The LOLCAT Method

You probably think the title of this post is a joke. Well, it is, but probably not in the way that you think it is.

LOLCAT helping me with SCIENCE!

You see, back in the waning days of my grad student career, I started working with an ambitious and enthusiastic young undergrad named Sagar Indurkhya who wanted to work on better ways to design synthetic biology circuits. I was just getting into the area myself, and our efforts quickly wandered sideways, from work on circuit design to work on simulators. Sagar was using stochastic simulators and found (as many people do) that they were way too slow for his taste. So he went to town on the optimization problem, finding all sorts of crazy ways to improve the speed, from highly general (factoring reactions to improve scaling properties), to super-specialized (making his own specialized virtual machine). Happy with the remarkable improvements in speed that we'd gotten, we decided to write it up and, liking publications without paywalls and having no particular reason to send it anywhere else, we sent it to PLOS ONE.

In the process of writing things up, however, we needed to give the algorithm a name, and one fateful day Sagar asked me: "Can I name it anything?" I said sure, and he continued, "Even something silly, like LOLCAT?" I hesitated, but couldn't really find any particularly good argument against it besides the fact that it was silly, which at the time didn't seem to me to be a sufficient argument against. And if it was a problem, the reviewers would ask us to change it, right?

Not a peep. I just looked back through and found that the reviewers were perfectly happy with our absurd title, engaged seriously with the paper to provide a sound and sober analysis of the LOLCAT method that resulted in significant improvement in manuscript presentation, and then the paper went through for publication. And then I mostly just forgot about it.  I don't use stochastic simulations very often, and when I have it's typically been on much smaller systems, so I just haven't ever had reason to use the work myself.

But others have. I was reminded of the paper this morning, in fact, by a citation alert. After a long period of dormancy, the LOLCAT method is gathering citations as reaction network simulations grow and people are apparently finding it to be of significance in their work. As of this writing, it has received 18 citations---not huge, but definitely showing a significant impact.  I am profoundly ambivalent about this fact: happy that it's a useful piece of work, cringingly embarrassed at my early career naiveté, yet also defiantly proud of our little joke. We didn't even have the good grace to try to make the name an acronym.

It's out there still, and will be in the scientific record forever after, for good or ill: "Reaction Factoring and Bipartite Update Graphs Accelerate the Gillespie Algorithm for Large-Scale Biochemical Systems."  The LOLCAT method.