I Love Science
Friday, October 24, 2008 @ 2:11pm
Wednesday night I got one hour of "sleep" in a dank, windowless, off-white stone room, awkwardly folded into the fetal position on an unpadded industrial-strength futton with a small stuffed beaver wadded up underneath my head for a pillow, my eyelids warm from the perpetually shining fluorescent light immediately above me.
And I've still never been happier.
On the bright side, the fruit of my labor is now posted. It's a review article on protein tagging that I wrote for my Frontiers in Chemical Biology class. Despite the fact that I pulled an all-nighter writing it, I had a lot of fun researching it (yes I'm a nerd), and it's given me ideas for research projects that I'm excited about discussing with various professors. I think I'm finally beginning to cross that threshold where I read scientific papers and can extract conclusions and brainstorm extensions without having to be spoon fed. I'm far from all the way there, but I can definitely tell a difference in my thought process reading a paper now than a year ago in my undergrad molecular biochemistry class. It's exciting and encouraging.
I have my first MIT exam today in my Analysis of Biological Networks class. A big group of 11 of us did a study session where we each took one "module" from the course and prepared an overview of it to present. I'd almost forgotten how much I love teaching. I'm also taking a certificate-granting training course on teaching, and I found that writing out my teaching philosophy (I'll post it when it's finalized) really made it clear to me that teaching is a passion of mine. I'm starting to seriously consider the possibility of an academic career...
New Article, Old Doubts
Friday, October 17, 2008 @ 3:02am
My second fashion article (this time on shoes) came out in the MIT paper on Tuesday, so again I've mirrored it here and provided links to the version on the MIT website and the PDF version. This was actually the first article I wrote, and the one I used as a writing sample to land my spot as a regular feature, so I think it's better than my first one. As before, the PDF is highly recommended.
I've always been upfront about the fact that I'm not very gifted at math, and I understand and accept the limitations that come with that. I believe mathematics is an immensely powerful tool with widespread applications, and I have the utmost respect and academic admiration for those gifted in math. However, I don't believe math is a "magic bullet" to human understanding, and I don't believe that every phenomenon known can be accurately described by currently available mathematics (I say currently available because it's at least theoretically possible that with knowledge of every atom in the universe, one could complete a mathematical description of everything). I particular, I believe that attempts to model/describe/predict biological systems mathematically is too often motivated by mathematical zeal rather than biological rigor, and I have the sneaking suspicion that there is a tendancy in such works to ascribe insightful biological meaning to what are actually just numerical "cutesies".
For example, today in class we talked about mathematical models of organism growth and death. Overall the instructor was very diligent about pointing out the inherent flaws or inconsistencies in the whole process, but he did put forth as "interesting" or "creepy" facts a few things that I'm just not convinced about. The first was the notion that human beings have a finite maximum lifespan based on the shape of the curve of the derivative of probability of death versus time. Now I'm not saying that I believe humans can or ever will live forever. But as I've made clear before, I believe that greatly expanded human lifespan is a realistic goal that should be a fundamental part of biological engineering. To reject this goal a priori simply because the derivative of probability of death has a positive slope seems short-sighted and complacent. From a mathematical perspective, even if the slope will always be positive, that says nothing about our ability to decrease it, thereby prolonging lifespan.
More fundamentally though, mathematical models are woefully bad at capturing nuances, complexities, and higher-order interactions. In fact, most of the time the entire goal of a mathematical model is to reduce a complicated, dynamic, interconnected, non-linear system into something that can be described by a series of matrices and solved numerically by MATLAB. In many ways the increasing reliance on mathematical models seems antithetical to the increasing focus on systems-wide, interconnected, network or "omic" biology, which by its very nature is interested in making systems more complicated. I believe models have their place and their usefulness, but I get very nervous when people start extracting biological meaning from parameters or facts that don't have a biological basis. One example is that cell growth patterns can be modeled as a fractal. I recognize that and I'm fine with that. But to take that sytem backwards, starting with the properties of fractals and saying that those properties must also be posessed by cells, seems dangerous. In this small example it would be simple enough to experimentally confirm whether or not cells actually showed that property, but if the property set you were examining was sufficiently large, such validation would not be possible for every prediction. Instead, the most likely strategy would be proving a subset of such predictions and then relying on induction to "prove" the rest. My fear here is that simple coincidence or careful/lucky (intentional vs accidental) picking of the data could provide support for predictions while still not being based in anything biological.
As a final example of the type of inductive reasoning that I'm critical of, I'll repeat the last point from class today. Human population death curves plotted from actuarial tables belong to a certain "family" of curves within mathematics, and as a "creepy" final thought our professor left us with the fact that several other processes -- mechanical failure of a chain, useable lifespan of an automobile -- also fit curves that belong to that family. I don't find that creepy or biologically insightful. Instead, I see it as a numbers/math "trick" that's simply a byproduct of the fact that there are only a limited number of families that curves can fit into, and is at best proof of the breadth and non-specificity of mathematical models. To attempt to derive novel or insightful biological ideas from such a "curiosity" seems fundamentally flawed in my mind, yet it is the same type of reasoning that I fear goes in so many papers today.
Full Swing
Saturday, October 11, 2008 @ 4:12am
Things have finally kicked into full swing, and I'm beginning to gain an appreciation for the "drinking from a firehose" analogy commonly applied to learning at MIT. In the past week or two I've had a number of completely new experiences, including solving a differential equation (don't laugh, that was big for me), reading a textbook for several hours straight, and doing homework on a Friday night. I don't think we're in Kansas anymore, Toto.
I think the biggest thing that's new is the temporal density of the work. In undergraduate, even when projects/homework/applications/etc. were due around the same time, there was still sufficient spacing (and/or the assignments were of sufficiently low difficulty) that I could tackle them in a linear fashion. Complete assignment one the night before the due date, turn it in, then complete assignment two, turn it in, etc. I got very used to this way of doing things, since it's how I've basically always worked. I don't have that luxury anymore. I currently have a paper to read for discussion, a review article on "bioorthogonal noncanonical amino acid tagging" to write, a grant proposal on the protein translation induced by platinum-family chemotherapy, a double-length kinetics problem set to complete, a kinetics paper from the primary literature to reproduce in MATLAB, and the applications for the Hertz and NSF fellowships to complete. It's a little overwhelming at times, and the due dates are close enough that it would be absolutely impossible to complete them sequentially. The only option is to work on several of them at a time and all of them much earlier, which is quite an adjustment.
But, at the same time, there are definitely "moments of clarity" where I appreciate all of this. Don't get me wrong. I'm not waxing nostalgic or poetic over the fact that I stayed in the student lounge until 4am tonight (it was a Friday!) working on kinetics problems. But there are times (mostly when I'm lying in my warm, comfy bed and thinking fondly about cheap, fast, hole-in-the-wall diner pancakes tomorrow morning) when I realize that the skills I'm learning, both topical (that is, kinetics) and extra-topical (juggling multiple simultaneous commitments) will be invaluable to me for the rest of my academic and professional career. There's also an incredible sense of pride that comes from finishing a problem that took an hour to make tractable, or from reproducing a set of figures from a primary paper using only the original paper and MATLAB.
So things are getting hectic, stressful, busy, overwhelming, nerve-wracking, humbling, terrifying. No sugar coating that.
But I still love it. I've still never been happier.
First Fashion Article
Wednesday, October 2, 2008 @ 4:52pm
My first mens fashion article was published in The Tech Tuesday, and I've mirrored it here as well as provided links to the online and full PDF versions. The article was actually really fun to write and has generated a lot of positive feedback, as well as a piece of hate mail -- which was strangely more exciting than most of the positive responses. I figure in journalism any press is good press, and hate mail is just an indication that people are reading my stuff.
The new design for the MIT graduate student ring (affectionately referred to as the "grad rat") was unveiled yesterday, and several of my nerdy friends and I promptly rushed to order one. My friend Christina seemed to show the same level of (potentially unhealthy) excitement as I did, and we wrote it off to the fact that this is basically the first time either of us has felt intense school pride -- sorry Ole Miss. If there was ever any doubt in my mind that this was the right place for me (there wasn't), it was washed away last night. The depth and vibrance of the culture surrounding MIT is unmatched, and going here not only pulls you into that fold by default, but also opens up the opportunity to dive deeper into it yourself. Needless to say, I've gone in head-first, and I haven't looked back yet.
Classes are still going well, even with the massive amount of time I've devoted to coding MATLAB this past week. A large part of 20.420 (Biomolecular Kinetics and Cell Dynamics) is a series of projects called "implementation", in which we take a paper from the primary literature and use MATLAB to reconstruct the models and figured used in the paper, then develop modifications to those models that test their validity. The process is quite involved, and the use of MATLAB had (and indeed still has) a ridiculously sharp learning curve. That being said, there's something deeply intellectually satisfying about running the code that you've been working on for 9 hours straight and watching it generate, point for point, the exact graphs in the paper. I also believe this is one of those classes that I will greatly appreciate after I've completed it. Now that I'm in the midst of it, it's hard to look past the heavy work load, high level theory, and general disconnection from my academic/research interests. However, at the same time, I recognize that the quantitative skills I'm learning in the class are invaluable, and that the ability to understand the mathematical framing of problems (even if I'm not able to generate those framings after the final) will be a lifelong need.
My other classes are starting to get into full swing, and my nerd side is kicking in making me absolutely love it. The frequent reference to topics of biochemistry and organic chemistry, coupled with the open discussion format, is tailor made to my strengths. The classes also seem to be having their intended effect of stimulating me to think about science, engineering, and biology problems outside of class, as a general topic of interest. In others words, the interest that I was attempting to cultivate over the summer (reading articles and brainstorming about them here) is starting to become natural through reading papers for class and then brainstorming about them with my fellow classmates. I've "stolen" a technique (guess it isn't really stealing if you're encouraged to use it) from Ed Boyden's blog, and I've started keeping track of my ideas/epiphanies/hair-brianed schemes in a small notebook that I keep with me at all times. I've currently got a couple of ideas floating around in my head that I think might have real potential, and I'm genuinely excited about researching them.
Don't look now, but I'm becoming a real scientist.