[kevinalexbrown]

John Graham-Cumming (jgrahamc here) co-authored a piece on making scientific code open. It was received well-enough that Nature published it [0]. This approach has inspired others to do better work by describing a concrete problem, then outlining steps to fix it on an individual and institutional level.

When someone finds fault with the way a field conducts itself, I would implore them to constructively influence that field. You might be surprised how many are actually sympathetic to your concerns.

I'm not dismissing this author's concerns: to do that would really require knowing the molecular biology field (which is more than sequencing, it turns out). I do neuroscience right now, and programming can be a problem for some. But a constructive suggestion to change can have much more impact than a long rant.

[0] http://www.runmycode.org/data/MetaSite/upload/nature10836.pd...

[chewxy]

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 mentioned in an earlier comment, Fred seems to be in a prime position to disrupt the bioinformatics field since he seems to know all the problems that afflict it

[troymc]

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

[nopinsight]

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?

[abdullahkhalids]

I am not sure how you based your conclusions.

Pakistan's internet is generally open (except youtube and pornography). But there is no widespread interest in ML particularly. Only a few companies - most of them outsourcing from the US.

[jflatow]

The problem is people who would have the experience / knowledge to really make it better, are not tempted to go in and fix it, because there's so much political / non-technical work involved in doing that. If someone wants to solve hard computational problems, they might as well go into another field. If they really care about doing biology, chances have been that they aren't the greatest programmers (I understand this may be changing, but still seemed to be the case 4 years ago when I left bioinformatics). This leaves the people who are happy with the status quo, staying in bioinformatics, and the people who are dissatisfied, going to other fields where they feel their work can have more of an impact.

In my experience, what happens is that biologists define the science, and they depend on the computer scientists / engineers to implement solutions to their computational problems. The computational people depend on the biologists to validate whatever results they produce. The iteration cycle can be painfully slow, especially for people used to telling machines what they want them to do, and getting results immediately. The proposition of changing that dynamic is not alluring to most people, but I still hope there will be some who try.