4 research outputs found

    Construction of a nasopharyngeal carcinoma 2D/MS repository with Open Source XML Database – Xindice

    Get PDF
    BACKGROUND: Many proteomics initiatives require integration of all information with uniformcriteria from collection of samples and data display to publication of experimental results. The integration and exchanging of these data of different formats and structure imposes a great challenge to us. The XML technology presents a promise in handling this task due to its simplicity and flexibility. Nasopharyngeal carcinoma (NPC) is one of the most common cancers in southern China and Southeast Asia, which has marked geographic and racial differences in incidence. Although there are some cancer proteome databases now, there is still no NPC proteome database. RESULTS: The raw NPC proteome experiment data were captured into one XML document with Human Proteome Markup Language (HUP-ML) editor and imported into native XML database Xindice. The 2D/MS repository of NPC proteome was constructed with Apache, PHP and Xindice to provide access to the database via Internet. On our website, two methods, keyword query and click query, were provided at the same time to access the entries of the NPC proteome database. CONCLUSION: Our 2D/MS repository can be used to share the raw NPC proteomics data that are generated from gel-based proteomics experiments. The database, as well as the PHP source codes for constructing users' own proteome repository, can be accessed at

    An analysis of extensible modelling for functional genomics data

    Get PDF
    BACKGROUND: Several data formats have been developed for large scale biological experiments, using a variety of methodologies. Most data formats contain a mechanism for allowing extensions to encode unanticipated data types. Extensions to data formats are important because the experimental methodologies tend to be fairly diverse and rapidly evolving, which hinders the creation of formats that will be stable over time. RESULTS: In this paper we review the data formats that exist in functional genomics, some of which have become de facto or de jure standards, with a particular focus on how each domain has been modelled, and how each format allows extensions. We describe the tasks that are frequently performed over data formats and analyse how well each task is supported by a particular modelling structure. CONCLUSION: From our analysis, we make recommendations as to the types of modelling structure that are most suitable for particular types of experimental annotation. There are several standards currently under development that we believe could benefit from systematically following a set of guidelines

    An object model and database for functional genomics

    No full text
    Motivation: Large-scale functional genomics analysis is now feasible and presents significant challenges in data analysis, storage and querying. Data standards are required to enable the development of public data repositories and to improve data sharing. There is an established data format for microarrays (microarray gene expression markup language, MAGE-ML) and a draft standard for proteomics (PEDRo). We believe that all types of functional genomics experiments should be annotated in a consistent manner, and we hope to open up new ways of comparing multiple datasets used in functional genomics. Results: We have created a functional genomics experiment object model (FGE-OM), developed from the microarray model, MAGE-OM and two models for proteomics, PEDRo and our own model (Gla-PSI—Glasgow Proposal for the Proteomics Standards Initiative). FGE-OM comprises three namespaces representing (i) the parts of the model common to all functional genomics experiments; (ii) microarray-specific components; and (iii) proteomics-specific components. We believe that FGE-OM should initiate discussion about the contents and structure of the next version of MAGE and the future of proteomics standards. A prototype database called RNA And Protein Abundance Database (RAPAD), based on FGE-OM, has been implemented and populated with data from microbial pathogenesis
    corecore