![]() ![]() We can analyze the data without hypotheses about what it might show. Petabytes allow us to say: "Correlation is enough." We can stop looking for models. In short, the more we learn about biology, the further we find ourselves from a model that can explain it. The discovery of gene-protein interactions and other aspects of epigenetics has challenged the view of DNA as destiny and even introduced evidence that environment can influence inheritable traits, something once considered a genetic impossibility. The models we were taught in school about "dominant" and "recessive" genes steering a strictly Mendelian process have turned out to be an even greater simplification of reality than Newton's laws. Now biology is heading in the same direction. The reason physics has drifted into theoretical speculation about n-dimensional grand unified models over the past few decades (the "beautiful story" phase of a discipline starved of data) is that we don't know how to run the experiments that would falsify the hypotheses - the energies are too high, the accelerators too expensive, and so on. A hundred years ago, statistically based quantum mechanics offered a better picture - but quantum mechanics is yet another model, and as such it, too, is flawed, no doubt a caricature of a more complex underlying reality. Consider physics: Newtonian models were crude approximations of the truth (wrong at the atomic level, but still useful). Data without a model is just noise.īut faced with massive data, this approach to science - hypothesize, model, test - is becoming obsolete. Once you have a model, you can connect the data sets with confidence. Instead, you must understand the underlying mechanisms that connect the two. Scientists are trained to recognize that correlation is not causation, that no conclusions should be drawn simply on the basis of correlation between X and Y (it could just be a coincidence). ![]() This is the way science has worked for hundreds of years. The models are then tested, and experiments confirm or falsify theoretical models of how the world works. These models, for the most part, are systems visualized in the minds of scientists. The scientific method is built around testable hypotheses. The big target here isn't advertising, though. ![]()
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