A catalysis meeting on long term experimental evolution.

Travel makes it easy to let blog posts slip away without being fully formed, written, and posted. Now that the semester is winding down, I'm going to try and follow through with writing the backlog of posts that have been piling up from my adventures over the last few weeks. Today's report is about the first part of my trip back to NESCent and North Carolina the week before Thanksgiving.

The catalysis meeting I attended on long term experimental evolution (you can read a little more about the meeting and participants here) was not only fantastic but also the last NESCent will host (more on this in a later post). Although the topic is outside of my main research interests, I answered the solicitation to participate in this meeting because of some research I've been doing with Joe Graves, Michael Rose and colleagues on experimentally evolved Drosophila populations. Moreover, there seem to be some really interesting opportunities to explore robustness of analytical methods using experimental evolution data, which is of particular interest to me.

Here are the things I found compelling about this meeting:

1. Meeting organizers set the tone. Rob Lanfear, the main organizer, put together a fantastic webpage and started a Mendeley group so we could share literature beforehand.
2. The participants were diverse. Forty four percent of attendees were female. There were graduate students, postdocs, early career scientists, and senior researchers present, and folks came from all over the world. Model systems included microbes, invertebrates, fish and trees. 
3. We capitalized on the group's diversity. As an early career scientist, I was pleased to develop relationships with a number of other folks starting faculty jobs at similar institutions. As a group, I was gratified to hear well-respected, senior scientists describing junior scientists' research as "brilliant." There were multiple types of interactions incorporated into the meetings such that folks who were hesitant to speak in full-group discussions could still contribute ideas. In short, this meeting exhibited many aspects of scientific discourse that are overlooked, but which I value deeply.
4. Attendees were invested in the meeting itself. Part of the meeting was structured (or perhaps more accurately, unstructured) as an "unconference," with participants determining topics for talks and group discussions on the fly. Despite this free-form format, folks in this group were very interested in talking about broader research ideas, rather than pushing their own agendas.

I left the meeting with a much wider and deeper understanding of experimental evolution as an active field of research, as well as a better grasp on different ways of thinking about the process of science and its limitations. I was also grateful to participate in one last meeting of this type at NESCent...stay tuned for my next post to hear more about that!

Casting a wide net.

I was fortunate as a post-doc at NESCent to have a huge community of like-minded scholars to help me develop intellectually. I'm still very fortunate to be surrounded by folks doing awesome research, but I was hired specifically to fill a missing niche (bioinformatics) in the department. That means I need to work extra hard to find ways to connect with my new students and colleagues. While my skills are definitely desired and I have lots to contribute, many things I'm doing simply haven't been done here before, so I'm thinking creatively about how to fit in on campus. I'm doing my best to think broadly (cast a wide net), while at the same time focusing my time and energy on tasks that will have an impact (and hopefully catch a few big fish).

The benefit of working as a bioinformaticist is that I can work with anyone who has data (hint: that means pretty much everyone). My specialty as a genomicist also makes me well suited for the emerging interests of other folks on campus. I've been sitting down to talk to lots of folks about opportunities for collaboration on such projects. It's incredibly interesting to learn about different model systems, and gratifying to know that I can contribute to such a breadth of projects. At the very least, I can save folks time by providing a bit of information in current genome assembly methods, for instance.

It's easy enough to work with folks in other science departments, but I've been casting an even wider net. I was delighted when a friend from the history department came over for a chat about filtering data. He had a large digital dataset of documents and was looking through them for a particular type of data. Luckily, that type of data was always described with a particular string of text. Three lines of bash scripting later, and we managed to save him days of work. I've long been interested in these broad approaches to academia, and even attended a THATCamp meeting at NCState several months back. My brain works best when building connections between seemingly disparate ideas, so a little bit of my time in pursuing small projects like that helps keep me happy.

The unexpected returns are also nice: getting to know folks over in nursing, for example, let me know about better ways to teach in ways for which they are distinguished: applied methods (for which bioinformatics certainly applies) as well as online classes. At the risk of extending the metaphor too far, casting a wide net is making the fishing expedition of research and academia more appealing to me.