Metabolomic studies generate large quantities of data. Metabolomics data sets have complex structure and will typically be subjected to a variety of processing and analysis techniques. The data sets are expensive to collect and can be expected to hold more useful information than is extracted and used by the studies, which collected them. These aspects of metabolomics have caused workers to consider, from the very early days of the field, what constitutes comprehensive and well structured metabolomics data, how it should be collected, how it should be transmitted and how, and where it should be stored. It has been generally assumed that the availability of well-curated data sets in standardised formats will pay large dividends for the science. This chapter considers the nature of reporting standards, the benefits that they can yield, existing data standardisation initiatives in metabolomics and related fields and discusses some issue surrounding their development.
|Is-deitl||A Powerful Tool in Systems Biology|
|Golygyddion||Michael C. Jewett, Jens Nielsen|
|Nifer y tudalennau||20|
|Dynodwyr Gwrthrych Digidol (DOIs)|
|Statws||Cyhoeddwyd - 26 Hyd 2007|
|Enw||Topics in Current Genetics Series|
|Cyhoeddwr||Springer Berlin Heidelberg|