Literature DB >> 19102773

RPPAML/RIMS: a metadata format and an information management system for reverse phase protein arrays.

Romesh Stanislaus1, Mark Carey, Helena F Deus, Kevin Coombes, Bryan T Hennessy, Gordon B Mills, Jonas S Almeida.   

Abstract

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 1,000 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.
RESULTS: In this report an RPPA Information Management System (RIMS) is described and made available with open source software. In order to implement the proposed system, we propose a metadata format known as reverse phase protein array markup language (RPPAML). RPPAML would enable researchers to describe, document and disseminate RPPA data. The complexity of the data structure needed to describe the results and the graphic tools necessary to visualize them require a software deployment distributed between a client and a server application. This was achieved without sacrificing interoperability between individual deployments through the use of an open source semantic database, S3DB. This data service backbone is available to multiple client side applications that can also access other server side deployments. The RIMS platform was designed to interoperate with other data analysis and data visualization tools such as Cytoscape.
CONCLUSION: The proposed RPPAML data format hopes to standardize RPPA data. Standardization of data would result in diverse client applications being able to operate on the same set of data. Additionally, having data in a standard format would enable data dissemination and data analysis.

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Year:  2008        PMID: 19102773      PMCID: PMC2639439          DOI: 10.1186/1471-2105-9-555

Source DB:  PubMed          Journal:  BMC Bioinformatics        ISSN: 1471-2105            Impact factor:   3.169


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