Policy ForumMEGASCIENCE

'Omics Data Sharing

Science  09 Oct 2009:
Vol. 326, Issue 5950, pp. 234-236
DOI: 10.1126/science.1180598

You are currently viewing the summary.

View Full Text

Via your Institution

Log in through your institution

Log in through your institution


Summary

Development of high-throughput genomic and postgenomic technologies has caused a change in approaches to data handling and processing (1). One biological sample might be used to generate many kinds of “big” data in parallel, such as genome sequence (genomics), patterns of gene and protein expression (transcriptomics and proteomics), and metabolite concentrations and fluxes (metabolomics). Extensive computer manipulations are required for even basic analyses of such data; the challenges mount further when two or more studies' outputs must be compared or integrated.

Related Content