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At least 109 records · Page 6Linked to original sources
PubMed1989

On the neurobiology of depression: research based on heterogeneous diagnostic groups produces heterogeneous biological data.

An improvement in the accuracy and specificity of the criteria for identifying people with major depressive disorder would be of great benefit not only in the diagnosis and treatment of patients with depression, but also in research concerning the biological substrates of the emotions. Unfortunately, attempts at developing a biological diagnostic test for depression based on the analysis of major depressive disorder patients identified on the basis of existing diagnostic criteria have not been successful. Undoubtedly, this is due in part to the complexity of the neurochemistry and neuroanatomy of the emotions. But more importantly, it is due to the broad global nature of the criteria used to identify depressed patients. This results in the biological study of patients who are similar in general terms but who differ in specific behavioral symptoms and underlying neurobiology. A detailed analysis of the behavior of depressed people might reveal subtle differences that could be used to separate patients with depression into more homogeneous subgroups for biological study. This would increase the probability of developing biological tests that would lead to further refinement in the diagnosis of depression and in the selection of the most appropriate therapeutic intervention for a particular patient.

Animals↗
PubMed1996

Estimating the prevalence of drug use from self-reports in a cohort for which biologic data are available for a subsample.

Diagnostic procedures, used singly or in combination, are crucial in the determination of the presence and prevalence of medical and other conditions. In the absence of a "gold standard," two or more measures or diagnostic tests are often available that may be used to estimate true prevalence. The authors have developed a statistical method with which to calculate more precise estimates of a condition in the presence of two diagnostic measures, one measurement being performed on the entire study sample and a second, more precise one being made in a random sample of the study sample. This method uses the well-known equations which express the probabilities of the four possible outcomes of the two measures in terms of the sensitivities and specificities of the measures and the prevalence of the condition and some properties of maximum likelihood estimates to obtain an expression for the estimated true prevalence and its precision. The method is illustrated by applying it to data collected by urinalysis and self-report in 1992-1993 in a national multisite study-the Cocaine Treatment Outcome Study. Through application of this methodology, a more precise estimate of the true prevalence of substance use can be obtained from two measures, one biologic and the other self-reported. Detailed equations and expressions are provided so that the method can be applied in other situations where diagnostic data from two different sources or procedures are available.

Bias↗
PubMed2005

Putting microarrays in a context: integrated analysis of diverse biological data.

In recent years, multiple types of high-throughput functional genomic data that facilitate rapid functional annotation of sequenced genomes have become available. Gene expression microarrays are the most commonly available source of such data. However, genomic data often sacrifice specificity for scale, yielding very large quantities of relatively lower-quality data than traditional experimental methods. Thus sophisticated analysis methods are necessary to make accurate functional interpretation of these large-scale data sets. This review presents an overview of recently developed methods that integrate the analysis of microarray data with sequence, interaction, localisation and literature data, and further outlines current challenges in the field. The focus of this review is on the use of such methods for gene function prediction, understanding of protein regulation and modelling of biological networks.

Algorithms↗
PubMedDate not supplied

Spectrometric and biological data of 1, N6-ethenoadenosine 3', 5'-cyclic monophosphate.

Spectroscopic properties of 1, N6-ethenoadenosine cyclic 3', 5'-monophosphate were studied and compared with cyclic adenosine 3', 5'-monophosphate. Date of nuclear magnetic resonance-, mass-, ultraviolet-, and fluorescence spectroscopy were given. Additionally biochemical activity was tested in protein kinase system of beef adrenals. No significant biological difference between cyclic adenosine 3', 5'-monophosphate and its fluorescent analog has been found.

Cyclic AMP↗
PubMed1978

[Hemoglobin anomalies and medico-biological data in 10,000 Africans (author's transl)].

Since 1962, the hemoglobin of all the foundation scholars of the French Cooperation addressed to the C.E.A.B.H. for a medical examination at their arrival in France was systematically studied. The distribution and the incidence of hemoglobin S and hemoglobin C were recorded in fourthy ethnic groups from Africa South of Sahara. Few significant correlations between the frequency of anomalies detected by the medico-biological check-up and the presence of an abnormal hemoglobin were found; AC seems to be less asymptomatic than AS. Some rare hemoglobins were detected.

Adult↗
PubMed2002

Biological data integration: wrapping data and tools.

Nowadays scientific data is inevitably digital and stored in a wide variety of formats in heterogeneous systems. Scientists need to access an integrated view of remote or local heterogeneous data sources with advanced data accessing, analyzing, and visualization tools. Building a digital library for scientific data requires accessing and manipulating data extracted from flat files or databases, documents retrieved from the Web as well as data generated by software. We present an approach to wrapping web data sources, databases, flat files, or data generated by tools through a database view mechanism. Generally, a wrapper has two tasks: it first sends a query to the source to retrieve data and, second builds the expected output with respect to the virtual structure. Our wrappers are composed of a retrieval component based on an intermediate object view mechanism called search views mapping the source capabilities to attributes, and an eXtensible Markup Language (XML) engine, respectively, to perform these two tasks. The originality of the approach consists of: 1) a generic view mechanism to access seamlessly data sources with limited capabilities and 2) the ability to wrap data sources as well as the useful specific tools they may provide. Our approach has been developed and demonstrated as part of the multidatabase system supporting queries via uniform object protocol model (OPM) interfaces.

Algorithms↗
PubMed2002

The NCTU BioInfo Archive of biological data sets for bioinformatics research and experimentation.

UNLABELLED: Most of the current bioinformatics literature lacks an explicit and clear description of the data used in experiments when introducing or evaluating computational tools. Without the exact data set that was fed into computational tools in experiments, any mistaken preparation of the data for later experiments may lead to discrepancy in conclusion. The NCTU BioInfo Archive is a new web-based bioinformatic data archive. It serves as a test bed for evaluating computational tools, as a bridge to link other research communities with bioinformatics, and also as an environment full of motivations and possibilities to encourage more exploratory research in bioinformatics. AVAILABILITY: http://bioinfo.cis.nctu.edu.tw

Computational Biology↗
PubMed2006

The Inferelator: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo.

We present a method (the Inferelator) for deriving genome-wide transcriptional regulatory interactions, and apply the method to predict a large portion of the regulatory network of the archaeon Halobacterium NRC-1. The Inferelator uses regression and variable selection to identify transcriptional influences on genes based on the integration of genome annotation and expression data. The learned network successfully predicted Halobacterium's global expression under novel perturbations with predictive power similar to that seen over training data. Several specific regulatory predictions were experimentally tested and verified.

Adenosine Triphosphatases↗
PubMedDate not supplied

Biclustering algorithms for biological data analysis: a survey.

A large number of clustering approaches have been proposed for the analysis of gene expression data obtained from microarray experiments. However, the results from the application of standard clustering methods to genes are limited. This limitation is imposed by the existence of a number of experimental conditions where the activity of genes is uncorrelated. A similar limitation exists when clustering of conditions is performed. For this reason, a number of algorithms that perform simultaneous clustering on the row and column dimensions of the data matrix has been proposed. The goal is to find submatrices, that is, subgroups of genes and subgroups of conditions, where the genes exhibit highly correlated activities for every condition. In this paper, we refer to this class of algorithms as biclustering. Biclustering is also referred in the literature as coclustering and direct clustering, among others names, and has also been used in fields such as information retrieval and data mining. In this comprehensive survey, we analyze a large number of existing approaches to biclustering, and classify them in accordance with the type of biclusters they can find, the patterns of biclusters that are discovered, the methods used to perform the search, the approaches used to evaluate the solution, and the target applications.

Algorithms↗
PubMed2006

Integrating biological data through the genome.

Owing to the ongoing success of the genome sequencing and structural genomics projects, the increase in both sequence and structural data is rapid. The development of tools for the annotation of sequence and structural data has become more important in the hope of keeping up with this data explosion. Scientists in this field have addressed these issues over the last 10 years and there now exists a wealth of methods and approaches to help interpret these data. However, there is no current way in which these methods can be incorporated easily so that the resulting annotations can be viewed together. This review discusses the development of these annotation methods and introduces the BioSapiens Network of Excellence, which has been formed in order to integrate the methods which have been developed in Europe.

Animals↗
PubMed2002

The semantic metadatabase (SEMEDA): ontology based integration of federated molecular biological data sources.

A system for "intelligent" semantic integration and querying of federated databases is being implemented by using three main components: A component which enables SQL access to integrated databases by database federation (MARGBench), an ontology based semantic metadatabase (SEMEDA) and an ontology based query interface (SEMEDA-query). In this publication we explain and demonstrate the principles, architecture and the use of SEMEDA. Since SEMEDA is implemented as 3 tiered web application database providers can enter all relevant semantic and technical information about their databases by themselves via a web browser. SEMEDA' s collaborative ontology editing feature is not restricted to database integration, and might also be useful for ongoing ontology developments, such as the "Gene Ontology" [2]. SEMEDA can be found at http://www-bm.cs.uni-magdeburg.de/semeda/. We explain how this ontologically structured information can be used for semantic database integration. In addition, requirements to ontologies for molecular biological database integration are discussed and relevant existing ontologies are evaluated. We further discuss how ontologies and structured knowledge sources can be used in SEMEDA and whether they can be merged supplemented or updated to meet the requirements for semantic database integration.

Databases, Genetic↗
PubMed2005

Meta-analysis of sex differences in rodent models of learning and memory: a review of behavioral and biological data.

The existence of sex differences in the standard rat and mouse models of learning and memory is a controversial and contested topic in the literature. The present meta-analysis of radial maze and water maze experiments was conducted to assess the reliablility and magnitude of sex effects in the standard rodent models of learning and memory. Data were culled from published and unpublished sources. Findings indicate large reliable male advantages for rats in radial maze and water maze protocols. Significant strain differences were also identified. In each paradigm, protocol variations were associated with differential sex effects. For the water maze, smaller male advantages were associated with pretraining regimens and for the radial maze, larger significant male advantages were observed in protocols that included unbaited arms (combined reference and working memory protocols). Mouse studies exhibited a different pattern of sex effects; small female advantages were evident in the water maze, but small male advantages were evident in the radial maze. Together these findings establish the reliability of male advantages in spatial working and reference memory for rats across strains, protocols, ages and rearing environments. The findings also support an important species dichotomy between rats and mice that should be considered when transitioning from rat to mouse models. In light of these results, the biological evidence supporting theoretical explanations of sex differences is reviewed and evaluated.

Animals↗
PubMed2006

Novel unsupervised feature filtering of biological data.

MOTIVATION: Many methods have been developed for selecting small informative feature subsets in large noisy data. However, unsupervised methods are scarce. Examples are using the variance of data collected for each feature, or the projection of the feature on the first principal component. We propose a novel unsupervised criterion, based on SVD-entropy, selecting a feature according to its contribution to the entropy (CE) calculated on a leave-one-out basis. This can be implemented in four ways: simple ranking according to CE values (SR); forward selection by accumulating features according to which set produces highest entropy (FS1); forward selection by accumulating features through the choice of the best CE out of the remaining ones (FS2); backward elimination (BE) of features with the lowest CE. RESULTS: We apply our methods to different benchmarks. In each case we evaluate the success of clustering the data in the selected feature spaces, by measuring Jaccard scores with respect to known classifications. We demonstrate that feature filtering according to CE outperforms the variance method and gene-shaving. There are cases where the analysis, based on a small set of selected features, outperforms the best score reported when all information was used. Our method calls for an optimal size of the relevant feature set. This turns out to be just a few percents of the number of genes in the two Leukemia datasets that we have analyzed. Moreover, the most favored selected genes turn out to have significant GO enrichment in relevant cellular processes.

Artificial Intelligence↗
PubMed1986

Essential thrombocythemias. Clinical evolutionary and biological data.

This retrospective study reviewed 94 patients, aged 6 to 90 years, with thrombocythemia. The women/men ratio was 1.76. At onset or, less commonly, during the course of the disease, 45% of the patients presented hemorrhagic manifestations, 29% thrombotic complications, and only 14% the association of hemorrhage and thrombosis. The average platelet count was 1200 X 10(9)/1, with no difference according to sex or age. Platelet hypoaggregation was seen in practically all the cases (94%), although myelofibrosis was less frequent (54%). The frequency of hemorrhages increased when the platelet count was above 1000 X 10(9)/1 (P less than 0.01), but the occurrence of thrombosis was correlated neither with platelet count nor with thrombopathy. Survival time was lengthy: 80% of survival (standard error 6%) was observed at 100 months. Transformation to acute leukemia was observed in five patients. Because the disease course is most often prolonged, therapeutic measures must be conservative: anti-aggregating drugs in small doses, and chemotherapy beginning with nonalkylating agents.

Adolescent↗
PubMed2006

Estimation of phospholipophilicity of 1-[3-(arylpiperazin-1-yl)-propyl]-pyrrolidin-2-one derivatives on immobilized artificial membrane stationary phase and its correlation with biological data.

A molecule library containing 42 1-[3-(arylpiperazin-1-yl)-propyl]-pyrrolidin-2-one derivatives has been designed and synthesized. The phospholipophilicity of the obtained compounds has been determined using immobilized artificial membrane high-performance liquid chromatography (IAM-HPLC). The performed analysis allowed the calculation of log k(we) values for each of the tested compounds. Experimental phospholipophilicity data (log k(we)) has been compared with the affinity of the tested compounds to alpha(2)-adrenoceptors. Performed quantitative structure-activity relationship studies indicated that, for the tested compounds, there are dependences between affinity for alpha(2)-adrenoceptors and their log k(we) values. The obtained results confirmed that the applied chromatographic IAM-HPLC method could be useful in fast characterization of the phosholipophilicity of structurally closely related compounds as well as for larger series of compounds, such as drug candidates. It could also be used as a tool for further research into this group of compounds.

Chromatography, High Pressure Liquid↗