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Scoop.it!
Until recently, the wet lab has been a crucial component of every biologist. Today's advances in the production of massive amounts of data and the creation of machine-learning algorithms for processing that data are changing the face of biological science—making it possible to do real science without a wet lab. David Heckerman shares several examples of how this transformation in the area of genomics is changing the pace of scientific breakthroughs. Via Szabolcs Kósa, Dr. Stefan Gruenwald 
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Scoop.it!
A dream of scientists has been to visualize details of structures within our cells in real time, a breakthrough that would greatly aid in the study of their function. However, even the best of current microscopes can take minutes to recreate images of the internal machinery of cells at a usable resolution. Thanks to a technical tour de force, Yale University researchers can now generate accurate images of sub-cellular structures in milliseconds rather than minutes.
This image of microtubules, which act as a cellular scaffolding, was captured in just 33 milliseconds. “We can now see research come to life and tackle complex questions or conditions which require hundreds of images, something we have not been able to do before,” said Joerg Bewersdorf, assistant professor of cell biology and biomedical engineering and senior author of the research, published in the journal Nature Methods. Via Dr. Stefan Gruenwald
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This 36 min video is well worth the time spent - to get an idea (hopefully a transferrable one) about Big Data and the frontiers of science. In this case both "wet lab" (test tubes microscopes) and "dry lab" (computer modeling with machine learning) and needed and so is content as well as computational literacy.