Why am I posting this on LessWrong?

Biological models inhabit the intersection between biology, philosophy, and computer science. I have not yet found good answers to my question, despite asking professional biologists, philosophers, and others. Perhaps the community has some ideas.

What does a complete model of biology look like?

Which genes increase my chances of Alzheimer’s, by what mechanisms, and what can we do about them?

How do eyes work?

How do I make flying monkeys?

These are the questions that people look to biology to answer. Is the mountains of data we biologists are generating, efficiently bringing us closer to answering them? How explanatory and predictive are the models we build upon this data?

How can we unify these models into one?

History unequivocally illustrates again and again how central this last question is. Maxwell’s unification of electromagnetism reconciled a patchwork of disparate observations into a coherent theory and made it far more powerful than the sum of its parts. Not only did hitherto disorganized and confusing experiments suddenly make sense, their incorporation into a whole immediately provided deep insights, such as reducing light to an electromagnetic wave.

Maxwell’s is not the only great unification. Newton’s Principia and Mendeleev’s Periodic Table are other examples.

Image 1: For millennia people have wondered what everything is made of. The Periodic Table is a sublimely succinct summary of our world. [1]

In biology, we have had analogous unifications, such as the Modern Synthesis of evolution and genetics. However, biology is still a cacophony far from an orchestra.

Most experiments today are generating only patchwork explanations and insights

Biology is generating enormous amounts of data. This data is extremely multimodal in its experimental sources and therefore encoding: everything from DNA and RNA sequencing, to mass spectrometry, to fluorescent imaging, to cryo-electron microscopy, and so on and so on, and each of these categories in turn are furthermore subdivided into a plethora of techniques and therefore data types.

I have tried to find decent estimates of the total amount of biological data generated annually without success. As a floor, considering only genomics research by itself, it is at the very, very least somewhere between 2 petabytes and 4 exabytes annually [2]. This an obvious underestimate. For example...

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