How to think about research much different from your own.

As a follow up to my post last week about the value in learning about a breadth of topics, I thought it apropos to briefly describe some of the most profound ways in which my scientific thinking has been altered because of talking about disparate research.

Here's a bit of context. I was trained as an undergrad in molecular systematics of plants. I knew a lot about plant evolution and a little about molecular genetics. What did I learn when I started grad school and had to attend seminars about cellular pathways in mice, or behavior in insects? Here are a few examples.

1. Researchers trained in particular fields approach the narratives of science from different perspectives. The way we ask scientific questions, design experiments, and convey our results differs widely depending on the biological scale and phenomena we're addressing. For example, my tendency towards thinking about organismal evolution is strikingly different from a reductionist view of molecular developmental pathways. These ways of thinking are not mutually exclusive, but sometimes it seems we get stuck in thinking about science the same way. One of my current officemates was trained as a physicist, which results in some pretty eye-opening revelations about biological complexity and uncertainty.
2. You can do really cool science by applying methods from one theoretical background to a novel question from another field. There are some obvious examples of the success of these mash-ups. The modern synthesis, evolutionary development, and systems biology are all examples of uniting previously disparate fields of research. My personal favorite is the application of ecological principles to genomics (some examples are here, here and here).
3. Cross-talk assists in uniting themes in biology that are exclusive of model system. A great example of this point comes from journal club last week. Metagenomic methods borrow largely from those developed by ecologists to evaluate how diversity and abundance of organisms differs between ecosystems. It's pretty obvious to ecologists who work on macro-organisms that the average size of species can factor heavily into their influence on an ecosystem. The same argument can apply for microbes that differ widely in average size, yet biomass is rarely considered in microbial studies. Talking about vastly different study systems helps remove model-system specific bias.

Of course, those are just a few of my favorite vignettes to validate the time I spend thinking about research that isn't directly related to my own. Dare I also say that such thought experiments are also simply fun? Basically, I refuse to let myself be impatient about attending seminars or meeting with visiting scientists if their work is very different from my own. I had a great one-on-one meeting with Darwin historian Alistair Sponsel  a few weeks back when he visited NESCent. We only spoke for half an hour, but the time was constructively spent talking about visualization of different types of data as conveyed across a time scale: certainly important insight for both historians and biologists.

My last point is that understanding a breadth of research helps make your own research deliverables more appealing to a broader audience. Some practical applications are obvious: how to communicate in a seminar to a broad audience, how to convince a panel of experts your grant is worth funding. I'll continue this thought in a few days, focusing on one particular part of our job: peer review.