Robotic laboratories are becoming commonplace, so computational data analysis has to as well

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It's not news that robots are better at routine experiments than postdocs are: Wikipedia points out, on the page on high-throughput screening, that

Automation is an important element in HTS's usefulness. Typically, an integrated robot system consisting of from one or more robots transports assay microplates from station to station for sample and reagent addition, mixing, incubation, and finally readout or detection. An HTS system can usually prepare, incubate, and analyze many plates simultaneously, further speeding the data-collection process. HTS robots currently exist which can test up to 100,000 compounds per day (Hann 2004). The term uHTS or ultra high throughput screening refers (circa 2008) to screening in excess of 100,000 compounds per day.

No scientist can review this many results by hand, but these methods are medically and technologically very important:

High-throughput screening methods have become essential for sifting through large chemical libraries in search of drug candidates, and several sensitive and reliable analytical techniques have been specifically adapted to high-throughput measurements of biocatalytic activity. High-throughput biocatalytic assay platforms thus enable rapid screening.

So to take advantage of the advances in experimental technique, we need advances in informatics to let us deal with this torrent of data.

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It's not news that robots are better at routine experiments than postdocs are: Wikipedia points out, on the page on high-throughput screening, that

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