农作物种质资源调查数据标准制定与共享

系统提取并分析了农作物种质资源普查数据、调查数据、评价数据和保存数据等数据信息,采用基于数据元技术方法制定了农作物种质资源调查数据标准和数据元目录;定义了种质资源调查数据集以及对象和属性的映射关系;给出了基于XML数据标准存储及交换策略。标准的制定使农作物种质资源调查在"数据层"上达到统一,规范了数据库构建,促进了农作物种质资源调查数据的整合和共享。     

Assessment of Data Quality: Errors of Measurement and Errors of Process

As projects progress from pilot studies with few simple variables and small samples, the research process as a whole becomes qualitatively more complex and subject to an array of contamination by errors and mistakes. Data usually undergo a series of manipulations (e.g., recording, computer entry, transmission) prior to final statistical analysis. The process, then, consists of numerous operations only ending with eventual statistical analysis and write-up. We present a means of estimating the impact of process error in the same terms as psychometric reliability and discuss the implications for reducing the impact of errors on overall data quality.     

MEXPRESS: visualizing expression,DNA methylation and clinical TCGA data

Background

In recent years, increasing amounts of genomic and clinical cancer data have become publically available through large-scale collaborative projects such as The Cancer Genome Atlas (TCGA). However, as long as these datasets are difficult to access and interpret, they are essentially useless for a major part of the research community and their scientific potential will not be fully realized. To address these issues we developed MEXPRESS, a straightforward and easy-to-use web tool for the integration and visualization of the expression, DNA methylation and clinical TCGA data on a single-gene level (http://mexpress.be).

Results

In comparison to existing tools, MEXPRESS allows researchers to quickly visualize and interpret the different TCGA datasets and their relationships for a single gene, as demonstrated for GSTP1 in prostate adenocarcinoma. We also used MEXPRESS to reveal the differences in the DNA methylation status of the PAM50 marker gene MLPH between the breast cancer subtypes and how these differences were linked to the expression of MPLH.

Conclusions

We have created a user-friendly tool for the visualization and interpretation of TCGA data, offering clinical researchers a simple way to evaluate the TCGA data for their genes or candidate biomarkers of interest.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1847-z) contains supplementary material, which is available to authorized users.     

Four spatial points that define enzyme families

The catalytic properties of enzymes, containing the Asp-His-Ser triads are deeply investigated for a long time. Serine endopeptidases, cutinases, acetylcholinesterases, cellulases, among other enzymes, contain these triads. We found that solely the geometric properties of just four points in the spatial structure of these enzymes are characteristic to their family (Fig. 3).     

The European Pollen Database: past efforts and current activities

Pollen stratigraphies are the most spatially extensive data available for the reconstruction of past land-cover change. Detailed knowledge of past land-cover is becoming increasingly important to evaluate the present trends in, and drivers of, vegetation composition. The European Pollen Database (EPD) was established in the late 1980s and developed in the early 1990s to provide a structure for archiving, exchanging, and analysing Quaternary pollen data from Europe. It provides a forum for scientists to meet and engage in collaborative investigations or data analysis. In May 2007 several EPD support groups were developed to assist in the task of maintaining and updating the database. The mapping and data accuracy work group (MADCAP) aims to produce an atlas of past plant distributions as detected by pollen analyses in Europe, in order to meet the growing need for this data from palaeoecologists and the wider scientific community. Due to data handling problems in the past, a significant number of EPD datasets have errors. The initial task of the work group, therefore, was a systematic review of pollen sequences, in order to identify and correct errors. The EPD currently (January 2009) archives 1,032 pollen sequences, of which 668 have age-depth models that allow chronological comparison. Many errors have been identified and corrected, or flagged for users, most notably errors in the pollen count data. The application of spatial analyses to pollen data is related to the number of data points that are available for analysis. We therefore take this opportunity to encourage the submission of pollen analytical results to the EPD or other relevant pollen databases. Only in this way will the scientific community be able to gain a better understanding of past vegetation dynamics.     

imzML--a common data format for the flexible exchange and processing of mass spectrometry imaging data

The application of mass spectrometry imaging (MS imaging) is rapidly growing with a constantly increasing number of different instrumental systems and software tools. The data format imzML was developed to allow the flexible and efficient exchange of MS imaging data between different instruments and data analysis software. imzML data is divided in two files which are linked by a universally unique identifier (UUID). Experimental details are stored in an XML file which is based on the HUPO-PSI format mzML. Information is provided in the form of a 'controlled vocabulary' (CV) in order to unequivocally describe the parameters and to avoid redundancy in nomenclature. Mass spectral data are stored in a binary file in order to allow efficient storage. imzML is supported by a growing number of software tools. Users will be no longer limited to proprietary software, but are able to use the processing software best suited for a specific question or application. MS imaging data from different instruments can be converted to imzML and displayed with identical parameters in one software package for easier comparison. All technical details necessary to implement imzML and additional background information is available at www.imzml.org.     

Providing information on environmental change: Data management,discovery and access in the UK Environmental Change Network Data Centre

Development of a clearer understanding of the causes and consequences of environmental change is an important issue globally. The consequent demand for objective, reliable and up-to-date environmental information has led to the establishment of long-term integrated environmental monitoring programmes, including the UK's Environmental Change Network (ECN). Databases form the core information resource for such programmes. The UK Environmental Change Network Data Centre manages data on behalf of ECN (as well as other related UK integrated environmental monitoring networks) and provides a robust and integrated system of information management. This paper describes how data are captured – through standardised protocols and data entry systems – as well more recent approaches such as wireless sensors. Data are managed centrally through a database and GIS. Quality control is built in at all levels of the system. Data are then made accessible through a variety of data access methods – through bespoke web interfaces, as well as third-party data portals. This paper describes the informatics approach of the ECN Data Centre which aims to develop a seamless system of data capture, management and data access interfaces to support research.     

i2dash: Creation of Flexible,Interactive, and Web-based Dashboards for Visualization of Omics Data

Data visualization and interactive data exploration are important aspects of illustrating complex concepts and results from analyses of omics data. A suitable visualization has to be intuitive and accessible. Web-based dashboards have become popular tools for the arrangement, consolidation, and display of such visualizations. However, the combination of automated data processing pipelines handling omics data and dynamically generated, interactive dashboards is poorly solved. Here, we present i2dash, an R package intended to encapsulate functionality for the programmatic creation of customized dashboards. It supports interactive and responsive (linked) visualizations across a set of predefined graphical layouts. i2dash addresses the needs of data analysts/software developers for a tool that is compatible and attachable to any R-based analysis pipeline, thereby fostering the separation of data visualization on one hand and data analysis tasks on the other hand. In addition, the generic design of i2dash enables the development of modular extensions for specific needs. As a proof of principle, we provide an extension of i2dash optimized for single-cell RNA sequencing analysis, supporting the creation of dashboards for the visualization needs of such experiments. Equipped with these features, i2dash is suitable for extensive use in large-scale sequencing/bioinformatics facilities. Along this line, we provide i2dash as a containerized solution, enabling a straightforward large-scale deployment and sharing of dashboards using cloud services. i2dash is freely available via the R package archive CRAN (https://CRAN.R-project.org/package=i2dash).     

PDBToSDF: Create ligand structure files from PDB file

Protein Data Bank (PDB) file contains atomic data for protein and ligand in protein-ligand complexes. Structure data file (SDF) contains data for atoms, bonds, connectivity and coordinates of molecule for ligands. We describe PDBToSDF as a tool to separate the ligand data from pdb file for the calculation of ligand properties like molecular weight, number of hydrogen bond acceptors, hydrogen bond receptors easily.     

A QconCAT informatics pipeline for the analysis, visualization and sharing of absolute quantitative proteomics data

Absolute protein concentration determination is becoming increasingly important in a number of fields including diagnostics, biomarker discovery and systems biology modeling. The recently introduced quantification concatamer methodology provides a novel approach to performing such determinations, and it has been applied to both microbial and mammalian systems. While a number of software tools exist for performing analyses of quantitative data generated by related methodologies such as SILAC, there is currently no analysis package dedicated to the quantification concatamer approach. Furthermore, most tools that are currently available in the field of quantitative proteomics do not manage storage and dissemination of such data sets.     

基于Visual C#语言的DICOM标准医学图像的显示和实现

介绍DICOM3.0医学图像文件的格式和C#语言的特点,首次利用Visual C#语言对该标准的图像进行显示和处理,能够直接读取DICOM格式原始图像数据,并可批量转换成BMP等格式进行处理,此项工作可为医学图像处理研究及相关医学图像软件开发奠定基础。     

A collection of open source applications for mass spectrometry data mining

We present several bioinformatics applications for the identification and quantification of phosphoproteome components by MS. These applications include a front‐end graphical user interface that combines several Thermo RAW formats to MASCOT? Generic Format extractors (EasierMgf), two graphical user interfaces for search engines OMSSA and SEQUEST (OmssaGui and SequestGui), and three applications, one for the management of databases in FASTA format (FastaTools), another for the integration of search results from up to three search engines (Integrator), and another one for the visualization of mass spectra and their corresponding database search results (JsonVisor). These applications were developed to solve some of the common problems found in proteomic and phosphoproteomic data analysis and were integrated in the workflow for data processing and feeding on our LymPHOS database. Applications were designed modularly and can be used standalone. These tools are written in Perl and Python programming languages and are supported on Windows platforms. They are all released under an Open Source Software license and can be freely downloaded from our software repository hosted at GoogleCode.     

Chronobiologic Evaluation of Drug Efficacy in Hypertension

Time-associated variations of blood pressure became accesible due to the modern development of pressure monitoring technology. The data collection and analysis should be standardized and formulated. Time-associated changes of pressure were evaluated not only by nonparametric and conventional but also by parametric and rhythmometric estimation. The reference data (chronodesms) are essential to define the deviant magnitude of pressure. This chronobiologic approach became feasible to quantitate the efficacy of antihypertensive agents in hypertensives.     

EANS-European Aeroallergen Network Server

Summary The setting up of the European Aeroallergen Network Server marks the creation of a central and redily accessible Data Bank aimed to collected the most significant data on allergenic pollen concentration in the air. It is designed to stimulate research as well as to simplify routine work and, in particular, enables all participating countries to get actual or statistical information. It is therefore to be considered as a valid contribution with respect to the working out of forecasting models. The access to the Data Bank is at the same time extremely simple and highly reliable as far as the safeguard of the Author's copyright is concerned.     

Chronobiologic Evaluation of Drug Efficacy in Hypertension

Time-associated variations of blood pressure became accesible due to the modern development of pressure monitoring technology. The data collection and analysis should be standardized and formulated. Time-associated changes of pressure were evaluated not only by nonparametric and conventional but also by parametric and rhythmometric estimation. The reference data (chronodesms) are essential to define the deviant magnitude of pressure. This chronobiologic approach became feasible to quantitate the efficacy of antihypertensive agents in hypertensives.     

Association rule mining based study for identification of clinical parameters akin to occurrence of brain tumor

Healthcare sector is generating a large amount of information corresponding to diagnosis, disease identification and treatment of an individual. Mining knowledge and providing scientific decision-making for the diagnosis & treatment of disease from the clinical dataset is therefore increasingly becoming necessary. Aim of this study was to assess the applicability of knowledge discovery in brain tumor data warehouse, applying data mining techniques for investigation of clinical parameters that can be associated with occurrence of brain tumor. In this study, a brain tumor warehouse was developed comprising of clinical data for 550 patients. Apriori association rule algorithm was applied to discover associative rules among the clinical parameters. The rules discovered in the study suggests - high values of Creatinine, Blood Urea Nitrogen (BUN), SGOT & SGPT to be directly associated with tumor occurrence for patients in the primary stage with atleast 85% confidence and more than 50% support. A normalized regression model is proposed based on these parameters along with Haemoglobin content, Alkaline Phosphatase and Serum Bilirubin for prediction of occurrence of STATE (brain tumor) as 0 (absent) or 1 (present). The results indicate that the methodology followed will be of good value for the diagnostic procedure of brain tumor, especially when large data volumes are involved and screening based on discovered parameters would allow clinicians to detect tumors at an early stage of development.