I probably take this blog too seriously. No, I definitely do. I am trying to make it like some serious review of the literature, and as a result, my true opinion is getting lost in the midst, and this is a shame. It should be what it is, and that is gloriously a blog.
I did some investigative reporting today. On what you may ask? Well basically what it would mean for me to be a PhD student in biostatistics. What it would mean in terms of what I could do, what the future challenges are for the field, and things like that.
What I found is that the PhD program would be course intensive at first, and from there it would move on to developing novel statistical methods. The novel part is important as it also counts for the "original research" requirement so often bandied about with that PhD (Doctor of Philosophy) thing. Yes.
But on the whole, the field of bioinformatics, biostatistics, what have you, appears to be one to me that is waiting for technology to happen. That is to say, the field is less likely to be advanced by nifty statistical methodologies that somehow can predict how the human genetic code is translated to create life, and is more likely to be advanced by cheaper more effective microchips and micropossessors which can capture all that cool RNA gene expression data which is working all the time in your body and making you, you.
Of course, this now brings on a daunting information technology job. One that demands high speed high capacity servers and brings a company like Google to mind in a hurry. But also, I must say, that it also appears to me to be an appealing entrepreneurial challenge, and one which could arguably have a greater impact on the field of genetic medicine than fancy statistical/computational techniques.
Of course, in fairness, I should also say that said techniques are yet vital, and that both should at least, develop at the same time.
