This Article Full Text Full Text (PDF) Supplemental Data Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in Web of Science Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via CrossRef Citing Articles via Web of Science (13) Citing Articles via Google Scholar Google Scholar Articles by Jenkins, H. Articles by Hardy, N. Search for Related Content PubMed PubMed Citation Articles by Jenkins, H. Articles by Hardy, N. Agricola Articles by Jenkins, H. Articles by Hardy, N.

BIOINFORMATICS-PLANT DATABASES

Toward Supportive Data Collection Tools for Plant Metabolomics^[w]

Department of Computer Science (H. Jenkins, N.H.), and Institute of Biological Sciences (H. Johnson), University of Wales, Penglais, Aberystwyth, Ceredigion, Wales, SY23 3DB, United Kingdom; and John Innes Centre, Norwich Research Park, Colney, Norwich, England, NR4 7UH, United Kingdom (B.K., T.W.)

Over recent years, a number of initiatives have proposed standard reporting guidelines for functional genomics experiments. Associated with these are data models that may be used as the basis of the design of software tools that store and transmit experiment data in standard formats. Central to the success of such data handling tools is their usability. Successful data handling tools are expected to yield benefits in time saving and in quality assurance. Here, we describe the collection of datasets that conform to the recently proposed data model for plant metabolomics known as ArMet (architecture for metabolomics) and illustrate a number of approaches to robust data collection that have been developed in collaboration between software engineers and biologists. These examples also serve to validate ArMet from the data collection perspective by demonstrating that a range of software tools, supporting data recording and data upload to central databases, can be built using the data model as the basis of their design.

www.plantphysiol.org/cgi/doi/10.1104/pp.104.058875.

^* Corresponding author; e-mail nwh{at}aber.ac.uk; fax 44–1970–628536.

Received December 22, 2004; returned for revision March 4, 2005; accepted March 4, 2005.

This article has been cited by other articles:

				H. Neuweger, S. P. Albaum, M. Dondrup, M. Persicke, T. Watt, K. Niehaus, J. Stoye, and A. Goesmann MeltDB: a software platform for the analysis and integration of metabolomics experiment data Bioinformatics, December 1, 2008; 24(23): 2726 - 2732. [Abstract] [Full Text] [PDF]

				I. Baxter, M. Ouzzani, S. Orcun, B. Kennedy, S. S. Jandhyala, and D. E. Salt Purdue Ionomics Information Management System. An Integrated Functional Genomics Platform Plant Physiology, February 1, 2007; 143(2): 600 - 611. [Abstract] [Full Text] [PDF]

				A. L. Castle, O. Fiehn, R. Kaddurah-Daouk, and J. C. Lindon Metabolomics Standards Workshop and the development of international standards for reporting metabolomics experimental results Brief Bioinform, June 1, 2006; 7(2): 159 - 165. [Abstract] [Full Text] [PDF]

				S. Y. Rhee and B. Crosby Biological Databases for Plant Research Plant Physiology, May 1, 2005; 138(1): 1 - 3. [Full Text] [PDF]