Currently operating out of a pilot lab inside Rockefeller University on the Upper East Side, the New York Genome Center is an independent, not-for-profit organization supported by Rockefeller and 10 other big name institutions including Columbia and Mount Sinai Medical Center.
"By pooling their resources they can make sure that the capital investment is constantly being made to keep the new technology on the latest," Kelley says. "The mapping of the human genome project ended in 2003 and cost $3 billion. Today you can sequence it, the whole human genome of an individual in about two weeks for less than $5,000."
The New York Genome Center's new home will be open in April of 2013.
However, the new headquarters would have been impossible were it not for another building, 375 Pearl Street.
The Building That Juices Genomes
"Access to that power is in our view probably worth more than the building because you just can't replicate that infrastructure," said Dave Sabey, CEO of the Seattle-based company.
Much has been said about the city's emergence as a tech hub. Far less attention has been paid to the electricity needed for the ever-growing data demands of business. Few buildings have 375 Pearl's electricity access. One exception is Google's Ninth Avenue building, a former Port Authority headquarters and freight station.
The Pearl Street data center, dubbed Intergate.Manhattan, will ultimately be able to draw as much as 40 megawatts of electricity. The juice will help power the genome center's immense data volume. Each sequenced genome will generate 130 gigabytes. After two years, the center expects to have five petabytes (5 million gigabytes) of info. Most will be stored at Sabey's data warehouses in Washington state (where electricity and space are cheaper) and connected via a secure network to 375 Pearl, which will act as a hub for scientists at the center's Sixth Avenue centerpiece.
The center is a collaborative effort of 11 health care research institutions. "Not one of these research institutions has the money to buy the computing infrastructure necessary to really be able to model these massively complex interactions between genetic communities," Sabey said.
He said other industries, especially finance, are likely to follow suit as these industries becomes ever more data-heavy and speed-dependent.