More for data capture and mining

Nearly three weeks have passed since my last entry. A big reason for that is the number of exciting papers and pertinent reviews recently published. In this regard, joining Twitter and being connected to the right people has been nothing short of amazing. Yes, I have learned much over the past three weeks, but have also been swimming in a stream of data, incorporating pathways, gene expression and proteomics data lists from supplemental files into my human genome database.

And all of that brings to mind what some elder statesmen in the nutrigenomics field have said - that one needs an army of data collectors and miners. This would be at the expense of some significant portion of the wet-lab work. Well, I agree. There are a lot of experiments that have already been done or two or three that when combined can give an insightful view into, say type 2 diabetes or obesity. This is essentially what Tiffin, Hyde et al. did a few years back. But with so much data, so many ideas to follow, too few partners (zero!) - swimming can easily become drowning. But it is really fun because our lab is looking into things and taking a view not often pursued.

Next I should write something about evolution of culture and chicken breeds.

Drug side effects and genetic and lifestyle factors

I just found a neat database (SIDER) from Peer Bork's group at EMBL: http://sideeffects.embl.de. This is a database one can query for drug indications and side effects. Using the data here, I find that there are 301 drugs with side effect or indication to alter body weight. Of those, 126 (41%) show both weight gain and decrease. This makes one wonder about genetic and environmental effects of those in the drug development trials. Therefore, there is a need to control things beforehand by partitioning based on genetics, if not also based on some lifestyle parameters.

The group's publication describing SIDER can be accessed here. The citation is Kuhn, et al. (2010) Molecular Systems Biology 6:343.