Abstract:
: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.
journal_name
Plant Physioljournal_title
Plant physiologyauthors
Jenkins H,Johnson H,Kular B,Wang T,Hardy Ndoi
10.1104/pp.104.058875subject
Has Abstractpub_date
2005-05-01 00:00:00pages
67-77issue
1eissn
0032-0889issn
1532-2548pii
138/1/67journal_volume
138pub_type
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