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The Bloombergs of Genomics

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This month we start with a question. What do Incyte’s Randy Scott, Celera’s Craig Venter, and Gene Logic’s Mike Brennan all have in common? Well, you know, aside from that.

At one time or another each has invoked the name of “Bloomberg” in describing his company’s business goals. In a nutshell, each in his own way would like his company to become the “Bloomberg of genomics” ¯ whatever that is.

Any metaphor so pervasive deserves closer examination, so here goes. To start with, what is a Bloomberg, anyway?

Most Americans who know of the Bloomberg organization know it as a provider of financial news on air, in print, and online, or have heard of Michael Bloomberg, its high-profile founder. But to financial professionals on Wall Street and in other global trading centers, Bloomberg is one of the world’s two major integrators of financial market data and related information. (The other one is Reuters, the venerable British news agency-turned-Internet powerhouse.)

That there might also be a “Bloomberg of genomics” carries several implications. Consider two. The first is that somehow the problem of consolidating and delivering vast quantities of financial data is like the problem of consolidating and delivering vast quantities of biological data. The second is that life sciences companies are prepared to fork over several billion dollars a year for database subscriptions, just like the big firms on Wall Street. (In the case of Bloomberg, an annual license for a single user costs well over $10,000, considerably more than a top-of-the-line DoubleTwist subscription.)

With regard to the first, the problem of data integration in genomics has turned out to be a recurring theme in this issue of Genome Technology (see, for example, Nat Goodman on p. 42). For Bloomberg the trick is to integrate real-time prices with historical data, news, research, earnings forecasts, indexes, SEC filings, and analytical software. The user then gets everything on one device at the desktop, can navigate among related databases with just a few keystrokes, can compare multiple investments or potential transactions, and can roll up everything into a report.

The technical challenges include the troublesome facts that (a) some of the data is changing second-by-second, (b) the relevant databases are all over the place, with some widely available and some highly proprietary, (c) few standards exist for naming the millions of financial instruments that have to be covered, and (d) the users (a demanding bunch) are scattered around the globe. Bloomberg does a good job at all of this ¯ not just for the mainstream stocks traded on US markets but also for bonds and currencies traded in remote corners of the world.

If you push it, the metaphor breaks down pretty quickly. Comparing the yields on two bonds is not the same as comparing the functions of two genes. Nonetheless, the scope of technology infrastructure that is needed to deliver the goods may not be that different. Bloomberg employs armies of programmers, maintains data centers throughout the world and provides 24/7 technical support for tens of thousands of users across all time zones. Could the “Bloomberg of genomics” get away with less?

The answer to that question ultimately depends on the customers’ willingness to pay, which is the second leg of the metaphor. Financial institutions have a long tradition of spending lots of money to access external databases. They need the data to do business and so they pay for it. (The current tab is about $5 billion a year, with most of that going to Bloomberg and Reuters.) This has given financial database vendors the resources and scale to make their data clean and well integrated and their applications robust and highly functional.

There is no comparable tradition in life sciences research, not in the private sector and certainly not in the academic sector where, if anything, the tradition is dirty, disjointed, and free. Revenue-wise, Bloomberg by itself is already an order of magnitude bigger than Incyte, Celera, and Gene Logic put together. So what of these would-be Bloombergs of genomics? Are they just blowing smoke?

We at GenomeWeb, perched, coincidentally, two blocks off Wall Street, are betting that they are not ¯ that sooner or later one or more Bloombergs of genomics will come into existence. True, we’ve barely begun to see the shift in business culture necessary to make it happen. Biology is becoming an information science, but spending big money on the quality and utility of information is not yet a matter of routine. If anything, it is that shift in business culture that defines what the new biology is all about.

Dennis P. Waters

 

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