There’s a database for everything, even uber-operons

I was playing around with Google Scholar’s new citation feature that allowed me to collect my papers in one place easily (worked pretty well, btw, save a few glitches, see below) when I noticed it missed a paper of mine from 2000: “Gene context conservation of a higher order than operons.” The abstract:

Operons, co-transcribed and co-regulated contiguous sets of genes, are poorly conserved over short periods of evolutionary time. The gene order, gene content and regulatory mechanisms of operons can be very different, even in closely related species. Here, we present several lines of evidence which suggest that, although an operon and its individual genes and regulatory structures are rearranged when comparing the genomes of different species, this rearrangement is a conservative process. Genomic rearrangements invariably maintain individual genes in very specific functional and regulatory contexts. We call this conserved context an uber-operon.

The uber-operon. It was my PI’s suggested term. Living and working in Germany at the time, I thought it was kind of funny. Anyway, I never really expanded more than another paper or so on that research and kind of lost track whether that paper resulted in much. I typed in ‘uber-operon’ in google today and found that it’s been cited a few times (88) and, I found this interesting: there have been a few databases built of “uber-operons.”

A Chinese research group created the Uber-Operon Database. The paper looks interesting, but unfortunately the server is down (whether this is temporary or permanent, I do not know), the ODB (Operon Database) uses uber-operons (which they call reference operons) to predict operons in the database , Nebulon is another, HUGO is another. Read the chapter on computational methods for predicting uber-operons :)

Just goes to show you, there’s a database for everything.

Oh, and back to Google Scholar citation. It did find nearly every paper I’ve published, though it missed two (including the one above) and had two false positives. Additionally, many citations are missing (like the 88 for this paper, and many others from other papers). That’s not to say it’s not useful, I find it a nice tool but it’s not perfect. You can find out more about google scholar citation here, and about Microsoft’s similar feature here.

Oh, and does this post put me in the HumbleBrag Hall of Fame? If that’s reserved for twitter, than maybe I should twitter this so I can get there :). (though I’m not sure pointing out relatively small databases based a relatively minor paper constitutes bragging, humbly or not LOL).