Thursday, January 16, 2014

Storytelling in science

There were just a couple of interesting pieces on storytelling in science on Nature Methods (point, counterpoint). Basically, one article says that storytelling is an important part of communicating science, and the rebuttal points out many of the dangers of the storytelling viewpoint. I think these writings put forth many of the basic aspects of the debate: storytelling makes things simpler and more compelling for the reader, increasing interest in and broadening the audience for your work, but storytelling also disfavors alternative hypotheses, unbiased presentation of the data (i.e., non-conforming data = supplementary figure 38) and so forth. All valid points, and I’m sort of on the fence about storytelling.

Here are some thoughts on the matter that they didn’t really touch upon very much in these articles, though. Firstly, although I haven’t read nearly as many papers in other fields, I think that biology has a lot more storytelling than other fields. For instance, you might read a chemistry paper about the photostability of fluorescent dyes. No real story, but the work can be extremely high impact. I’m wondering if the reason we have more stories in biology is that, unlike in other fields, the universe of things you could study is so large that you have to devote a pretty significant portion of your thinking to explaining why you chose to study what you studied; i.e., why is this interesting? I could be completely wrong about this, but in physics, I think there are just fewer different (non-applied) phenomena to study, and so you don’t have to have a story–nobody would question why you study dark matter or the Higg’s Boson. In principle, I like the idea that one could just measure things in biology for the sake of filling in the knowledge of the universe, but in reality, I think we’ve all seen those “so what’s the point of this?” papers. On the other hand, it’s hard to really know the point of anything; we just make stories about how it could be important because of evolution, which is sort of a cop out. Anyway, I’m not sure which way I stand on this.

One other argument I have against storytelling is something fundamental to the very idea of storytelling, namely that a story has a beginning, middle, and an end. It’s the last part that’s the problem. By definition, the end means that it’s all wrapped up. Where does it go from there? What avenues do these results open to further study? In a way, the more satisfying the end, the less need for a follow up. Take, for example, our 2010 C. elegans paper with the title “Variability in gene expression underlies incomplete penetrance”. Well, the title pretty much sums it up. So what do we do from there? I guess you can find more examples of it to test the generality of the conclusion and so forth, but that’s definitely diminishing returns and not exactly how you want to start a new lab. Don’t get me wrong, I like that work a lot, but to me, it felt like that story had an end and I didn’t know where to go from there. Maybe that’s my own lack of imagination, though–any thoughts? On the other hand, our PLoS Bio 2006 paper was much more open ended, and I think it had a much broader impact. There, we characterized a phenomenon (transcriptional bursting and cell-to-cell variability) and made some measurements of it, which raised some interesting possibilities.

Which leads me to another few observations about biology and storytelling. In physics, you can make measurements of something important (like the g factor) and the results are meaningful without a story. In biology, it is very hard to make absolute measurements of something, so everything must be relative, like LGR5 is 5 fold more abundant in condition A than condition B. Even with RNA FISH, which does give absolutes, the context could be different ("oh, you used this media prepared on this day, which is why you got a different answer”). So there are no biological “constants” to measure. Maybe you could argue that measuring crystal structures is like measuring biological constants? Certainly not the endless compendiums of high throughput RNA abundance data, which are not really very good resources for a variety of reasons.

Another thing about biology is that the tools and approaches render negative results far less meaningful than positive results. The storytelling approach (as Gautham pointed out) is one in which you experiment based on “Wouldn’t it be cool if X?”, whereas the opposite result of “not X” would be considerably less cool. In principle, shouldn’t the negative be equally informative? In some cases, yes. But what about a genetic screen? What is the meaning of a negative result? Not much, I think. But Gautham’s point is well-taken. I think it’s a lot better to go about asking questions for which the answer is cool either way. Or, let’s say, where the answer is interesting either way. I never really was good at knowing what was cool to begin with.

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