Research

My research focus:
I’m a life sciences doctoral student at Virginia Commonwealth University. I’m working on a massive project at the moment: that is, I study protein-protein interactions across hundreds of species of bacteria at once. I’m interested in how changes in interaction patterns drive microbial evolution and vice-versa. It’s an especially thorny problem that requires me to apply molecular biology and bioinformatics skills. If you also study this subject or even if you'd just like to know more, please contact me at the following address:
caufieldjh@vcu.edu.
I'm always glad to hear about new research, postdoc opportunities, or good jokes.

On networks of the social variety

It's a strange time when I'm feeling better about Facebook and more uncertain about more specific social networks. In theory, the Book of Faces really is the internet's Walmart: it's a place to get all your social interaction needs as long as your needs aren't too specific. It's great for small talk but actually quite inefficient for any kind of extensive dialogue (to see what I mean, try picturing your next Facebook comment thread as a real-life conversation. It gets pretty difficult in those 10+ comment rigmaroles). The same goes for Twitter.* Even so, there's something to be said for small talk. It's better than no talk at all.

The constant level of background chatter is also preferable to noise with a perceived sense of urgency. In real-life terms, I'm talking about ringing phones, ambulance sirens, or other warning klaxons. These are notifications designed to get your intention; they signal immediacy and the need for rapid action. That phone isn't going to ring all day and that ambulance may need the road you're on. A bit of that urgency shows up in email and social networking messages. In each case, we see a tally indicating how many new requests for our attention there are today. Most of those cases aren't even as urgent as a ringing phone. We can ignore most of what happens on Facebook without any cost.

I've been trying out Researchgate over the past few weeks. It's one of the smaller, more specific social networks I alluded to above. It came strongly recommended by folks in my personal development class. Researchgate is essentially a social network specifically for scientists. Each user has a profile as with other sites, but the focus is less on their biographic details and more on their scientific accomplishments (read: publications). The site is well-designed and leverages a more natural approach to networking than sites like Linkedin do. Connection suggestions are frequent but appear to be weighted in favor of real-world contexts (i.e., colleagues in your department, people in your field, or authors you've cited) rather than a largely generic network structure.

The mildly irritating part about Researchgate is the question-and-answer portion. Much like Stackoverflow, it's a forum for technical questions sorted by method or scientific topic. Unlike Stackoverflow (or even Reddit, for that matter), the moderation is minimal. Many questions are hardly questions at all. I can excuse the lack of English proficiency in many cases but it renders many questions impossible to interpret. In other cases, the phrasing is nearly perfect but the question asker fails to provide anything but the most basic details. The worst part may be the sense of urgency: these questions give the impression that entire careers are on the line. A wrong answer, employed in earnest, may waste weeks or even months of valuable research time. I know it isn't my fault if people don't know how to ask helpful questions or how to take advice from internet strangers.** Social networks are just enough of a potential waste of time as it is.


*I'd suggest that Twitter is the Starbucks of social interaction. It's ubiquitous, frequently noisy, and redolent with fashionable credibility, yet even the people who use it often don't seem to devote much mindspace to it. It's usually pleasant yet generally forgettable.

**This is the way.


Additional note to self: don't forget that Biostars exists. It's Stackoverflow for bioinformatics.

Today I found out about the grid.arrange function for R (it's in the gridExtra package). It's one of those things which would have been useful to know about years ago. I just found it on a Stackoverflow answer today. The function just takes plots and squishes them together into a single canvas. It's easy, too: just enter

grid.arrange(p1, p2, nrow=2)

and you have everything in one place. The results look great with ggplot's faceting, too!
The extensive package library is absolutely one of the nicest things about R.

Despite the absolutely ideal weather this past weekend*, I spent a small chunk of time beginning to learn Ruby. The programming language itself seems fun and friendly; it's billed as a conceptual hybrid of Perl and Python with the object-oriented nature of something like Java. There are a few reasons why I'd like to learn the language:

1. Learning new programming languages enhances understanding of the others. My Perl and Python can always be improved.
2. I've seen a few bioinformatics-related job postings lately which specifically mention the desirability of Ruby experience. They're usually talking about Ruby on Rails and its use in web development. 
3. It's either that or go back to learning Haskell. As far as learning a new language goes, most programmers seem to take Ruby seriously, at least.

I do have a few concerns.

1. Is Ruby (or Rails) becoming obsolete? There's clearly room for a great diversity of frameworks in the scope of web application development. I'm also not qualified to answer such a question. Programming is just one of those areas where a newly-learned language or skill can quickly become a dusty relic. Every framework might as well be Esperanto in the long run: they all have their strengths, even if the only strength is facilitating communication between the right people.
2. Will I ever really need to know Ruby (or Rails)? This question is even more difficult to answer, but I'll give it a try: "probably not." There will always be someone with better code than mine and it may even be in a different language or even an entirely different framework (for all I know, even scientific applications will be most frequently run in a mobile OS in a decade from now). 

Learning for fun seems like the best plan of attack. I can do it at my own pace without worrying about how applicable it is to Doing Bioinformatics. I'll just have the background to know it when I see it. 

*Here's a shot of the grounds at the University of Virginia.

Brooks Hall.

I've been enjoying the short "Futures" science fiction stories in Nature since they started. They tend to be concise, punchy, taut, and perfectly suited for the science-savvy audience. The most recent entry, "How Kameron Layas rode out the crash", is an ideal example. It breezes through some post-cyberpunk hallmarks without getting bogged down in anything but the most critical details, yet hints at a fully-fleshed periphery. It might even make a nice novella.

The author is Rahul Kanakia. The guy studied economics at Stanford but now writes SF. It's a natural progression but not a common one. He's also just a tad older than I am, a sure fire trigger for the "what are you doing with your life when this guy has already written a bunch of novels" effect.  This is alleviated somewhat by his great blog.  It's very analytical and unpretentious. If I ever decide to give up science for science fiction, I'll have to follow some of his examples. He's not big on advice, though.