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A farewell to bioinformatics (2012)

madhadron.com

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Re: A farewell to bioinformatics (2012)

#91

Post by nopinsight »

troymc wrote: post #81
chewxy wrote: post #58

Earlier quoted context omitted.

Off topic, but since you mentioned jgrahamc's article in Nature, interestingly, this was what I read last night on Simply Statistics: http://simplystatistics.org/2013/01/23/statisticians-and-com... It's a similar issue. I think statisticians are taking constructive steps to correct their path, since you know, ML is the new sexy thing. Bioinformatics could take a much longer time to self-correct though. Although, as I…

Regarding "ML is the new sexy thing," check out these graphs: http://books.google.com/ngrams/graph?content=machine+learnin... http://www.google.com/trends/explore#q=machine%20learning

From your second graph, Iran and Pakistan have stronger interests in Machine Learning than the US. (I am not surprised about India, South Korea, and China though).

Is the interest in advanced Info Tech that widespread in those countries or simply because the only people who could use Google in those countries are government-sanctioned researchers? Anyone familiar with the reason could shine light for the rest of us?

Re: A farewell to bioinformatics (2012)

#92

Post by FreeKill »

michaelhoffman wrote: post #82
FreeKill wrote: post #41

If you really want to get a feel for how deluted the Bioinformatics community is, look for a job in the field as an outsider. It's not uncommon to see requirements like: "Must be an expert in 18 technologies" "Must have a PHD in Computer Science or Molecular Biology" "Must have 12 years experience and post doctoral training" "Pay: $30,000" It's delusional because they apply the requirements it took for themselves to…

I assume these are separate requirements. I have not seen any doctoral-level positions advertised for a salary of $30,000. The minimum NIH salary for postdoctoral trainees is more than that. It's only delusional if they can't find people to fill the jobs. The idea that, as an outsider, you know what requirements they should use in their hiring process better than they do is perhaps more delusional.

I'm not an outsider and the 30K was a bit of an exaggeration, and I apologize for that. The point I was trying to make was that if you look in as an outsider, you would see the requirements being extremely daunting compared to what you might see elsewhere with a pay scale that is very low and unappealing to anyone who might match it. Unless, of course, you just finished your degree in some biological discipline where the jobs are scarce. They are absolutely delusional (and so am I, most likely) because in most cases what they really need to solve the problems they have, is the same type of person most companies would need in a similar situation, a quality software engineer with experience building quality applications that are both extensible and maintainable.

I worked in bioinformatics for more than 10 years before I moved on, and In my experience they do have a lot of trouble finding people to fill positions, especially outside of massive government funded groups like the NIH. This often results in passing on competent software engineers with a B.Sc. that don't meet the requirements in favor of PHD level biology graduates who have taken a year or so of undergrad computer science courses. In my experience, this leads to many of the problems discussed (and exaggerated) by the OP. While some of these people are smart and produce good work, much of the time they produce poor quality software that gets the job done, but as inefficiently as possible and they leave a code base that is virtually unusable. Overall, I mostly just wanted say that it's a mindset they REALLY need to get past for the long term success of the industry.

Re: A farewell to bioinformatics (2012)

#94

Post by ansgri »

zerohp wrote: post #25
leoh wrote: post #10

Earlier quoted context omitted.

Part of the problem is grant money. Sometimes it's faster to buy more machines and get more results as opposed to rewriting entire algorithms. But the author does correctly identify, I think, some tendencies of some academic bioinformaticists.

I have enough experience to know if this is true or not. Many times it was faster to buy more machine, but often it was not. We already had 10000 cores. I proposed, implemented, and tested an 8 line change to our alignment tool that saved 6% cpu time. It took me two days, most of which was my spare time at home. This one program was using 15 cpu years every month. Nobody cared. It never went into production. I starte…

How complicated was the bureocracy that you couldn't push the change into production yourself after verifying that it is a strict speed-up and doesn't break anything? I think such barriers are incompatible with the word 'research', where the first you need is freedom.

Re: A farewell to bioinformatics (2012)

#95

Post by neilk »

Maybe overblown, but it echoes complaints I've heard from other bioinformatics people.

Surely this means there's a goldmine waiting there for someone to produce a non-broken toolchain for bioinformatics?

Or is it even possible to produce standard tools? Maybe all the labs are too bespoke?

Re: A farewell to bioinformatics (2012)

#96

Post by Inufu »

chrisamiller wrote: post #62

Some thoughts on this article: - This guy clearly has a limited understanding of the field. This quote is laughable: "There are only two computationally difficult problems in bioinformatics, sequence alignment and phylogenetic tree construction." - As a bioinformatician, I feel sorry for this guy. Just like any other field, there are shitty places to work. If I was stuck in a lab where a demanding PI with no computer…

Out of curiosity, what other computationally difficult problems are there?

I'm very interested in bioinformatics, but sadly don't know as much about the field as I'd like.

Re: A farewell to bioinformatics (2012)

#97

Post by kevin_rubyhouse »

chrisamiller wrote: post #62

Some thoughts on this article: - This guy clearly has a limited understanding of the field. This quote is laughable: "There are only two computationally difficult problems in bioinformatics, sequence alignment and phylogenetic tree construction." - As a bioinformatician, I feel sorry for this guy. Just like any other field, there are shitty places to work. If I was stuck in a lab where a demanding PI with no computer…

What's the backstory on the author's tangent about the human genome? It sounded like the human genome project didn't actually do what the name implies.

Re: A farewell to bioinformatics (2012)

#99

Post by kevin_rubyhouse »

FreeKill wrote: post #92
michaelhoffman wrote: post #82

Earlier quoted context omitted.

I assume these are separate requirements. I have not seen any doctoral-level positions advertised for a salary of $30,000. The minimum NIH salary for postdoctoral trainees is more than that. It's only delusional if they can't find people to fill the jobs. The idea that, as an outsider, you know what requirements they should use in their hiring process better than they do is perhaps more delusional.

I'm not an outsider and the 30K was a bit of an exaggeration, and I apologize for that. The point I was trying to make was that if you look in as an outsider, you would see the requirements being extremely daunting compared to what you might see elsewhere with a pay scale that is very low and unappealing to anyone who might match it. Unless, of course, you just finished your degree in some biological discipline where…

If 30k is the inaccurate number, what's the accurate one? I'm curious as to what the realistic requirements are from your experience with the field.

Re: A farewell to bioinformatics (2012)

#100

Post by ht_th »

ansgri wrote: post #94
zerohp wrote: post #25

Earlier quoted context omitted.

I have enough experience to know if this is true or not. Many times it was faster to buy more machine, but often it was not. We already had 10000 cores. I proposed, implemented, and tested an 8 line change to our alignment tool that saved 6% cpu time. It took me two days, most of which was my spare time at home. This one program was using 15 cpu years every month. Nobody cared. It never went into production. I starte…

How complicated was the bureocracy that you couldn't push the change into production yourself after verifying that it is a strict speed-up and doesn't break anything? I think such barriers are incompatible with the word 'research', where the first you need is freedom.

Research is highly competitive business mixed with industry involvement (or government involvement). You have to publish and fast. You have to develop your discoveries into something that can be monetized. You have to collaborate with industry to get funded. You have to cut costs to keep doing what you want to do. And so on. The idea of freedom in (fundamental) research seems long dead. How I long for the freedom in the research labs in the first half of the 20th century. To really explore an idea without regard for cost, returns, (publishable) results. A researcher can dream :-(
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