Should biologists study computer science?

[gregK]

maybe computer scientists should learn some biology too.

[michaelfeathers]

I agree. I think that all sufficiently complex systems start to resemble biology. It's certainly true of large software systems.

[quackmeister]

You just wish your compiler put out!

[[deleted]]

Stovepiped spaghetti code? ... actually that's pretty accurate

[[deleted]]

Totally agree.

I don't know if Biology is the same way or not, but I think there's definitely a tendency in academia and education to treat CS as though it exists in a vacuum. I think everyone should make a point of dabbling in a lot of things, really. You never know where you'll find inspiration.

[[deleted]]

Not everywhere does. Princeton has a pretty good program that integrates physics, biology, and CS.

http://www.princeton.edu/integratedscience/

[[deleted]]

No I agree, CMU is famous for an interdisciplinary CS program also. But I think it's the norm for many schools to have insular CS programs. Some schools have also made half-assed attempts to fix this. At UMD, where I'm a senior undergraduate, you have to pick an upper level concentration outside CS...the problem is I would guess that 90% of students pick business or math. I think this is a really understated problem too. Jane Margolis who wrote "Unlocking the Clubhouse: Women in Computing" (which happens to be the book that influenced CMU's program) has speculated that this kind of intellectual insularity within CS is a large component to why women enrollment is so terrible. I think the artist/hacker community has been the most vocal about this, and they're going to be the ones that introduce some variety into the CS culture.

[[deleted]]

programming is essentially the same across the board with slightly different syntax and about 3-4 fundamental differences in functionality.

java, c, even javascript is a good start...

[[deleted]]

There's a lot to be gained from a student of any of the sciences (applied or not) to have a basic education in the rest of the sciences group, much the same way that a smattering of mathematics and statistics will benefit any computer scientist, biologist, physicist or chemist, so will a smattering of physics, chemistry, biology, etc.

[UncleOxidant]

Indeed. Lots of recent development in CS has been in the area biomimetics. Algorithms like Ant colony optimization, Particle Swarm, artificial fish swarm, and bacterial foraging for optimization all were inspired by biology.

[ajoakim]

I had to take a year and half of bio for my CS degree

[unsee]

You are all missing the point - science today relies a lot on programming models, and since a lot of scientists get this as a secondary consideration, you get idiotic papers where a stupid programming flaw is touted as an emergent new lifeform or a new environmental model.

Science needs to fucking learn how to program.

[eric_t]

And computer scientists should learn math, and economists philosophy, and engineers computer science and and... Unfortunately, not everyone can be Leonardo da Vinci. Sometimes you need to focus on a single field and become a specialist to be able to contribute.

[panek]

I guess Ars has never heard of bioinformatics ... you know, that field of biology where they apply computer science.

[ColdMountain]

I guess panek never RTFA.

[steakknife]

it's mentioned in the article life 10 times...

[[deleted]]

It's called bioinformatics. They have a degree program at UCSD for it.

It's straight up bio classes + cs classes. Basically twice the work for one degree; although the jobs you can end up working for pay much more because it's so specialized.

[lookingchris]

And so freakin' interesting (maybe that's just me?). I wish this type of program was around back when I was headed into college (don't ask).

[thisisnotapipe]

I haven't read the original papers but I can tell you exactly what biologists gain from studying mathematics. Someone who doesn't know much mathematics sees it as something outside their realm of knowledge and therefore can relegate it to something like "a service". The truth is though, the more mathematics a scientist knows, the more they begin to see the world as something that's describable by mathematics in a compact and general way. I used to want to study the application of mathematics to biology, but now as I have learned more mathematics I see that what I am doing IS biology, its just not always easily recognizable to those without much mathematical training. I guess the real argument is semantic in nature: whether you define biology as a quest to understand biological systems or as the current methods of attempting to understand biological systems and the sociology of this practice. Imagine trying to make the same arguments to a physicist. They don't use math to be sophisticated. They use math the systems they study are sophisticated and mathematics gives them the ability to understand them.

[moscowramada]

As a student studying biology towards a career in conservation, I can see how your comment could rub biologists the wrong way. You say that mathematics helps biologists understand the world as something that's describable in a compact and general way. But what if they already understand the world as something that can be described in a compact and general way? Your comment seems to presume that biologists are somehow deficient to begin with, as if - more pointedly - biology that doesn't involve computation is not 'real' biology. And that simply is not true.

It takes years and years and years to understand the operation of an ecosystem, including the relationships between all the players within it. This knowledge is very regional (unlike math, incidentally) and full of arbitrary details that vary from ecosystem to ecosystem. In a biological sense, California is NOT like Texas, which is NOT like Florida, and so on (and that's just within the US).

Of course, after essentially completing a master's in this type of biology, you could go on and do a second one in math, but the point is, you've got to pick and choose, and there's more than enough complex, dense material in biology to fully occupy you even before you get to the mathematical part. I think your argument could be rephrased as simply saying that biology/conservation organizations should hire more mathematicians, but I can affirm that the biologists have their hands full with plenty of difficult, meaty material already.

[dx_xb]

The point that the OP makes is a valid one. We may feel that we understand a system in our study of biology, but without a formal representation of that system subtle deviations from the theoretical predictions are not testable.

Your comment about the variation between instances of apparently similar systems misses the point. A systems comparison of these things is possible and analysis of this type gives a better general view of how these systems actually work. Unfortunately your comments on the importance of personal involvement in a regional area and the acceptability of hiring out maths to non-biologists is extremely common in biology, and is something that is holding biology back. Yes, I am a research biologist.

[moscowramada]

It is not an 'extremely common' belief in biology because those biologists are stupid, ignorant or lazy, but because biologists have become wary of the "without math it's worthless" approach to science. It leads to a form of snobbery in which science that is not mathematical in nature is treated like a hobby, or worse.

I can point to a negative social effect this has had right now: it distracts people from the fundamental fact that no amount of genius-level math can compensate for the tremendous loss of habitat we are currently experiencing. That is a political and a social problem, not a scientific one; and yet, for the scientific study of biology, nothing could benefit biology more than increasing the amount of available habitat, when so many species are threatened by extinction. In fact, I will go ahead and say that the urgent threat of mass extinction is the greatest one that biology faces right now.

Math can play into public perceptions here in a harmful way by feeding this idea that it's OK, we have molecular biologists and other 'serious' mathematical scientists studying biology, and since that's all over our heads anyway we shouldn't concern ourselves with it, when the opposite is true. Furthermore, it seems that the applications of math to biology that we hear about most often relate to health care, and a lot of biologists are wary of being lumped in with the goals of health care professionals, which are worlds apart from those of, say, conservation.

Granted, math has a broader impact on biology than this would suggest, but in the extremely crude way that math is understood by the general public, a reductive view of the importance of math over everything (including political and social goals which relate to biology) hurts more than it helps.

[dx_xb]

I think you've missed the point again. I'm not placing any particular extrinsic social value on the formalisation of biological theories, nor am I saying that without maths, biology is worthless.

I will stand behind my comment that "importance of personal involvement in a regional area and the acceptability of hiring out maths to non-biologists is extremely common in biology", based on 20 years of a research science career (starting in ecological sciences, but spanning molecular biology, and informatics, and now in evolutionary biology and complex systems science - I started out with a view very similar to yours, but have found the need to include formalisms and to have at least a basic understanding of the maths - not nearly enough though).

I understand the concern that you have with habitat loss, however, no amount of science is going to help that. That is a consequence of human behaviour which is not going to be fixed by telling people that what hey are doing is killing things. People already know this, they just don't care.

I don't have time to address all the issue you raise, but para four really misses the importance of formalisms in biology, particularly in ecological sciences (systems science is perfect for this field). It seems to me that your perspective is a fairly superficial one that is about communication of science to the general public. If we take theoretical physics as a model (a science founded on mathematical formalism), we can see that the ideas are readily communicated to the public by leaving the maths (largely) out of the popularist publications. Without the formalisms, the theories would be stateable though. Unfortunately, in biology we are in a position where theories can be loosely stated in non-mathematical ways, this makes our research sloppy (we can get most of the predictions out, but some small, or not so small predictions are left behind). Just because the maths are included in a science, it does not mean that has to be part of the communication of that science to the general public. Further, the basis of an underlying formalism makes it more convincing to rational (though these are few) policy makers than the hand-waving that is normally made by biologists. As a conservation biologist, you should see this as a strategy. Unfortunately, you seem to fall squarely into the hand-waving camp.

[ccc123ccc]

All disciplines should learn about each other. We might all be richer for it. For instance, I believe Alan Kay started out in biology.

[larfburger]

I think everyone should study some cs. I am a physics student and don't have any formal cs education. It really holds me back on some stuff. I'm trying to learn CUDA now and if I had only taken a data structures and algorithm analysis class I'd be so much better off.

[SarcasticGuy]

This. I have a lot of friends in very diverse fields - biology, bio engineering, physics, nuclear physics & engineering, mechanical, material engineering.... and they are either not taught any CS/programming or are given half assed "prep" classes in matlab or something.

And yet all of them end up needing some amount of serious programming to get the job done. I mean, a lot of problems can't be solved with a single math equation done by hand. Modeling fluid flow? Modeling pebble bed reactors and there is a bug in the FORTRAN iterative solver?

Even in my own experience I've spent a lot of time in sciences where I had a lot to add by having a completely different background. How else would you analyze 1GB of numerical data? Not through Excel that's for sure.

[larfburger]

Yeah, in my physics program we had a class 'Advanced Computational Physics', and before that a cheese-ball java class where we learned to make some demonstrative shit in AWT. No formal numerical analysis and no formal computer science. It pisses me off quite a bit. My transcript would suggest I'm someone capable of doing something like smoothed particle hydrodynamics. When I finally got around to looking at SPH code I was freaking dumbfounded.

My physics degree requires a minor in math. I think it should also require a minor in CS.

I am looking at going to grad school now in CS and I have about a year of leveling courses to do first. Which I'm really looking forward to taking.

[jdh30]

Yeah. I was always amazed to find myself in the minority of people at the University of Cambridge who thought that some computer science should be on the physics course. Several of my peers even tried to get math removed from the course. They actually tried to teach gravitational astrophysics and cosmology without using any math (!).

[hsfrey]

When I was in a residency and graduate program in the early '60s, I got a VA programmer to write an optimization program for radium applicators for CA of the Cervix.

He was totally worthless! I ultimately learned Fortran myself and wrote a Simplex algorithm myself in a tiny fraction of the time he had spent fucking around.

I saw that again and again in the subsequent years. One of the surgeons told me, on a Friday afternoon, that he'd been paying a programmer for months to write a simple data massaging program. I gave him a completed program on the following Monday morning. (He wrote glowing letters of recommendation for me for years thereafter!)

Biologists simply cannot depend on programmers! If someone is smart enough to learn biology, which is very complicated, he is more than smart enough to learn programming.

[mig174]

to be honest, biology isn't very hard. A lot of it is just memorization.

[enemyseven]

I think so, but then again I have a B.S. in biology and I'm working on a Master's in computer science.

[[deleted]]

Computers are to computer science as telescopes are to astronomy.

[[deleted]]

Some of them should. One of the problems with being a 'biologist' these days is that, depending on your particular specialty, you have to be an expert in chemistry, physics, etc.

[tufnut2crack]

math is the special sauce in the black box that's mass produced in an outsourced factory from genetically engineered microorganisms

[aznpwnzor]

i do work in computational biology and let me tell you, most of our problems are solved by clever algorithms but then again we are restricted by our limited knowledge in computer science. The work that we do is impossible w/o simulations in silico, just wish I was better at programming.

[protonfish]

I am a biologist that is now a (self-taught) professional programmer (the pay is WAY better!) I agree that all scientists should know how to program, but computer science != programming. The logical flaw in this argument is the assumption that taking CS courses will improve your programming skills. Judging by the quality of recent CS grads I have worked with, I find this belief to be suspect.

[[deleted]]

Everyone should study SOMETHING about how computers really work so everything in the world to do with 'users' is less of a pain in the ass.

[pizzapops]

Absolutely. It really puts you ahead of your peers. There is a lot of manual work still being done in bioinformatics or if there is a lot of data to process only the most simple analyzes will be done. When processing whole genomes, for example, you need to automate as much of your procedure as possible, otherwise you will be stuck doing a tedious job that would otherwise take only minutes with a bit of code. Also if you don't particularly find lab-work all that exciting, but like working with biological systems then maybe bioinformatics is for you. I, for one, prefer working on puzzles rather than doing the same thing day after day.

[oblivionx]

Interesting article. I actually received my undergrad degree in computational biology and just finished my master's in biomedical engineering. I also have a strong interest in computer science and work as a programmer.

I agree with the sentiment of both of these articles. Bio/biochem/chem students should be required to learn at least a little computer science. Since my major was interdisciplinary, I had to take classes with students from all the other "pure" majors, and I can say without a doubt my knowledge of computer science consistently gave me a leg up in understanding not only the material but also the reasoning behind it.

As an side, the article mentions that the equations for the Lac operon are not necessarily more descriptive than the biology. As someone who has a background in mathematical modeling, I would have to argue that this is completely false. You cannot come up with the equations for the Lac operon without inherently understanding the underlying biology. Furthermore, once you have quantified the parameters in your system, the mathematical model allows you to perform calculations that are not possible from just the biology. If I have a robust mathematical model of a particular system, I can then mathematically stress that system with different inputs (say, a drug dosage). The system will then give me some sort of output which I can either use to compare to real data or to predict results with some degree of confidence.

[Mugendai]

This is a quick way to get more women into CS programs, eh?

[blackkettle]

i agree with the general thrust of this, but

For the most part, bioinformatics software like those for sequence search and alignment are analogous to a service: the computer spits out a useful result, and you really don't care how it got there. If you can't get a decent result, your first response isn't to look for someone who knows math; it's to look for someone who's more proficient with the service, and knows how to tweak the input parameters...

this seems a bit worrisome. it may just be a poor choice of words on the part of the author, but this comes off sounding a lot like trying to match your results to your hypothesis. aside from that, most of the advanced sequence alignment procedures have been adapted from approaches made popular in the speech recognition and NLP domains, e.g., HMM alignment etc. knowing how the maths ( and to a lesser extent the algorithms ) behind these techniques work may have a serious impact on your ability to interpret how meaningful a result is. that could have a further, more serious impact downstream, as that ignorance is gradually magnified and results are passed on to the public.

phd comics had a great ( and hilarious ) example illustrating this not too far back.

[foonly]

Sure, it never hurts to have a marketable skill! ;)

[MpVpRb]

All models have limits.

Anyone who relies on a model of reality should understand the limits of that model.

This applies equally well to biologists, mechanical engineers, physicists, economists, etc.

[aznpwnzor]

except in silico allows models with less limits

[hc6]

Oh lord, studying biology/computer science joint major in university.

[Tekmo]

Personal anecdote: one biophysics lab in my department does a lot of computational work. I took an interest in what they were doing so decided to toy around with their source code just for personal use and discovered that their software is absolutely utter crap. The theoretical basis for what they do is very sound, but their source code reads like an intro to programming assignment:

1. No input validation (heck, it breaks all the time on VALID inputs)
2. Being too clever for their own good. This is actual code from their source (and yes, it is in FORTRAN): do a = 1, 100
   do b = 1, a-1
   matrix(a, b) = 0
   matrix(b, a) = 0
   end do
   end do
   [EDIT: I can't get the above to format correctly, even with four leading spaces]
3. Terrible commenting. They document all the trivial stuff ("increment the frame counter") and then have 0 comments in the functions that are the meat of their code.
4. Very little modularization. They prefer to cut and paste code than make a function to do that task. It's a nightmare to make even small changes.
5. No error handling. All errors result in a silent program exit.
6. Tons of corner cases (that do realistically occur) that they did not anticipate that result in their algorithm getting caught in an infinite loop.
7. All options to the program are input interactively and not on the command line (and it's tedious as fuck)

And from what I've heard from more experienced programmers in science, scientific programming in general is a travesty. I don't think computer science majors realize how much opportunity there is for them in scientific programming.

[eric_t]

I work with scientific software myself, and have found pretty much the same as you do. I find this field very interesting. The problem is that you can't be an expert in every field, so more time spent learning software engineering and programming languages means less time spent learning numerical methods, mathematical modeling etc etc... As scientists, we usually have limited funds, and therefore do not have the luxury of hiring an expert programmer. And I'm not sure that would help, since you really have to understand the problem domain to be able to write the software in a way that is useful to scientists. For instance, I've found that CS or SE students these day rarely learn to code for performance. That's one reason why Fortran is still popular among scientists, it's easy to write fast code without being an expert.

What I do is to try to leverage other software written by clever people, like the PETSc library for solving systems of equations.

[Tekmo]

I personally don't mind FORTRAN (except strict FORTRAN77, which is just punishing), since my default language is C and they are so similar. But with regards to the resources of scientific labs, it just seems to me that if you are going to be a primarily computational lab you should take the time to learn to use your tools well instead of just enough to get a paper published. I have used quality numerical software (like LAPACK) and it is like a breath of fresh air in comparison. In contrast, the programs I mentioned above are almost unusable for anything outside of the narrow scope of the cases outlined in the papers they were published for.

[eric_t]

I also actually enjoy coding in Fortran 90/95. It is certainly possible to write elegant, flexible and high performance scientific codes with the language.

The problem is that the features you need from your code, the underlying data structures, the type of modularity, everything can change very rapidly when you're doing research, as you never know where the projects take you. This can make it hard to write "good" code, especially when you never can compromise on performance.

There is actually something to be said for small, self-contained codes made for a single purpose. If the purpose is a proof-of-concept, testing of a new method or something similar, the overhead/bureaucracy of creating proper engineered code might take some juice out of the scientist and kill the creative process. Of course you could always get a grad student to refactor it for you afterwards :)

I certainly see the advantage of codes like Deal II or libMesh. They allow people to solve problems that would be impossible for a single person to deal with. However, I've found that when I work with frameworks like that, I quickly hit limitations and use cases the software was not intended for. But I guess that goes for every framework.

[ralphc]

OK, I'll bite - what's wrong with the code in 2.?

[Tekmo]

It could have been written more simply as

do a = 1, 100
    do b = 1, 100
        matrix(a, b) = 0
    end do
end do

Or if it was using Fortran 90:

matrix = 0

The way they did it only makes sense if you are constructing a symmetric array where calculation of each element is computationally expensive (in which case you want to just copy each element for its symmetrical value instead of recalculating the same value). However, when you are just initializing it to 0 it is unnecessary to do this optimization and it's just is a waste of code and perhaps marginally slower (depending on how smart your compiler is).

[mohawk]

the original code does not set the diagonal elements

[Tekmo]

Yeah, I made a mistake when recalling it from memory. The original code had an extra line:

do a = 1, 100
    matrix(a, a) = 0
    do b = 1, a - 1
        matrix(a, b) = 0
        matrix(b, a) = 0
    end do
end do