, which cover more biological classes than using random selections. An optimally diverse subset without redundant structures containing only 38% of one original dataset was generated, where no structure is more similar than 0.85 to its nearest neighbor, but all biological classes were represented. When it is acceptable to cover only 90% of all biological targets, 3.5-3.7 times more compounds need to be selected using a random approach than in a rational design approach. Such coverage rate shows the highest efficiency of design techniques compared to a random approach. In those subsets no compound is closer than 0.70 to its nearest neighbor. Furthermore a comparative molecular field analysis (CoMFA) is used to evaluate designed and randomly chosen subsets for a database consisting of inhibitors of the angiotensin-converting enzyme. It was shown that designed subsets using maximum dissimilarity methods lead to more stable quantitative structure-activity relationship (QSAR) models with higher predictive power compared to randomly chosen compounds. This predictive power is especially high when there is no compound in the test dataset with a similarity coefficient less than 0.7 to its nearest neighbor in the training set.

Databases as Topic↗
PubMed1998

Molecular phylogenetics of finches and sparrows: consequences of character state removal in cytochrome b sequences.

The complete mitochondrial cytochrome b genes of 53 genera of oscine passerine birds representing the major groups of finches and some allies were compared. Phylogenetic trees resulting from three levels of character partition removal (no data removed, transitions at third positions of codons removed, and all transitions removed [transversion parsimony]) were generally concordant, and all supported several basic statements regarding relationships of finches and finch-like birds, including: (1) larks (Alaudidae) show no close relationship to any finch group; (2) Peucedramus (olive warbler) is phylogenetically far removed from true wood warblers; (3) a clade consisting of fringillids, passerids, motacillids, and emberizids is supported, and this clade is characterized by evolution of a vestigial 10th wing primary; and (4) Hawaiian honeycreepers are derived from within the cardueline finches. Excluding transition substitutions at third positions of codons resulted in phylogenetic trees similar to, but with greater bootstrap nodal support than, trees derived using either all data (equally weighted) or transversion parsimony. Relative to the shortest trees obtained using all data, the topologies obtained after elimination of third-position transitions showed only slight increases in realized treelength and homoplasy. These increases were negligable compared to increases in overall nodal support; therefore, this partition removal scheme may enhance recovery of deep phylogenetic signal in protein-coding DNA datasets.

Animals↗
PubMed2003

Mixed discrete and continuous Cox regression model.

The Cox (1972) regression model is extended to include discrete and mixed continuous/discrete failure time data by retaining the multiplicative hazard rate form of the absolutely continuous model. Application of martingale arguments to the regression parameter estimating function show the Breslow(1974) estimator to be consistent and asymptotically Gaussian under this model. A computationally convenient estimator of the variance of the score function can be developed, again using martingale arguments. This estimator reduces to the usual hypergeometric form in the special case of testing equality of several survival curves, and it leads more generally to a convenient consistent variance estimator for the regression parameter. A small simulation study is carried out to study the regression parameter estimator and its variance estimator under the discrete Cox model special case and an application to a bladder cancer recurrence dataset is provided.

Analysis of Variance↗
PubMed2005

Exploiting scale-free information from expression data for cancer classification.

Most studies concerning expression data analyses usually exploit information on the variability of gene intensity across samples. This information is sensitive to initial data processing, which affects the final conclusions. However expression data contains scale-free information, which is directly comparable between different samples. We propose to use the pairwise ratio of gene expression values rather than their absolute intensities for a classification of expression data. This information is stable to data processing and thus more attractive for classification analyses. In proposed schema of data analyses only information on relative gene expression levels in each sample is exploited. Testing on publicly available datasets leads to superior classification results.

Breast Neoplasms↗
PubMed1997

Incremental learning of probabilistic rules from clinical databases based on rough set theory.

Several rule induction methods have been introduced in order to discover meaningful knowledge from databases, including medical domain. However, most of the approaches induce rules from all the data in databases and cannot induce incrementally when new samples are derived. In this paper, a new approach to knowledge acquisition, which induce probabilistic rules incrementally by using rough set technique, is introduced and was evaluated on two clinical databases. The results show that this method induces the same rules as those induced by ordinary non-incremental learning methods, which extract rules from all the datasets, but that the former method requires more computational resources than the latter approach.

Algorithms↗
PubMed2006

Increasing prevalence of HIV-1 protease inhibitor-associated mutations correlates with long-term non-suppressive protease inhibitor treatment.

Treatment of human immunodeficiency virus type 1 with protease inhibitors (PIs) is associated with the emergence of resistance-associated mutations. Treatment-characterized datasets have been used to identify novel treatment-associated protease mutations. In this study, we utilized two large reference laboratory databases (>115,000 viral sequences) to identify non-established resistance-associated protease mutations. We found 20 non-established protease mutations occurring in 82% of viruses with a PI resistance score of 4-7, 62% of viruses with a resistance score of 1-3, and 35% of viruses with no predicted PI resistance. We correlated mutational prevalence to treatment duration in a treatment-characterized dataset of 2161 patients undergoing non-suppressive PI therapy. In the non-suppressed dataset, 24 mutations became more prevalent and three mutations became less prevalent after more than 48 months of non-suppressive PI-therapy. Longer durations of non-suppressive treatment correlated with higher PI resistance scores. Mutations at eight non-established positions that were more common in viruses with the longest duration of non-suppressive therapy were also more common in viruses with the highest PI resistance score. Covariation analysis of 3036 protease amino acid substitutions identified 75 positive and nine negative correlations between resistance associated positions. Our findings support the utility of reference laboratory datasets for surveillance of mutation prevalence and covariation.

Amino Acid Sequence↗
PubMed2006

The impact of presumed consent legislation on cadaveric organ donation: a cross-country study.

In the U.S., Great Britain and in many other countries, the gap between the demand and the supply of human organs for transplantation is on the rise, despite the efforts of governments and health agencies to promote donor registration. In some countries of continental Europe, however, cadaveric organ procurement is based on the principle of presumed consent. Under presumed consent legislation, a deceased individual is classified as a potential donor in absence of explicit opposition to donation before death. This article analyzes the impact of presumed consent laws on donation rates. For this purpose, we construct a dataset on organ donation rates and potential factors affecting organ donation for 22 countries over a 10-year period. We find that while differences in other determinants of organ donation explain much of the variation in donation rates, after controlling for those determinants presumed consent legislation has a positive and sizeable effect on organ donation rates. We use the panel structure of our dataset to test and reject the hypothesis that unmeasured determinants of organ donation rates confound our empirical results.

Cadaver↗
PubMed2004

Influence of microarrays experiments missing values on the stability of gene groups by hierarchical clustering.

BACKGROUND: Microarray technologies produced large amount of data. The hierarchical clustering is commonly used to identify clusters of co-expressed genes. However, microarray datasets often contain missing values (MVs) representing a major drawback for the use of the clustering methods. Usually the MVs are not treated, or replaced by zero or estimated by the k-Nearest Neighbor (kNN) approach. The topic of the paper is to study the stability of gene clusters, defined by various hierarchical clustering algorithms, of microarrays experiments including or not MVs. RESULTS: In this study, we show that the MVs have important effects on the stability of the gene clusters. Moreover, the magnitude of the gene misallocations is depending on the aggregation algorithm. The most appropriate aggregation methods (e.g. complete-linkage and Ward) are highly sensitive to MVs, and surprisingly, for a very tiny proportion of MVs (e.g. 1%). In most of the case, the MVs must be replaced by expected values. The MVs replacement by the kNN approach clearly improves the identification of co-expressed gene clusters. Nevertheless, we observe that kNN approach is less suitable for the extreme values of gene expression. CONCLUSION: The presence of MVs (even at a low rate) is a major factor of gene cluster instability. In addition, the impact depends on the hierarchical clustering algorithm used. Some methods should be used carefully. Nevertheless, the kNN approach constitutes one efficient method for restoring the missing expression gene values, with a low error level. Our study highlights the need of statistical treatments in microarray data to avoid misinterpretation.

Cluster Analysis↗
PubMed2005

Emotion recognition through facial expression analysis based on a neurofuzzy network.

Extracting and validating emotional cues through analysis of users' facial expressions is of high importance for improving the level of interaction in man machine communication systems. Extraction of appropriate facial features and consequent recognition of the user's emotional state that can be robust to facial expression variations among different users is the topic of this paper. Facial animation parameters (FAPs) defined according to the ISO MPEG-4 standard are extracted by a robust facial analysis system, accompanied by appropriate confidence measures of the estimation accuracy. A novel neurofuzzy system is then created, based on rules that have been defined through analysis of FAP variations both at the discrete emotional space, as well as in the 2D continuous activation-evaluation one. The neurofuzzy system allows for further learning and adaptation to specific users' facial expression characteristics, measured though FAP estimation in real life application of the system, using analysis by clustering of the obtained FAP values. Experimental studies with emotionally expressive datasets, generated in the EC IST ERMIS project indicate the good performance and potential of the developed technologies.

Adaptation, Psychological↗
PubMed2006

[Geriatrics in Bavaria-Database (GiB-DAT): Conception, structure and results of implementation (part I)].

In the year 2000, a database was implemented in Bavaria, covering the majority of geriatric clinics. Benchmarking statistics are generated in quarterly periods and scientifically analyzed. Actually, 41 of the 57 geriatric clinics in Bavaria participate in the project 'Geriatrics in Bavaria-Database' (GiB-DAT). For geriatric rehabilitation, the coverage is 82.4%. In addition, all 7 geriatric day clinics participate; thus, a total of 24,000 cases are documented each year. Therefore, GiB-DAT is the largest database for geriatric rehabilitation in Germany and Europe. To make documentation more effective and easy, new software (GERIDOCTM) has been generated which is integrated in the process of daily treatment. GiB-DAT offers good data quality, especially concerning completeness of items. This manuscript describes conception and construction of GiB-DAT and identifies differences compared to the Geriatric Minimum-Dataset (GEMIDAS), a nationwide geriatric database in Germany.

Aged↗
PubMed2005

Web-based distributed data management in the childhood asthma research and education (CARE) network.

A well-designed distributed data management application provides an efficient, effective process to collect quality data in multicenter clinical trials. This paper describes the web-based clinical center data management application that was developed by the Data Coordinating Center of the Childhood Asthma Research and Education (CARE) Network. A series of modules was designed to allow the clinical staff at the remote clinical centers to enter clinical trial data, correct entry errors, respond to queries from the Data Coordinating Center, and submit data corrections for previously entered data to ultimately provide a clean and accurate dataset for analysis.

Adolescent↗
PubMed2005

Visual exploration of landmarks and trends in the medical informatics literature.

This study presents preliminary results from a visual study of a new dataset of forty years of citation data from publications of twelve journals in the medical informatics field covering the time period from 1964-2004. Highly cited and pivotal documents, areas of specialization within medical informatics, and emergence of research topics are visually mapped through a progressive knowledge domain visualization approach to detecting and visualizing trends and patterns in scientific literature.

Bibliometrics↗
PubMed1997

Better prediction of protein cellular localization sites with the k nearest neighbors classifier.

We have compared four classifiers on the problem of predicting the cellular localization sites of proteins in yeast and E. coli. A set of sequence derived features, such as regions of high hydrophobicity, were used for each classifier. The methods compared were a structured probabilistic model specifically designed for the localization problem, the k nearest neighbors classifier, the binary decision tree classifier, and the naïve Bayes classifier. The result of tests using stratified cross validation shows the k nearest neighbors classifier to perform better than the other methods. In the case of yeast this difference was statistically significant using a cross-validated paired t test. The result is an accuracy of approximately 60% for 10 yeast classes and 86% for 8 E. coli classes. The best previously reported accuracies for these datasets were 55% and 81% respectively.

Algorithms↗