Stochastic, our master's voice, asks:
Assuming that time and money were not obstacles, what area of scientific research, outside of your own discipline, would you most like to explore? Why?
Well, of course it'd be
bioinformatics.
Why?
Interestingly technical, lots of data, wide open fundamental problems, impression that is is undersubscribed by researchers, both pure and applied problems, interdisciplinary.
I've seen some of the serious side of bioinfo related issues through my astrobiology hat, and it looks interesting and fun.
- Log in to post comments
More like this
This weeks question:
Assuming that time and money were not obstacles, what area of scientific research, outside of your own discipline, would you most like to explore? Why?
Tough question. I've got lots of ideas about what I'd do with limitless funding within my own area, but until the question…
I've been reluctant to answer the latest question from the Head Office, because it sucks. Nothing personal, but it just doesn't work for me.
Assuming that time and money were not obstacles, what area of scientific research, outside of your own discipline, would you most like to explore? Why?
I'm…
Yikes! An "Ask a ScienceBlogger" question already? Well, had I been a SciBlog some weeks ago, I would have quickly answered in response to the question (paraphrasing here), "Which modern technology should not have been invented?" My answer: pantyhose. They are the garments of pure unadulterated…
This week's (and my first) "Ask a Science Blogger" question comes from a Science Blogs reader named Jake Bryan (aka chezjake). He asks:
Assuming that time and money were not obstacles, what area of scientific research, outside of your own discipline, would you most like to explore? Why?
The answer…
Ooh! I'm applying for a course in that.
I'm coming from a maths background though, so I don't have a broad overview of the field. What would you say the major unsolved problems are?
If you know how to program, you can start now.
Define "know how to program...", I have dabbled a bit in some code.
Seriously, I don't have a broad overview of the field, I have seen some interesting presentations on reconstructing ancestral gene sequences and and evolutionary trees, the different metrics, assumptions and priors.
From my perspective some interesting constraints were being ignored, I inferred for computational simplicity.
I've also always wanted to apply some of my active expertise to molecular modeling, in particular protein folding problems - problem is quite analogous to classical dynamics of self-gravitating systems with serious algorithm overlap and even same level of approximations. Again, lack of time, though we looked seriously at applications of mean field codes to molecular dynamics in background fluids, looked straightforward but computationally itensive.