>This post was inspired out of frustration – one of the biggest problems with bioinformatics is how quickly things change. It is also a huge strength, but it can be a major problem for people in the field.
The idea came out of a simple annoyance: someone renamed all of our reference genome fasta files last night, and clearly forgot to let people know. At least, those people I spoke to didn’t know anything about it, so it wasn’t just me missing a meeting. I can see the advantages of doing it, and I fully support it – but it should have been done a year ago, and when they finally got around to it, they should have sent a major email. Instead, I queued up a bunch of jobs and fired them off only to watch as they all started crashing.
Wonderful use of resources.
At any rate, that got me thinking about the change of pace of next-generation sequencing. I’ve seen several threads asking questions about getting set up to use the MAQ aligner, obviously written by people who are just getting started in with aligners. These threads, unfortuantely, are being written after the author of the software has already abandoned that project and moved on to a new aligner. So much goes on without people realizing they’re working on the last wave of the technology.
That’s far from an isolated case – I found a program called NestedMICA for doing motif scanning, which would be a cool side project. I won’t link to it, though, because it’s clearly also been abandoned. Only two years ago it was a very promising application with a decent publication. Now, it won’t compile and the author isn’t responding to emails. I’ve spoken to motif people and they all change motif scanners and tools about as often as they change their socks. (well, no, the socks get changed a little more often.)
Keeping up with the latest and greatest tools is a huge burden for people in this field, and it’s practically impossible to do if your interests are at all diversified out of one of the major subjects.
I suppose that bioinformatics is far from the only field in which these things happen, but I just can’t think of another example where the ante to get in the game is so low (being able to program), the subject is so accessible (internet access gets you access to the data), and the questions are so fundamental (how does the cell work?)
All this churn and people jumping head first into the field leads to a plethora of unmaintainable perl programs, abandoned code and half baked packages without documentation. (At the worst case, of course!) In industry, any field with this kind of bandwagon would be ripe for consolidation, but in academica, it’s just a Darwinian process where many many failures seem to be required for each success. And somehow, I have no idea how to pick the winner.
All of this leaves me wondering where the field will be in 6 months or a year or two. I guess that’s why scientists go to conferences: to see if we can get a glipse into the crystal ball.
Compare this with biology. Can you imagine if every 4 months, there would be a completely different way of doing cloning or that the pcr technique you used would become obsolete?
How about chemists? Need a new way to determine your compounds melting point every 4 months?
Or Physicists… your model of gravity changes every 4 months?
I dunno. the pace is exhilarating… but sometimes exhausting.
Excuse me while I go make a few more changes to change the way I process chip-seq samples…. again.