« Focus on single-molecule analysis | Main | Going for algorithm gold »

Data overload

How do you handle terabytes of data? That is a question that more and more investigators must face, on a weekly basis.

Are you one of them? Light-sheet fluorescence imaging, for example, generates so much data in each experimental run that handling and storing the raw data is a challenge. Next-generation sequencing is another, much more ubiquitous, case.

Read the July issue editorial “Byte-ing off more than you can chew” and let us know about your own experience, problems and practical (or impractical) solutions.

TrackBack

TrackBack URL for this entry:
http://blogs.nature.com/cgi-bin/mt/mt-tb.cgi/7497

Comments

This is a paramount problem in everyday up-dating as well as researching. Besides all difficulties, the article refers to, there is another problem, unfortunately overlooked, which plays a central role: neither all humans nor all animal are borne equal (e.g. from my website: 115. Stagnaro Sergio. Single Patient Based Medicine: its paramount role in Future Medicine. Public Library of Science. http://medicine.plosjournals.org/perlserv/?request=read-response 2005). In a few words, in spite of a tremendous number of data, it's really difficult to apply them to a single individual!

Post a comment

(If you haven't left a comment here before, you may need to be approved by the site owner before your comment will appear. Until then, it won't appear on the entry. Thanks for waiting.)


Please enter the numbers you see below - this helps us to cut down on spam. If you are having trouble with this system, you can instead e-mail a comment to 'methagora at nature.com'.