Switching Roles

At Mather House, where I'm staying for the summer, there exists a common room, equipped with a TV, couches, kitchen, table, and ping pong table. Often I had come back late at night after work, hoping to get in a game, but for some reason my card never got me in. I finally found an alternate route on Monday, and got in a couple of good games. Up till now, because of my schedule and my somewhat reserved nature, I had not met many people other than my immediate neighbors, and I didnt know anyone very well. It was nice, then, to meet these people, and I've since gotten into the habit of spending an hour or longer in the lounge after getting back from work. This means I sleep daily after 2, and wake up at 6 or 7, but that's not too much of a loss, and most of it is self inflicted time wasting anyway.

Anyway, one day, relaxing in the common room after a few games of ping pong, I met a student who happened to be working in the same lab as Fiona Wood, one of Lily's roommates for the upcoming year. When I told him that I was doing bioengineering, he asked if I had heard of biocomputing. As it happens, I did know about the field, but this was a huge fluke: as far as I know, there are only a few good books currently out about this work as a whole, and I had come across one of them accidentally. More than anything else, though, I was surprised he had heard of the field, given that he was an EE major. I asked him about it, and he told me that went to USC, and worked with Leonard Adleman during the year.

I'm not sure how many people have heard of Adleman before. Those who have, though, almost exclusively associate him with RSA, the encryption algorithm used extensively today (this algorithm is actually pretty cool, you should all take a look into it). His more recent foray into biology is not as well known, despite the fact that he more or less founded the field of biocomputing. Apparently he now spends his time working on analytic problems in pure math. Talking about Adleman's work, old and new, got my really excited about biocomputing all over again, and since I think most of you haven't read the books I was talking about, I wanted to just write a little about the subject.

Computational Biology is the use of standard computing to simulate and understand biological systems and their underlying processes. Biocomputing is the exact opposite, i.e. the use of biological systems to solve difficult computational problems. The underlying principle here is that biological systems are inherently parallel in nature. It's never just one process going on, there are always thousands proceeding simultaneously. Of course, it doesn't have to be this way, we could easily make a living system with very few processes, but the point is that we can have a massively parallel system of processes that do not get hopelessly tangled up. Since parallel processing can speed up recursive or iterative processes by an arbitrarily large factor, biocomputing, in terms of general notions, seemed to be an excellent approach to vast computational problems. All that remained were the specifics: for a given problem, how to encode information in biological molecules, and how to encode operations on the information that would be performed legally, automatically, and in parallel.

Despite the work that has been done in the field, no system of encoding information and operations has been successful as a general computing framework., and consequently a new system had to be developed to fit every problem the field chose to tackle. Here I'll just describe the way in which biocomputing was used to solve the N-Vertex Hamiltonian Path Problem, i.e. finding a Hamiltonian Path in a graph with N vertices. For each vertex, assign a sequence of nucleotide basepairs of length M, such that 4^M is at least as great as N. Then, for each edge in the graph, assign a sequence of nucleotide basepairs of length L, such that 4^L is at least as great as E, the number of edges in the graph. Now, for each edge, create two DNA fragments:

1. M basepairs for the vertex from which the edge originates followed by the L basepairs for the edge.
2. The L basepairs that are complementary to the sequence for the edge followed by the M basepairs for the vertex at which the edge terminates.

Finally, for each vertex, also create the DNA fragment corresponding to the M basepairs of the vertex. If these strands are all synthesized and then replicated many times over using PCR, then just by putting them in solution, due to complementary basepairing they will automatically recurse through paths in the graph, all in parallel, very quickly, and each recursion will terminate when the strand corresponding to a lone vertex (i.e. no edge) is incorporated into the growing strand corresponding to the path. Finally, by checking the length of each path strand formed, and by ensuring the presence of the DNA corresponding to each vertex, one can very easily find a solution to the Hamiltonian Path Problem in almost linear time.

Anyway, I hope that gave you a little taste for the subject. I did finish writing this at 4:55 in the morning, so if something doesnt make sense, just let me know and I'll rewrite/clarify.

~jnub

Connections

Ved recently wrote a blog post about television shows. It amused me that every single show that he mentioned was at core a comedy (we exclude Burn Notice because no one knows why we watch it). This is interesting: are we only capable of coupling emotionally with those who have pleasant lives? I think we can safely that this is false. So let's rephrase a little: can we only connect with those who are ultimately happy. This, too, I believe is false.

The reason these shows appeal to us, of course, is part of the reason for which we seek friendship: to be able to immerse ourselves in the lives of others, and to empathize with them. But this differs in a critical way from making the same connection with TV show characters: as we come to know our friends, we are constantly changing, but as we watch a TV show, despite the effect we feel it has on us in retrospect, we are much more static.

But I do not think this explains our (or at least my) preference for comedies. For if we are static while watching TV, is not the same true doing the reading of a book. Yet, I find that I more often connect with characters who have deep underlying regret and sorrow than with happy-go-lucky characters. And here, of course, is the true motivation for this post: I have finished, for what is at least the 10th time, the Ender Series. As has become the norm, I cried when Ender died, because I had come to love him, the small, broken boy who bore the guilt of a million murders, the man who spent his whole life trying to atone for a crime that was not his.

Why should a book be so different from a TV show in the way it effects me? And are these tastes peculiarly mine, or does everyone feel this way?

A Revival of Sorts

Tonight, 450 miles from this room I sit in now, too lazy or tired to return to my dorm on the other side of town, 450 miles from here the Class of 2010 graduated. I don't pretend to know what it meant to them, collectively or individually, but I suspect it hasn't really hit them yet, what they just finished, what they're leaving behind more or less forever. As this new day begins, the first day on which they are no longer high school students, ANGP is in full flow. Hell, they have a whole summer to go, no need to get a jumpstart on the nostalgia.

It matters to me though. For one, I'm losing a huge anchor to a school that I love. I'll still visit, more often than most others I suspect, and there'll still be people I know, but at the end of the day I'm more or less detached at this point.

More importantly, it reminds me why I started this blog. I've been somewhat negligent, and I intend to fix that.

I've been back in Boston for nearly two weeks now. I'm spending the summer working on a systems biology project in Sean Megason's lab. We're looking at morphogenetic dynamics in the inner ear of zebrafish (the process is more or less identical to inner ear formation in humans, just at a different rate). At some point, I'll post a small summary of what we're actually doing, because I'm pretty excited about it. The project was part of an internship program in systems biology, and so my housing was organized through this program as well.

I'm also doing a part time thing from 6 PM to 10:30 PM or so on weekdays called iGEM. This is a synthetic biology competition, where each team basically decides to design a system of some sort and implements the system entirely biologically. For our project, we decided to make a touch screen that essentially produces a crystallized photograph of the pattern we draw. It's pretty neat, and I'll go into a little bit more detail on this in a future post as well.

Since I'm working pretty late on a daily basis, I don't really get a lot of chances to interact with the other people living in my dorm. I've met some pretty cool people, though, and I do have 8 more weeks to get to know them.

Anyway, today a group of us (Chris, Jessica, Five Other People, One Other Person, and I) went to watch Toy Story 3. I had already seen the first 70 minutes of this during the year at a free advance screening, but the ending was excellent, and definitely worth rewatching the first part of the movie. The first movie was obviously a classic, and the second one was excellent as well, but this one struck a chord in me that the other two missed. You should all go watch it.

Anyway, let's see how long the next hiatus lasts!

~jnub