I came to biology from physics over a decade ago thinking that theory would matter. But modern biology is not waiting for a Grothendieck. We are not wanting for a deep theoretical view to reinterpret our data with. We are wanting for cheap, high quality data about cells and organisms in the first place.

Those of you who have not done biology can't realize how primitive things still are. A CS analogy is that we're trying to reverse engineer a non-deterministic alien architecture from the future via a remote debugger over a noisy line that has no error correction and runs at a fraction of a millibaud, where every peek or poke costs hundreds to thousands of dollars. With the advent of high-throughput sequencing we just figured out how to get noisy ROM/RAM dumps (genotype), but still have precious little ability to quickly interact with the biological systems under study (phenotype). Biology is much more like hacking and reverse engineering than it is like physics or mathematics.

A working exploit is worth much more than general pontification. The transformative events in biology these days are the clever hacks that enable whole new classes of fast experiments to be done: quick homologous recombination induced by CRISPR, optical interrogation of neural systems using light-sensitive ion channels, the development of adeno-associated viruses for rapid introduction of genetic material, etc. In the coming decades the combination of such clever hacks with cheaper automation and sensors will hopefully bring a flood of new data that will make a predictive, quantitative science of biology possible.

With cheap and plentiful data, perhaps clever minds might discover general quantitative principles that we can't see yet. But the data is what's lacking, not cleverness.