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1.
Willows: a memory efficient tree and forest construction package   总被引:1,自引:0,他引:1  

Background  

Existing tree and forest methods are powerful bioinformatics tools to explore high dimensional data including high throughput genomic data. However, they cannot deal with the data generated by recent genotyping platforms for single nucleotide polymorphisms due to the massive size of the data and its excessive memory demand.  相似文献   

2.

Background  

A main goal in understanding cell mechanisms is to explain the relationship among genes and related molecular processes through the combined use of technological platforms and bioinformatics analysis. High throughput platforms, such as microarrays, enable the investigation of the whole genome in a single experiment. There exist different kind of microarray platforms, that produce different types of binary data (images and raw data). Moreover, also considering a single vendor, different chips are available. The analysis of microarray data requires an initial preprocessing phase (i.e. normalization and summarization) of raw data that makes them suitable for use on existing platforms, such as the TIGR M4 Suite. Nevertheless, the annotations of data with additional information such as gene function, is needed to perform more powerful analysis. Raw data preprocessing and annotation is often performed in a manual and error prone way. Moreover, many available preprocessing tools do not support annotation. Thus novel, platform independent, and possibly open source tools enabling the semi-automatic preprocessing and annotation of microarray data are needed.  相似文献   

3.

Background  

In systems biology, and many other areas of research, there is a need for the interoperability of tools and data sources that were not originally designed to be integrated. Due to the interdisciplinary nature of systems biology, and its association with high throughput experimental platforms, there is an additional need to continually integrate new technologies. As scientists work in isolated groups, integration with other groups is rarely a consideration when building the required software tools.  相似文献   

4.

Background  

Very often genome-wide data analysis requires the interoperation of multiple databases and analytic tools. A large number of genome databases and bioinformatics applications are available through the web, but it is difficult to automate interoperation because: 1) the platforms on which the applications run are heterogeneous, 2) their web interface is not machine-friendly, 3) they use a non-standard format for data input and output, 4) they do not exploit standards to define application interface and message exchange, and 5) existing protocols for remote messaging are often not firewall-friendly. To overcome these issues, web services have emerged as a standard XML-based model for message exchange between heterogeneous applications. Web services engines have been developed to manage the configuration and execution of a web services workflow.  相似文献   

5.
6.

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   

7.

Background  

The advancements of proteomics technologies have led to a rapid increase in the number, size and rate at which datasets are generated. Managing and extracting valuable information from such datasets requires the use of data management platforms and computational approaches.  相似文献   

8.

Background  

Gene clustering has been widely used to group genes with similar expression pattern in microarray data analysis. Subsequent enrichment analysis using predefined gene sets can provide clues on which functional themes or regulatory sequence motifs are associated with individual gene clusters. In spite of the potential utility, gene clustering and enrichment analysis have been used in separate platforms, thus, the development of integrative algorithm linking both methods is highly challenging.  相似文献   

9.

Background  

Recent studies have shown that copy number variations (CNVs) are frequent in higher eukaryotes and associated with a substantial portion of inherited and acquired risk for various human diseases. The increasing availability of high-resolution genome surveillance platforms provides opportunity for rapidly assessing research and clinical samples for CNV content, as well as for determining the potential pathogenicity of identified variants. However, few informatics tools for accurate and efficient CNV detection and assessment currently exist.  相似文献   

10.

Background  

Reverse Phase Protein Arrays (RPPA) are convenient assay platforms to investigate the presence of biomarkers in tissue lysates. As with other high-throughput technologies, substantial amounts of analytical data are generated. Over 1000 samples may be printed on a single nitrocellulose slide. Up to 100 different proteins may be assessed using immunoperoxidase or immunoflorescence techniques in order to determine relative amounts of protein expression in the samples of interest.  相似文献   

11.

Background  

Microarrays are powerful tools for DNA-based molecular diagnostics and identification of pathogens. Most target a limited range of organisms and are based on only one or a very few genes for specific identification. Such microarrays are limited to organisms for which specific probes are available, and often have difficulty discriminating closely related taxa. We have developed an alternative broad-spectrum microarray that employs hybridisation fingerprints generated by high-density anonymous markers distributed over the entire genome for identification based on comparison to a reference database.  相似文献   

12.

Background  

There is a large amount of microarray data accumulating in public databases, providing various data waiting to be analyzed jointly. Powerful kernel-based methods are commonly used in microarray analyses with support vector machines (SVMs) to approach a wide range of classification problems. However, the standard vectorial data kernel family (linear, RBF, etc.) that takes vectorial data as input, often fails in prediction if the data come from different platforms or laboratories, due to the low gene overlaps or consistencies between the different datasets.  相似文献   

13.

Background  

High-throughput re-sequencing, new genotyping technologies and the availability of reference genomes allow the extensive characterization of Single Nucleotide Polymorphisms (SNPs) and insertion/deletion events (indels) in many plant species. The rapidly increasing amount of re-sequencing and genotyping data generated by large-scale genetic diversity projects requires the development of integrated bioinformatics tools able to efficiently manage, analyze, and combine these genetic data with genome structure and external data.  相似文献   

14.

Background  

Constraint-based models enable structured cellular representations in which intracellular kinetics are circumvented. These models, combined with experimental data, are useful analytical tools to estimate the state exhibited (the phenotype) by the cells at given pseudo-steady conditions.  相似文献   

15.

Background  

Repbase is a reference database of eukaryotic repetitive DNA, which includes prototypic sequences of repeats and basic information described in annotations. Updating and maintenance of the database requires specialized tools, which we have created and made available for use with Repbase, and which may be useful as a template for other curated databases.  相似文献   

16.
Asan  Xu Y  Jiang H  Tyler-Smith C  Xue Y  Jiang T  Wang J  Wu M  Liu X  Tian G  Wang J  Wang J  Yang H  Zhang X 《Genome biology》2011,12(9):R95-12

Background

Exome sequencing, which allows the global analysis of protein coding sequences in the human genome, has become an effective and affordable approach to detecting causative genetic mutations in diseases. Currently, there are several commercial human exome capture platforms; however, the relative performances of these have not been characterized sufficiently to know which is best for a particular study.

Results

We comprehensively compared three platforms: NimbleGen's Sequence Capture Array and SeqCap EZ, and Agilent's SureSelect. We assessed their performance in a variety of ways, including number of genes covered and capture efficacy. Differences that may impact on the choice of platform were that Agilent SureSelect covered approximately 1,100 more genes, while NimbleGen provided better flanking sequence capture. Although all three platforms achieved similar capture specificity of targeted regions, the NimbleGen platforms showed better uniformity of coverage and greater genotype sensitivity at 30- to 100-fold sequencing depth. All three platforms showed similar power in exome SNP calling, including medically relevant SNPs. Compared with genotyping and whole-genome sequencing data, the three platforms achieved a similar accuracy of genotype assignment and SNP detection. Importantly, all three platforms showed similar levels of reproducibility, GC bias and reference allele bias.

Conclusions

We demonstrate key differences between the three platforms, particularly advantages of solutions over array capture and the importance of a large gene target set.  相似文献   

17.

Background  

The majority of information in the biological literature resides in full text articles, instead of abstracts. Yet, abstracts remain the focus of many publicly available literature data mining tools. Most literature mining tools rely on pre-existing lexicons of biological names, often extracted from curated gene or protein databases. This is a limitation, because such databases have low coverage of the many name variants which are used to refer to biological entities in the literature.  相似文献   

18.

Background  

The preprocessing of gene expression data obtained from several platforms routinely includes the aggregation of multiple raw signal intensities to one expression value. Examples are the computation of a single expression measure based on the perfect match (PM) and mismatch (MM) probes for the Affymetrix technology, the summarization of bead level values to bead summary values for the Illumina technology or the aggregation of replicated measurements in the case of other technologies including real-time quantitative polymerase chain reaction (RT-qPCR) platforms. The summarization of technical replicates is also performed in other "-omics" disciplines like proteomics or metabolomics.  相似文献   

19.
20.

Background  

To aid in bioinformatics data processing and analysis, an increasing number of web-based applications are being deployed. Although this is a positive circumstance in general, the proliferation of tools makes it difficult to find the right tool, or more importantly, the right set of tools that can work together to solve real complex problems.  相似文献   

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