共查询到20条相似文献,搜索用时 15 毫秒
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Max A Little Patrick E McSharry Stephen J Roberts Declan AE Costello Irene M Moroz 《Biomedical engineering online》2007,6(1):23
Background
Voice disorders affect patients profoundly, and acoustic tools can potentially measure voice function objectively. Disordered sustained vowels exhibit wide-ranging phenomena, from nearly periodic to highly complex, aperiodic vibrations, and increased "breathiness". Modelling and surrogate data studies have shown significant nonlinear and non-Gaussian random properties in these sounds. Nonetheless, existing tools are limited to analysing voices displaying near periodicity, and do not account for this inherent biophysical nonlinearity and non-Gaussian randomness, often using linear signal processing methods insensitive to these properties. They do not directly measure the two main biophysical symptoms of disorder: complex nonlinear aperiodicity, and turbulent, aeroacoustic, non-Gaussian randomness. Often these tools cannot be applied to more severe disordered voices, limiting their clinical usefulness. 相似文献3.
Background
To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In addition, gene expression analyses focus on individual probes and genes with little or no consideration of pathways. These approaches reveal little information about pathways that are key to a full understanding of the building blocks of biological systems. Therefore, there is a need to provide useful tools that can generate pathways without manually building images and allow gene expression data to be integrated and analyzed at pathway levels for such experimental organisms as Arabidopsis. 相似文献4.
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Thomas Naiser Oliver Ehler Jona Kayser Timo Mai Wolfgang Michel Albrecht Ott 《BMC biotechnology》2008,8(1):48
Background
The high binding specificity of short 10 to 30 mer oligonucleotide probes enables single base mismatch (MM) discrimination and thus provides the basis for genotyping and resequencing microarray applications. Recent experiments indicate that the underlying principles governing DNA microarray hybridization – and in particular MM discrimination – are not completely understood. Microarrays usually address complex mixtures of DNA targets. In order to reduce the level of complexity and to study the problem of surface-based hybridization with point defects in more detail, we performed array based hybridization experiments in well controlled and simple situations. 相似文献6.
Background
The integration of genomic information with quantitative experimental data is a key component of systems biology. An increasing number of microbial genomes are being sequenced, leading to an increasing amount of data from post-genomics technologies. The genomes of prokaryotes contain many structures of interest, such as operons, pathogenicity islands and prophage sequences, whose behaviour is of interest during infection and disease. There is a need for simple and novel tools to display and analyse data from these integrated datasets, and we have developed ProGenExpress as a tool for visualising arbitrarily complex numerical data in the context of prokaryotic genomes. 相似文献7.
Background
Chromatin immunoprecipitation followed by microarray hybridization (ChIP-chip) is used to study protein-DNA interactions and histone modifications on a genome-scale. To ensure data quality, these experiments are usually performed in replicates, and a correlation coefficient between replicates is used often to assess reproducibility. However, the correlation coefficient can be misleading because it is affected not only by the reproducibility of the signal but also by the amount of binding signal present in the data. 相似文献8.
Florent Baty Daniel Jaeger Frank Preiswerk Martin M Schumacher Martin H Brutsche 《BMC bioinformatics》2008,9(1):289
Background
Multivariate ordination methods are powerful tools for the exploration of complex data structures present in microarray data. These methods have several advantages compared to common gene-by-gene approaches. However, due to their exploratory nature, multivariate ordination methods do not allow direct statistical testing of the stability of genes. 相似文献9.
Background
Biochemical networks play an essential role in systems biology. Rapidly growing network data and versatile research activities call for convenient visualization tools to aid intuitively perceiving abstract structures of networks and gaining insights into the functional implications of networks. There are various kinds of network visualization software, but they are usually not adequate for visual analysis of complex biological networks mainly because of the two reasons: 1) most existing drawing methods suitable for biochemical networks have high computation loads and can hardly achieve near real-time visualization; 2) available network visualization tools are designed for working in certain network modeling platforms, so they are not convenient for general analyses due to lack of broader range of readily accessible numerical utilities. 相似文献10.
Background
Procedures for genetic analyses based on oligonucleotide probes are powerful tools that can allow highly parallel investigations of genetic material. Such procedures require the design of large sets of probes using application-specific design constraints. 相似文献11.
Philipp N Seibel Jan Krüger Sven Hartmeier Knut Schwarzer Kai L?wenthal Henning Mersch Thomas Dandekar Robert Giegerich 《BMC bioinformatics》2006,7(1):490
Background
Today, there is a growing need in bioinformatics to combine available software tools into chains, thus building complex applications from existing single-task tools. To create such workflows, the tools involved have to be able to work with each other's data – therefore, a common set of well-defined data formats is needed. Unfortunately, current bioinformatic tools use a great variety of heterogeneous formats. 相似文献12.
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Oliver Keller Florian Odronitz Mario Stanke Martin Kollmar Stephan Waack 《BMC bioinformatics》2008,9(1):278
Background
For many types of analyses, data about gene structure and locations of non-coding regions of genes are required. Although a vast amount of genomic sequence data is available, precise annotation of genes is lacking behind. Finding the corresponding gene of a given protein sequence by means of conventional tools is error prone, and cannot be completed without manual inspection, which is time consuming and requires considerable experience. 相似文献14.
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Background
The construction of complex spatial simulation models such as those used in network epidemiology, is a daunting task due to the large amount of data involved in their parameterization. Such data, which frequently resides on large geo-referenced databases, has to be processed and assigned to the various components of the model. All this just to construct the model, then it still has to be simulated and analyzed under different epidemiological scenarios. This workflow can only be achieved efficiently by computational tools that can automate most, if not all, these time-consuming tasks. In this paper, we present a simulation software, Epigrass, aimed to help designing and simulating network-epidemic models with any kind of node behavior. 相似文献16.
Marc Bruckskotten Mario Looso Franz Cemiĉ Anne Konzer Jürgen Hemberger Marcus Krüger Thomas Braun 《BMC bioinformatics》2010,11(1):336
Background
Several tools have been developed to explore and search Gene Ontology (GO) databases allowing efficient GO enrichment analysis and GO tree visualization. Nevertheless, identification of highly specific GO-terms in complex data sets is relatively complicated and the display of GO term assignments and GO enrichment analysis by simple tables or pie charts is not optimal. Valuable information such as the hierarchical position of a single GO term within the GO tree (topological ordering), or enrichment within a complex set of biological experiments is not displayed. Pie charts based on GO tree levels are, themselves, one-dimensional graphs, which cannot properly or efficiently represent the hierarchical specificity for the biological system being studied. 相似文献17.
Schneider J Buness A Huber W Volz J Kioschis P Hafner M Poustka A Sültmann H 《BMC genomics》2004,5(1):29-9
Background
The requirement of a large amount of high-quality RNA is a major limiting factor for microarray experiments using biopsies. An average microarray experiment requires 10–100 μg of RNA. However, due to their small size, most biopsies do not yield this amount. Several different approaches for RNA amplificationin vitrohave been described and applied for microarray studies. In most of these, systematic analyses of the potential bias introduced by the enzymatic modifications are lacking. 相似文献18.
Background
Genome wide microarray studies have the potential to unveil novel disease entities. Clinically homogeneous groups of patients can have diverse gene expression profiles. The definition of novel subclasses based on gene expression is a difficult problem not addressed systematically by currently available software tools. 相似文献19.
Yadhu?Kumar Ralf?Westram Sebastian?Behrens Bernhard?Fuchs Frank?Oliver?Gl?ckner Rudolf?Amann Harald?Meier Wolfgang?Ludwig
Background
Taxon specific hybridization probes in combination with a variety of commonly used hybridization formats nowadays are standard tools in microbial identification. A frequently applied technology, fluorescence in situ hybridization (FISH), besides single cell identification, allows the localization and functional studies of the microbial community composition. Careful in silico design and evaluation of potential oligonucleotide probe targets is therefore crucial for performing successful hybridization experiments. 相似文献20.