New technology; Large set of samples; Quantify x<1> … x<n> mRNAs, proteins, lipids, metabolites; Estimate how units stick together (statistically or literally); Develop a “theory” of what units and groups of units interact to account for and predict higher order phenotypes (risk of neurodegeneration; lifespan).
Data take precedence. Mini-theories of molecular and cellular causality are assembled with some basic brain power and yes—-a dollop of theory and priors—-on the back of a massive pool of well structured data.
Exploratory biology of this type is/was insulted using the terms “fishing” or “mere description” but with current high throughput and high content technologies should be considered research “trawling” and factory-level science; not a cottage industry of small labs. This new style of science can be highly effective in biology and in astronomy as we are learning from Webb.
But it bugs the hell out of some classically trained reductionists who demand that clear hypotheses should drive science forward.
Much of the progress in modern biology falls into this alternative almost hypothesis-free style. I would say “story-free” style of science. Too damn many story-tellers.
- Many brute-force combinations of these specific organic molecules will yield interesting results (this is the main hypothesis of the experiment)
- We don't need to include the molecules that we haven't included
- We have good criteria for determining what results are interesting
- Our instruments/methods of phenotype prediction are well-understood and working as expected
Once the experiment is run, the observations are meaningless unless interpreted in the context of whatever prevailing theories the scientists have in mind.
> Why not spend the rest of his life checking different properties of the one sample?
The material in question is called LK-99 because it was first produced in 1999. Why not, indeed :) ?