An XML standard for the dissemination of annotated 2D gel electrophoresis data complemented with mass spectrometry results.
BACKGROUND
Many proteomics initiatives require a seamless bioinformatics integration of a range of analytical steps between sample collection and systems modeling immediately assessable to the participants involved in the process. Proteomics profiling by 2D gel electrophoresis to the putative identification of differentially expressed proteins by comparison of mass spectrometry results with reference databases, includes many components of sample processing, not just analysis and interpretation, are regularly revisited and updated. In order for such updates and dissemination of data, a suitable data structure is needed. However, there are no such data structures currently available for the storing of data for multiple gels generated through a single proteomic experiments in a single XML file. This paper proposes a data structure based on XML standards to fill the void that exists between data generated by proteomics experiments and storing of data.


RESULTS
In order to address the resulting procedural fluidity we have adopted and implemented a data model centered on the concept of annotated gel (AG) as the format for delivery and management of 2D Gel electrophoresis results. An eXtensible Markup Language (XML) schema is proposed to manage, analyze and disseminate annotated 2D Gel electrophoresis results. The structure of AG objects is formally represented using XML, resulting in the definition of the AGML syntax presented here.


CONCLUSIONS
The proposed schema accommodates data on the electrophoresis results as well as the mass-spectrometry analysis of selected gel spots. A web-based software library is being developed to handle data storage, analysis and graphic representation. Computational tools described will be made available at http://bioinformatics.musc.edu/agml. Our development of AGML provides a simple data structure for storing 2D gel electrophoresis data.
Stanislaus
Romesh
R
Department of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA. stanisrc@musc.edu
Jiang
Liu Hong
LH
Swartz
Martha
M
Arthur
John
J
Almeida
Jonas S
JS
D019295:Computational Biology / Q000592:standards; D003196:Computer Graphics; D015180:Electrophoresis, Gel, Two-Dimensional / Q000145:classification* / Q000592:standards*; D006801:Humans; D013058:Mass Spectrometry / Q000145:classification / Q000592:standards; D008962:Models, Theoretical; D011381:Programming Languages; D040901:Proteomics / Q000145:classification / Q000379:methods / Q000592:standards; D012015:Reference Standards; D012984:Software; D009626:Terminology as Topic; D014584:User-Computer Interface