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That's a strong statement. I'd say it 'ceases to be trivially interpretable'. And I think this is part of where the 'the published paper said ___ so it must be
by jfarlow 10y ago
That's a strong statement. I'd say it 'ceases to be trivially interpretable'. And I think this is part of where the 'the published paper said ___ so it must be true!' disparity between scientists and public becomes more apparent.
In biology when you design a good experiment, run it, come up with a model that fits your experiment, no scientist would ever pretend that their articulated model was how things actually worked. It's close, it's reasonable, but many more publications would be needed to confirm it. A single publication just is not enough to decomplexify the entanglements in biology. Many other scientists will use that model as the basis for their newer experiment, and when their results do not comport, they alter, adjust, or if need be, discard the original model.
The trouble with biology is it might take an entire 'Cell' paper (12 pages of dense publication - ie, many many grad-student-years of work) just to come up with the most simplistic model for what the biological experiment observed. That doesn't mean it wasn't meaningful - it was just much more complicated and less easily well-describable than physics and chemistry experiments. But very much like physics and chemistry, there is a definite trend towards a well-described and predictable system. Models actually get increasingly accurate over time. And this feature might be part of the border in defining a 'robust' science.
- xaa 10y ago> just to come up with the most simplistic model Yeap. Bioinformatician here. Not only are most published models overly simplistic -- which everyone acknowledges -- but I think our bigger problem is we don't even have a reasonable "meta-model" of biology. What I mean by that is, imagine experiments were instantaneous and free. How would we then incorporate the results into a mathematical/computational/predictive framework that describes biological reality in a way analogous to physics? AFAIK, we haven't the foggiest clue. Biology is pretty theory-light and empiricism-heavy, probably because we have good results with things like "I dunno what this mold is secreting, but it seems to be killing the bacteria!" So our experimental results are pretty precise (although arguably not "robust" between strains/conditions/etc), when people bother to use n>3, but the models and theory are anything but.