The Futile Cycle

Sorry for the lack of posts, but alas, science (especially biology) does not wait, and things die when neglected.

Meanwhile, I have around three weeks left in my final laboratory rotation before I have to choose my thesis lab, and I’m having a hard time deciding. Coincidentally, Nature Reviews Molecular Cell Biology just published a two-part article called “How to succeed in science: a concise guide for young biomedical scientists.”. There are some interesting tidbits in here, and it gives an interesting, biology-centric perspective on how to look on one’s career. Part I is focused on choosing a field and a lab for graduate school and post-doctoral work. Part II focuses mostly on how to generate ideas and make discoveries. I thought both were excellent reads.

I also recently found Dent Cartoons, which is the home of the famous Nine Types cartoon trilogy. Check it out; very amazingly true!

Ah, Ph.D. comics, how true it all is.

I remember my father once telling me about a time in his lab, in which the lab members were sitting around talking, disappointed that they didn’t have anything to submit to a conference. Suddenly, one of them had a great idea! He checked the time: 12 hours to go until the submissions deadline! All the lab members got together and cranked out some preliminary data. Someone rushed out, sat down, plugged out a poster abstract based on the preliminary data, and emailed it to the conference with 30 minutes left! And it was accepted!

In the mix of the whole “Scienceblogs is white!!” non-event, Razib at Gene Expression had some questions to ask about the underrepresentation of Asians in blogging, even though Asians tend to be over-represented in science research. He speculates that maybe Asian American cultures tend not to cultivate literary talents as much.

I’m going to go out on a limb and speculate some more. I think Asian Americans tend to emphasize mathematical and technical fields because of social and migratory selection.

Namely, the over-representation of Asians in certain fields has to do with the immigrant language barrier. It’s hard to get a job if you don’t speak English well; part of being successful in the humanities is being able to communicate, as that’s largely what one does in those fields: communicate and analyze other people’s communications. On the other hand, technical fields, especially highly mathematical fields, tend to translate better across language barriers because mathematics is universal these days. Those immigrants who are able to obtain green cards or visas are those who have valuable skills that can translate immediately to results, and those skills tend to be technical.

You’d think that it would still be hard to survive any academic job without a good command of English, but immigrants can be amazingly resourceful, and academia can be surprisingly forgiving of bad speaking ability (let’s face it, professors are often not model speakers, even the native English speakers). I know that my dad had an insane amount of trouble learning english, but his mathematical ability was top-notch. He survived his thesis defense by writing down his entire presentation beforehand and memorizing it, word-for-word.

So what I’m saying is that the American barriers and limitations to immigration create an artificial, societal selection such that only those immigrants with technical abilities are able to pass through the immigration filter with any amount of ease.

This model, of course, makes some predictions. As English language teaching abroad increases, more immigrants and more minorities with backgrounds from those countries should start to appear in the humanities. In addition, this kind of filter effect should happen even with non-Asian ethnic groups, as long as there is some sort of language barrier. I’m curious as to how many British scholars, for example, populate the humanities compared to, say, German speakers (I’m trying to pick countries that have roughly the same overall economic status, and similar “white”-ness and cultural backgrounds). More Africans and Hispanics should populate the sciences compared to other disciplines, too.

The main problem with generalizing this model to other immigrant and minority groups is that there are fewer scholars that are, say, black, or Hispanic in academia, compared to Asians. There might be too much noise to definitively affirm or rule out this “filter effect” in such groups. There might be enough immigration, however, from Britain and Europe to do some sort of preliminary analysis.

In between running around to experiments, attending classes and seminars, reading the literature, eating, and sleeping, I’ve manage to catch chapters of Intuition, by Allegra Goodman. I started the book because of a glowing review from Dr. Free-Ride. I finished it last week, and I’ve been mulling it over in my head.

This book is quite possibly one of the best novels I’ve read in the past year (though, it’s looking like it might be the only novel I’ll read this year…).

It is set in Cambridge, Massachusetts, at a biomedical research institute that’s right next to Harvard’s campus. If this sounds familiar, that’s because the author did some research for the book at the Whitehead Institute, a huge biomedical research institute geographically in between MIT and Harvard. Allegra Goodman did some wonderfully thorough research for the book, because it abounds in the small details of a real lab. Old machines, nude mice, foil-capped bottles of reagents and media.

And the people, the characters, the scientists: how wonderful! They are the classical archetypes that anyone who’s worked for a while in academia would recognize instantly: the hard-working, technically brilliant East Asian immigrant, the powerful lab techs, the rising star who suffers from “imposter syndrome”, the senior post-doc who resents the rising star for all the breaks he’s had going to prestigious schools, the lab head who’s too scientifically cautious to promote her lab well, the star oncologist with a flair for selling the research (”a poet of the NIH form”) but with less-than-stringent scientific skepticism.

Yet, none of the characters are stereotypes. None of them fit their archetypes. All of the characters are quite real, with real motivations, dreams, emotions, and agendas. That, in the end, is probably what ignites the central conflict of the entire book. I will not divulge much about the book’s plot, as I suggest to all of you that you go out and read it if you haven’t yet.

Still, a little thought as to what I see from the book, without spoiling the book (I hope). It seems like the book makes plain that truth — even in science — is hard to know, as it is always seen through the eyes of a person, through a glass darkly. Even the events of the story, told from so many points of view, are not clear. Agendas are confused. All because of people.

The conflict between the exacting requirements of science and the people who actually synthesize and propagate the knowledge seems to be almost the central conflict in the book. Science — true science — happens on the scale of years and decades: ideas are proposed, experiments are done, hypotheses are rejected or accepted, experiments are replicated. Science takes time, and truth only emerges with a grain of certainty years after the fact.

But for many of us in science, especially in the present day, we are forced to live on a faster time scale. Grants are due, demanding results. Jobs demand papers. Papers, of course, require experiments. One can get scooped, if one doesn’t move fast enough. Scientists don’t have the luxury to wait for science proper to catch up, and so sometimes, in the milieu of researchers running back and forth in their frantic-paced lives, some can trip and get crushed under the slow-moving glacier that is real, absolute truth, not for evil or malicious intents in their souls, but for the fact that they, too, have dreams.

But the book does hold out hope. Although science is harsh, people are resilient, and that is why science is able to happen at all. The book is almost a tribute to scientists, and an acknowledgment of the many sacrifices that people make to pursue a career that they love.

Go read it. It is delightful!

I have yet to take my general exam (a.k.a. qualifying exam), which is what I need to pass in order to get to the next stage of my Ph.D. studies. Up until now, I’m basically a masters’ student, doing some research, taking classes, attending seminars, and basically learning my way around being a research scientist. After generals (assuming I pass…), my department expects us to teach and focus on completing my thesis.

I know some schools don’t do this, but in my department, the general exam is basically an oral exam — we present our thesis proposal, as well as one paper that is on a related (but different) field. The prospect of it frightens me to no end, but it’s still about a year away.

Of course, the main thing that I’ll be judged on is my science, but humans are humans, and since the exam is quite subjective, I’ve got to use every edge I’ve got, including improving my speaking skills.

At MIT, there’s a famous annual lecture given by Prof. Patrick Winston called “How to Speak.” This year, a blogger managed to take some notes from the lecture, for those less fortunate of us who don’t have a chance to see it. There are even some tips on speaking specifically for oral exams. I like this one:

3. Practice. Ask your friends to listen to your talk. Tell them to try to make you cry.

In the first major casualty of the etBLAST algorithm and Deja Vu database has been found at Harvard Medical School, where Prof. Lee Simon’s review paper has been found to have large sections copied from another professor’s paper.

I had hoped that Deja Vu would consist of articles from random foreign countries and small, obscure universities, but alas, I was perhaps a little naïve. Perhaps the good part about this will be that it encourages authors to be much more reluctant to plagiarize.

On the other hand, it depends on whether the journals care. Elsevier, in this case, did the right thing and acted upon the evidence to retract the paper, but other journals don’t have such “enlightened” policies. I heard once about a professor that was reviewing a manuscript for a journal when he found that the other author had plagiarized sections from one of the professor’s own papers! When the professor notified the journal editor, they informed him that this was commonplace, and that he should just review the article anyway.

What floats to the top in science is often beautiful, but there’s a lot of crap that sinks to the bottom.

Via Ars Technica, there’s apparently a new database online called Deja Vu, which catalogues duplicate (or near duplicate) entries in MEDLINE, using an algorithm very similar to BLAST.

The majority of the entries retained in the database seem to be cases of outright plagiarism. Going through a few of the entries is like dredging the bottoms of the academic pool; most of the journals are pretty obscure or quite poor in quality, and I bet most of the authors are pretty unknown, too. It’s a strange world down in the pits…

As I was studying like mad for my prokaryotic molecular genetics final exam, I found an (alas) engrossing anecdotal essay from Seymour Benzer, called Adventures in the rII Region, which contains the following rather amusing story.

Seymour Benzer, who died just one and a half months ago, was one of the giants of early molecular biology. He was one of the first geneticists to show that genes weren’t indivisible subunits on DNA (like beads on a string), but rather linear “regions” of DNA, which he called cistrons. Many consider his mapping of mutations within individual genes to be one of the most elegant and amazing achievements of early molecular biology.

When he first showed Delbruck (his mentor and another giant back in the day) his manuscript, apparently Delbruck commented, “Delusions of grandeur.” Benzer follows:

Delbruck knocked the paper so badly that not until a visit to Caltech the following spring did I dare to approach him with another version. He submitted it to the Proceedings of the National Academy of Sciences, and it contained an appropriate acknowledgement of his “moderating influence.”

Tough love, indeed!

There are all sorts of anecdotes in that essay that a pleasure to read, about the entire molecular biology revolution of the mid-20th century, and the close relationships of the biggest players of the time. Some of those scientists were probably more than a little crazy! Check it out!

I’ve always had a strong dislike about certain biology naming conventions, but one thing that I always found rather strange was some of the whimsical and utterly meaningless names given to some genes and mutants. Take hedgehog, for example, or Bicoid. Meaningless names, really; they vaguely correspond to some sort of phenotype, but other than that, have very little to do with the actual biological function.

A paper I’m reading for a class, however, gleefully points out that meaningless names have their purpose: they don’t go obsolete with new information:

Epstein was struck by the similarity of the amber mutants and the so-called hd, or host-defective mutants….Who first had the idea that amber mutations are a general class of “suppressor-sensitive” mutations, I don’t recall….That year, Campbell did further experiments to show that the hd mutants (then renamed sus, for suppressor-sensitive) were in fact responding to a bacterial suppressor gene…

(It is amusing to note that Campbell found it necessary to rename his mutants after learning more about them, whereas the name amber is just as meaningless, and thus just as useful, now, as when the mutants were first discovered and named for Mrs. Bernstein.)

Edgar, R.S. 1966. In: Phage and the Origins of Molecular Biology, Cold Spring Harbor Laboratory, NY. p. 166-170.

hd and amber mutants are the same type of mutant, and “amber” is the English version of the German name “Bernstein.”

So, perhaps those Drosophila geneticists are doing a service to the rest of us after all.

In my current rotation, I’ve been doing a little self-experiment; the lab has a group wiki where everyone can post things that would be relevant to everyone else, such as protocols, lab reagent lists, etc., and I figure that my lab notebook is of interest to other people. After all, it’s not just for my own records.

Thus, I’ve been keeping my lab notebook on our lab’s wiki. I know that OpenWetWare and other groups have been doing the whole “keep a lab notebook online” for a while, but I’ve been skeptical up until now about the value of an online notebook. I’m a wet lab scientist, not a dry lab scientist, and so I thought that I might run into some trouble with data and such that I wouldn’t be able to put online (or that would be too cumbersome to do so). In this day and age, though, everything is electronic. The microscope takes digital pictures, I scan in pictures of my gels, and the 96-well plate reader exports plaintext files that I can process with Python and R. Everything basically has to be able to get onto a computer anyway in order to be written into a paper.

So far, it’s been going great! It’s nice to be able to access the notebook from home or from any computer in the lab, for example, and I don’t misplace it. If I have a contact on a particular project, his contact information is always online at my fingertips. I can even search my lab notebook, or cross-reference easily! I’m a convert!

Unfortunately, I am not an open lab notebook convert, for two reasons. First, I’ve signed a non-disclosure agreement with a company to use one of their proprietary discoveries, and though we’re allowed to publish results, I figure blabbing about it all over the internet is something I’m clearly not allowed to do. Second, I work in a very competitive, fast moving, popular field, and it’s very possible that we would get scooped. We’ve already had that happen once. Even if the likelihood that someone will swoop by our lab wiki and scoop us that way is low, any little bit can be quite detrimental. And because I’m collaborating heavily, and not all of my collaborators may feel the same way about open science that I do, I am unable, alas, to endanger their own careers by putting my lab notebook on the open.

I also think that open notebooks work best in small communities, such as fields with very few people that are all friendly, or a small group of collaborators. Or even a field that moves slowly enough that it wouldn’t be possible to scoop someone based on their lab notebook. I do think that small communities make it much less likely that you’ll get scooped, as people tend not to mistreat people they’ve met and put a face to.

But in any case, as god is my witness, I’ll never keep a physical lab notebook again!