The Hoard addendum

So I think my post about the Hoard was somewhat rambling and failed to make any clear point. My concern is this: science has outgrown its incentive structure. Good science needs to be done on a scale that involves many hardworking individuals, not all of which will be writing the manuscript and scribbling their name at the front of the author list.

Take, as an example, a massive study to sequence genes in cancer X. This is going to involve intellectual contribution from dozens of people, if not hundreds. Doctors will be involved in enrolling patients and providing detailed clinical annotations of their progress. Surgeons will carefully select samples. Pathologists will carefully grade those samples and possibly select which can truly be classified as cancer X and sent to the lab. Lab workers will perfect protocols, churn them through a pipeline they design. Bioinformaticians and statisticians will then undergo a rigorous analysis of resulting data, perhaps even writing new programs and methods for their processing.

The result, surely, is going to be an enormous multiauthor publication or series of publications. None of this could happen without a few organizing minds at the top, and they, rightfully, claim a great deal of the credit. But what of the multitude of other researchers also involved? They are sandwiched somewhere between et. and al., without the due credit many of them deserve. Much of their work is crammed, often in tiny font, into the often discarded 'methods' section.

To come back around, I am concerned for my place as a growing scientist in the sea of collaborative studies. I truly enjoy the thrill of pushing back scientific boundaries, and specifically I think that modern sequencing offers a powerful tool to do just that. But as a new graduate student who will not be leading the studies, I am concerned that these projects lead me nowhere towards a first author publication. I'm therefore treading water with respect to fulfilling my requirements for graduation. I want very much to be a good scientist and even more to work on important discoveries, but I worry that some ways of doing that come at the expense of my own career.

The Panopticon, Part I

First off, I just want to mention that the word panopticon is one of my favorites. This post is going to be about something that might more properly be called "Heisenberg's Device", but I am going with The Panopticon. The traditional use of panopticon is more dire than the one I describe, although I hope to draw a line between the two in later posts.

I'm going to lay out this story over a couple of days, since I don't want to spend too much time on it each day. A little suspense never hurt anyone. No device like the one I describe exists, or really could exist, but I think it's an interesting point from which to inquire about our scientific methods.

Please forgive my use of the second person. I like it because it makes the whole thing feel like the lead up to a question, which is exactly what this story is intended to be.

Here we go:

You are a biologist tasked with the study of disease X. You've been studying the disease for decades, and you understand a great deal about the workings of this illness, from the molecular biology to the physiology to the pathology and epidemiology. Your efforts have been fruitful. Bit by bit you've knocked back the boundaries of ignorance and revealed certain properties of disease X that have garnered you recognition in your field, though done less to actually cure it.

You come in to work in your lab one day and notice a large package sitting outside in the hall. It has your name on it, but no other identifying information. Curious, you begin to rip into this strange gift. When you tear all the packaging away you find you have a device that looks not unlike a refrigerator coated in a series of snaking tubes, valves and wires. Like a refrigerator it has a door in the front, which can be sealed with three enormous locks. Behind it has an industrial scale plug, a usb port with cord and, tucked away in a small leather pouch, a booklet.

Of course you grab the booklet, looking for some information, any information, about what this strange shipment is. Have your graduate students gotten carried away with themselves? Have the minus 80 freezer designers gone all 'steampunk'?

The front of the booklet has only the following words in bold letters

PANOPTICON

Twenty-five uses

Tantilized, you open the manual and read further. It reads:

Greetings! You are one of a select group of scientists that has been chosen to receive our latest revolutionary technology. We are aware of your tireless pursuit of knowledge and your prior successes, and we are assured that you will know how best to use our device to maximal benefit. The machine we have provided (the Panopticon, hereafter), is just another tool in your pursuit of the cure. We provide 25 uses, all this machine is capable of, at no cost to you or obligation of future purchase.

This device has been developed in secret by our labs and is able to perform perhaps the most rigorous scientific assay conceivable. With just simple setup procedure, this machine is capable of detecting and reporting the precise position and movements (within Heisenburg's limitations, of course) of every atom and molecule contained within the chamber. This data can be downloaded to a computer where it can be stored for analysis and detailed examination. The machine can track this information for five seconds before it becomes inactivated due to the risk of power overload. Never fear, though, the technology is perfectly safe and can even assay living subjects at no harm to or effect on the assayee (see: FDA certification information in Appendix F).

The details of operation and the proper interpretation of the data output formats are provided in this manual, but we have removed key elements of the Panopticon's operation which we consider trade secrets. We hope that you will make use of your 25 assays fruitfully. Good luck!

You sit down at one of your labs benches, confused. Every position of every atom and molecule in the chamber? For five seconds? No microscope or imaging technology even comes close! It's like transmission electron microscopy in real time, on a massive massive scale. And in living subjects!  You take a moment to ponder the implications


So that's it for today. I'll explore the reactions to the machine in later posts.

The Hoard

Science is built on the daring and unconventional ideas of a few going against the hive mentality of the pack. Things that seem like strange artifacts in the data emerge as cryptic signposts pointing to bold new ideas. The bizarre non-Newtonian behavior of light led to relativity, and the equally bizarre downregulation of supposedly overexpressed genes in petunias eventually became RNAi.

But in the era of big science, how do we pick what anomalies are worth following up on? As science becomes more and more dependent upon technology to progress, any line of inquiry becomes expensive both in dollars and man hours. Within this paradigm, is independent investigation possible?

I would argue that in many ways it is not, but our current model still does little to promote the large scale collaboration necessary for modern research. There is still a big emphasis (in biology at least) on first author publications rather than roles in large collaborative studies. Collaborative openness, while often touted as a cornerstone of an institution, often does not make careers. We like to put a name on a given discovery, or maybe two names. We award Nobel Prizes to a handful of researchers, not a collaborative team.


That's not to say that we're not trying. Take The Cancer Genome Atlas (TCGA). This massive effort by six major research centers will work to sequence tumors and matched normal tissue from the same individual across dozens, then hundreds, then thousands of individuals. Eventually it will trace the contours of the cancer genome at extremely high resolution by using very powerful (but expensive) sequencing technology on a massive scale. This is the sort of google maps of the cancer genome. This atlas will be available to everyone, publicly, at no cost to the users.

It will be interesting to see if this new paradigm works. As great as these new, massive, collaborative databases are I think we have one risk, which is a sort of inverse tragedy of the commons. If the data is public and everyone has access to it, no one will have a vested interest in following up on that data. Publishers just aren't as impressed with computational follow up as they are with studies that generate new data. Furthermore we seem to have very little interest, in our modern scientific society, in 'negative' results. Much of what these databases will do, I think, is wash away the apparent significance of correlative studies done with our scientific eye trained on just a few pathways. If we look at two genes and see that they go up and down together we call them a signaling pathway. But if we look at 2000 genes and see them go up and down together, do we still come to the same conclusion?

It's a rocky road we embark upon.

On the dilution of science and loss of value

The other day, Will and I were discussing the vast number of scientific papers already published and what little room there will be for our own contributions. In our despair, we forgot a crucial part of life, that quality will always outlast quantity; in a strict capitalistic sense, while there might be imitators, the ideas of good products will always be bought and sold. Take for instance the iPhone app store. At its conception, the few apps that existed served very specific purposes and developers were able to charge a fair but profitable price for their services. Once the app store began to get diluted with apps such as "Goal2Action" and "Looptastic Gold", the power of the market once again shifted to consumers to find and support quality apps. So in regards to science, how far can I take my favorite metaphor? Who are our consumers?

The scientific community plays a large role in judging the quality of our work, but in a deeper philosophical sense, Time plays the final judge in determining quality. Because as scientists, what we're really striving for is to discover truth. Pontius Pilate once asked "What is truth?" and the answer is maintained by methods that are still unreachable to us. Therefore the discovery of truth will always remain the final barometer for our work. Scientific discoveries such has Mendel's postulations on genetics or Galileo's astronomical work (haha) has stood the test of time. Even Darwin's evolutionary thought has accrued evidence to defend itself. And while our contributions might not be as large, if they reflect truth, they should withstand both the scrutiny of our peers and also the interrogation of Time.

And that is what we should be aiming for, to understand truth, as opposed to trying to publish for the sake of our career. Ambition is not necessarily evil, but it should not be the forefront of our motivations. Too often in science we see work being done because it is required for a grant, as opposed to a more "pure" motivation of just wanting to know for the advancement of knowledge. Such work de-values the body of science because the act of merely spinning your wheels gains you no distance. And the community itself is to blame for adopting an environment that is a microcosm of the capitalistic world at large, a model that struggles to succeed because the end goal is always selfish achievement.

So while it can be discouraging to see the volumes and volumes of scientific literature, I find peace that not all of it is noteworthy, not all of it is significant, and not all of it is true. And I remain hopeful that as I continue to seek truth, I will find it.

The Blog to Nowhere

So I never really introduced this blog. Since I am not really sure who is reading it (anyone?) I want to take an opportunity to say a few things, if only as kind of a mission statement for my own reference.

First off, this blog is about mulling through the big ideas in science. I've noticed that graduate school often follows a long decline from the big picture to a sort of niche myopia, where you are aware only of the things going on in your subfield. The technical details of the day to day work of research overwhelm those high minded considerations that made science interesting in the first place. There are so many exciting things happening in biological research, and cancer research in particular, that I think deserve a wider conversation.

Secondly, I want to write about the culture of science and science education. In some ways science is nothing more than a culture. It's a way of thinking about ideas, communicating those ideas and evaluating their utility. The way we do science is inherently linked to the institutions we've built up to pursue it. Better technology and better science is as much about designing the right culture of inquiry as designing the right experiment.

Thirdly, I hope to improve, if slightly, my communication of scientific ideas. I hope to make each post clear, contained and concise. For some reason the scientific writing style has become an impenetrable thicket of technical language. So many of the journal articles I have read are accessible only to the most up-to-date members of the field. They can be unreachable even to those using the same model organism, but studying different areas. To my mind this is a deep weakness. An idea is only as good as its communicability, and while it's great to be the first to discover something you've done very little if it doesn't reach the person who can use it to maximal impact. Wherever possible I hope to practice avoiding the technical language and giving the complete background.


Lastly I want to have a record of my naive youthful hopes and dreams when I'm a grizzled senior grad student so that maybe I can keep the flame alive when the going gets rough.

Biology and Black Holes

I attended a talk Monday in which the speaker proposed that biology was on the cusp of a new era. This era, he claims, will see biology increasingly resembling the discipline of astronomy. We will more and more be training our genomic telescopes on small parts of the genome, building models, and testing that model against other parts of the genome.

While I don't disagree with him that this is where the field is going, I think we need to do everything we can to avoid the possible consequences. The astronomical model seems, to me, to be a black hole of correlative, descriptive analysis with no useful predictions or clear connection to human application. We risk getting lost in a biological string theory, which makes no substantive claims but which drains brainpower and dollars from more applicable efforts.

What do I mean by this? Take CHiP-seq studies, for example. These are incredibly powerful experiments that document behavior of transcription factors throughout the genome, and they reveal new interactions and possible regulatory pathways. But they often do so in a deluge, and teasing apart the specific and biologically relevant (read: predictive and useful) associations from the less specific, less relevant results can be an entire career's worth of work. In short, we have more data than we know what to do with.

I don't want to sound totally negative about biological astronomy. If we train our telescopes specifically towards disease states we may be able to sort out relationships between genomic, epigentic, trancriptional or other states and prognosis or even treatment responses. Massive biological data coupled with excellent clinical annotation could go a long way towards personalized medicine. But in the complex regulatory network of the cell it seems unlikely that any simple interpretations for these data sets will emerge anytime soon. For now, we should expect biological astrology; We can make some predictions about the future but be damned if we know anything about the mechanism.

Dear Graduate Student Professors

I am currently sitting in genetics class reflecting on the quality of graduate education in science. Let's just say that the class is taught with a 'challenging' style. I'm going to list a few key requirements of good graduate school teaching that are often disregarded.

1. Enunciate. This is not that hard, people.
2. Get to know your students' names. Grad classes tend to be small, and any one of us could be a future colleague. At least make an effort.
   
3. Look at your slides before class and understand the flow of your presentation. By this I mean understand the logical progression of the ideas. Make sure that everything you need to understand a slide is presented before your arrive at that slide.
4. If you're explaining an experimental result or protocol, take your time. These tend to make a lot of sense after you understand them, but are impenetrable the first time you look at them. That's usually because there are a lot of tools that go into the experiment with which students may be unfamiliar. How can you understand a genome wide association study if you don't know what a SNP is?
   
5. When you plan to ask questions, make sure that the answer is actually available given the information you've presented. If students can't guess the answer then it's a bad question or you've failed to lay out the setup to the question. If a student answers your question incorrectly explain clearly but without condescension why the answer is wrong.
6. Do not get stuck on one slide. Your students, as interested as they may be, will start to tune out.
7. Balance and manage questions in class. This is an art. Don't get bogged down, but don't race through material and leave everyone in the dust. Actively ask your students about your pacing, perhaps on an individual basis to avoid peer pressure.
8. Vary your cadence. Show the importance of a particular part of your presentation with vocal emphasis. 
9. Don't be afraid of the blackboard. It's a great way to draw out and clarify a point.
10. Try to make sure that if you're teaching without a textbook that students who get lost have a written resource to which they can refer that has complete information (this doesn't have to be powerpoint slides, but that's one good place).
    

Some of the above are so damn simple that I can't understand why anyone wouldn't be able to manage them.  Others are not all easy to live up to, but your students will massively appreciate your efforts if you try.

PS: To add a few more...

• Never ever ever condescend to your students. It's immature and unprofessional.
• Avoid the adversarial model of professor vs. student.
• Did I mention enunciate?
  

Sitting in class

Hello dear readers. This is my first post.

As I'm sitting in class, I'm wondering about effective techniques for students to learn. Most of these effective techniques are not included in this class. To be fair, graduate school classes are no worse than medical school classes. Just replace one bad lecture with another. However, at least medical school will eventually allow us to take a hands on approach to the material with third and fourth year rotations whereas graduate school will never allow me to apply my skeletal knowledge of transposons in the lab.

Karmic Koalas Crash Eclipse

So I took the plunge and updated my system to 9.10 (karmic koala) from 9.4 (jaunty jackalope). So far I'm happy with the small aesthetic changes and what seems to be a mild speed increase, but I was miffed to find out that the new release broke my version of Eclipse. I used the workaround found here, which worked well. Ubuntu is great and all, but its moments like this that I wonder if it'll ever make it to the mainstream.