The problem is that in many fields there is a weird dichotomy between people who know how to get data and people who know what to do with it. This is not a sustainable situation. Proper experimental design requires knowledge of how the data will be analyzed.
My proposed solution is to require that the leaders of research groups have expert knowledge of both experimental procedures and data analysis, because that is the expertise required to pick an appropriate hypothesis and supervise the corresponding scientific project from start to finish. Because students 1) work in a lab with diverse knowledge and 2) desire to become professors themselves, they are likely to acquire these skills as well. Aspiring professors who have substantially greater aptitude for either data collection or data analysis should form a joint lab with a researcher with the complementary skill set so that their students can learn both fields.
The problem is that if the data ends up in inconsistently formatted spreadsheets or poorly conceived custom formats, the effort required to extract the data for analysis later (especially across multiple projects) can be prohibitive.
"If you are leading a project that creates huge amounts of data, instead of employing a bioinformatician in your own group, why not collaborate with an existing bioinformatics group and fund a post there?"
If that's your goal, perhaps using a less derisive and incendiary tone towards the straw man scientist in the post would've been good?
> “Yes. Now, let’s see. It’s an amazing, visionary proposal, a great collaboration, and congratulations on pulling it together. I just have one question” said the director “This proposal will generate a huge amount of data – how do you plan to deal with it all?”
“Oh that’s easy!” answered Smith. “It’s all on page 6. We’ve requested funds to employ a bioinformatician for the lifetime of the project. They’ll deal with all of the data” he stated, triumphantly.
I dunno...this sounds like a problematic mindset across many, many domains in science. What makes the field of biology less prone to it?
Given the behavior and stories of lots of PIs and advisors, and how they treat grad students these days (especially in biology and medicine), I'm not sure that we need to be sticking up for them.
One of the local institutes just dissolved their bioinformatics group because they couldn't convince enough research groups to hand over grant money. They'd be part of the grant proposal in order to secure the grant, but then the money would end up being spent elsewhere...
Things may look messy in science, and they often are, but I'm optimistic about the future.
I got a MS degree in Bioinformatics and for the past three years the only role it has served is collecting dust in my closet upstairs :)
I was the young bioinformatician in 2006 and when working in a lab it felt very isolating. The PI and Postdocs just had me solve simple computational problems (or even IT problems). It felt very much like I was a cog in their grant writing machine rather than a collaborator that deserved any kind of authorship in a publication.
And looking back there was no one to teach me about good practices of writing software like source control, SOLID, testing, etc. Or even storage of our microarrays.
I eventually went to work for a biotech consultancy but I discovered that biotech software was a gimmick used to hike up the prices on software. Sure it was a niche field but we would charge clients hundreds of thousands of dollars for software that was barely functional.
I think a lot of Research groups were badly burned by this and eventually started trying to do everything in house. I eventually became disillusioned/burned out and left the field entirely.
I've been out of the field for four years now but still feel badly as I felt I've wasted my training. I still have a retainer client as a way back 'in' back into bioinformatics.
It would be nice to find these 'bioinformatics groups' and see how they're successfully collaborating with other labs/research groups.
So for anyone from a CS-oriented background, or who is thinking of doing a degree program in bioinformatics that isn't oriented around research- try to help out in various labs, and find a good mentor. See what environments work best for you, and what sort of problems you want to apply yourself to. The field is developing far faster than most college programs can move, but by getting out there and seeing what skills/knowledge will actually be useful, you can work on filling in the gaps sooner.
The silver lining is that you can have a lot of freedom in what you learn and what you do and that you can become completely indispensable.
Yes, I was working on a bioinformatics data warehouse a while back. Yes, we did have to write an import filter to extract data from Excel files.
> Both constructions are standard. The plural construction is more common in print, evidently because the house style of several publishers mandates it.
The most complete online version of it that Google knows about is at http://www-old.accademiadellacrusca.it/forum/htdocs/phpBB2/v... .
Some key points and quotes:
- data isn't an ordinary plural. "Ordinary plurals ... can be modified by cardinal numbers; ... no one, it seems, can tell you how many data."
- "To summarize, data has never been the plural of a count noun in English. It is used in two constructions - plural, with plural apparatus, and singular, as a mass noun, with singular apparatus. Both constructions are fully standard at any level of formality. The plural construction is more common. If you are an editor for a publisher whose house style insists on the plural construction only, take care to be consistent ..."
- "There have been more occurrences of datum in popular sources since [about the middle 1960s]. Perhaps the insistence of many editors that data is a plural has accelerated the tendency for datum to be used as a singular of data"
Languages change slowly over time. I find myself using plural data when I'm talking science and singular data when I'm talking about hard drives. Hadn't noticed until your post!
Strange isn't it?
