In response to this question asked of us by our Seed Overlords (the readers), Steinn says that he would do bioinformatics. As a biologist, I’m really unclear as to what bioinformatics actually is, other than a word you put into your grants to get funding. Let me add that I’m the PI on a federally-funded bioinformatics grant, so I’m supposed to be an expert in this area.
As I see it, bioinformatics usually means one of three things:
- The generation of large (massive, actually) datasets.
- The analysis of large data sets, and development of computational tools to handle these large datasets.
- The storage of large datasets and the creation of accessible databases.
It seems to me that with bioinformatics we are moving away from the “-ology” oriented approaches (i.e., intellectual disciplines). While this sounds exciting, synergistic, and groundbreaking, in reality it can lead to a lot of bad science because the technology is driving the intellectual development (or lack thereof). One example is genomics where I think a lot of shoddy analyses have been performed. I swear to the Intelligent Designer if I see one more comparison of two to four genomes where every nonsynonymous change (i.e., a DNA change that alters amino acid structure) is assumed to be under positively selection, I’m going to get really Mad.
Another instance of this is the microarray thing. While it seems to have settled down a bit, a lot of claims were being made for microarrays that just weren’t appropriate (reproducibility, for example). And I still haven’t heard a good statistical treatment for how you deal with the multiple comparisons issue (if you’re comparing the gene expression between two organisms, and you’re dealing with 5000 genes, some differences are expected simply by random chance.) You can’t Bonferroni correct this (p < 0.05/5000. Oh yeah, that's gonna work). And while I'm a big fan of log likelihood ratios, pulling a significant difference of two log units out of thin air is a little arbitrary.
While I don’t want to overplay hypothesis driven science, because sometimes you need to do non-hypothesis driven science, but bioinformatics often seems to be large amounts of data and funding desperately seeking a hypothesis (although if anyone wants to throw some funding my way, I’ll be more than happy to come up with a hypothesis for you…). So, I think bioinformatics is both a useful tool and a useless buzzword.
I’m just not sure it’s an intellectual discipline.